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What Is Business Forecasting? Definition, Methods, and Model

What Is Business Forecasting?

Business forecasting involves making informed guesses about certain business metrics, regardless of whether they reflect the specifics of a business, such as sales growth, or predictions for the economy as a whole. Financial and operational decisions are made based on economic conditions and how the future looks, albeit uncertain.

Key Takeaways:

• Forecasting is valuable to businesses so that they can make informed business decisions.
• Financial forecasts are fundamentally informed guesses, and there are risks involved in relying on past data and methods that cannot include certain variables.
• Forecasting approaches include qualitative models and quantitative models.

Understanding Business Forecasting

Companies use forecasting to help them develop business strategies. Past data is collected and analyzed so that patterns can be found. Today, big data and artificial intelligence has transformed business forecasting methods. There are several different methods by which a business forecast is made. All the methods fall into one of two overarching approaches: qualitative and quantitative .

While there might be large variations on a practical level when it comes to business forecasting, on a conceptual level, most forecasts follow the same process:

• A problem or data point is chosen. This can be something like "will people buy a high-end coffee maker?" or "what will our sales be in March next year?"
• Theoretical variables and an ideal data set are chosen. This is where the forecaster identifies the relevant variables that need to be considered and decides how to collect the data.
• Assumption time. To cut down the time and data needed to make a forecast, the forecaster makes some explicit assumptions to simplify the process.
• A model is chosen. The forecaster picks the model that fits the dataset, selected variables, and assumptions.
• Analysis. Using the model, the data is analyzed, and a forecast is made from the analysis.
• Verification. The forecast is compared to what actually happens to identify problems, tweak some variables, or, in the rare case of an accurate forecast, pat themselves on the back.

Once the analysis has been verified, it must be condensed into an appropriate format to easily convey the results to stakeholders or decision-makers. Data visualization and presentation skills are helpful here.

Types of Business Forecasting

There are two key types of models used in business forecasting—qualitative and quantitative models.

Qualitative Models

Qualitative models have typically been successful with short-term predictions, where the scope of the forecast was limited. Qualitative forecasts can be thought of as expert-driven, in that they depend on market mavens or the market as a whole to weigh in with an informed consensus.

Qualitative models can be useful in predicting the short-term success of companies, products, and services, but they have limitations due to their reliance on opinion over measurable data. Qualitative models include:

• Market research : Polling a large number of people on a specific product or service to predict how many people will buy or use it once launched.
• Delphi method : Asking field experts for general opinions and then compiling them into a forecast.

Quantitative Models

Quantitative models discount the expert factor and try to remove the human element from the analysis. These approaches are concerned solely with data and avoid the fickleness of the people underlying the numbers. These approaches also try to predict where variables such as sales, gross domestic product , housing prices, and so on, will be in the long term, measured in months or years. Quantitative models include:

• The indicator approach : The indicator approach depends on the relationship between certain indicators, for example, GDP and the unemployment rate remaining relatively unchanged over time. By following the relationships and then following leading indicators, you can estimate the performance of the lagging indicators by using the leading indicator data.
• Econometric modeling : This is a more mathematically rigorous version of the indicator approach. Instead of assuming that relationships stay the same, econometric modeling tests the internal consistency of datasets over time and the significance or strength of the relationship between datasets. Econometric modeling is applied to create custom indicators for a more targeted approach. However, econometric models are more often used in academic fields to evaluate economic policies.
• Time series methods : Time series use past data to predict future events. The difference between the time series methodologies lies in the fine details, for example, giving more recent data more weight or discounting certain outlier points. By tracking what happened in the past, the forecaster hopes to get at least a better than average view of the future. This is one of the most common types of business forecasting because it is inexpensive and no better or worse than other methods.

Criticism of Forecasting

Forecasting can be dangerous. Forecasts become a focus for companies and governments mentally limiting their range of actions by presenting the short to long-term future as pre-determined. Moreover, forecasts can easily break down due to random elements that cannot be incorporated into a model, or they can be just plain wrong from the start.

But business forecasting is vital for businesses because it allows them to plan production, financing, and other strategies. However, there are three problems with relying on forecasts:

• The data is always going to be old. Historical data is all we have to go on, and there is no guarantee that the conditions in the past will continue in the future.
• It is impossible to factor in unique or unexpected events, or externalities . Assumptions are dangerous, such as the assumption that banks were properly screening borrowers prior to the subprime meltdown .  Black swan events have become more common as our reliance on forecasts has grown.
• Forecasts cannot integrate their own impact. By having forecasts, accurate or inaccurate, the actions of businesses are influenced by a factor that cannot be included as a variable. This is a conceptual knot. In a worst-case scenario, management becomes a slave to historical data and trends rather than worrying about what the business is doing now.

Negatives aside, business forecasting is here to stay. Appropriately used, forecasting allows businesses to plan ahead for their needs, raising their chances of staying competitive in the markets. That's one function of business forecasting that all investors can appreciate.

Kesh, Someswar and Raja, M.K. "Development of a Qualitative Reasoning Model for Financial Forecasting."  Information Management & Computer Security, vol. 13, no. 2, 2005, pp. 167-179.

Infiniti Research. " Business Forecasting: The Challenges in Knowing the Unknown ."

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What Is Business Forecasting? Why It Matters

April 25, 2021 - 10 min read

Companies conduct business forecasts to determine their goals, targets, and project plans for each new period, whether quarterly, annually, or even 2–5 year planning.

Forecasting helps managers guide strategy and make informed decisions about critical business operations such as sales, expenses, revenue, and resource allocation . When done right, forecasting adds a competitive advantage and can be the difference between successful and unsuccessful companies.

In this guide to business forecasting, we'll cover: 

• What is business forecasting?
• What are the best forecasting techniques?
• Why forecasting in management is important
• How to conduct business forecasts
• A few forecasting examples for businesses

An introduction to business forecasting

What is business forecasting? Business forecasting is a projection of future developments of a business or industry based on trends and patterns of past and present data. 

This business practice helps determine how to allocate resources and plan strategically for upcoming projects, activities, and costs. Forecasting enables organizations to manage resources , align their goals with present trends, and increase their chances of surviving and staying competitive. 

The purpose of forecasts is to develop better strategies and project plans using available, relevant data from the past and present to secure your business's future . Good business forecasting allows organizations to gain unique, proprietary insights into likely future events, leverage their resources, set product team OKR , and become market leaders.

Managers conduct careful and detailed business forecasts to guarantee sound decision-making based on data and logic, not emotions or gut feelings.  

What are important business forecasting methods?

There are several business forecasting methods. They fall into two main approaches: 

• Quantitative forecasting

Qualitative forecasting

Quantitative and qualitative forecasting techniques use and provide different sets of data and are needed at different stages of a product's life cycle.

Note that significant changes in a company, such as new product focus, new competitors or competitive strategies, or changing compliance requirements diminish the connection between past and future trends. This makes choosing the right forecasting method even more important.

Quantitative business forecasting

Use quantitative forecasting when there is accurate past data available to analyze patterns and predict the probability of future events in your business or industry. 

Quantitative forecasting extracts trends from existing data to determine the more probable results. It connects and analyzes different variables to establish cause and effect between events, elements, and outcomes. An example of data used in quantitative forecasting is past sales numbers.

Quantitative models work with data, numbers, and formulas. There is little human interference in quantitative analysis. Examples of quantitative models in business forecasting include:

• The indicator approach : This approach depends on the relationship between specific indicators being stable over time, e.g., GDP and the unemployment rate. By following the relationship between these two factors, forecasters can estimate a business's performance. 
• The average approach : This approach infers that the predictions of future values are equal to the average of the past data. It is best to use this approach only when assuming that the future will resemble the past.
• Econometric modeling : Econometric modeling is a mathematically rigorous approach to forecasting. Forecasters assume the relationships between indicators stay the same and test the consistency and strength of the relationship between datasets.
• Time-series methods : Time-series methods use historical data to predict future outcomes. By tracking what happened in the past, forecasters expect to get a near-accurate view of the future.

Qualitative business forecasting is predictions and projections based on experts' and customers' opinions. This method is best when there is insufficient past data to analyze to reach a quantitative forecast. In these cases, industry experts and forecasters piece together available data to make qualitative predictions.

Qualitative models are most successful with short-term projections. They are expert-driven, bringing up contrasting opinions and reliance on judgment over calculable data. Examples of qualitative models in business forecasting include:

• Market research : This involves polling people – experts, customers, employees – to get their preferences, opinions, and feedback on a product or service.
• Delphi method : The Delphi method relies on asking a panel of experts for their opinions and recommendations and compiling them into a forecast.

How do you choose the right business forecasting technique?

• Choosing the right business forecasting technique depends on many factors. Some of these are:
• Context of the forecast
• Availability and relevance of past data
• Degree of accuracy required
• Allocated time to conduct the forecast
• Period to be forecast 
• Costs and benefits of the forecast
• Stage of the product or business needing the forecast

Managers and forecasters must consider the stage of the product or business as this influences the availability of data and how you establish relationships between variables. A new startup with no previous revenue data would be unable to use quantitative methods in its forecast.

The more you understand the use, capabilities, and impact of different forecasting techniques, the more likely you will succeed in business forecasting. 

Why is business forecasting important?

Any insight into the future puts your organization at an advantage. Forecasting helps you predict potential issues, make better decisions, and measure the impact of those decisions. 

By combining quantitative and qualitative techniques, statistical and econometric models , and objectivity, forecasting becomes a formidable tool for your company. 

Business forecasting helps managers develop the best strategies for current and future trends and events. Today, artificial intelligence, forecasting software, and big data make business forecasting easier, more accurate, and personalized to each organization.

Forecasting does not promise an accurate picture of the future or how your business will evolve, but it points in a direction informed by data, logic, and experiential reasoning. 

What are the integral elements of business forecasting?

While there are different forecasting techniques and methods, all forecasts follow the same process on a conceptual level. Standard elements of business forecasting include:

• Prepare the stage : Before you begin, develop a system to investigate the current state of business.
• Choose a data point : An example for any business could be "What is our sales projection for next quarter?"
• Choose indicators and data sets : Identify the relevant indicators and data sets you need and decide how to collect the data.
• Make initial assumptions : To kickstart the forecasting process, forecasters may make some assumptions to measure against variables and indicators.
• Select forecasting technique : Pick the technique that fits your forecast best.
• Analyze data : Analyze available data using your selected forecasting technique.
• Estimate forecasts : Estimate future conditions based on data you've gathered to reach data-backed estimates. 
• Verify forecasts : Compare your forecast to the eventual results. This helps you identify any problems, tweak errant variables, correct deviations, and continue to improve your forecasting technique.
• Review forecasting process : Review any deviations between your forecasts and actual performance data.

How do you do business forecasting?

Successful business forecasting begins with a collaboration between the manager and forecaster. They work together to answer the following questions:

• What is the purpose of the forecast? How will it be used? 
• What are the components and dynamics of the system the forecast is focused on? 
• How relevant is past data in estimating the future? 

Once these answers are clear, choose the best forecasting methods based on the stage of the product or business life cycle, availability of past data, and skills of the forecasters and managers leading the project.

With the right forecasting method, you can develop your process using the integral elements of business forecasting mentioned above. 

How do you get data for business forecasting?

A forecast is only as good as the data supplied. Before collecting data, ask:

• Why do you need it?
• What kind of data do you need?
• When will you collect it?
• Where will you gather it?
• Who is in charge of collecting it?
• How will you collect it?
• How will you analyze it?

When you have these answers, you can start collecting data from two main sources:

• Primary sources : These sources are gathered first-hand using reporting tools — you or members of your team source data through interviews, surveys, research, or observations.
• Secondary sources : Secondary sources are second-hand information or data that others have collected. Examples include government reports, publications, financial statements, competitors' annual reports, journals, and other periodicals.

Business forecasting examples

Some forecasting examples for business include: 

• Calculating cash flow forecasts, i.e., predicting your financial needs within a timeframe
• Estimating the threat of new entrants into your market
• Measuring the opportunity of developing a new product or service
• Estimating the costs of recurring bills
• Predicting future sales growth based on past sales performance
• Analyzing relationships between variables, e.g., Facebook ads and potential revenue
• Budgeting contingencies and efficient allocation of resources
• Comparing customer acquisition costs and customer lifetime value over time

What are the limits of business forecasting?

You can follow the rules, use the right methods, and still get your business forecast wrong. It is, after all, an attempt to predict the future. Some limits to business forecasting include:

• Biases and errors by the forecasters or managers 
• Incorrect information from employees, experts, or customers 
• Inaccurate past numbers 
• Sudden change in market conditions
• New industry regulations

How Wrike helps with business forecasting

The more accurate your business forecasting, the more effective your strategies and plans can be. While many things in business are out of your control, having an informed forecast of what lies ahead makes you prepared and confident about the future.

Wrike helps gather data in one central platform, extract insights, and communicate findings with forecasters and managers. Other benefits of Wrike include real-time data, integrations with other forecasting software, streamlined collaboration, and visibility into every business forecasting project. 

Are you ready to make projections for your business, allocate your resources for the best results, and improve your business forecasting process? Get started with a two-week free trial of Wrike today.

Kelechi Udoagwu

Kelechi is a freelance writer and founder of Week of Saturdays, a platform for digital freelancers and remote workers living in Africa.

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7 Financial Forecasting Methods to Predict Business Performance

• 21 Jun 2022

Much of accounting involves evaluating past performance. Financial results demonstrate business success to both shareholders and the public. Planning and preparing for the future, however, is just as important.

Shareholders must be reassured that a business has been, and will continue to be, successful. This requires financial forecasting.

Here's an overview of how to use pro forma statements to conduct financial forecasting, along with seven methods you can leverage to predict a business's future performance.

What Is Financial Forecasting?

Financial forecasting is predicting a company’s financial future by examining historical performance data, such as revenue, cash flow, expenses, or sales. This involves guesswork and assumptions, as many unforeseen factors can influence business performance.

Financial forecasting is important because it informs business decision-making regarding hiring, budgeting, predicting revenue, and strategic planning . It also helps you maintain a forward-focused mindset.

Each financial forecast plays a major role in determining how much attention is given to individual expense items. For example, if you forecast high-level trends for general planning purposes, you can rely more on broad assumptions than specific details. However, if your forecast is concerned with a business’s future, such as a pending merger or acquisition, it's important to be thorough and detailed.

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Forecasting with Pro Forma Statements

A common type of forecasting in financial accounting involves using pro forma statements . Pro forma statements focus on a business's future reports, which are highly dependent on assumptions made during preparation⁠, such as expected market conditions.

Because the term "pro forma" refers to projections or forecasts, pro forma statements apply to any financial document, including:

• Income statements
• Balance sheets
• Cash flow statements

These statements serve both internal and external purposes. Internally, you can use them for strategic planning. Identifying future revenues and expenses can greatly impact business decisions related to hiring and budgeting. Pro forma statements can also inform endeavors by creating multiple statements and interchanging variables to conduct side-by-side comparisons of potential outcomes.

Externally, pro forma statements can demonstrate the risk of investing in a business. While this is an effective form of forecasting, investors should know that pro forma statements don't typically comply with generally accepted accounting principles (GAAP) . This is because pro forma statements don't include one-time expenses—such as equipment purchases or company relocations—which allows for greater accuracy because those expenses don't reflect a company’s ongoing operations.

7 Financial Forecasting Methods

Pro forma statements are incredibly valuable when forecasting revenue, expenses, and sales. These findings are often further supported by one of seven financial forecasting methods that determine future income and growth rates.

There are two primary categories of forecasting: quantitative and qualitative.

Quantitative Methods

When producing accurate forecasts, business leaders typically turn to quantitative forecasts , or assumptions about the future based on historical data.

1. Percent of Sales

Internal pro forma statements are often created using percent of sales forecasting . This method calculates future metrics of financial line items as a percentage of sales. For example, the cost of goods sold is likely to increase proportionally with sales; therefore, it’s logical to apply the same growth rate estimate to each.

To forecast the percent of sales, examine the percentage of each account’s historical profits related to sales. To calculate this, divide each account by its sales, assuming the numbers will remain steady. For example, if the cost of goods sold has historically been 30 percent of sales, assume that trend will continue.

2. Straight Line

The straight-line method assumes a company's historical growth rate will remain constant. Forecasting future revenue involves multiplying a company’s previous year's revenue by its growth rate. For example, if the previous year's growth rate was 12 percent, straight-line forecasting assumes it'll continue to grow by 12 percent next year.

Although straight-line forecasting is an excellent starting point, it doesn't account for market fluctuations or supply chain issues.

3. Moving Average

Moving average involves taking the average—or weighted average—of previous periods⁠ to forecast the future. This method involves more closely examining a business’s high or low demands, so it’s often beneficial for short-term forecasting. For example, you can use it to forecast next month’s sales by averaging the previous quarter.

Moving average forecasting can help estimate several metrics. While it’s most commonly applied to future stock prices, it’s also used to estimate future revenue.

To calculate a moving average, use the following formula:

A1 + A2 + A3 … / N

Formula breakdown:

A = Average for a period

N = Total number of periods

Using weighted averages to emphasize recent periods can increase the accuracy of moving average forecasts.

4. Simple Linear Regression

Simple linear regression forecasts metrics based on a relationship between two variables⁠: dependent and independent. The dependent variable represents the forecasted amount, while the independent variable is the factor that influences the dependent variable.

The equation for simple linear regression is:

Y ⁠ = Dependent variable⁠ (the forecasted number)

B = Regression line's slope

X = Independent variable

A = Y-intercept

5. Multiple Linear Regression

If two or more variables directly impact a company's performance, business leaders might turn to multiple linear regression . This allows for a more accurate forecast, as it accounts for several variables that ultimately influence performance.

To forecast using multiple linear regression, a linear relationship must exist between the dependent and independent variables. Additionally, the independent variables can’t be so closely correlated that it’s impossible to tell which impacts the dependent variable.

Qualitative Methods

When it comes to forecasting, numbers don't always tell the whole story. There are additional factors that influence performance and can't be quantified. Qualitative forecasting relies on experts’ knowledge and experience to predict performance rather than historical numerical data.

These forecasting methods are often called into question, as they're more subjective than quantitative methods. Yet, they can provide valuable insight into forecasts and account for factors that can’t be predicted using historical data.

6. Delphi Method

The Delphi method of forecasting involves consulting experts who analyze market conditions to predict a company's performance.

A facilitator reaches out to those experts with questionnaires, requesting forecasts of business performance based on their experience and knowledge. The facilitator then compiles their analyses and sends them to other experts for comments. The goal is to continue circulating them until a consensus is reached.

7. Market Research

Market research is essential for organizational planning. It helps business leaders obtain a holistic market view based on competition, fluctuating conditions, and consumer patterns. It’s also critical for startups when historical data isn’t available. New businesses can benefit from financial forecasting because it’s essential for recruiting investors and budgeting during the first few months of operation.

When conducting market research, begin with a hypothesis and determine what methods are needed. Sending out consumer surveys is an excellent way to better understand consumer behavior when you don’t have numerical data to inform decisions.

Improve Your Forecasting Skills

Financial forecasting is never a guarantee, but it’s critical for decision-making. Regardless of your business’s industry or stage, it’s important to maintain a forward-thinking mindset—learning from past patterns is an excellent way to plan for the future.

If you’re interested in further exploring financial forecasting and its role in business, consider taking an online course, such as Financial Accounting , to discover how to use it alongside other financial tools to shape your business.

Do you want to take your financial accounting skills to the next level? Consider enrolling in Financial Accounting —one of three courses comprising our Credential of Readiness (CORe) program —to learn how to use financial principles to inform business decisions. Not sure which course is right for you? Download our free flowchart .

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The Complete Guide to Building a Sales Forecast

Set your company up for predictable revenue growth with the right forecasting processes and tools.

Paul Bookstaber

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Building a sales forecast is both an art and a science. Accurate sales forecasts keep your leaders happy and your business healthy. In this guide, we’ll explain everything you need to know about sales forecasting — so you can get a clear picture of your company’s projected sales and keep everyone’s expectations on track.

We’ve organized this reference guide by the top questions sales teams have about the sales forecasting process, based on our internal conversations and more than 20 years of experience developing  sales solutions .

Build sales forecasts with accuracy

Use the real-time data updates and insights of Sales Cloud to keep your forecasts accurate and your teams on track to hit targets.

What you’ll learn:

What is a sales forecast, why is sales forecasting important, who is responsible for sales forecasts, who uses sales forecasts, what are the objectives of sales forecasting, how do i design a sales forecasting plan.

• What happens to sales forecasting in unpredictable times?

How accurate are sales forecasts?

What tools do you use to forecast sales revenue and how do crm systems forecast revenue, how is forecasting better with crm vs. other methods.

If you’re a sales leader who’s already well-versed in the who and what of sales forecasts, skip to the sections on  designing a sales forecasting plan  and  tools to improve sales forecasts  for more relevant knowledge. Sales forecasting can become especially tough when we face an unexpected turn of events, so head to the section on  what happens to sales forecasts in unpredictable times  for more on that.

A sales forecast is an expression of expected sales revenue. A sales forecast estimates how much your company plans to sell within a certain time period (like quarter or year). The best sales forecasts do this with a high degree of accuracy, and they’re only as accurate as the data that fuels them.

A strong data culture is at the heart of an accurate sales forecast. This means all sales data is available to everyone at the company, and all teams do their part in keeping it updated, leaning on AI and automation to help. More on that in the section on  tools used to forecast sales revenue .

All sales forecasts answer two key questions:

• How much:  Each sales opportunity has its own projected amount it’ll bring into the business. Whether that’s $500 or $5 million, sales teams have to come up with one number representing that new business. To create the number, they take everything they know about the prospect into account.
• When:  Sales forecasts pinpoint a month, quarter, or year when the sales team expects the revenue to hit.

Coming up with those two sales projections is no easy feat. So sales teams factor in the important ingredients of who, what, where, why, and how to make their forecasts:

• Who:  Sales teams are responsible for sales forecasting.
• What:  Forecasts should be based on the exact solutions you plan to sell. In turn, that should be based on problems your prospects have voiced, which  your company can uniquely solve .
• Where:  Where is the buying decision made, and where will the actual products be used? Sales teams see better accuracy when they get closer (at least for a visit) to the center of the action.
• Why:  Why is the prospect or existing customer considering new services from your company in the first place? Is there a compelling event making them consider it now? Without a forcing function and a clear why, the deal may stall inevitably.
• How:  How does this prospect tend to make purchasing decisions? If you’re not accounting for how they do it now and how they’ve done it in the past in your forecast, it may be fuzzy math.

Forecasting lets leaders set realistic sales targets, create attainable and motivating quotas for sales reps, and gauge expected revenue, aiding in budgeting and spending decisions for the whole company. If forecasts are inaccurate, businesses may overspend (putting themselves in a risky spot), and set unreachable quotas (which is demoralizing for reps).

To understand why sales forecasting is so important to business health, think about two example scenarios: one with a car manufacturer and another with an e-commerce shop.

In the case of a car manufacturer, cars take a long time to build. The manufacturer has a complex supply chain to ensure every car part is available exactly when they need to build cars, so the number of cars available to purchase will meet demand.

When you buy something online, whether that’s from a large marketplace or a small boutique, you get a delivery estimate. If your delivery comes a day or a week after it’s promised, that’ll affect your satisfaction with the company — and decrease your willingness to want to do business with them again.

Sales forecasting is similar in both cases. Sales forecasts help the entire business plan resources to ship products, pay for marketing, hire employees, and beyond. Accurate sales forecasting yields a well-oiled machine that meets customer demand, both today and in the future. And internally on sales teams, sales revenue that delivers in its estimated time period keeps leaders and collaborators happy, just like a shipment that arrives on time.

If forecasts are off, the company faces challenges that affect everything from pricing to product delivery to the end user. Meanwhile, if forecasts are on point and  sales quotas  are met, the company can make better investments, perhaps hiring 20 new developers instead of 10, or building a much-needed new sales office in a prime new territory.

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Each organization has its own sales forecast owners. These are some of the teams who are usually responsible:

• Product leaders:  They put a stake in the ground for what products will be available to sell when.
• Sales leaders:  They promise the numbers that their teams will deliver. Depending on the seniority of the leader, how they forecast varies. For example, first-line managers forecast collections of opportunities, where third-line managers consider a wide set of numbers and traditional close rates to come up with an overall forecast.
• Sales reps:  They report their own numbers to their managers.

No matter how a company calculates its sales forecasts, the process should be transparent. And at the end of the day, sales leadership has to be responsible to call a number. Whether met, exceeded, or missed, the forecast responsibility falls on them.

Sales forecasts touch virtually all departments in a business. For example, the finance department uses sales forecasts to decide how to make annual and quarterly investments. Product leaders use them to plan demand for new products. And the HR department uses forecasts to align recruiting needs to where the business is going.

At some level, sales forecasting affects everyone in the company.

The main objective of sales forecasting is to paint an accurate picture of expected sales. Leaders are looking to these numbers when they’re building out their operational roadmap and budget. If they’re confident in the projected growth, they can get to planning.

They could decide to staff more customer service touchpoints, fund more external marketing events, or invest more in the community. They could get ahead of purchasing new equipment or upgrades that get more expensive the longer they wait. Without a sales forecast, leaders are making critical spending decisions in the dark. If sales don’t go as planned, it could lead to cutting workforce, reducing support, or halting product development.

Sales forecasting is a muscle, not an item to check off your to-do list. While you should absolutely design a framework for your sales forecasting plan each year, you should also change up your strategies from time to time so new muscles develop.

Craft a sales forecasting plan with your team by focusing on three primary activities:

• Calculating number and time  period:  Your plan should explain how you’ll calculate the estimated monetary amount and what the timeframes will be. See the section on  how a CRM can help with forecasting  later in this guide for more on the sales forecasting tools you can use to do this.
• Reviewing and revising:  You should also plan to review the forecast at key milestones and revise it if necessary. Most sales leaders track progress against their forecast daily! But you’ll also want to schedule designated check-ins throughout the quarter. Make sure you’re reviewing the latest numbers with  sales automation tools  that sync your CRM’s forecast data.
• Breaking the patterns:  Even the best sales organizations need to shake up their  sales process  once in a while. Breaking your patterns can help you find new ways of crafting even more accurate forecasting. Try skip-level forecasting, ask different questions, have executive sponsorship reviews, and take different angles of the data.

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What happens to sales forecasts in unpredictable times.

Unpredictable events have an enormous impact on your sales forecast. Extreme weather or economic crises all dramatically change your forecast. What you thought you knew about expected revenue growth can be suddenly flipped on its head.

As soon as an extraordinary event hits, sales and finance leaders at your company will quickly want to know:

• How’s our  sales pipeline  looking today?
• What are the best- and worst-case scenarios?
• How has the forecast changed from a week or a month ago?

Your forecast implicates resourcing, headcount, and more (see the section on  sales forecasting objectives ). So although things may be changing quickly, you don’t want to give up on your forecast.

Rather than attempt to recalculate your forecast based on dubious estimates or conjecture, your best bet is to  rely on a CRM solution  to get an accurate view of deal status and pipeline in real time.

During a crisis, reps need to feed their CRM with data as events unfold so leaders have clear visibility into the rapidly evolving pipe. That data enables those leaders to support their reps with corporate-level decisions about where they should be focusing their time — and craft the new forecasts. Your forecast is only as good as the data coming into it from your sales teams.

In uncertain times, quick access to sales data and the ability to pivot  sales territory  and resource deployment accordingly can make the difference between business continuity and dissolution. There’s no silver bullet to forecast perfectly in a crisis or unforeseen scenario. But vigilantly updating what’s in the pipeline and analyzing sales data more frequently than usual will help you see trends and retool your forecast accordingly.

Empathy and care are always fundamental, but this is especially true in these situations. Empathizing with your customers’ challenges and caring for your own sales reps should come before anything else. Build trust with internal and external partners. That trust will help you grow again in the future. Learn more about  maintaining customer relationships as a sales leader .

Only 45% of sales leaders are confident in their organization’s sales forecasts,  according to Gartner . While it’s natural for sales reps to bring in some intuition to their sales forecasts, that’s where room for error can creep in.

This brings us back to embracing a  strong data culture . To get a more accurate forecast, everyone in the sales cycle — from reps to managers to execs — should have a stake in making sure those numbers reflect the latest reality. Reps can keep all prospect info up to date, managers can track pipeline progress, and leaders can review how all teams are tracking toward those forecast numbers, with AI playing backup to spot any inaccuracies or chances to adjust along the way.

A  CRM  gives sales leaders a real-time view into their entire team’s forecast. The tool forecasts revenue by giving you:

• An accurate view of your entire business.  Comprehensive forecasts in a CRM come with a complete view of your pipeline.
• Tracking of your top performers.  See which reps are on track to beat their targets with up-to-the-minute leaderboards.
• Forecasting for complex sales teams.  Overlay splits allows you to credit the right amounts to sales overlays, by revenue, contract value, and more.

A forecast is based on the gross rollup of a set of opportunities. You can think of a forecast as a rollup of currency or quantity against a set of dimensions: owner, time, forecast categories, product family, and territory. You can collaborate on forecasts with all the necessary people to see how opportunities are stacking up. Drill down into opportunities by sales leader, operating unit, manager, and individuals.

We also love a CRM with  reports and dashboards . These highlight where the business challenges are, in plain and simple terms. It could be that four of five selling teams are at the right growth rate, and we just need to focus on another one. It could be that a certain product is challenged. The data opens up new doors to grow sales and see what could be working more effectively.

Another thing that’s great about a CRM is the guidance from AI. An  AI for sales  tool offers a neutral perspective on what’s actually happening in sales. For example, AI might note that an opportunity has been pushed out three quarters in a row — a finding that would’ve taken an individual reviewing the data longer to discover. Think of AI as your personal data scientist, taking your forecasting and entire sales operations to a new level.

Predictive AI tools take a look at historical sales data to give you a glimpse of what you might expect in the future. The AI will analyze factors like win rate or number of customer meetings. It takes some of the guesswork out of sales forecasting and helps you get to more accurate numbers. Try to analyze sales data for at least 12 months. Otherwise, there may not be enough data to get accurate sales predictions.

Sales forecasting is significantly more accurate when using a CRM instead of a spreadsheet. When a company is just starting out, sales teams usually rely on spreadsheets or back-of-the-napkin ways to calculate their sales forecasts. This may work for a while, but eventually, you’ll find this doesn’t scale.

The reality is, selling is more complex than ever. It involves everything from how demand generation campaigns are performing to how your phone calls to prospects are landing. The more you want to sell, the more you’ll want to  rely on a CRM .

See how Salesforce manages forecasts with confidence

The secret to an accurate forecast? Reliable, well-maintained pipelines. See how we manage both efficiently (with the help of the right technology), and use our best practices in your business.

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Paul Bookstaber is a writer at Salesforce. He has a decade of experience in content marketing in B2B tech. Before that, he published a magazine and ran a tabloid blog. Today, he splits his time between Florida and the Mountain West, and loves to hike, ski, and watch Bravo. He is in a polyamorous relationship with Luke and Roger, who are cats.

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The Last Guide to Sales Forecasting You’ll Ever Need: How-To Guides and Examples

By Kate Eby | January 26, 2020 (updated August 26, 2021)

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Sales forecasts are a critical part of your business planning. In this comprehensive guide, you’ll learn how to do them correctly, including explanations of different forecasting methods, step-by-step tutorials, and advice from experienced finance and sales leaders.

Included on this page, you'll find details on more than 20 sales forecasting techniques , information regarding how to forecast sales for new businesses and products , a step-by-step guide on how to forecast sales , and a free sales forecast template .

What Is Sales Forecasting?

When you produce a sales forecast , you are predicting what your sales or revenue will be in the future. An accurate sales forecast helps your firm make better decisions and is arguably the most important piece of your business plan. 

A sales forecast contrasts with a sales goal . The former is the realistic representation of what you believe will occur, while the latter is what you want to occur. Forecasts are never perfectly accurate, but you should be as objective as possible when creating a sales forecast. Goals, on the other hand, can be based on optimistic or motivational targets.

Because the sales forecast is critical to business planning, many different stakeholders in a company (beyond sales managers and representatives) rely on these estimates, including human resources planners, finance directors, and C-level executives. 

In this article, you’ll learn about different sales forecasting methods with varying levels of sophistication. The most basic method is called naive forecasting , which uses the prior period’s actual sales for the new period’s forecast and does not apply any adjustments for growth or inflation. Naive forecasts are used as comparative figures for more robust methods.

What Is Sales Planning?

A sales plan describes the goals, strategies, target customers, and likely hurdles for your sales effort. The sales plan defines your sales strategy and the method of execution you will use to achieve the numbers in your sales forecast.

Overview of Sales Forecasting Steps

Your sales forecasting model can ultimately become very sophisticated, but to grasp the basics, you should first gain a high-level understanding of what is involved. There are three primary steps to getting started:

• Decide which forecasting method or technique you will use. Also, determine the time period for your forecast. Later in this guide, we will review different methods of forecasting sales, including how to know which is best for your business.  
• Gather the data to plug into your forecast model. The data points will vary by method, but will almost always include your actual past sales and current growth rate.
• Pick a tool to support your forecasting effort. For learning purposes, you can start with pencil and paper, but soon after, you’ll want to take advantage of digital solutions. Common tools include spreadsheets, accounting software, and customer relationship management (CRM) or sales management solutions.

As you get going, remember not to be overly focused on complex formulas. Do regular reality checks to make sure your sales forecasts accord with common sense. Bounce forecasts off sales reps to get realistic feedback, and revise.

You will likely achieve greater accuracy if you build your forecasts based on unit sales wherever possible, because pricing can move independently from unit sales. Use data if you have it.

Benefits and Importance of Sales Forecasting

Sales forecasting helps your business by giving you data to make decisions concerning allocating resources, assigning staff, and managing cash flow and overhead. Using this data reduces your risk and supports your growth. 

Your sales forecast enables you to predict both short and long-term performance and customer demand for your product. In the short term, having a sales forecast makes it easy for you to spot when actual sales are not meeting estimates and gives you an opportunity to make corrections early in the period.

The forecast guides how much you spend on marketing and administration, and the projections generate your sales reps’ objectives. In this way, sales forecasts are an important benchmark for gauging the performance of your sales reps. 

Sales forecasts also lead to better management of inventory levels. With a good idea of how much product you will sell, you can stock enough to meet customer demand without missing any sales and without carrying more than you need. Excess inventory ties up capital and reduces profit margins. 

In the long term, sales forecasts can help you prepare for changes in your business. For example, you might see that within a few years, your company will require more manufacturing capacity to meet growing sales. To expand capacity, you may need to build a new factory, so now you can start planning how you will pay for it. Predictive sales forecasting is a critical part of your presentation if you are seeking equity capital from investors or commercial loans for expansion. 

In short, sales forecasting helps your business avoid surprises, so you aren’t making decisions in a crisis environment. Companies with trustworthy sales forecasts see a 10 percentage point  greater increase in annual revenues compared to counterparts without, according to research from the Aberdeen Group .

What Makes a Good Sales Forecast?

The most important quality for a sales forecast is accuracy. But, the benefits of accuracy must be weighed against the time, effort, and expense of the forecasting technique.

Useful sales forecasts are also easily understood and often include visual elements, such as charts, graphs, and tables, to make important trends visible. 

Ideally, you can quickly build a highly reliable sales forecast with simple, economical methods. The ultimate forecast method would automatically (i.e., without manual intervention) fetch the relevant data and make predictions using an algorithm finely tuned to your business. 

In reality, the forecasting process is more time consuming and subjective. Sales forecasts often depend on reps’ assessments of how likely their prospects are to close, and perceptions vary widely. (A conservative rep’s 60 percent probability may be understated, while another rep’s 60 percent may be overly optimistic.) 

Sales managers, who are usually responsible for forecasting, spend a lot of time factoring in these nuances and other market factors when calculating forecasts. 

Surprisingly, spending more time on forecasting does not always improve accuracy. According to research from CSO Insights, sales managers who spend 15 to 20 percent of their time producing their forecast had win rates for approximately 46.5 percent of deals. But, when they spend more than 20 percent of their time on forecasting, the win rate declined by more than two percentage points. 

An axiom of forecasting is that accuracy is highest during time periods that are close at hand and lowest during those that are far into the future. Short-term forecasts draw upon the following: deals that are already in the sales pipeline, the current economic environment, and actual market trends. So, the data underlying short-term forecasts is more reliable.

Forecasting for distant time periods requires bigger guesses about opportunities, demand, competitor activity, and product trends, so it makes sense that the forecast becomes less accurate the further into the future you go. (This concept applies to many companies, especially those that are young and growing; the concept becomes more relevant for all businesses at three years and beyond.) Bear this thought in mind when you look at your sales forecast in order to make long-term decisions.

Sales Forecasting Methods: Qualitative and Quantitative

Sales forecasting methods break down broadly into qualitative and quantitative techniques. Qualitative forecasts depend on opinions and subjective judgment, while quantitative methods use historical data and statistical modeling.

Qualitative Methods for Sales Forecasting

Sales forecasting often uses five qualitative methods. These are based on different ways of generating informed opinions about sales prospects. Creating and conducting these kinds of surveys is often expensive and time intensive. These five qualitative methods include the following: 

• Jury of Executive Opinion or Panel Method: In this method, an executive group meets, discusses sales predictions, and reaches a consensus. The advantage of this method is that the result represents the collective wisdom of your most informed people. The disadvantage is that the result may be skewed by dominant personalities or the group may spend less time reflecting.
• Delphi Method: Here, you question or survey each expert separately, then analyze and compile the results. The output is then returned to the experts, who can reconsider their responses in light of others’ views and answers. You may repeat this process multiple times to reach a consensus or a narrow range of forecasts. This process avoids the influence of groupthink and may generate a helpful diversity of viewpoints. Unfortunately, it can be time consuming.  
• Sales Force Composite Method: With this technique, you ask sales representatives to forecast sales for their territory or accounts. Sales managers and the head of sales then review these forecasts, along with the product owners. This method progressively refines the views of those closest to the customers and market, but may be distorted by any overly optimistic forecasts by sales reps. The composite method also does not take into account larger trends, such as the political or regulatory climate and product innovation. 
• Customer Surveys: With this approach, you survey your customers (or a representative sample of your customers) about their purchase plans. For mass-market consumer products, you may use market research techniques to get an idea about demand trends for your product.  
• Scenario Planning: Sales forecasters use this technique most often when they face a lot of uncertainty, such as when they are estimating sales for more than three years in the future or when a market or industry is in great flux. Under scenario planning, you brainstorm different circumstances and how they impact sales. For example, these scenarios might include what would happen to your sales if there were a recession or if new duties on your subcomponents increased prices dramatically. The goal of scenario planning is not to arrive at a single accepted forecast, but to give you the opportunity to counter-plan for the worst-case scenarios.

Quantitative Methods for Sales Forecasting

Quantitative sales forecasting methods use data and statistical formulas or models to project future sales. Here are some of the most popular quantitative methods:

• Time Series: This method uses historical data and assumes history will repeat itself, including seasonality or sales cycles. To arrive at future sales, you multiply historical sales by the growth rate. This method requires chronologically ordered data. Popular time-series techniques include moving average, exponential smoothing, ARIMA, and X11. 
• Causal: This method looks at the historical cause and effect between different variables and sales. Causal techniques allow you to factor in multiple influences, while time series models look only at past results. With causal methods, you usually try to take account of all the possible factors that could impact your sales, so the data may include internal sales results, consumer sentiment, macroeconomic trends, third-party surveys, and more. Some popular causal models are linear or multiple regression, econometric, and leading indicators.

Sales Forecasting Techniques with Examples

In reality, most businesses use a combination of qualitative and quantitative methods to produce sales forecasts. Let’s look at the common ways that companies put sales forecasting into action with examples.

Intuitive Method

This forecasting method draws on sales reps’ and sales managers’ opinions about how likely an opportunity is to close, so the technique is highly subjective. Estimates from reps with a lot of experience are likely to be more accurate, and the reliability of the forecast requires reps and managers to be realistic and honest.

This method can be especially helpful if you do not have historical data or if you are assessing  new prospects early in your funnel. In these cases, a rep’s gut feeling after initial contact can be a good indicator. If you are a manager, you will review reps’ estimates with an eye for any outliers and work with those reps to make any necessary adjustments. 

Here is an example of the intuitive method in action: You manage a team of four sales reps. You go to each one and inquire about the leads they are nurturing. You ask each rep which opportunities they believe they will win in the next quarter and how much those sales will be worth. John, your strongest rep, tells you $175,000. Alice, another strong performer, says $115,000. Bob, who is in his second year at your company, reports $85,000. Jennifer, a recent college graduate, projects $100,000. You calculate the total of those forecasts and arrive at an intuitive forecast of $450,000. However, you suspect Jennifer’s forecast is unrealistic, because she is inexperienced, so you ask her more questions. Based on what you learn, you decide that only half of Jennifer’s deals are likely to close, so you reduce her contribution to $50,000 and revise your total quarterly forecast to $400,000.

Scenarios Method

Scenario forecasts are qualitative and involve you projecting sales outcomes based on a variety of assumptions. This process can also be a helpful business planning exercise, because once you identify major risks or uncertainty for your company, you can develop action plans to deal with these circumstances if they arise.

Scenario forecasts require an in-depth knowledge of your business and industry, and the quality of the forecast will vary with the expertise of the person or group who prepares the estimate.

To create a scenario forecast, think about the key factors that affect sales, external forces that could influence the outcome, and major uncertainties. Then, write a narrative and numerical description of how the scenario would play out under various combinations of these key factors, external forces, and uncertainties.

Here is an example of the scenarios method in action: Your company sells components for military vehicles. You notice that the most impactful things your sales reps do are meeting with procurement officers in the defense departments of major nations and holding factory tours and product demonstrations for them. These are your key factors. 

The external forces are the number of tenders or requests for proposals that military procurement departments announce, and the value of those items. The risk of conflict in various parts of the world, scarcity of your raw materials, and trends in budget authorizations for defense by major countries are your critical uncertainties. 

You look at how your key factors, external factors, and major uncertainties might combine. One scenario might entail the outcome if your reps increased the number of meetings and product events by 20 percent, the value of U.S. tenders launched rose by six percent, and France decreased defense spending by two percent. 

Under this scenario, you might forecast a six percent increase in unit sales resulting from the following: 

• Having more in-person sales contacts should boost sales by five percent based on past performance.
• You can increase revenue by three percent due to greater U.S. tender opportunities and your current market share.
• Major customer France will not purchase anything, reducing sales by two percent.

Sales Category Method

The category forecasting method looks at the probability that an opportunity will close and divides opportunities into groups based on this probability. The technique relies somewhat on intuition, as does the intuitive method, but the sales category method brings more structure and discipline to the process.

The categories that each company uses vary widely, but they correspond broadly to stages in the sales pipeline. These are some typical labels and definitions:

• Omitted: The deal has been lost or the prospect is no longer engaging. 
• Pipeline: The opportunity will not realistically close during the quarter.
• Possible, Best Case, Upside, or Longshot: There is a realistic possibility that the deal could close at the projected value in the quarter if everything falls into place, but this is not certain. Overall, fewer than half of the opportunities in this group end up closing in the quarter at the planned value.
• Probable or Forecast: The sales rep is confident that the deal will close at the planned value in the quarter. Most of these opportunities will come to fruition as expected.
• Commit or Confident: The salesperson is highly confident that the deal will close as expected in this quarter, and only something extraordinary and unpredictable could derail it. The probability in this category is 80 to 90 percent. Any deal that does not close as forecast should generally experience only a short, unanticipated delay, rather than a total loss.
• Closed: The deal has been completed; payment and delivery have been processed; and the sale is already counted in the quarter’s revenue. 

To compile your forecast, look at the combined value of the potential deals in the categories under three scenarios:

• Worst Case: This is the minimum value you can anticipate, based on the closed and committed deals. If you have very good historical data for your sales reps and categories and feel confident making adjustments, such as counting a portion of probable deals, you may do so, but it is important to be consistent and objective.
• Most Likely: This scenario is your most realistic forecast and looks at closed, committed, and probable deal values, again with possible adjustments based on historical results. For example, if you have tracked that only 60 percent of your probable deals tend to close in the quarter, adjust their contribution downward by 40 percent.
• Best Case: This is your most optimistic forecast and hinges on executing your sales process perfectly. You count deals in the closed, commit, probable, and possible categories, with adjustments based on past performance. The possible category, in particular, requires a downward adjustment.  

As the quarter or period progresses, you revise the forecast based on updated information. This method can quickly get cumbersome and time consuming without an analytics solution.

Here is an example of the sales category method in action: You interview your sales team and get details from the reps on each deal they are working on. You assign the opportunities to a category, then make adjustments for each scenario based on past results. For example, you see that over the past three years, only half the deals in the possible category each quarter came to fruition. Here’s what the forecast looks like:

Top-Down Sales Forecasting

In top-down sales forecasting, you start by looking at the size of your entire market, called the total addressable market (TAM), and then estimate what percentage of the market you can capture. 

This method requires access to industry and geographic market data, and sales experts say top-down forecasting is vulnerable to unrealistic objectives, because expectations of future market share are often largely conjecture.

Here is an example of top-down sales forecasting in action: You operate a new car dealership in San Diego County, California. From industry and government statistics, you learn that in 2018, 112 dealers sold approximately 36,000 new cars and light trucks in the county. You represent the top-selling brand in the market, you have a large sales force, and your dealership is located in the most populous part of the county. You estimate that you can capture eight percent of the market (2,880 vehicles). The average selling price per vehicle in the county last year was $36,000, so you forecast gross annual sales of $103.7 million. From there, you determine how many vehicles each rep must sell each month to meet that mark.

Bottom-Up Sales Forecasting

Bottom-up sales forecasting works the opposite way, by starting with your individual business and its attributes and then moving outward. This method takes account of your production capacity, the potential sales for specific products, and actual trends in your customer base. Staff throughout your business participates in this kind of forecasting, and it tends to be more realistic and accurate. 

Begin by estimating how many potential customers you could have contact with in the period. This potential quantity of customers is called your share of market (SOM) or your target market . Then, think about how many of those potential customers will interact with you. Then, make an actual purchase.

Of those who do purchase, factor in how many units of your product they will buy on average and then how much revenue that represents. If you aren’t sure how much your customers will spend, you can interview a few. 

Here is an example of bottom-up sales forecasting in action: Your firm sells IT implementation services to mid-sized manufacturers in the Midwest. You have a booth at a regional trade show, and 3,000 potential customers stop by and give you their contact information. You estimate that you can engage 10 percent of those people in a sales call after the trade show and convert 10 percent of those calls into deals. That represents 30 sales. Your service packages cost an average of $250,000. So, you forecast sales of $7.5 million.

Market Build-Up Method

In the market build-up method, based on data about the industry, you estimate how many buyers there are for your product in each market or territory and how much they could potentially purchase. 

Here is an example of the market build-up method in action: Your company makes safety devices for subways and other rail transit systems. You divide the United States into markets and look at how many cities in each region have subways or rail. In the West Coast territory, you count nine. To implement your product, you need a device for each mile of rail track, so you tally how many miles of track each of those cities have. In the West Coast market, there are a total of 454 miles of track. Each device sells for $25,000, so the West Coast market would be worth a total $11.4 million. From there, you would estimate how much of that total you could realistically capture.

Historical Method

The historical sales forecasting technique is a classic example of the time-series forecasting that we discussed under quantitative methods. 

With historical models, you use past sales to forecast the future. To account for growth, inflation, or a drop in demand, you multiply past sales by your average growth rate in order to compile your forecast. 

This method has the advantage of being simple and quick, but it doesn’t account for common variables, such as an increase in the number of products you sell, growth in your sales force, or the hot, new product your competitor has introduced that is drawing away your customers.

Here is an example of the historical method in action: You are forecasting sales for March, and you see that last year your sales for the month were $48,000. Your growth rate runs about eight percent year over year. So, you arrive at a forecast of $51,840 for this March.

Opportunity Stage Method

The opportunity stage technique is popular, especially for high-value enterprise sales that require a lot of nurturing. This method entails looking at deals in your pipeline and multiplying the value of each potential sale by its probability of closing. 

To estimate the probability of closing, you look at your sales funnel and historical conversion rates from top to bottom. The further a deal progresses through the stages in your funnel or pipeline, the higher likelihood it has of closing.

The strong points of this method are that it is straightforward to calculate and easy to do with most CRM systems. 

But, opportunity-stage forecasting can be time consuming. 

Moreover, this method doesn’t account for the unique characteristics of each deal (such as a longtime repeat customer vs. a new prospect). In addition, the deal value, stage, and projected close date have to be accurate and updated. And, the age of the potential deal is not reflected. This method treats a deal progressing quickly through the stages of your pipeline the same as one that has stalled for months. 

If your sales process, products, or marketing have changed, the use of historical data may make this method unreliable.

Here is an example of the opportunity stage method in action: Say your sales pipeline comprises six stages. Based on historical data, you calculate the close probability at each stage. Then, to arrive at a forecast, you look at the potential value of the deals at each stage and multiply them by the probability.

Length-of-Sales-Cycle Method

This is another quantitative method that shares some similarities with the deal stage method. However, this model looks at the length of your average sales cycle. 

First, determine the average length in days of your sales process. This figure is also known as time to purchase or sales velocity . Add the total number of days it took to close all of the past year’s deals and divide by the number of deals. Then, calculate the probability of new deals closing in a certain period of time as a percentage of the average sales cycle length. 

With this method, the biases of individual reps are less of a factor than with the deal stage model. Also, with this technique, you can fine-tune the probabilities for different lead types. (For example, prospects referred by current customers may close in an average of 27 days, while prospects who make contact after an online search need an average of 62 days.) But, this technique requires you to know and record how and when prospects enter your pipeline, which can be time intensive.

Here is an example of the length-of-sales-cycle method in action: You review the 37 deals your company won last year and see that they took a total of 2,997 days to close. To calculate the average length of the sales cycle, you divide 2,997 by 37 and see that the average sales cycle lasted 81 days. You then look at the five deals currently in your pipeline.

Lead Scoring Method

This technique requires you to have lead scoring in place. With lead scoring, you profile your ideal customers based on attributes (like industry, size, and location) as well as behavior (such as whether they have recently raised capital or whether the contact person has requested a demonstration of your product). 

You then classify future leads based on how closely they match your ideal customer. You can label the categories with distinctions such as A, B, or C or hot, warm, or cold, or you can assign numbers up to one hundred using formulas that add and subtract points for different attributes and behaviors. (For example, “They requested a demo, which adds 15 points, but they are not in your ideal industry, which subtracts 10 points.”)  

To create your forecast, you then look at the historical close rate for leads in each category and multiply that by the value of the opportunities currently in the group. 

Here is an example of the lead scoring method in action: Your company sells textbooks for advanced math and science. Your ideal customer is a university with at least 25,0000 students that has an engineering school and is located on the east coast. These are your A prospects. B prospects have at least 10,000 students. C prospects have at least 10,000 students, but are located elsewhere in the country.

You then look at the close rates and potential deal values for each lead score. Finally, you multiply the close rate by the potential value of the deals in the category or by your average sales value.

Lead Source Method

This model forecasts future sales based on how you acquired the lead, using the behavior of previous leads as a benchmark.

For example, say your company sells a software application. Some leads come from search traffic to your website; some originate with demonstration requests at conferences, and some are referrals from existing customers. 

Look at your historical data to track the percentage of leads who converted to sales for each lead source. In addition, calculate the average value of a sale for each source. Then, by using the conversion probability and sales values, you can forecast the sales that the leads at the top of your funnel are likely to generate. 

Here is an example of the lead source method in action: Based on source, you compile your historical data and discover the following conversion rates and sales value for leads.

One advantage of this sales forecasting method is that you can project how many leads of each type you would need to generate in order to hit a target. Suppose you have a conference coming up where participants will be able to request demonstrations of your product, and you would like to win an additional $30,000 in sales from the demo leads. Based on the average lead value of $600, you know you will want to generate 50 leads who request demos at the conference. 

One drawback to lead source forecasting is that the method does not account for potential differences in the length of the sales cycle for the lead types. That makes it difficult to pinpoint the period in which the revenue will occur. Therefore, you should do a separate analysis of time to purchase in order to allocate sales to the right period.

Another challenge is that sometimes you may not be sure of the lead source. For example, suppose that another customer has recommended your product to a contact and that that contact decides to first check you out on your website. You might very well assign a lower lead value to this prospect, assuming they will behave like our web-originated leads, when, in reality, they will probably behave more like the customer referral leads. 

Lastly, remember that this method won’t account for changes in your marketing or pricing that influence conversion rates and customer behavior.

Sales by Row Method

This method is a good fit for small businesses that sell different products or services. Rather than forecasting sales for each individual product type, you project sales for categories. 

Each row in your forecast will cover different physical products (such as pick-up trucks, heavy trucks, and delivery vans) and service units (such as hours of labor or service types like replacing a faucet, unclogging a drain, or installing a toilet). 

You can employ this method to forecast units and then factor them by average prices to arrive at revenue. Or, you can look exclusively at revenue. If you sell a subscription service, you can calculate recurring revenue for each product type.

For each row, you would look at how much you sold in the same period a year earlier and then adjust for factors such as inflation, organic growth, new products, increased workforce, or special circumstances.

Here is an example of the sales by row method: You operate a combination fuel station and mini-market. Your forecast would cover the broad categories of your business, such as sales of gasoline, diesel, food, beverages, and sundries.

For March’s forecast, you take into account that the new housing development near your business, which was under construction last year, is now almost completely sold and that there are many more commuters filling up. Your gas sales have been growing by almost 15 percent year over year. Also, in March, there will be a special event at the nearby fairgrounds that could draw thousands of additional vehicles to your area. 

On the downside, a new retail complex with a full-service grocery store has opened nearby, so your sales of food and drinks have slipped. Also, increased congestion in the neighborhood has caused some long-haul truckers who used to stop for fuel to reroute.

Regression or Multivariable Analysis Method

Regression or multivariable analysis is one of the most sophisticated forecasting methods, and allows you to build a custom model combining any factors that you feel are relevant to your sales.

For regression analysis, you need accurate historical data on all the variables under consideration, expertise in statistics, and, for practical purposes, an analytics solution or application that can perform the analysis. 

Because this method incorporates a multitude of influences on your sales, the resulting forecast is the most accurate. But, the costs tend to be high because of the data collection, expertise, and technology requirements.  

Regression analysis looks at the dependent variable (the factor that you are trying to predict, in this case, the amount of future sales) and independent variables (the factors that you believe affect sales results, such as opportunity stage or lead score). 

In a simple example, you would create a chart, plotting the sales results on the Y axis and the independent variable on the X axis. This chart will reveal correlations. If you draw a line through the middle of the data points, you can calculate the degree to which the independent variable affects sales. 

This line is called the regression line , and, by calculating the slope of the line, you can use numbers to represent the relationship between the variable and sales. The equation for this is Y = a + bX. Excel and other software will perform this analysis and calculate a and b for you. In more sophisticated applications, the formula will also include a factor for error to account for the reality that other variables are also at work.

Going further, you can look at how multiple variables interplay, such as individual rep close rate, customer size, and deal stage. Making these kinds of calculations becomes increasingly difficult with simple charts and demands more advanced math knowledge. 

Remember that correlation is not the same as causation. Bear in mind that while two variables may seem closely related to each other, the reality may be more subtle. 

Here is an example of the regression method in action: You want to look at the relationship between the amount of time a prospect has progressed in your sales cycle and the probability of the deal closing. 

So, plot on a chart the probability of close for past deals when they were at various stages of your sales cycle, which lasts an average of 100 days. Deals early in the sales cycle have a low probability of closing compared to those that occur in the later stages of negotiation and contract signing on day 85 and up. (Be sure to eliminate any prospects that stall or disengage at any stage.)

By drawing a line through those points (i.e., the intersection between the sales close probability and the percentage of the average sales cycle), you can see that there is a nearly one-to-one relationship between percentage point increases in time elapsed relative to the average sales cycle and percentage point increases in the probability of closing.

This calculation becomes more complex when you consider multiple variables. Let’s say you have two sales reps working with prospects. Gloria, your best closer, is giving a product demonstration to a new Fortune 500 account. Leonard, a strong performer, whose close rate is a little lower than Gloria’s, is negotiating with a repeat customer, a mid-sized company. 

Your multivariable analysis of these situations could take into account each rep’s average close rate for an opportunity, given the following factors: the specific stage; deal size; time left in the period; probability of close for a repeat customer versus a new customer; and time to close for an enterprise customer with more than 10 people involved in decision making versus a mid-sized business with a single decision maker.

Time Horizons in Sales Forecasting

Choosing the time period for your sales forecast is an important step. Depending on your business, the purpose of your forecast, and the resources you can devote to making forecasts, the time frame you target will vary. 

A short-term forecast will help set sales rep bonus levels for next quarter, but you need a long-term forecast to decide whether you should plan to build a new factory. A startup that has been doubling revenue every year will have more difficulty making a 20-year forecast than a century-old concern in a mature industry. Here are the three time frames for forecasts: 

• Short-Term Forecasts: These cover up to a year and can include monthly or quarterly forecasts. They help set production levels, sales targets, and overhead costs.
• Medium-Term Forecasts: These range from one to four years and guide product development, workforce planning, and real estate needs.
• Long-Term Forecasts: These extend from five to 20 years and inform capital investment, capacity planning, long-range financing programs, succession planning, and workforce skill and training requirements.

Getting Started with Sales Forecasting: What You Need to Know

Regardless of the sales forecast method you use, you generally need to have certain pieces of information and conditions in place. These include the following:

• Well-Documented and Defined Sales Process: You need to understand your customer journey and have an established sequence for nurturing each prospect. Without this, you cannot predict which opportunities are getting closer to purchasing. This structure creates accountability. 
• Consensus on Pipeline Stages: Your sales team needs to have a clear and shared understanding of what you mean by lead, prospect, qualified, possible, probable, committed, and other relevant terms. 
• Definition of Success: Communicate clearly what your sales team is striving for in terms of sales quotas or goals; include these quotas and goals for each individual rep, for the team as a whole, and for conversion through each stage of your pipeline.
• Historical Data: You require benchmarks for data points, such as average time to close, conversion rates, average deal size, lifetime customer value, win-loss ratio, and seasonal sales trends. These sales metrics and KPIs are often critical pieces of your forecast.
• Current Status: Up-to-date knowledge of your pipeline is essential, including how many opportunities are at each stage and the potential value of these sales.
• Forecasting Tools: This will almost always include a CRM application and may also include financial management or accounting software, analytics solutions, and spreadsheets.

Influences and Assumptions in Sales Forecasting

Sales forecasting should not happen in a vacuum. Take into account changes in the business environment and question assumptions, such as that past growth will continue. Also, be sure to factor in your ideas about global economic trends and competitor behavior.

Here are some common factors to consider regarding your sales forecast. Many of these can have either a positive or negative influence on sales. For example, changing reps’ account assignments may reduce sales, because members of your team will have to familiarize themselves with customers that are new to them. However, sales could increase if your new hotshot gets your biggest opportunity.

• Economic Trends: Inflation, growth, consumer sentiment, risk appetite, and purchasing power
• Regulation: Trade policies such as tariffs, duties, and quotas; health, safety, and environmental rulings on products or processes; court decisions; intellectual property disputes; and competition policy
• Seasonal Trends: Cyclical demand fluctuation, production patterns, and variation in raw material availability 
• Competitor Behavior: New product innovations, pricing changes, and market entries and exits
• Business Economics: Selling prices, direct prices, unit costs, gross margins, and the impact of accrual versus cash accounting on when you can book a sale
• Staffing and Compensation: Hiring or firing new reps, changes in leadership, policies on commissions and bonuses, and training
• Territory Management: Redrawing of territories and changes in account assignments
• Products and Services: Product lifecycle, new products and services, user experience, defects, ticket resolution, changes in distribution, and market entries and exits
• Marketing: Demand generation, advertising, pricing, special campaigns, social media activity, and prospecting

Sales Forecasting for New Businesses and Products

If you are starting a new business or launching a new product, your sales forecasts are crucial because they will determine how much you can spend in order to break even. However, when dealing with a new entity, you lack the advantage of historical data, which you need for almost every forecasting technique. 

If you don’t have historical data, you can use industry benchmarks from trade publications, industry associations, and consultants. For example, if you are launching a new recipe app, look at market research on how other cooking apps have performed. 

Dining establishments can look at number of tables, hours of service, and menu prices to estimate average order amounts and table turnover. Retail outlets use square feet, foot traffic, and average selling prices to forecast sales.

If you are adding a new product to your line, you can forecast sales by looking at how your most similar existing product performed at launch. Then, you can make tweaks based on other relevant information, such as that the new product is harder to master than its predecessor, that it is a later entrant into a crowded space, or that it already has a backlog of orders before launch.

New service businesses can base forecasts on capacity, such as number of staff and service hours and how much to charge for the most popular services. Once you have this data, you can make adjustments accordingly.

Michael Barbarita, President of Next Step CFO , works as a contracted CFO to produce sales forecasts for companies. He likes to tie the sales forecast for service businesses to a metric called sales per direct labor hour , which you can calculate this by dividing sales by the working hours of people in the field performing customer work. For example, an electrical contractor would calculate the sales per direct labor hour of its electricians and multiply that figure by the number of electricians and the hours they work.  

For instance, you may decide that operating at half capacity is a good estimate for your first six months in business. Then, you may operate at three-quarters capacity for the second six months. Therefore, you would multiply maximum capacity by average revenue and then multiply that resulting figure by 0.50 and 0.75, respectively.

Quick-Start: Sales Forecasting Formulas

If you are eager to dive in and want to generate some simple sales forecasts, you can make use of basic equations. Here are a few easy ones:

• Simple Forecast with No Organic Growth: This formula assumes that this period will duplicate the prior period, except for the impact of inflation.  Revenue Prior Period) + (Revenue Prior Period x Inflation Rate) = Sales Forecast  
• Historical Plus Growth: This formula helps you reflect current trends.You look at the prior year and then factor it by your recent growth rate. (Last Year Revenue x Percentage Growth Rate) + Last Year Revenue = Sales Forecast
• Partial Year: In this method, you project the rest of the year based on historical patterns and early results. Imagine that you know your sales for the first two months of the year and that last year these months represented seven and nine percent of your sales respectively and totaled $100,000. Using the formula below, you would forecast sales of $625,00 for the year: ($100,000 x 100) ÷ 16 = $625,000. (Current Period Revenue x 100) ÷ Percent That Equivalent Period Represented Last Year = Forecast Sales
• Pipeline Formula: This formula replicates the opportunity stage method that we discussed earlier. You calculate the value of deals at each stage of your pipeline by multiplying the potential deal value by the close probability and adding up the result for each stage. (Deal Amount x Close Probability) + (Deal Amount x Close Probability) etc. = Sales Forecast

How to Make a Basic Sales Forecast Step by Step

Here are step-by-step instructions for a manually generated sales forecast:

• Pick Your Time Period: The way in which you will use your forecast determines the most appropriate time interval, whether that be monthly, quarterly, annually, or on an even longer timeline. If you are making your first forecast, estimating on a monthly or quarterly basis for the upcoming year is a good starting point. Experts suggest doing monthly estimates for the first year and then doing annual forecasts for years two through five. 
• List Products or Services: Write down the items or services that you sell. If you have a lot of them, group them into categories. For example, if you sell clothing, your rows might include shirts, pants, and shoes. Match these revenue streams to the way you organize your accounting. So, if your books look at women’s and men’s clothing separately, do the same for your sales forecast. That way, you can pair your sales forecast with information on your cost of goods sold and overhead to project profit.  
• Estimate Unit Sales: Predict how many units you will sell in the selected time period. If you have historical data, use that and then factor in assumptions about demand for the upcoming period. For example, is your business growing? Is the economy in recession? Did you launch a big promotion? Use the answers to these questions to make downward or upward adjustments to the historical figure. You can also interview some customers to get insights into their likely purchasing plans. Lastly, don’t forget to factor in seasonal fluctuations. 
• Multiply by the Selling Price: Multiply the unit sales numbers by the average selling price (ASP). Determine the ASP by analyzing historical sales and adjusting for inflation and other factors. To obtain this figure, you also need to consider discounts, free trials, and unsold inventory. 
• Repeat for Each Forecast Period: Go through the same calculation for each category and time interval. As you forecast more distant periods, your estimates are likely to be less accurate, so you may want to make a range of forecasts, such as for best, worst, and average scenarios. As time passes, add the actual values and fine-tune your forecast. For instance, you may see that for the first few months of the year, you underestimated sales by 12 percent. Therefore, you decide to increase your forecasted sales amounts in the upcoming months.

How to Forecast Sales in Excel

Here is a step-by-step guide to building your own sales forecast in Excel:

• Enter Historical Data: Open a worksheet and enter your past date data in the first column. Then, in the second column, enter the corresponding sales values. If possible, make sure you space the dates consistently (e.g., the first day of every month). 
• Create Forecast: In the date column, fill out the next date cell with the future date you are forecasting. Select the corresponding sales value cell and in the function field, type: =(FORECAST( A10, B2:B9, A2:A9)), where A10 is the future date cell, B2 to B9 are the historical sales amounts, and A2 to A9 are the historical dates. Hit enter and the forecast sales amount will appear.
• Repeat: Continue the pattern for your remaining future dates. Remember that the formula uses only known variables, so do not add forecasted amounts to the cell ranges. This function is a linear forecasting method.
• Power Up: If you have Excel 2016, you can use the forecast sheet function, which automates forecasting and adds a chart. To use this function, select both data columns, and, on the data tab, click the forecast sheet. In the create forecast worksheet box, select whether you want a line or bar chart. In the forecast end field, choose an ending date and then click create. Excel will create a new worksheet that contains both historical and forecast sales data as well as a visual representation. 

For a pre-made basic sales forecast, download this template that projects product sales with both units and sales amount.

Basic Sales Forecast Sample Template

Excel | Google Sheets | Smartsheet

For a wide range of pre-built sales forecast templates in a variety of formats, see this comprehensive collection .

How to Choose the Right Sales Forecasting Methodology

Your goal is to build the most reliable forecast possible, with the minimum amount of resources you need to be effective. To choose the method that fits best, consider these seven questions:

• Is the Time Frame Short, Medium, or Long Term? Qualitative methods are a good choice for short-term horizons, but they generally underperform quantitative methods for periods beyond a few months. Similarly, consider where you are in your business or product lifecycle. If you are ramping up or in a high-growth phase, you may be making costly investment decisions, so you need a method with a high degree of accuracy, but also relatively quick production time. When you are in a mature phase of your business, decisions about production and marketing are more routine. 
• How Much Data Do You Have? The less data you have, the more likely you will be to select a qualitative technique. If you have limited data, you will turn toward more simplistic models. A company that has collected a lot of data and has great confidence in its reliability can choose sophisticated quantitative models. 
• How Relevant Will History Be in Predicting the Future?  If your business has undergone big changes, such as launching major new products, experiencing large growth in the sales force, or introducing a different pricing structure, your past results will have less value as a guide to future performance. So, methods that diminish the weight put on historical data and qualitative techniques are a better choice.  
• In Terms of Time and Money, How Much Does It Cost to Produce the Forecast? How Does This Cost Compare to the Value of the Potential Benefits?You will need to make tradeoffs between the time and cost to build your forecast and the potential benefits, such as cost savings. Also, consider the potential cost of error. For example, suppose you are contemplating a high-cost sales-forecasting technique (one that takes a lot of data gathering, the creation of a custom model, and expensive staff and technology to produce). The forecast could allow your company to reduce the amount of inventory it holds. Weigh the value of inventory savings against the forecasting cost. If you reduce inventory and the forecast proves inaccurate, what are the potential costs of lost sales — because you did not stock adequately or because you did not cut back enough?  
• What Degree of Accuracy Do You Need?  Forecast accuracy rises with the cost and complexity of the methodology. Depending on how you will use the forecast, the size of your company, and the variability of your business, you may feel that it’s not cost effective to produce a maximum-accuracy forecast. If you are a giant global company, a fraction of a percentage point error in your sales forecast could represent many millions. So, the bigger the dollar values, the more meaningful every degree of enhanced accuracy becomes.
• How Complex Are the Factors That Will Drive the Forecast?   If your sales dynamic is straightforward — the more sunny days there are, the more beach umbrellas you sell at your beach kiosk — then building a sophisticated, AI-driven forecasting model will be overkill. “It's important not to spend time and energy developing a complex model, when a much simpler one will do the job,” says Nicholas. But when you are facing a subtle and complex interplay of variables, you need a technique that accounts for them. Suppose you have new products, changes in your marketing, and additional sales reps. A sophisticated model would allow you to forecast the net effects and also try out different scenarios in which the variables fluctuated.

Why Accuracy Is Important in Sales Forecasts

According to CSO Insights, 60 percent of forecasted deals do not close and 25 percent of sales managers are unhappy with the accuracy of their forecasts. Inaccuracy in sales forecasts causes problems for businesses and impacts performance. 

People throughout your company depend on your forecasts to make a multitude of decisions — from pay raises to real estate acquisitions. Let’s look at some of the important reasons to strive for accuracy:

• Early Warning: Your sales forecast helps you spot trouble early, like when revenues are not materializing as expected; the forecast also allows you to intervene and problem solve before this underperformance becomes a crisis.
• Decision Making: The forecast gives leaders confidence and a sound basis for deciding how much and where to spend or invest. Production planners, HR, and others will use the forecast.
• Goal Setting: You set achievable targets for sales reps when you have an accurate forecast. Goal setting prevents sales reps from getting discouraged by unrealistic expectations. Following this strategy also ensures that your commission and bonus scale are calibrated appropriately. 
• Customer Satisfaction: When you are prepared for the right level of demand, your company can improve its record of fulfilling orders on time and in full.
• Inventory Management: You will be more likely to have the right level of inventory if your sales forecasts are accurate. Making accurate predictions allows you to better manage your supply chain and order raw materials or parts in a timely fashion. You also gain more control over your pricing if you have the right amount of inventory. When you have to resort to discounting to get rid of excess inventory, your profitability suffers.

How to Improve Sales Forecast Accuracy and More Best Practices from Experts

Producing high-quality forecasts takes organizational commitment and long-term effort, and best practices will help improve accuracy.

”Sales forecasting is both an art and a science. Where companies tend to go wrong is relying too heavily on one or the other. You need a consistent process and reliable data,” says Charlene DeCesare, CEO of sales training and advisory firm Charlene Ignites .

She emphasizes five best practices:

• Ensure that the pipeline feeding the forecast is accurate. You don't need historical data to predict the future when you have a well-defined sales process.
• Everyone must use the CRM, and should enter notes and coding opportunities in a clear, consistent way. 
• Buyer behavior is a much more reliable predictor of future sales than gut feel. Challenge optimism that doesn't align with the applicable stage in the sales cycle or isn't supported by clear, mutually agreed-upon next steps.
• In general, buyer/seller behavior is the leading indicator to rely upon. Too many companies rely on results, which is actually the lagging indicator.
• Sales leadership can have a huge impact. Sales reps must be rewarded for both honesty and accuracy. Sales forecasting must be an individual, team, and company priority. 

Rob Stephens, a CPA whose firm CFO Perspective advises businesses on forecasts, adds: “A big planning mistake is spending too much of your precious time trying to find the one right scenario… Start with a range of reasonable forecasts based on solid fundamentals. For example, you may project from historical growth rates, customer indications of future sales, or projections of market growth. A company with a new product may need to extrapolate from existing products or early indications from potential customers. Use a higher-probability scenario as a beginning base scenario, but identify why the future may deviate from it.”

Common Mistakes and Pitfalls in Sales Forecasts

Sales pros say they see the same sales forecasting errors on a regular basis and that these often relate to letting the discipline of the forecasting process lapse. 

“The most common operational mistakes are basing forecasts on hope rather than evidence, ignoring repeated close date slippage, failing to take into account the historic forecast accuracy (or inaccuracy) of the salesperson concerned, and failing to hold salespeople accountable for the relative accuracy of their forecasts,” notes Bob Apollo, Founder of Inflexion-Point Strategy Partners, a sales training firm.  

“The most common cultural mistake is when sales leaders press salespeople to forecast a target number without any evidence or confidence that it will actually be achieved," he notes.

Evan Lorendo , Director of Revenue Accelerator, which advises service companies on revenue strategies, says he sees companies with monthly recurring revenue (MRR), such as software as a service (SaaS), frequently make mistakes in sales forecasting.

He gives the example of a company with an MRR product that wants to generate $120,000 in revenue a year. How much in new sales do they need each month? “Most of my clients say $10,000/month, but that is wrong. Because a client is paying on a monthly basis, a client that signs up in January is actually paying 12 times during the year. On the flip side, a client signing up in July will make six payments during the year,” he explains. 

That means there are a total of 78 potential payment configurations per year, not 12. The customer who buys in January will make 12 payments, but November’s buyer will make two. (12 + 11 + 10 + 9 + 8 + 7+ 6 + 5 + 4 + 3 + 2 + 1 = 78.)

“If you want to know how much you need to sell in new sales each month to hit that $120,000 goal, the answer is $1,539 ($120,000/78). That actually seems much more manageable, doesn't it? Based on poor forecasting, a miscalculation can turn off good salespeople who can't hit their quota,” he says.

KPIs for Sales Forecasting

As your sales forecasting improves, you reap bigger benefits, such as better planning and higher profits. So, you will want to assess and monitor your forecasting effort by using key performance indicators (KPIs).

Below are the main KPIs for sales forecasting. Some of them draw from statistics concepts, such as standard deviation, and computer applications and statistics guides can help you calculate them.

• Bias or Variance: This KPI tells how much the actual results deviated from the forecast over a given period of time. Calculate bias as an absolute number of dollars or units or as a percent of sales. A positive number means sales exceeded projections and a negative number indicates underperformance. Actual Units - Forecast Units = Bias
• Mean Absolute Deviation (MAD): This metric describes the size of your forecast error in total units or dollars. You calculate how much the actual results deviated from the forecast average, add the deviations, and divide the result by the total number of data points.   
• Mean Absolute Percentage Error (MAPE): This is similar to MAD, but gives the forecast error as a percent of sales volume. 
• Tracking Signal: This is another expression of forecast error and looks at how the error rate varies among forecast values. Normally, you expect all forecast amounts to be wrong by about the same degree. If, from one data point to another, there is a large variation in the error rate, you need to rework your model.  Tracking Signal = Accumulated Forecast Errors ÷ Mean Absolute Deviation
• Forecast Value Added: This metric measures how much better the forecast was than simply using unadjusted historical data. If your forecasting effort got you closer to actual than the so-called naive forecast (i.e., using historical figures as your forecast), you have added positive value. You calculate this metric by comparing the MAPE of your forecast to the naive forecast.
• Linearity: This looks at how sales are paced over the course of the period. As your reps seek to meet quota, you might see a flurry of deals at the end of the quarter. Or, deals might be spread evenly across the time period. The most stable situation is a deal cadence or velocity that is constant. If expressed as a trend line, this stable situation would appear visually as a flat line. This pattern is called highly linear .

Application of Sales Forecasting

Your sales forecast obviously gives you an idea of how much you will sell in the future, but sales forecasting has other important use cases. Here are five ways you can apply your forecast to business questions:

• Sales Planning: As noted earlier, your sales plan encompasses your goals, tactics, and processes for achieving your sales forecast. As part of this plan, your sales forecast helps you decide if you need to hire more sales reps to achieve your forecast and if you need to put more energy and resources into marketing.
• Demand Planning: Demand planning is the process of forecasting how much product your customers will want to buy and making sure inventory aligns with that forecast. In ideal conditions, forecast demand and sales would be virtually the same. But, consider a scenario in which your new product becomes the hot gift of the holiday season. You forecast demand of 100,000 units (the number consumers will want to buy). A large shipment turns out to be defective, and the product is unsellable. So, you forecast sales of just 75,000 units (how much you will actually sell.)   
• Financial Planning: Your sales forecast is vital to the work of your finance department. The finance team will rely on the forecast to build a budget, manage overhead, and figure out long-term capital needs. 
• Operations Planning: The unit-sales numbers in your forecast are also important for operations planners. They will look at the production required to meet those sales and confirm that manufacturing capacity can accommodate them. They will want to know when sales are likely to rise or fall, so they can avoid excess inventory. A big increase in sales will also require operations managers to make changes in warehousing and distribution. Retailers may change the product mix at individual stores based on your sales forecast.
• Product Planning: The trends you foresee in sales will have big implications for product managers too. They will look at products that you forecast as top sellers for ideas about new products or product modifications they should introduce. A forecast of declining sales may signal it is time to discontinue or revamp a product.

Levels of Maturity in Sales Forecasting

Sales forecasts can be simply scribbled-down estimates, or they can be statistical masterpieces produced with the aid of the most sophisticated technology. The style you pursue relates in large part to your level of forecasting maturity (as well as the size and history of your business). 

Below is a description of the four levels of the sales forecasting maturity model:

• Level One: In the beginning stages of sales forecasting, the estimates are usually not very accurate and take a lot of time to produce. The forecasting process depends on reps’ best guesses, and sales managers spend a lot of time gathering these guesses by interviewing each rep. Then, they roll them up into a consolidated forecast. Inconsistent data collection and personal bias can skew the results. Sales managers use spreadsheets, which quickly become outdated, and the forecasts often reflect little more than intuition.
• Level Two: As your forecasting culture grows, you are probably still inputting data by hand, and the forecast is often inaccurate or outdated. But, a CRM solution is enabling your team to have a shared repository for contacts, sales activity, and deal status. Reps don’t see value in spending time contributing to the forecast, and quality is weak. Your CRM automatically aggregates those results, so you can start to examine trends and anomalies. But, your system is not very flexible, and forecasting remains unwieldy and resource intensive.
• Level Three: At this point, automation starts to offer radical improvements in sales forecasting. Solutions backed by artificial intelligence automatically bring together data from a multitude of sources, including email, CRM, marketing platforms, chat logs, and calendars. There is no more manual data entry, and sales managers gain increased visibility into the sales pipeline. KPIs become reliable and an important tool for monitoring performance.
• Level Four: Technology ensures sales that data is accurate and timely. AI and machine learning find patterns and correlations in your historical data, and predictive analytics offer robust forecasting. The forecasting model is continually refined. Forecast accuracy rises, and sales managers can focus more of their time on supporting reps and developing opportunities. These tools make it apparent when reps are sandbagging or being too optimistic, and accountability increases.

Advances in Sales Forecasting Methodologies

While sales forecasting has been around as long as private enterprise, the field continues to evolve, and researchers are looking at ways to improve sales forecasting methodologies. 

Indiana University Professor Douglas J. Dalrymple performed an influential study in 1987 that surveyed how businesses prepared sales forecasts. He found that qualitative and naive techniques predominated, but that early adopters were reducing errors by using computer analysis. At this time, PCs were starting to proliferate and come down in price. 

By 2008, Zhan-Li Sun and his researchers at the Institute of Textiles and Clothing at Hong Kong Polytechnic University were experimenting with an advanced AI-driven technique called extreme learning machine to see if they could improve forecasts for the volatile retail fashion industry by quantifying the influence of factors such as design on sales.  

Scholars F.L. Chen and T.Y. Ou at the National Tsing Hua University in Taiwan took this further with a 2011 study. The study documented sales forecasting advances when combining extreme learning-machine, so-called Taguchi statistical methods for manufacturing quality with novel analysis theories that work on variables with imperfect information.

Features to Look for in a Sales Forecasting Tool

Paper forecasts and Excel spreadsheets quickly become cumbersome. Sales forecasting capability is available in CRM software, sales analytics and automation platforms, and AI-driven sales technology. These capabilities often overlap among these applications.

Here are some of the features to look for when evaluating a sales forecasting tool:

• Integrations with other software, such as ERP, CRM, marketing suites, contact management, calendars, and more
• Automated collection of data and sales rep activity
• Real-time reporting
• Robust data security
• Analytics and automated scoring of deals
• Insights on most promising deals
• Scenario modeling
• Lead scoring
• Automated forecast roll-ups or summaries by category and team
• Dashboards and graphic displays of KPIs
• Benchmarking
• Customizable forecasting algorithms
• Forecast auditing and error analysis

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How to write a sales forecast for a business plan

Table of Contents

What is a sales forecast?

Why do you need a sales forecast, how do you write a sales forecast, top-down or bottom-up, writing your sales forecast, calculating a sales forecast, how can countingup help manage your forecasting.

Sales forecasts are an important part of your business plan . If done correctly, they can give accurate projections of your business’ cash flow, and let you better prepare for the year ahead. They can also make it easier to find the right investors . While it’s easier for existing businesses with plenty of data, you can still calculate a sales forecast for a new business .

In this guide, we’ll explore:

• How can you manage your forecasting?

A sales forecast is a prediction of your business’ future revenue. In order to be an accurate prediction, the forecast is based on previous sales, current economic trends, and industry performance. Having a sales forecast is a useful tool, because it gives you a better idea of how to manage your business. 

Having a sales forecast is like using the past to have a peek into the future of your company. It might not be 100% accurate, but it can help you plan any future spending, or prevent any cash flow issues from occurring. 

You can also use your sales forecast to monitor your business’ progress. For instance, if your business regularly performs better than your forecast, it could be a sign that your business is continuing to grow. On the other hand, if your actual sales are frequently less than expected, this could be a sign that your business is struggling and needs adjustment. 

It’s important to remember that any projections you make aren’t guaranteed, there can be advantages and disadvantages of financial forecasting . 

Now we’ve run through why having a sales forecast can help you run your business, let’s look at how to write one. 

While there are two types of sales forecasting (top-down and bottom-up), one is a lot more accurate for small businesses than the other. A top-down forecast looks at the market as a whole and attributes a portion of the market to your business. 

A top-down approach may work for large businesses that already own a significant chunk of the market. When forecasting for a small business, it’s easy to overestimate your market share. For example, a 1% market share may not seem like a lot, but a small restaurant owning 1% of the £89.5 billion UK market is extremely unrealistic.

The alternative to top-down is bottom-up. A bottom-up sales forecast starts with existing company data (like customer or product information) and works up to revenue. Since this starts with the company, it’s easier to 

Your sales forecast is ultimately a prediction of your revenue over a set period. It considers the amount you think you’ll sell, and the cost of those sales. We’ve included how to calculate a sales forecast below.

A sales forecast consists of three separate values: revenue, cost of goods sold, and gross profit. For estimating values in the calculations below, it’s best to use any existing business data to be as accurate as possible. 

To calculate your predicted revenue:

• Make a list of your available goods and services
• Note the price of each of your goods and services
• Estimate the expected sales of each good or service
• Multiply the price by the estimated sales to get your estimated revenue
• Add them all together to get your total revenue

For example, if your food truck business sold pizzas at £10 and burgers at £5, you would multiply these values by how much you expected to sell. For calculating a weekly sales forecast, you might estimate selling 60 pizzas and 80 burgers. Your predicted revenue for that week would be £600 for pizzas and £400 for burgers — giving £1,000 total.

In order to figure out how much profit you’ll make, you also need to calculate your costs for those predicted sales. To calculate your predicted costs:

• Figure out how much each good or service will cost per unit
• Multiply each cost by the projected sales

Using the same example as above, assume a single pizza cost £3.50 to make and a burger cost £2. Using the estimated sales, the total cost for your pizzas (3.5 x 60) would be £210, and £160 for your burgers (2 x 80). Combining these two figures gives you a total cost of £370.

The last step is to work out your gross profit , and it’s a relatively simple calculation.

• Subtract the total predicted cost from your total predicted revenue

Continuing with the example above, your revenue (£1,000) minus your costs (£370), leaves you with a projected gross profit of £630 for the week. Using this estimate, you can then plan how much working capital your business should have access to. It’s important to remember that these are only estimates, and your actual values can be higher or lower than your forecast.

If you want your forecasts to be as accurate as possible, you need to refer to all of your business’ financial data. Since collecting and collating this data can be challenging, you may want to use financial management software like the Countingup app. 

When trying to calculate your sales forecasts, having an up-to-date log of your current sales can be hugely beneficial. By combining a business current account with accounting software, Countingup is the only software that provides real-time cash flow tracking. 

The Countingup app also provides business owners with access to automatically generated profit and loss statements. These can prove invaluable when trying to stay aware of all your business’ costs.

Start your three-month free trial today. Find out more here .

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Sales forecasting: How to create a sales forecast template (with examples)

A strong sales team is the key to success for most companies. They say a good salesperson can sell sand at the beach, but whether you’re selling products in the Caribbean or Antarctica, it all comes down to strategy. When you’re unsure if your current strategy is working, a sales forecast can help.

What is a sales forecast?

A sales forecast predicts future sales revenue using past business data. Your sales forecast can predict a number of different things, including the number of new sales for an existing product, the new customers you’ll gain, or the memberships you’ll sell in a given time period. These forecasts are then used during project planning to determine how much you should allocate towards new products and services. 

Why is sales forecasting important?

Sales forecasting helps you keep a finger on your business’s pulse. It sets the ground rules for a variety of business operations, including your sales strategy and project planning. Once you calculate your sales projections, you can use the results to assess your business health, predict cash flow, and adjust your plans accordingly.

An effective sales forecasting plan:

Predicts demand: When you have an idea of how many units you may sell, you can get a head start on production.

Helps you make smart investments: If you have future goals of expanding your business with new locations or products, knowing when you’ll have the income to do so is important. 

Contributes to goal setting: Your sales forecast can help you set goals outside of investments as well, like outshining competitors or hiring new team members.

Guides spending: Your sales forecast may be the wake-up call you need to set a budget and use cost control to reduce expenses.

Improves the sales process: You can change your current sales process based on the sales projections you’re unhappy with.

Highlights financial problems: Your sales forecast template will open your eyes to problem areas you may not have noticed otherwise. 

Helps with resource management: Do you have the resources you need to fill orders if it’s an accurate sales forecast? Your sales forecast can guide how you allocate and manage resources to hit targets.

When you have an accurate prediction of your future sales, you can use your projections to adjust your current sales process.

Sales forecasting methods

Sales forecasting is an important part of strategic business planning because it enables sales managers and teams to predict future sales and make informed decisions. But why are there multiple sales forecasting methods? Simply put, businesses vary in size, industry, and market dynamics, so no single methodology suits all.

Choosing the right sales forecasting method is more of an art than a science. It involves:

Analyzing your business size and industry

Assessing the available data and tools

Understanding your sales cycle's complexity

A few telltale signs that you've picked the correct approach include:

Improved accuracy in sales target predictions

Enhanced understanding of market trends

Better alignment with your business goals

Opportunity stage forecasting

Opportunity stage forecasting is a dynamic approach ideal for businesses using CRM systems like Salesforce. It assesses the likelihood of sales closing based on the stages of the sales pipeline. This method is particularly beneficial for sales organizations with a clearly defined sales process.

For example, a software company might use this method to forecast sales by examining the number of prospects in each stage of their funnel, from initial contact to final negotiation.

Pipeline forecasting method

The pipeline forecasting method is similar to opportunity stage forecasting but focuses more on the volume and quality of leads at each pipeline stage. It's particularly useful for businesses that rely heavily on sales forecasting tools and dashboards for decision-making.

A real estate agency could use it by examining the number of properties listed, the stage of negotiations, and the number of closings forecasted in the pipeline.

Length of sales cycle forecasting

Small businesses often prefer the length of sales cycle forecasting. It's straightforward and involves analyzing the duration of past sales cycles to predict future ones. This method is effective for businesses with consistent sales cycle lengths.

A furniture manufacturer, for instance, might use this method by analyzing the average time taken from initial customer contact to closing a sale in the past year.

Intuitive forecasting

Intuitive forecasting relies on the expertise and intuition of sales managers and their teams. It's less about spreadsheets and more about market research and understanding customer behavior. This method is often used with other, more data-driven approaches.

A boutique fashion store, for example, might use this method, relying on the owner's deep understanding of fashion trends and customer preferences.

Historical forecasting

Historical forecasting uses past performance data to predict future sales. This method is advantageous for businesses with ample historical sales data. It's less effective for new markets or rapidly changing industries.

An established book retailer could use historical data from previous years, considering seasonal trends and past marketing campaigns, to forecast next quarter's sales.

Multivariable analysis forecasting

Multivariable analysis forecasting is a more sophisticated method that's ideal for larger sales organizations. It analyzes factors like market trends, economic conditions, and marketing efforts to provide a holistic view of potential sales outcomes.

An automotive company, for example, could analyze factors like economic conditions, competitor activity, and past sales data to forecast future car sales.

How to calculate sales forecast

Sales forecasts determine how much you expect to do in sales for a given time frame. For example, let’s say you expect to sell 100 units in Q1 of fiscal year 2024. To calculate sales forecasts, you’ll use past data to predict future trends. 

When you’re first creating a forecast, it’s important to establish benchmarks that determine how much you normally sell of any given product to how many people. Compare historical sales data against sales quotas—i.e., how much you sold vs. how much you expected to sell. This type of analysis can help you set a baseline for what you expect to achieve every week, month, quarter, and so on.

For many companies, this means establishing a formula. The exact inputs will vary based on your products or services, but generally, you can use the following:

Sales forecast = Number of products you expect to sell x The value of each product

For example, if you sell SaaS products, your sales forecast might look something like this: 

SaaS FY24 Sales forecast = Number of expected subscribers x Subscription price

Ultimately, the sales forecasting process is a guess—but it’s an educated one. You’ll use the information you already have to create a data-driven forecasting model. How accurate your forecast is depends on your sales team. The sales team uses facts such as their prospects, current market conditions, and their sales pipeline. But they will also use their experience in the field to decide on final numbers for what they think will sell. Because of this, sales leaders are more likely to have better forecasting accuracy than new members of the sales team.

Sales forecast vs. sales goal

Your sales forecast is based on historical data and current market conditions. While you always hope your sales goals are attainable—and you can use data to estimate what your team is capable of—your goals might not line up directly with your forecast. This can be for a number of reasons, including wanting to create stretch goals that push your sales team beyond what they’ve done in the past or big, pie-in-the-sky goals that boost investor confidence.

How to create a sales forecast

There are different sales forecasting methods, and some are simpler than others. With the steps below, you’ll have a basic understanding of how to create a sales forecast template that you can customize to the method of your choice. 

1. Track your business data

Without details from your past sales, you won’t have anything to base your predictions on. If you don’t have past sales data, you can begin tracking sales now to create a sales forecast in the future. The data you’ll need to track includes:

Number of units sold per month

Revenue of each product by month

Number of units returned or canceled (so you can get an accurate sales calculation)

Other items you can track to make your predictions more accurate include:

Growth percentage

Number of sales representatives

Average sales cycle length

There are different ways to use these data points when forecasting sales. If you want to calculate your sales run rate, which is your projected revenue for the next year, use your revenue from the past month and multiply it by 12. Then, adjust this number based on other relevant data points, like seasonality.

Tip: The best way to track historical data is to use customer relationship management (CRM) software. When you have a CRM strategy in place, you can easily pull data into your sales forecast template and make quick projections.

2. Set your metrics

Before you perform the calculations in your sales forecast template, you need to decide what you’re measuring. The basic questions you should ask are:

What is the product or service you’re selling and forecasting for? Answering this question helps you decide what exactly you’re evaluating. For example, you can investigate future trends for a long-standing product to decide whether it’s worth continuing, or you can predict future sales for a new product. 

How far in the future do you want to make projections? You can decide to make projections for as little as six months or as much as five years in the future. The complexity of your sales forecast is up to you.

How much will you sell each product for, and how do you measure your products? Set your product’s metrics, whether they be units, hours, memberships, or something else. That way, you can calculate revenue on a price-per-unit basis.

How long is your sales cycle? Your sales cycle—also called a sales funnel—is how long it takes for you to make the average sale from beginning to end. Sales cycles are often monthly, quarterly, or yearly. Depending on the product you’re selling, your sales cycle may be unique. Steps in the sales cycle typically include:

Lead generation

Lead qualification

Initial contact

Making an offer

Negotiation

Closing the deal

Tip: You can still project customer growth versus revenue even if your company is in its early phases. If you don’t have enough historical data to use for your sales forecast template, you can use data from a company similar to yours in the market. 

3. Choose a forecasting method

While there are many forecasting methods to choose from, we’ll concentrate on two straightforward approaches to provide a clear understanding of how sales forecasting can be implemented efficiently. The top-down method starts with the total size of the market and works down, while the bottom-up method starts with your business and expands out.

Top-down method: To use the top-down method, start with the total size of the market—or total addressable market (TAM). Then, estimate how much of the market you think your business can capture. For example, if you’re in a large, oversaturated market, you may only capture 3% of the TAM. If the total addressable market is $1 billion, your projected annual sales would be $30 million. 

Bottom-up method: With the bottom-up method, you’ll estimate the total units your company will sell in a sales cycle, then multiply that number by your average cost per unit. You can expand out by adding other variables, like the number of sales reps, department expenses, or website views. The bottom-up forecasting method uses company data to project more specific results. 

You’ll need to choose one method to fill in your sales forecast template, but you can also try both methods to compare results.

Tip: The best forecasting method for you may depend on what type of business you’re running. If your company experiences little fluctuation in revenue, then the top-down forecasting method should work well. The top-down model can also work for new businesses that have little business data to work with. Bottom-up forecasting may be better for seasonal businesses or startups looking to make future budget and staffing decisions.

4. Calculate your sales forecast

You’ve already learned a basic way to calculate revenue using the top-down method. Below, you’ll see another way to estimate your projected sales revenue on an annual scale.

Divide your sales revenue for the year so far by the number of months so far to calculate your average monthly sales rate.

Multiply your average monthly sales rate by the number of months left in the year to calculate your projected sales revenue for the rest of the year.

Add your total sales revenue so far to your projected sales revenue for the rest of the year to calculate your annual sales forecast.

A more generalized way to estimate your future sales revenue for the year is to multiply your total sales revenue from the previous year.

Example: Let’s say your company sells a software application for $300 per unit and you sold 500 units from January to March. Your sales revenue so far is $150,000 ($300 per unit x 500 units sold). You’re three months into the calendar year, so your average monthly sales rate is $50,000 ($150,000 / 3 months). That means your projected sales revenue for the rest of the year is $450,000 ($50,000 x 9 months).

5. Adjust for external factors

A sales forecast predicts future revenue by making assumptions about your growth rate based on past success. But your past success is only one component of your growth rate. There are external factors outside of your control that can affect sales growth—and you should consider them if you want to make accurate projections. 

Some external factors you can adjust your calculations around include:

Inflation rate: Inflation is how much prices increase over a specific time period, and it usually fluctuates based on a country’s overall economic state. You can take your annual sales forecast and factor in inflation rate to ensure you’re not projecting a higher or lower number of sales than the economy will permit.

The competition: Is your market becoming more competitive as time goes on? For example, are you selling software during a tech boom? If so, assess whether your market share will shrink because of rising competition in the coming year(s).

Market changes: The market can shift as people change their behavior. Your audience may spend an average of six hours per day on their phones in one year. In the next year, mental health awareness may cause phone usage to drop. These changes are hard to predict, so you must stay on top of market news.

Industry changes: Industry changes happen when new products and technologies come on the market and make other products obsolete. One instance of this is the invention of AI technology.

Legislation: Although not as common, changes in legislation can affect the way companies sell their products. For example, vaping was a multi-million dollar industry until laws banned the sale of vape products to people under the age of 21. 

Seasonality: Many industries experience seasonality based on how human behavior and human needs change with the seasons. For example, people spend more time inside during the winter, so they may be on their computers more. Retail stores may also experience a jump in sales around Christmas time.

Tip: You can create a comprehensive sales plan to set goals for team members. Aside from revenue targets and training milestones, consider assigning each of these external factors to your team members so they can keep track of essential information. That way, you’ll have your bases covered on anything that may affect future sales growth. 

Sales forecast template

Below you’ll see an example of a software company’s six-month sales forecast template for two products. Product one is a software application, and product two is a software accessory. 

In this sales forecast template, the company used past sales data to fill in each month. They projected their sales would increase by 10% each month because of a 5% increase in inflation and because they gained 5% more of the market. They kept their price per unit the same as the previous year.

Putting both products in the same chart can help the company see that their lower-cost product—the software accessory—brings in more revenue than their higher-cost product. The company can then use this insight to create more low-cost products in the future.

Sales forecast examples

Sales forecasting is not a one-size-fits-all process. It varies significantly across industries and business sizes. Understanding this through practical examples can help businesses identify the most suitable forecasting method for their unique needs.

Sales forecasting example 1: E-commerce

In the e-commerce sector, where trends can shift rapidly, intuitive forecasting is often useful for making quick, informed decisions.

Scenario: An e-commerce retailer specializing in fashion accessories is planning for the upcoming festive season.

Trend analysis phase: The team spends the first week analyzing customer feedback and current fashion trends on social media, using intuitive forecasting to predict which products will be popular.

Inventory planning phase: Based on these insights, the next three weeks are dedicated to selecting and ordering inventory, focusing on products predicted to be in high demand.

Sales monitoring and adjustment: As the holiday season approaches, the team closely monitors early sales data, ready to adjust their inventory and marketing strategies based on real-time sales performance.

This approach allows the e-commerce retailer to stay agile , adapting quickly to market trends and customer preferences.

Sales forecasting example 2: Software development

For a software development company, especially one working with B2B clients, opportunity stage forecasting can help predict sales and manage the sales pipeline effectively.

Scenario: A software development company is launching a new project management tool.

Lead generation and qualification phase: In the initial month, the sales team focuses on generating leads, qualifying them, and categorizing potential clients based on their progress through the sales pipeline.

Proposal and negotiation phase: For the next two months, the team works on creating tailored proposals for high-potential leads and enters negotiation stages, using opportunity stage forecasting to predict the likelihood of deal closures.

Closure and review: In the final phase, the team aims to close deals, review the accuracy of their initial forecasts, and refine their approach based on the outcomes.

Opportunity stage forecasting enables the software company to efficiently manage its sales pipeline , focusing resources on the most promising leads and improving their chances of successful deal closures.

Pair your sales forecast with a strong sales process

A sales forecast is only one part of the larger sales picture. As your team members acquire leads and close deals, you can track them through the sales pipeline. A solid sales plan is the foundation of future success.  

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Business Forecasting: Why You Need It & How to Do It

Table of Contents

What is business forecasting, the importance of business forecasting, business forecasting process, business forecasting methods, elements of business forecasting, sources of data for forecasting, business forecasting only goes so far, how projectmanager helps business forecasting.

Well-run organizations don’t fly by the seat of their pants; they’re constantly working on business forecasting and business planning. Every decision and every process is based on data obtained from business forecasting, business intelligence tools, market research and scenario planning. Companies focus their energies on ways to predict market trends to help them set successful long-term strategies.

Some business forecasts are based on highly sophisticated statistical methods while others are based on experience and past data. Others simply follow a gut feeling. One thing remains constant: all industries rely on business forecasting.

Business forecasting refers to the process of predicting future market conditions by using business intelligence tools and forecasting methods to analyze historical data.

Business forecasting can be either qualitative or quantitative. Quantitative business forecasting relies on subject matter experts and market research while quantitative business forecasting focuses only on data analysis.

You can access historical data with project management tools such as ProjectManager , project management software that delivers real-time data for more insightful business forecasting. Our live dashboard requires no setup and automatically captures six project metrics which are displayed in easy-to-read graphs and charts. Get a high-level view of your project for better business planning. Get started with ProjectManager for free today.

Quantitative Forecasting

Quantitative forecasting is applicable when there is accurate past data available to predict the probability of future events. This method pulls patterns from the data that allow for more probable outcomes. The data used in quantitative forecasting can include in-house data such as sales numbers and professionally gathered data such as census statistics. Generally, quantitative forecasting seeks to connect different variables in order to establish cause and effect relationships that can be exploited to benefit the business.

Qualitative Forecasting

Qualitative forecasting is based on the opinion and judgment of consumers and experts. This business forecasting method is useful if you have insufficient historical data to make any statistically relevant conclusions. In such cases, an expert can help piece together the known bits of data you do have to try to make a qualitative prediction from that known information.

Qualitative business forecasting is also useful when little is known about the future in your industry. Relying on historical data is useless if that data is not relevant to the uncharted future you are approaching. This can be the case in innovative industries, or if there’s a new constraint entering the market that has never occurred before such as new tax law.

Business forecasting is critical for businesses whenever the future is uncertain or whenever an important strategic business decision is being made. The more the business can focus on the probable outcome, the more success the organization has as it moves forward.

Here are the steps that a business forecaster should typically follow:

• Define the question or problem you need to solve with your business forecasting efforts. For example, you might be interested in estimating whether your organization will be able to meet product demand for the next quarter.
• Identify the datasets and variables that need to be taken into consideration. In this case, datasets such as the sales records from the previous year and variables related to capacity, production and demand planning .
• Choose a business forecasting method that adjusts to your dataset and forecasting goals. That depends on whether your problem or question can be solved using a qualitative, quantitative or mixed approach.
• Based on the analysis of historical data, you can proceed to estimate future business performance. Keep in mind that the accuracy of your business forecasting depends on the quality of your data.
• Determine the discrepancy between your business forecast and actual business performance. Document your findings and improve your business forecasting process.

As stated above, there are two main types of business forecasting methods, qualitative and quantitative. We’ve compiled some of the more common forecasting models from both sides below.

Delphi Method

This qualitative business forecasting method consists in gathering a panel of subject matter experts and getting their opinions on the same topic in a manner in which they can’t know each other’s thoughts. This is done to prevent bias , which makes it possible for a manager to objectively compare their opinions and see if there are patterns, consensus or division.

Market Research

There are many market research techniques that evaluate the behavior of customers and their response to a certain product or service. Some of those market research methods collect and analyze quantitative data, such as digital marketing metrics and others qualitative data, such as product testing, or customer interviews.

Time Series Analysis

Also referred to as “trend analysis method,” this business forecasting technique simply requires the forecaster to analyze historical data to identify trends. This data analysis process requires statistical analysis as outliers need to be removed. More recent data should be given more weight to better reflect the current state of the business.

The Average Approach

The average approach says that the predictions of all future values are equal to the mean of the past data. Past data is required to use this method, so it can be considered a type of quantitative forecasting. This approach is often used when you need to predict unknown values as it allows you to make calculations based on past averages, where one assumes that the future will closely resemble the past.

The Naïve Approach

The naïve approach is the most cost-effective and is often used as a benchmark to compare against more sophisticated methods. It’s only used for time series data where forecasts are made equal to the last observed value. This approach is useful in industries and sectors where past patterns are unlikely to be reproduced in the future. In such cases, the most recent observed value may prove to be the most informative.

• Develop the Basis: Before you can start forecasting, you must develop a system to investigate the current economic situation around you. That includes your industry and its present position as well as its popular products to better estimate sales and general business operations.
• Estimating Future Business Operations: Now comes the estimation of future conditions, such as the course that future events are likely to take in your industry. Again, this is based on collected data to help with quantitative estimates for the scale of operations in the future.
• Regulating Forecasts: Whatever your forecast is, it must be compared to actual results. This is the only way to find deviations from the norm. Then the reasons for those deviations must be figured out, so action can be taken to correct those deviations in the future.
• Reviewing Forecasting Process: By reviewing the deviations between forecasts and actual performance data, improvements are made in the process, allowing you to refine and review the information for accuracy.

Your forecast will only be as good as the data you put into it. Before collecting data, ask yourself these questions:

• Why collect data?
• What kind of data?
• When to collect it?
• Where to collect it?
• Who will collect it?
• How will it be collected?

These are the questions that will shape your plan for the collection of data, a crucial facet of business forecasting. Once you have your plan, you can collect data from a variety of sources.

Primary Sources

Primary sources contain first-hand data, often collected with reporting tools . These are the ones that you or the person assigned this task to collect personally. If primary data is not available, you must go out and source it through interviews, questionnaires or observations.

Secondary Sources

Secondary sources contain published data or data that has been collected by others. This includes official reports from governments, publications, financial statements from banks or other financial institutions, annual reports of companies, journals, newspapers, magazines and other periodicals.

If business forecasting were a crystal ball, then everyone would be reaping the rewards of their foresight. While business forecasting is a tool to get a better view of what the future might have in store, there’s the argument that it’s wasting valuable time and resources on little return.

It’s true; you can follow the steps, use a variety of methodologies and still get it wrong. It is, after all, the future. There’s no way to ever manage all the variables that can impact future events. There are errors in calculations and the innate prejudices of the people managing the process, all of which add to the unpredictability of the results.

While you’re not going to have a clear, unobscured vision of the future by using business forecasting, it can provide you with insight into probable future trends to give your organization an advantage. Even a small step can be a great leap forward in the highly competitive world of business. By combining statistical and econometric models with experience, skill and objectivity, business forecasting is a formidable tool for any organization looking for a competitive advantage.

Clearly, business forecasting is a project unto itself. To manage a project and collect the data in a way that’s useful in the future, you need a project management tool that can help you plan your process and select the data that helps you decide on a way forward. 

ProjectManager is award-winning software that organizes projects with features that address every phase. The first thing in forecasting is choosing how you’ll take action and make a plan. For example, if you’re going to interview customers to see where the market is likely headed, you’ll need to schedule those interviews. Our online Gantt chart places those interviews as tasks on a timeline so you can get everyone interviewed before your deadline. 

Store All of Your Data in One Place

Those interviews will produce a lot of paperwork, and your data needs to be collected and stored somewhere easily accessible. You can attach notes to each task so the paperwork for each interviewee is saved with the notes that you took. You can also tag those tasks to make it easier to filter the project and locate the interview subjects for which you’re looking. If you’re worried that there’ll be too many documents and images attached to one task, don’t worry as we have unlimited file storage. 

ProjectManager can’t predict the future, but it does provide you with the tools you need to take advantage of business forecasting. Our project management software collects data in real-time, and stores past data, allowing you to filter information and pull up the metrics you need to make the right decision. Try it today with this free 30-day trial.

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Bringing a real-world edge to forecasting

CFOs know what a “good” forecasting process should look like: it should be accurate and compre­hensive but flexible enough to inform a range of critical business decisions—capital reallocation, hiring, strategy, sales, production, and more.

But CFOs also recognize that there is no “typical” forecasting process: it will look different in different organizations based on sector-specific factors, feedback cycles, and, most critically, how the forecast is being used. A maker of packaged foods that is releasing new products every quarter will rely on the forecast to keep a close watch on inventory, while a mining company that is considering new plant construction over the next three years will use the forecast to predict capacity and pricing.

How do your forecasts roll?

The best predictor of satisfaction among the CFOs we surveyed was whether or not they used a “rolling” forecast—one that provides frequent updates and adjusts inputs in a predictable way as conditions change. These types of forecasts are common in a retail or software setting, where customers provide near-real-time feedback through usage, traffic, and purchasing patterns. Rolling forecasts can be used to great effect in other situations as well. An organization that maintained industrial equipment built a simple model to update its forecasts as equipment came into the shop, rather than waiting until end-of-year estimates to adjust financial figures. This helped the company avoid sudden swings in recognized revenue in a percent-complete contract model. It also put the management team on the offensive as certain contracts over- or underperformed during the year.

Data availability is typically a major inhibitor of rolling forecasts. But it doesn’t have to be. Many companies have reams of data at their fingertips but don’t know where to get started. In our survey, we found that less than half of companies use any given form of nonfinancial internal data in creating their forecasts. Only 35 percent use external market data, and only 18 percent use additional types of data like weather, traffic, and other external factors as leading indicators of the business (exhibit). With such scant inputs, it’s no surprise that forecast outputs are often underwhelming.

Of course, there is still an important place for one-time forecasting to make major decisions. When it comes to drug development, the initiation of capital projects, or the decision to enter new markets, for instance, senior leaders’ over­­optimism about projects, concerns about sunk costs, and other biases can get in the way of their review of the full range of potential outcomes. In these cases, conducting an assessment against a carefully selected reference class of similar business scenarios can produce valuable insights.

What’s more, companies’ access to ever-larger data sets continues to complicate the forecasting process as much as it enlightens it, leading to even more variety in how forecasts are built. Many of the 130 CFOs we surveyed in a recent study 1 We polled 130 CFOs—90 from small and medium-size companies (less than $200 million in revenue) and 40 from large companies (greater than $1 billion in revenue). Half of them were members of the CFO Leadership Council, a North American professional association of finance executives. The research base included companies from a range of sectors, including technology, healthcare, and industrials. say they now run more than one type of forecasting process in their organizations—rolling forecasts to manage the business, and ad hoc processes to make specific decisions (see sidebar, “How do your forecasts roll?”).

But while many of the CFOs we surveyed expressed general satisfaction with the results of their fore­casting efforts (exhibit), some 40 percent also told us that their forecasts are not particularly accurate and that the process takes far too much time.

That’s likely because they use financial measures rather than operational outcomes as indicators of forecasting effectiveness—if they review the success of their forecasting efforts at all. A focus only on financial inputs can mask big issues with companies’ forecasting processes. By contrast, incorporating real-world operations insights into the financial-forecasting process can help CFOs and finance teams predict bottom-line issues early, based on a careful assessment of quality, operations, and customer-retention measurements. Senior leaders can then address performance issues before they become big problems, and the incentives of even the smallest subunit of the business would be targeted toward long-term value creation.

Integrating operations data within forecasts won’t be easy, of course. Finance and business leaders will need to let go of traditional budgeting mindsets and explore new ways of working together. The good news? Automation and other digital technologies now make that easier. And four criteria show promise for injecting more accuracy and reli­ability into forecasting models, regardless of industry: build a momentum case separate from the business plan, use a variety of operational and external inputs, automate the forecast, and measure effectiveness with a fine-grained level of detail.

Building a better forecast

The typical forecasting process follows a pattern that contributes to inaccurate projections and a defeating, self-reinforcing cycle.

At one large indus­trial manufacturing and services company, for instance, managers in the business units and sub­units are held to earnings targets that are rolled up into the overarching forecast. Over the years, these managers have become adept at finding the one or two things that will help them make their number, often at the expense of longer-term investment in quality, customer retention, and oper­a­tional effi­ciency. Under the typical finance-focused forecasting exercise, no one checks operational metrics so long as the bottom line comes in strong, which it had for a while. Now the com­pany’s per­formance is stuck in low gear: the most successful business units keep committing to higher numbers that eventually lead to a deterioration in quality, while the least successful businesses get scruti­nized, adjusted, and fixed. The winners and losers flip, and the cycle repeats itself.

Some companies have worked at breaking this disappointing pattern. They’ve begun rethinking how they measure the success of their forecasting processes—focusing on the following four questions:

Have we built a momentum case? Many financial-planning and analysis (FP&A) teams spend most of their time looking at historical data to explain current outcomes. When they do get to look forward, they are likely focused on the budget, or on rolling up commitments from different business units into the overall business plan. Sometimes the business plan itself passes for the forecast. This, of course, just creates an echo chamber.  No one is explicitly discussing how external factors and impending market shifts could affect forecasts. A better approach is to create a market-momentum case that relies on internal and external data as well as end-market trends to build the forecast. Once this unbiased momentum case is in place, senior managers can layer new and additional market infor­mation on top. Then any initiatives, investments, and strategic moves can be assessed relative to the base case.

In one industrial company that makes construction products, for instance, initiatives proposed across different lines of business were being valued in a vacuum. The teams charged with managing grouts and concrete, for instance, had no line of sight into what was going on with the frame-protection or frame-reinforcement business units. It was hard for senior leaders, then, to understand how to react to market shifts throughout the year and what actions the company should take. The FP&A team built a momentum case that set targets based on market dynamics in individual lines of business rather than allocating a single rate of improvement to all products. These targets much more closely reflected the full potential of the individual business lines, and, when compared with base-case and other scenarios, allowed the company to allocate resources and take on initiatives to address market changes with much more agility than before.

The CFO’s role in this process is to work with business-unit leaders to set realistic but aggressive targets in light of the market environment in which they operate. That means providing clear direction to all the business-unit finance leaders about which basic assumptions to use in the forecasts—for instance, market-growth rates—even if the process of forecasting sales and profit for each business remains distributed.

Are we using a variety of operational indicators and external inputs? Operational inputs are important leading indicators of performance; often, line leaders know how the company is faring months before the financial reports appear. Many times, however, operating data sit in disparate systems that don’t work well with financial enterprise resource planning (ERP) systems. And rather than adhere to a standard set of key performance indicators (KPIs) for use throughout the organization, managers at different levels use different indicators. Some track the business, some manage individual performance, and some review indicators of financial performance.

One aerospace company had collected thousands of data points on every aircraft in its fleet. However, when the time came to create the annual forecast, it used only a small fraction of the data because much of the information was inaccessible. Opera­tional and financial data were siloed, spread across many different IT systems. Recognizing a lost opportunity, the company created a thin analytics layer—a simple rules-based SQL program in a data lake—on top of its existing IT infrastructure. This program automatically gathered data from the multiple systems, allowing business-unit leaders to see infor­mation about the entire fleet on a single screen. They finally had operational KPIs integrated into the financial picture. If one site went overbudget on a repair, that information would get immediately recorded in the master model. Leaders at the company are now more confident about setting targets and stretch goals based on a distinct set of operational issues.

Surprisingly, the technical changes required were not difficult; in most cases, it takes no more than a few weeks or months (depending on product complexity) to rebuild forecasting models and link them to the company’s financial-management systems.

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Have we explored automation? Once business leaders have identified the most critical inputs to include in the forecast model, they should consider ways to automate the process and make it easier for business and operations teams to work together on forecasts.

In some cases, the company will need to explore new technologies and modeling techniques. Leadership at a multinational pharmaceutical company, for instance, used machine learning and advanced analytics to understand the variables affecting the performance of its clinical trials. The operations team worked with the business side to aggregate five years of data from more than 300 separate clinical trials (involving more than 100,000 patients) and to evaluate factors such as the clinical trials’ time and costs across multiple geographies. They saw correlations between the rate of enrollment in certain sites and the success of the trials, and they used the data to introduce improvements.

In other instances, the whole forecasting model may be run automatically using macro commands in an Excel spreadsheet, with only a handful of manual inputs from the operations team, the CFO, and the finance team.

Whichever method is chosen, companies can use data that already exist in the company’s ERP or other functional databases and, with simple transformations, spit out a real-time dashboard.

Once the CFO or another senior finance leader decides that automation is a high priority for FP&A, he or she should convene a small team (no more than three to five people from IT and finance) to “connect the pipes.” The team should tackle this challenge incrementally—automating some elements of the forecasting process initially and adding others once the value of the effort is proved.

Are we measuring effectiveness at a fine-grained level? Once the forecast incorporates a range of internal and external inputs, CFOs can test the accuracy of each input, as well as the accuracy of aggregate estimates. By monitoring detailed measures, such as labor productivity, on-time delivery, and other metrics associated with costs and revenues, business leaders will be able to spot the “softer” KPIs that are being overlooked in light of temporarily strong bottom-line perfor­mance. They can then react accordingly.

When the CFO and operations leader at one consumer-goods company reviewed underlying performance metrics for each of the business lines, they saw that a major business unit was being propped up by one rapidly growing product. Based on this insight, senior leadership decided to sell the underperforming parts of that business and double-down where they saw profitable growth. The team had until that point not looked past the simple financial performance of the business unit to the product-level sales and profitability.

If finance and operations leaders can maintain the forecast as a living model, with a clear feed-back loop, they can ensure that any forecasting failures (and there will be failures) lead to real improvements.

The right role for multiples in valuation

Getting started.

Making these changes to the forecasting processes can seem like a monumental shift—“rebuilding the plane while it is flying” is a common complaint among finance teams. With that in mind, the most effective move is to start small. For instance, the CFO should task the FP&A team in a single business unit or region to come up with a model and pressure test it both in the finance function and with nonfinancial leaders. Once there is agreement that the model is unearthing valuable insights, it can be automated, and a similar process can be scaled to the rest of the business.

It’s important that the forecast be pulled out of the politics of budgeting, and that inputs are streamlined, automated, and pressure tested. Even if the business units each manage their own forecast, there is a role for central FP&A to debias the process. The FP&A team at one fashion company, for instance, built a simple regression analysis to understand which business units were forecasting statistically significant changes in their performance or growth trajectory. The outliers were required to provide a detailed buildup of initiatives to prove the forecast was achievable.

Once the hard work of process reengineering is done, finance teams will see a dramatic change in the value of forecasts to the business. They can use time previously spent justifying assumptions to focus on delivering new ideas for improving the performance of the business—and serving as proactive business partners.

Ankur Agrawal is a partner in McKinsey’s New York office, and Jonathan Slonim is a consultant in the New Jersey office. Mark Khavkin is the chief financial officer of Pantheon Platform in San Francisco.

The authors wish to thank the CFO Leadership Council for its contributions to this article.

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What Is Business Forecasting? Predictions to Drive Success

November 29, 2021

by Alexandra Vazquez

In this post

Types of business forecasts, business forecasting methods, benefits of business forecasting, business forecasting challenges, business forecasting vs. scenario planning, business forecasting process, business forecasting examples.

It’s time to look inside your crystal ball and start forecasting. Forecasting gives you the tools you need to make reliable predictions about foreseeable events. 

What is business forecasting? 

Business forecasting is the process of analyzing data to predict future company needs and make insight-driven development decisions. 

There’s really no downside to being prepared! Building a strong forecast prepares businesses for potential issues and identifies areas for profitable growth. Even if your predictions end up being inaccurate, you’ll have all the necessary data and information to get closer to the final forecast. 

Some companies utilize   predictive analytics software   to collect and analyze the data necessary to make an accurate business forecast. Predictive analytics solutions give you the tools to store data, organize information into comprehensive datasets, develop predictive models to forecast business opportunities, adapt datasets to data changes, and allow import/export from other data channels. 

Businesses can create various types of forecasts with business forecasting strategies. Because historical data and market trends affect so many aspects of business, comprehensive predictions can help prepare almost every element of your company. 

• General business forecasting predicts overall market trends and external factors that affect your business’ success. 
• Accounting forecasting creates projections of future business costs . 
• Budget forecasting makes predictions for allocating the budget needed for future projects or addressing potential issues.   Budgeting and forecasting software   is an indispensable tool if you’re looking to forecast for budgeting your business activities.
• Financial forecasting projects a company’s monetary value as a whole. You can use the current assets and liabilities from your  balance sheet  to help you make a prediction.
• Demand forecasting predicts the future needs of your target customer base. 
• Supply forecasting works with demand forecasting to allocate the necessary resources for fulfilling upcoming customer demands.
• Sales forecasting predicts the expected success of the company offerings and how it’ll affect future sales and cash flow.
• Capital forecasting makes predictions about a company’s future assets and liabilities.

There are two main types of business forecasting methods: quantitative and qualitative. While both have unique approaches, they’re similar in their goals and the information used to make predictions – company data and market knowledge. 

Quantitative forecasting

The quantitative forecasting method relies on historical data to predict future needs and trends. The data can be from your own company, market activity, or both. It focuses on cold, hard numbers that can show clear courses of change and action. This method is beneficial for companies that have an extensive amount of data at their disposal.

There are four quantitative forecasting methods: 

• Trend series method: Also referred to as time series analysis, this is the most common forecasting method. Trend series collects as much historical data as possible to identify common shifts over time. This method is useful if your company has a lot of past data that already shows reliable trends.  
• The average approach: This method is also based on repetitive trends. The average approach assumes that the average of past metrics will predict future events. Companies most commonly use the average approach for inventory forecasting.
• Indicator approach: This approach follows different sets of indicator data that help predict potential influences on the general economic conditions, specific target markets, and supply chain. Some examples of indicators include changes in Gross Domestic Product (GDP), unemployment rate, and Consumer Price Index (CPI). By monitoring the applicable indicators, companies can easily predict how these changes may affect their own business needs and profitability by observing how they interact with each other. This approach would be the most effective for companies whose sales are heavily affected by specific economic factors.
• Econometric modeling: This method takes a mathematical approach using regression analysis to measure the consistency in company data over time. Regression analysis uses statistical equations to predict how variables of interest interact and affect a company. The data used in this analysis can be internal datasets or external factors that can affect a business, such as market trends, weather, GDP growth, political changes, and more. Econometric modeling observes the consistency in those datasets and factors to identify the potential for repeat scenarios in the future.

Qualitative forecasting

The qualitative forecasting method relies on the input of those who influence your company’s success. This includes your target customer base and even your leadership team. This method is beneficial for companies that don’t have enough complex data to conduct a quantitative forecast.

There are two approaches to qualitative forecasting:

• Market research: The process of collecting data points through direct correspondence with the market community. This includes conducting surveys, polls, and focus groups to gather real-time feedback and opinions from the target market. Market research looks at competitors to see how they adjust to market fluctuations and adapt to changing  supply and demand . Companies commonly utilize market research to forecast expected sales for new product launches.  
• Delphi method: This method collects forecasting data from company professionals. The company’s foreseeable needs are presented to a  panel of experts, who then work together to forecast the expectations and business decisions that can be made with the derived insights. This method is used to create long-term business predictions and can also be applied to sales forecasts.

There are several benefits to making effective forecasts for your business. You gain valuable insights into its different aspects and the future of its success.

• Foresee upcoming changes with a heads up on potential market changes that can affect your business. With the right prediction, you can strategize the decisions to succeed in the face of the challenges ahead before they become costly surprises.
• Decrease the cost of unexpected demand by preparing ahead of time. Business forecasting is a great starting point for   demand planning . If you plan to incorporate demand forecasting into your business processes, you’ll be prepared for upcoming market demands and avoid the extra costs associated with an influx of demand that you weren’t ready for.
• Increase customer satisfaction by giving them what they want, when they want it. Demand planning doesn’t just benefit you. With the right business forecast, your company can offer products or services to the target industry and meet their expectations. A company ready to serve its market is always met with customer satisfaction and loyalty.
• Set long- and short-term goals by tracking your progress. Business forecasting tools help you outline your future company objectives. Continuous predictions allow you to track the progress of your proposed goals as those future expectations become the present reality. 
• Learn from the past by analyzing it. Forecasting enables you to collect and study extensive historical company data. Keeping a close eye on this data can help you identify where things may have gone wrong in the past. With this new information, your company can make the necessary adjustments to avoid similar mistakes in the future.

While the benefits of business forecasting highlight all of the amazing advantages it has to offer, it’s not a surefire way to prepare for the future. Companies who plan to forecast should also keep the challenges in mind and make sure that forecasting has more pros than cons for their business. Below are some of the notable challenges of business forecasting.

• You can’t always expect the unexpected. While old data can help you gain insights into company processes and learn from mistakes, history doesn’t always repeat itself. Business forecasting isn’t a perfect process, and although helpful, it may not precisely predict future trends or business matters using old company data alone. It operates on the assumption that what happened will most likely happen again. Unfortunately, this is not always the case, and the hard work put into preparing for a forecasted event may never come to fruition. 
• It takes time to create an accurate forecast. Forecasting can be a lengthy process when started from scratch. Some companies find it challenging to gather the resources needed to begin predicting and allocate the time to do it correctly. 
• Historical data will always be outdated. There’s no way to know what’ll happen next. Although historical information is very valuable, it’s forever considered “old”. Forecasts are never based on the present and, therefore, are only as accurate as the data you already collected.

Business forecasting is often confused with scenario planning because of their shared goal of preparing for the future. Both rely on learning from past mistakes and reflecting on what decisions must be made to drive success. However, business forecasting and scenario planning differ in the preparation process. 

Business forecasting focuses on a problem at hand and uses historical data to predict what might happen next. It emphasizes   predictive analytics   and the need to eliminate existing uncertainties. The problem can be as broad as the actual performance of the entire company, or as specific as how a single product might sell in the future based on past market trends. 

While built on tangible data, forecasting is essentially a guess of the future and you need to make assumptions ahead of time to prepare for any predicted issues. Forecasting is an all-hands-on-deck approach that involves many departments, including analysts, economists, managers, and more.

Scenario planning   creates multiple scenarios to help prepare for the future. With these scenarios in mind, a company can begin planning a course of action to achieve the desired outcome. This includes creating step-by-step strategies and timelines for achieving objectives. 

While business forecasting focuses on past information, scenario planning takes the past, present, and future into consideration with learnings from the past, understanding the capabilities of the present, and aspiring for future success. Although a team’s input is important in scenario planning, company’s primary decision-makers carry out the bulk of the process.   

The way a company forecasts is always unique to its needs and resources, but the primary forecasting process can be summed up in five steps. These steps outline how business forecasting starts with a problem and ends with not only a solution but valuable learnings.

1. Choose an issue to address

The first step in predicting the future is choosing the problem you’re trying to solve or the question you’re trying to answer. This can be as simple as determining whether your audience will be interested in a new product your company is developing. Because this step doesn’t yet involve any data, it relies on internal considerations and decisions to define the problem at hand. 

2. Create a data plan

The next step in forecasting is to collect as much data as possible and decide how to use it. This may require digging up some extensive historical company data and examining the past and present market trends. Suppose your company is trying to launch a new product. In this case, the gathered data can be a culmination of the performance of your previous product and the current performance of similar competing products in the target market.

3. Pick a forecasting technique

After collecting the necessary data, it’s time to choose a business forecasting technique that works with the available resources and the type of prediction. All the forecasting models are effective and get you on the right track, but one may be more favorable than others in creating a unique, comprehensive forecast. 

For example, if you have extensive data on hand, quantitative forecasting is ideal for interpretation. Qualitative forecasting is best if you have less hard data available and are willing to invest in extensive market research.  

4. Analyze the data

Once the ball starts rolling, you can begin identifying patterns in the past and predict the probability of their repetition. This information will help your company’s decision-makers determine what to do beforehand to prepare for the predicted scenarios.

5. Verify your findings

The end of business forecasting is simple. You wait to see if what you predicted actually happens. This step is especially important in determining not only the success of your forecast but also the effectiveness of the entire process. Having done some forecasting, you can compare the present experience with these forecasts to identify potential areas for growth.

When in doubt, never throw away “old” data. The final information of one forecasting process can also be used as the past data for another forecast. It’s like a life cycle of business development predictions.

With the different types of business forecasting come different potential use cases. A company may choose to utilize several elements of business forecasting to prepare for various situations. Here are some real-life examples where business forecasting would be valuable. 

The seasoned veteran

Suppose you represent a company that has been in the market for a long time but has never tried business forecasting. Because of the long history of company data, you choose to try out quantitative business forecasting. Your aim is to make predictions using the most cost-effective and least time-consuming method. With those considerations, you may opt for the trend series method to manually identify common trends in old data, determine the likelihood of repeat instances, and forecast accordingly.

The new kid on the block

Imagine you are a new company that has entered the market to start selling your own brand of smartphones. You may think that business forecasting is impossible because you don’t have any historical company data to work off of. However, you can utilize qualitative business forecasting! Because the smartphone industry is a highly competitive one, you can use market research to take advantage of publicly available market data.

The one who wants the best of both worlds

Imagine you work for a recruiting company that has noticed that the country’s unemployment rate heavily affects company performance and has the data to prove it. As you have a clear indicator that directly impacts the potential for success, using the indicator approach to create long-term predictions would be the right call.

However, your company stresses the importance of integrating expert knowledge into the forecasting process. This extra note means that some qualitative forecasting can be used as well. You may choose to use the Delphi method to collect expert opinions and weigh that into the final forecasts as well.

What do the stars have in store for you?

Creating comprehensive predictions isn’t rocket science. With business forecasting, seeing the future is as easy as learning from the past. What you do with your findings is what will set you apart. 

Want to start forecasting for your business? Learn more about  business analytics  and how it helps collect the necessary data and insights. 

The future starts now

Automate business forecasting data analysis with predictive analytics software.

Alexandra Vazquez is a Senior Content Marketing Specialist at G2. She received her Business Administration degree from Florida International University and is a published playwright. Alexandra's expertise lies in writing for the Supply Chain and Commerce personas, with articles focusing on topics such as demand planning, inventory management, consumer behavior, and business forecasting. In her spare time, she enjoys collecting board games, playing karaoke, and watching trashy reality TV.

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Six Rules for Effective Forecasting

The goal of forecasting is not to predict the future but to tell you what you need to know to take meaningful action in the present.

Reprint: R0707K

The primary goal of forecasting is to identify the full range of possibilities facing a company, society, or the world at large. In this article, Saffo demythologizes the forecasting process to help executives become sophisticated and participative consumers of forecasts, rather than passive absorbers. He illustrates how to use forecasts to at once broaden understanding of possibilities and narrow the decision space within which one must exercise intuition.

The events of 9/11, for example, were a much bigger surprise than they should have been. After all, airliners flown into monuments were the stuff of Tom Clancy novels in the 1990s, and everyone knew that terrorists had a very personal antipathy toward the World Trade Center. So why was 9/11 such a surprise? What can executives do to avoid being blindsided by other such wild cards, be they radical shifts in markets or the seemingly sudden emergence of disruptive technologies?

In describing what forecasters are trying to achieve, Saffo outlines six simple, commonsense rules that smart managers should observe as they embark on a voyage of discovery with professional forecasters. Map a cone of uncertainty, he advises, look for the S curve, embrace the things that don’t fit, hold strong opinions weakly, look back twice as far as you look forward, and know when not to make a forecast.

People at cocktail parties are always asking me for stock tips, and then they want to know how my predictions have turned out. Their requests reveal the common but fundamentally erroneous perception that forecasters make predictions. We don’t, of course: Prediction is possible only in a world in which events are preordained and no amount of action in the present can influence future outcomes. That world is the stuff of myth and superstition. The one we inhabit is quite different—little is certain, nothing is preordained, and what we do in the present affects how events unfold, often in significant, unexpected ways.

• PS Paul Saffo ( [email protected] ) is a forecaster based in Silicon Valley, in California.

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Run » finance, how to create a financial forecast for a startup business plan.

Financial forecasting allows you to measure the progress of your new business by benchmarking performance against anticipated sales and costs.

When starting a new business, a financial forecast is an important tool for recruiting investors as well as for budgeting for your first months of operating. A financial forecast is used to predict the cash flow necessary to operate the company day-to-day and cover financial liabilities.

Many lenders and investors ask for a financial forecast as part of a business plan; however, with no sales under your belt, it can be tricky to estimate how much money you will need to cover your expenses. Here’s how to begin creating a financial forecast for a new business.

[Read more: Startup 2021: Business Plan Financials ]

Start with a sales forecast

A sales forecast attempts to predict what your monthly sales will be for up to 18 months after launching your business. Creating a sales forecast without any past results is a little difficult. In this case, many entrepreneurs make their predictions using industry trends, market analysis demonstrating the population of potential customers and consumer trends. A sales forecast shows investors and lenders that you have a solid understanding of your target market and a clear vision of who will buy your product or service.

A sales forecast typically breaks down monthly sales by unit and price point. Beyond year two of being in business, the sales forecast can be shown quarterly, instead of monthly. Most financial lenders and investors like to see a three-year sales forecast as part of your startup business plan.

Lower fixed costs mean less risk, which might be theoretical in business schools but are very concrete when you have rent and payroll checks to sign.

Tim Berry, president and founder of Palo Alto Software

Create an expenses budget

An expenses budget forecasts how much you anticipate spending during the first years of operating. This includes both your overhead costs and operating expenses — any financial spending that you anticipate during the course of running your business.

Most experts recommend breaking down your expenses forecast by fixed and variable costs. Fixed costs are things such as rent and payroll, while variable costs change depending on demand and sales — advertising and promotional expenses, for instance. Breaking down costs into these two categories can help you better budget and improve your profitability.

"Lower fixed costs mean less risk, which might be theoretical in business schools but are very concrete when you have rent and payroll checks to sign," Tim Berry, president and founder of Palo Alto Software, told Inc . "Most of your variable costs are in those direct costs that belong in your sales forecast, but there are also some variable expenses, like ads and rebates and such."

Project your break-even point

Together, your expenses budget and sales forecast paints a picture of your profitability. Your break-even projection is the date at which you believe your business will become profitable — when more money is earned than spent. Very few businesses are profitable overnight or even in their first year. Most businesses take two to three years to be profitable, but others take far longer: Tesla , for instance, took 18 years to see its first full-year profit.

Lenders and investors will be interested in your break-even point as a projection of when they can begin to recoup their investment. Likewise, your CFO or operations manager can make better decisions after measuring the company’s results against its forecasts.

[Read more: ​​ Startup 2021: Writing a Business Plan? Here’s How to Do It, Step by Step ]

Develop a cash flow projection

A cash flow statement (or projection, for a new business) shows the flow of dollars moving in and out of the business. This is based on the sales forecast, your balance sheet and other assumptions you’ve used to create your expenses projection.

“If you are starting a new business and do not have these historical financial statements, you start by projecting a cash-flow statement broken down into 12 months,” wrote Inc . The cash flow statement will include projected cash flows from operating, investing and financing your business activities.

Keep in mind that most business plans involve developing specific financial documents: income statements, pro formas and a balance sheet, for instance. These documents may be required by investors or lenders; financial projections can help inform the development of those statements and guide your business as it grows.

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Financial Forecasting: How to Do It with Different Methods, Models, & Software

Published: June 07, 2023

Planning for your company's future is significantly easier and more effective when you have a picture of what that future might look like. That's why any business interested in sound financial planning needs to have a grip on financial forecasting — the process of making accurate projections that can frame thoughtful, productive financial decisions in real time.

Here, we'll explore the concept of financial forecasting in depth, review some popular financial forecasting models, go over some prominent financial forecasting methods, and see some of the best financial forecasting software solutions on the market.

1. What is financial forecasting?

Forecasting vs. Budgeting

2. Financial Forecasting Models

• Top-Down Financial Forecasting
• Delphi Financial Forecasting
• Statistical Forecasting
• Bottom-Up Financial Forecasting

3. Financial Forecasting Methods

• Straight Line
• Simple Linear Regression
• Multiple Linear Regression
• Moving Average

4. How to do Financial Forecasting

5. Financial Forecasting Software

What is financial forecasting?

Financial forecasting is a process where a business leverages its current and past financial information to project its future financial performance. Forecasts are typically applied to assist with budgeting, financial modeling, and other key financial planning activities.

Financial forecasting is often conflated with the other key financial planning processes it generally informs — namely, budgeting. Though the two activities are often closely linked, it's important to differentiate between them.

The difference between a financial forecast and a budget boils down to the distinction between expectations and goals. A forecast details what a business can realistically expect to achieve over a given period.

When done correctly, it represents a reasonable estimate of how a company will likely perform — based on current and historical financial data, broader economic trends, foreseeable factors that might impact performance, and other variables that can be viably accounted for.

A budget, on the other hand, is the byproduct of a financial analysis rooted in what a business would like to  achieve. It's typically updated once per year and is ultimately compared to the actual results a business sees to gauge the company's overall performance.

Now that we have a picture of what financial forecasting is, let's take a look at some of its most popular models.

Financial Forecasting Models

1. top-down financial forecasting.

Top-down forecasting is a financial forecasting model where a company starts by analyzing broader market data and ultimately whittles down company-specific revenue projections from there.

It's one of the more simple, straightforward forecasting models — essentially amounting to a company looking at its total market size and calculating potential revenue based on its assumed market share with the help of  fp&a software  to collect all the data you need.

Top-Down Financial Forecasting Example

Let's say a company occupies space in a market that generates an estimated $1,000,000,000 in revenue annually. If the business assumes it will have a market share of 2.5%, a top-down forecast would suggest that it will see $25,000,000 in revenue in the coming year.

Benefits of Top-Down Forecasting

• It provides a more streamlined approach for larger, established businesses with diverse revenue sources than a concentrated, product-level forecast.
• It's often the only viable forecasting avenue for early-stage companies without extensive financial data.

Drawbacks of Top-Down Forecasting

• It's often seen as hastier and more superficial than more granular forecasting methods.
• A top-down forecast is generally seen more as a starting point than a concrete projection.

2. Delphi Forecasting

The term "Delphi" here is a reference to the ancient Greek city where the Greeks consulted the mythical oracle Pythia . Fittingly, the Delphi forecasting method involves financial forecasters consulting experts for their takes on projections.

With this method, a business sends multiple rounds of questionnaires to a panel of experts, covering the company's financial data. With each new round, the experts see an aggregated summary of the previous round and adjust their perspectives accordingly. Ultimately, the hope is that a few rounds can produce a consensus among the experts that can be applied to the company's financial projections.

Delphi Financial Forecasting Example

If a company were to leverage the Delphi model, it would gather a diverse array of experts and send them questionnaires without any of them ever meeting face-to-face. After one round, the experts would each receive a summary, detailing what the other experts thought with respect to the business's potential financial performance.

The experts would be at least partially moved by the group response and submit a new questionnaire accordingly. The panel would continue to receive questionnaires until it arrived at a consensus, and the forecast would be based on that insight.

Benefits of Delphi Forecasting

• It tends to be more objective than conventional, in-house forecasting.
• Contributions are anonymous, so respondents can answer candidly.

Drawbacks of Delphi Forecasting

• The method doesn't allow for a productive, open dialogue like a face-to-face meeting would.
• Response times can be long or unpredictable, prolonging forecast delivery.

3. Statistical Forecasting

Statistical forecasting is a broad term that accounts for a variety of forecasting methods. At its core, the model is exactly what it sounds like — forecasting based on statistics. More specifically, the term is essentially a catch-all that covers forecasting rooted in the use of statistics derived from historical, quantitative data.

Statistical Financial Forecasting Example

One method that generally falls under the statistical financial forecasting umbrella is the moving average method listed below. A company might look at the revenue it generated over the past 100 days and apply that statistic to its potential performance over the next similar period.

Benefits of Statistical Forecasting

• It rests on a more solid basis than other methods.
• It can be more straightforward than other methods — provided you have the right data.

Drawbacks of Statistical Forecasting

• Certain methods that fall under this umbrella can provide relatively hasty estimates, relative to other models.
• Companies without extensive historical data might not be able to produce reliable statistical forecasts.

4. Bottom-Up Financial Forecasting

As you can probably assume, bottom-up financial forecasting is essentially the opposite of top-down forecasting — it's a model where a company starts by referencing its detailed, ground-level customer or product information and works its way up to a broader revenue projection.

Bottom-Up Financial Forecasting Example

A bottom-up financial forecast could start with a business taking a look at its sales volume — or the total number of units of its product it moved in a given period — from the previous year. Then, it would estimate the price it expects to charge for that product in the coming year. From there, it would calculate its projected revenue by multiplying the two figures.

Obviously, that example is unrealistically straightforward. In most cases, the business in question here would consider other lower-level variables as well — potentially including customer-related information like total customers or retention rate.

Benefits of Bottom-Up Forecasting

• The model allows for more detailed analysis than most others.
• It offers more room for input from various departments.

Drawbacks of Bottom-Up Forecasting

• Any errors made at the micro-level can be amplified to the macro-level with this model.
• A thorough bottom-up forecast can be time-consuming and particularly labor-intensive.

Financial Forecasting Methods

1. Straight Line

True to its name, straight line forecasting is probably the most straightforward financial forecasting method businesses can leverage. It's rooted in basic math and tends to provide rougher projections than the other, more sophisticated methods listed here.

With straight line forecasting, a business gathers rough growth estimates — typically pulled from past figures — and applies them to coming months, quarters, or years. It's generally employed when a company assumes it will see steady growth over a given period.

For instance, if your business has seen revenue reliably grow 5% year over year for the past four years, you might use that figure to guide your straight line forecasting and assume that level of growth will continue for the next few years.

2. Simple Linear Regression

The simple linear regression is a common financial forecasting method where a business explores the relationship between two variables — one independent and one dependent. For instance, a company could use this method to forecast revenue by gauging how it might be impacted by shifts in GDP.

3. Multiple Linear Regression

Simple linear regression analysis often isn't enough to make accurate financial projections, as financial performance is rarely a function of a single factor. The nature of the multiple linear regression is covered by its name — instead of trying to predict how financial performance will play out in response to a single variable, the model considers two or more independent factors.

4. Moving Average

Moving average forecasting is a method most commonly used to identify the trend-direction of a stock, but businesses can still leverage it to project their financial performance. It involves taking the arithmetic mean of a dataset from a past period and applying that average to future projections. The method is typically used to evaluate potential performance over shorter periods — like weeks, months, or quarters.

How to do Financial Forecasting

1. Define your purpose for using a financial forecast.

To get the most out of a financial forecast, you have to know why you're using it in the first place. Ask yourself questions such as:

• What are you hoping to learn and take away from its results?
• Are you trying to get a better gauge of the company budget?
• Are you trying to reach a certain goal or threshold for product sales?

When you have clear intent behind your financial forecast, you'll have a more concise and clear result to search for once you begin.

2. Gather historical data.

To track the progress of your financial forecast, you have to have a good idea of your current and past finances. Take the time to analyze your historical financial data and records, including:

• Revenue and losses
• Equity and liabilities
• Fixed costs
• Investments
• Earnings per share

Your forecast will only be as accurate as the information you collect, so get as much relevant data as possible for better results and understanding.

3. Set a time frame for your forecast.

Decide how far into the future you're committed to recording and documenting your business' financial performance. This can look like weeks, months, quarters, or even years of data collection. 

It's most common for a business to conduct a forecast over the course of a fiscal year, but it's unique for every business. And if you need to adjust your forecast as time goes by, or if your goals change, you're ultimately in control and can make adjustments if need be.

4. Choose a forecasting method.

We've already give you four financial forecasting methods, so when choosing the one for your business, make sure it aligns with your previously declared purpose and goals.

5. Monitor and analyze your forecast results.

As your financial forecast delivers new data, you should monitor and analyze it differently. When you get enough data, try to think about how you can use it:

• Identify potential issues: Monitoring and analyzing financial results can help a business identify potential issues before they become more significant problems. For example, if expenses are higher than anticipated, a business can identify the cause and take corrective action to prevent it from negatively impacting financial performance.
• Measure progress towards goals: A financial forecast provides a business with financial goals and expectations. Weighing financial results against these goals enables a business to measure its progress toward achieving them. This can help the business identify where it is falling short and adjust to get back on track.
• Manage cash flow: Monitoring and analyzing financial results can give a business insights into its cash flow situation. By understanding how much cash is coming in and going out, a business can make smarter decisions about budgeting and spending.

And it doesn't have to be a tedious task to analyze your financial data, thankfully there's plenty of forecasting, decision-making and financial-planning tools available for this purpose. Let's go through some of our favorites.

Financial Forecasting Software

1. sage intacct, pricing: contact for pricing.

Sage Intacct is a multifaceted accounting and financial planning software with an accessible interface and a suite of features that can streamline your financial forecasting time by over 50%. The platform's automated forecasting resources effectively eliminate the stress, legwork, and room for error that often come with financial planning via spreadsheets.

Best for Collaboration

Sage Intacct separates itself from similar applications through its accessibility and room for collaboration. The software is particularly user-friendly and offers a singular, centralized solution for virtually any stakeholder within an organization to easily contribute to and make sense of financial projections.

2. PlanGuru

Pricing: plans starting at $99 per month.

PlanGuru is a dedicated financial forecasting software — supporting 20 separate forecasting methods that can cover projections of up to 10 years. The program also allows you to incorporate non-financial data into your forecasts and has scenario analysis features to help you interpret the ramifications of potentially impactful events. PlanGuru also offers a range of plans to suit most SMBs' budgets.

Best for Pure Financial Forecasting

Some of the other resources listed here are multifaceted accounting solutions that happen to cover financial forecasting — not PlanGuru. This application is primarily dedicated to creating financial projections.

As I mentioned, it offers 20 unique financial forecasting methods to support more effective strategic planning — along with a host of other features tailored to help you gauge your future financial performance. If you're interested in a cost-effective, forecasting-specific platform, look into PlanGuru.

3. Workday Adaptive Planning

Workday Adaptive Planning provides financial forecasting resources that reconcile accessibility with powerful functionality. The software lets you leverage both real-time financial and operational data to create and compare multiple accurate, effective what-if scenario models. It also allows you to forecast across any time horizon — whether it be daily, monthly, quarterly, or long-term.

Best for a Dynamic Range of Forecasting Options

Workday Adaptive Planning's ability to support detailed bottom-up and top-down forecasts makes it a particularly attractive option for businesses of virtually any size. It allows you to create compelling forecasts based on targets from executive guidance or ground-level operational plans.

That dynamic range of forecasting options helps set the program apart from similar options. If you're interested in software that lets you forecast from various perspectives without sacrificing accuracy or effectiveness, look into Workday Adaptive Planning.

4. Limelight

Limelight is an integrated, web-based financial planning that provides businesses with a centralized solution for almost all of their forecasting needs. Designed primarily to suit finance and accounting teams, the software offers powerful general automation and automated data integration to streamline and simplify forecasting without losing out on quality.

Best for a Familiar, Excel-Esque UX

Limelight's user experience is designed to reflect Excel — making it a familiar, particularly easy option for CFOs, controllers, budget managers, and other users to adapt to. If you're interested in a powerful forecasting resource with that kind of accessibility, Limelight might be your best option.

It's never too late to run a financial forecast.

Forecasting is a central component of sound, productive financial planning. If you have no idea what to expect financially, you'll have a hard time preparing for obstacles, setting attainable goals, and identifying aspects of your business that should be of particular interest. No matter the scale or nature of your organization, having a pulse on your financial future is always in your best interest.

Editor's note: This article was originally published in June 2022 and has been updated for comprehensiveness.

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How to Create a Cash Flow Forecast

10 min. read

Updated May 3, 2024

A good cash flow forecast might be the most important single piece of a business plan . All the strategy, tactics, and ongoing business activities mean nothing if there isn’t enough money to pay the bills.

That’s what a cash flow forecast is about—predicting your money needs in advance.

By cash, we mean money you can spend. Cash includes your checking account, savings, and liquid securities like money market funds. It is not just coins and bills.

Profits aren’t the same as cash

Profitable companies can run out of cash if they don’t know their numbers and manage their cash as well as their profits.

For example, your business can spend money that does not show up as an expense on your  profit and loss statement . Normal expenses reduce your profitability. But, certain spending, such as spending on inventory, debt repayment, and purchasing assets (new equipment, for example) reduces your cash but does not reduce your profitability. Because of this, your business can spend money and still be profitable.

On the sales side of things, your business can make a sale to a customer and send out an invoice, but not get paid right away. That sale adds to the revenue in your profit and loss statement but doesn’t show up in your bank account until the customer pays you.

That’s why a cash flow forecast is so important. It helps you predict how much money you’ll have in the bank at the end of every month, regardless of how profitable your business is.

Learn more about the differences between cash and profits .

• Two ways to create a cash flow forecast

There are several legitimate ways to do a cash flow forecast. The first method is called the “Direct Method” and the second is called the “Indirect Method.” Both methods are accurate and valid – you can choose the method that works best for you and is easiest for you to understand.

Unfortunately, experts can be annoying. Sometimes it seems like as soon as you use one method, somebody who is supposed to know business financials tells you you’ve done it wrong. Often that means that the expert doesn’t know enough to realize there is more than one way to do it.

• The direct method for forecasting cash flow

The direct method for forecasting cash flow is less popular than the indirect method but it can be much easier to use.

The reason it’s less popular is that it can’t be easily created using standard reports from your business’s accounting software. But, if you’re creating a forecast – looking forward into the future – you aren’t relying on reports from your accounting system so it may be a better choice for you.

That downside of choosing the direct method is that some bankers, accountants, and investors may prefer to see the indirect method of a cash flow forecast. Don’t worry, though, the direct method is just as accurate. After we explain the direct method, we’ll explain the indirect method as well.

The direct method of forecasting cash flow relies on this simple overall formula:

Cash Flow = Cash Received – Cash Spent

And here’s what that cash flow forecast actually looks like:

Let’s start by estimating your cash received and then we’ll move on to the other sections of the cash flow forecast.

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Forecasting cash received

You receive cash from three primary sources: 

1. Sales of your products and services

In your cash flow forecast, this is the “Cash from Operations” section. When you sell your products and services, some customers will pay you immediately in cash – that’s the “cash sales” row in your spreadsheet. You get that money right away and can deposit it in your bank account. You might also send invoices to customers and then have to collect payment. When you do that, you keep track of the money you are owed in  Accounts Receivable . When customers pay those invoices, that cash shows up on your cash flow forecast in the “Cash from Accounts Receivable” row. The easiest way to think about forecasting this row is to think about what invoices will be paid by your customers and when.

2. New loans and investments in your business

You can also receive cash by getting a new loan from a bank or an investment. When you receive this kind of cash, you’ll track it in the rows for loans and investments. It’s worth keeping these two different types of cash in-flows separate from each other, mostly because loans need to be repaid while investments do not need to be repaid.

3. Sales of assets

Assets are things that your business owns, such as vehicles, equipment, or property. When you sell an asset, you’ll usually receive cash from that sale and you track that cash in the “Sales of Assets” section of your cash flow forecast. For example, if you sell a truck that your company no longer needs, the proceeds from that sale would show up in your cash flow statement.

Forecasting cash spent

Similar to how you forecast the cash that you plan on receiving, you’ll forecast the cash that you plan on spending in a few categories:

1. Cash spending and paying your bills

You’ll want to forecast two types of cash spending related to your business’s operations: Cash Spending and Payment of Accounts Payable. Cash spending is money that you spend when you use petty cash or pay a bill immediately. But, there are also bills that you get and then pay later. You track these bills in  Accounts Payable . When you pay bills that you’ve been tracking in accounts payable, that cash payment will show up in your cash flow forecast as “payment of accounts payable”. When you’re forecasting this row, think about what bills you’ll pay and when you’ll pay them. In this section of your cash flow forecast, you exclude a few things: loan payments, asset purchases, dividends, and sales taxes. These will show up in the following sections.

2. Loan Payments

When you make loan repayments, you’ll forecast the repayment of the principal in your cash flow forecast. The interest on the loan is tracked in the “non-operating expense” that we’ll discuss below.

3. Purchasing Assets

Similar to how you track sales of assets, you’ll forecast asset purchases in your cash flow forecast. Asset purchases are purchases of long-lasting, tangible things. Typically, vehicles, equipment, buildings, and other things that you could potentially re-sell in the future. Inventory is an asset that your business might purchase if you keep inventory on hand.

4. Other non-operating expenses and sales tax

Your business may have other expenses that are considered “non-operating” expenses. These are expenses that are not associated with running your business, such as investments that your business may make and interest that you pay on loans. In addition, you’ll forecast when you make tax payments and include those cash outflows in this section. 

Forecasting cash flow and cash balance

In the direct cash flow forecasting method, calculating cash flow is simple. Just subtract the amount of cash you plan on spending in a month from the amount of cash you plan on receiving. This will be your “net cash flow”. If the number is positive, you receive more cash than you spend. If the number is negative, you will be spending more cash than you receive. You can predict your cash balance by adding your net cash flow to your cash balance.

• The indirect method

The indirect method of cash flow forecasting is as valid as the direct and reaches the same results.

Where the direct method looks at sources and uses of cash, the indirect method starts with net income and adds back items like depreciation that affect your profitability but don’t affect the cash balance.

The indirect method is more popular for creating cash flow statements about the past because you can easily get the data for the report from your accounting system.

You create the indirect cash flow statement by getting your Net Income (your profits) and then adding back in things that impact profit, but not cash. You also remove things like sales that have been booked, but not paid for yet.

Here’s what an indirect cash flow statement looks like:

There are five primary categories of adjustments that you’ll make to your profit number to figure out your actual cash flow:

1. Adjust for the change in accounts receivable

Not all of your sales arrive as cash immediately. In the indirect cash flow forecast, you need to adjust your net profit to account for the fact that some of your sales didn’t end up as cash in the bank but instead increased your accounts receivable.

2. Adjust for the change in accounts payable

Very similar to how you make an adjustment for accounts receivable, you’ll need to account for expenses that you may have booked on your income statement but not actually paid yet. You’ll need to add these expenses back because you still have that cash on hand and haven’t paid the bills yet.

3. Taxes & Depreciation

On your income statement, taxes and depreciation work to reduce your profitability. On the cash flow statement, you’ll need to add back in depreciation because that number doesn’t actually impact your cash. Taxes may have been calculated as an expense, but you may still have that money in your bank account. If that’s the case, you’ll need to add that back in as well to get an accurate forecast of your cash flow.

4. Loans and Investments

Similar to the direct method of cash flow, you’ll want to add in any additional cash you’ve received in the form of loans and investments. Make sure to also subtract any loan payments in this row.

5. Assets Purchased and Sold

If you bought or sold assets, you’ll need to add that into your cash flow calculations. This is, again, similar to the direct method of forecasting cash flow.

• Cash flow is about management

Remember: You should be able to project cash flow using competently educated guesses based on an understanding of the flow in your business of sales, sales on credit, receivables, inventory, and payables.

These are useful projections. But, real management is minding the projections every month with plan versus actual analysis so you can catch changes in time to manage them. 

A good cash flow forecast will show you exactly when cash might run low in the future so you can prepare. It’s always better to plan ahead so you can set up a line of credit or secure additional investment so your business can survive periods of negative cash flow.

• Cash Flow Forecasting Tools

Forecasting cash flow is unfortunately not a simple task to accomplish on your own. You can do it with spreadsheets, but the process can be complicated and it’s easy to make mistakes. 

Fortunately, there are affordable options that can make the process much easier – no spreadsheets or in-depth accounting knowledge required.

If you’re interested in checking out a cash flow forecasting tool, take a look at LivePlan for cash flow forecasting. It’s affordable and makes cash flow forecasting simple.

One of the key views in LivePlan is the cash flow assumptions view, as shown below, which highlights key cash flow assumptions in an interactive view that you can use to test the results of key assumptions:

With simple tools like this, you can explore different scenarios quickly to see how they will impact your future cash.

See why 1.2 million entrepreneurs have written their business plans with LivePlan

Tim Berry is the founder and chairman of Palo Alto Software , a co-founder of Borland International, and a recognized expert in business planning. He has an MBA from Stanford and degrees with honors from the University of Oregon and the University of Notre Dame. Today, Tim dedicates most of his time to blogging, teaching and evangelizing for business planning.

Table of Contents

• Profits aren’t the same as cash

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How to create a sales forecast for your small business

July 25, 2023 | 7 minute read

What you know about tomorrow can help you make better decisions about running your small business today. A sales forecast can be a helpful tool in estimating future sales, so you can take that information into account in your planning. Simply put, a sales forecast estimates the quantity of goods and services you can reasonably expect to sell over a specified period, the cost of those goods and services and the potential profit. It’s based on your sales in the past, industry benchmarks and market conditions. 

A sales forecast is an invaluable tool for better  managing your cash flow , spending, staffing and more. Once you complete your forecast, you’ll have a better sense of what’s driving your revenues and profits, know where to put your time and resources and be able to identify efforts that are not fueling growth so you can consider eliminating them. 

Why sales forecasting is important

A sales forecast helps you understand your financial position. It can be a good starting point for setting goals and provides guidance in many areas of your business, such as planning for new hires, purchasing inventory and equipment, knowing when to preserve cash, increasing your marketing budget or alerting you that you need to find new  ways to make more money . It can also help you illustrate your business’s potential to investors.

What factors impact a sales forecast?

A forecast is really an educated guess. There are any number of conditions that might shake up your projections, such as new laws and regulations. A downturn in the economy could mean a change in business conditions, making it harder to get credit. A dip in consumer confidence could lead to less spending on your company’s goods and services. New competition in your market, a drop in customer satisfaction or extreme weather (a major storm that essentially shuts down a city for a few days, for example) could all make a difference in what you thought was going to happen. Something like seasonality can also impact your forecast. Internal factors like new production processes and procedures can also keep you from hitting your target. 

Sales forecasting methods

There are several methods to creating a sales forecast. Here are three that many small businesses use:

Historical forecasts

This method is based on your business’s past performance. If you’ve been in business for a year or more, you can look back at data by the week, month, quarter or year. If you’ve launched your business recently, this option won’t work well because you won’t have enough data available. 

Bottom-up forecasts

To come up with these forecasts, you must project the number of units you will sell, then multiply that figure by the average cost per unit. If you run a larger small business, you can also include metrics like the number of locations, sales representatives or online interactions. The rationale behind a bottom-up sales forecast is to begin with the smallest components of the forecast and build up from there. The advantage of this type of forecast is that if any variables change (like cost per item or number of reps), the forecast is easy to adjust. 

Top-down sales forecasts

Start with the total size of the market and estimate what percentage of the market the business can capture. If the size of a market is $20 million, for example, a company may estimate it can win 10% of that market, making its sales forecast $2 million for the year. If you’re a natural optimist, it’s a good idea to ask an advisor to provide a reality check on the percentage of customers in your market that you can reasonably expect to attract and serve so that your projections are more accurate. 

How to create a sales forecast

Once you’ve selected a sales forecasting method, you’ll want to take several steps.

1. List the goods and services you sell

In a sales forecast, you’ll want to account for each product or service that you are selling so your forecast is accurate. 

2. Quantify your sales

Each sales forecasting method has its own way of estimating future sales: 

In  historical forecasting , you will need to project the quantity of each product or service you will sell and multiply the unit price by that number. In this type of forecasting, you can base your estimate on the sales figure you brought in last month as long as nothing major has changed in the marketplace. So, if you sold $50,000 worth of your product in July, you might estimate selling $50,000 worth in August. 

In  bottom-up forecasts , you must first estimate the total number of orders that customers will place for your products or services through your website, social media channels and other places you make sales. Then you estimate the average price minus any discounts you offer. Finally, you must multiply the estimated number of orders for each item by the average price to get estimated revenue. 

In  top-down forecasts , you start by estimating the total market for each item you sell. For example, if you were lucky enough to capture 100% of the sales, how much would you have sold? Then project how much of that market you can realistically capture. So, for instance, if the total addressable market for what you sell is $1 million, and you capture 7% of that with your product, your estimated sales will be $70,000. 

3. Make adjustments

Some owners adjust their forecasts to reflect projected market conditions, regulatory changes, new marketing efforts and other variables.

4. Subtract costs

Business owners will typically subtract the costs of creating each good or service they sell from their estimated sales forecast to understand how much profit would be generated from sales. Let’s say you sell a backyard game you invented by outsourcing the manufacturing to a local factory. You might subtract  overhead expenses , such as paying the factory and buying materials, from your projected revenue to anticipate how much money would be left over as profit. Or if you run a social media agency that has taken on new clients who’ve hired you on retainer, you might subtract costs, such as paying freelancers to write social media posts and subscribing to a website that provides stock photos, to get a clearer picture of future profits. 

Tools for sales forecasting

If you haven’t done so already, you might want to consider software to help with sales forecasting. 

Sales forecasting software

Sales forecasting software can use historical business data and trends to create a report of expected sales revenue. Forecast reports can compare sales targets with actual sales. 

Ideally, sales software can help you answer questions like: 

What is your expected revenue? 

Which forecasting method produces the most accurate forecast for your business? 

How did actual sales compare to expected sales?

Sales pipeline forecasting software

With sales pipeline forecasting software, you’ll get an analysis of existing opportunities and a calculation of your success rate in pursuing them, helping you prioritize your efforts. This method focuses on pipeline management and calculates a historical win-rate percentage based on the value and age of the opportunity and the sales representative working on it. Some software programs include features that will give you the ability to view pipeline activity and internal sales data or save you time, letting you integrate information from third-party sales software, for instance. You can create sales forecasts using software such as QuickBooks, Salesforce Sales Cloud, Zoho CRM and Pipedrive.

Historical sales forecasting software

Historical sales forecasting software analyzes previous company performance to calculate a mean (or average) sales level you can expect for the following month, quarter or year. It emphasizes historical trends and seasonality of products and services sold, but it does not consider the opportunities in your pipeline. This software is ideal for small businesses that don’t have big swings in their monthly sales. 

Bottom line

Your sales forecast can be a vital tool as you make plans to grow your business or adjust to challenges. By comparing your actual performance to your forecasts, you’ll be able to get a clear handle on your success and failures, fine-tune your strategies and capitalize on what is working for you so you can keep your business moving to the next level. 

Explore more

Cash flow management basics for small businesses

How to write an effective business plan

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Financial forecast example for new businesses and startups

The financial forecast is an essential step when creating a business plan. The financial forecast allows you to anticipate the revenues and expenses of your new business over a given period.

Even if the exercise is sometimes delicate to carry out, it is nevertheless essential for any entrepreneur. Indeed, it allows you to define quantified objectives, which, if meticulously tracked, will allow you to grow your business in good conditions.

To help you, here's a financial forecast example as well as tools you can use to create yours. 

Financial forecast examples for new businesses

Example of a sales forecast.

The sales forecast is used to estimate the company's turnover. It is generally presented by category of products and services, types of customers, or time slots.

In our financial forecast example, we have included below a sales forecast for a hostel, organised by categories of services with the bed's occupancy forecast broken down based on seasonality:

To ensure a fair and realistic evaluation of your company's revenues, You will need to base your forecast on thorough and reliable market analysis, including an analysis of what your competition offers. You will also need to think carefully about your pricing policy and distribution strategy beforehand.

Examples of financial statements to include in your forecast

Your forecast will need to include 3 financial statements:

• The P&L statement
• The cash flow statement
• The balance sheet

P&L statement

The profit and loss statement enables you to assess:

• the growth of the company by analyzing the evolution of the turnover over several years;
• the profitability of the company by looking at the difference between the expected revenues and the costs which will need to be incurred to generate these sales.

The main shortcoming of the projected income statement is that it does not take into account cash flows. Your profits should turn into cash at some point, but based on when your clients pay you, how much inventory you keep, or when you pay your suppliers, the cash flow could be very different from your profit.

To overcome this shortcoming, we need to look at the forecasted cash flow statement included in our financial forecast example.

Cash flow statement

The cash flow statement shows all anticipated cash movements for a given year.

It enables you to evaluate:

• the ability to generate operating cash flow;
• the company's investment and financing policies.

The cash flow statement is highly complementary to the P&L statement. Together they provide a clear view of the company's profitability, the cash generated by the operations, the investments made and the financing flows.

Balance sheet

The forecasted balance sheet, the last link in the chain, provides an overview of the company's net worth at a given moment in time and is part of our financial forecast example. It enables you to evaluate:

• the value of the company's assets;
• the weight of its working capital;
• the level of financial indebtedness;
• the book value of shareholders' equity.

The forecasted balance sheet complements the other two tables. Nevertheless, it has two weak points:

• It provides a snapshot of the company's net worth at a specific moment in time - giving a very static view of the company. Especially given the balance sheet is usually produced several months after the end of the financial year (and therefore the information it contains is already stale!)
• It gives an accounting vision of the company, based on historical cost, and not a financial vision, based on market value.

Where can I find other financial forecast examples?

At The Business Plan Shop, we offer an online software that includes a financial forecasting tool and helps you throughout the drafting of the business plan on top of financial forecast examples included in our business plan templates . 

Using a software like ours to realize your business plan has several advantages:

• You can easily create your financial forecast by letting the software take care of the calculations and financial aspects for you.
• You are guided in the drafting process by detailed instructions and examples for each part of the plan.
• You get a professional document, formatted and ready to be sent to your bank or investors.

If you are interested in our solution, you can try our software for free here .

Our article is coming to an end. We hope that our financial forecast example has given you a better understanding of what this exercise is all about.

The forecast is a crucial element of a business plan that will be of particular interest to your financial partners if you are looking for financing; but don't forget that it is also a mean for you, as an entrepreneur, to evaluate the viability of your new business idea.

Also on The Business Plan Shop

• How to do financial projections for a new business?
• How to establish a Profit & Loss forecast in your business plan?
• How to do a financial forecast for a restaurant?

Founder & CEO at The Business Plan Shop Ltd

Guillaume Le Brouster is a seasoned entrepreneur and financier.

Guillaume has been an entrepreneur for more than a decade and has first-hand experience of starting, running, and growing a successful business.

Prior to being a business owner, Guillaume worked in investment banking and private equity, where he spent most of his time creating complex financial forecasts, writing business plans, and analysing financial statements to make financing and investment decisions.

Guillaume holds a Master's Degree in Finance from ESCP Business School and a Bachelor of Science in Business & Management from Paris Dauphine University.

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Master Cash Flow Forecasting with Colin Hewitt CFO Weekly

Cash flow is the lifeblood of any business, and for small businesses, it is even more vital. Accurate cash flow forecasting allows business owners to better manage their finances, make informed decisions, and plan for the future. To help us better leverage cash flow forecasting for financial leadership and strategic decision-making, we discuss it with Colin Hewitt. Colin is the CEO and Co-founder of Float Cash Flow Forecasting. He has spent more than twenty years in the software industry, focusing on helping small businesses understand their finances. Colin co-founded Flow to offer simple, precise tools for scenario planning and budgeting that work with well-known accounting platforms. Previously, he served as the Director at IfLooksCouldKill. In this episode, we discuss: - How accurate cash flow forecasting empowers CFOs - How Float's scenario planning allows CFOs to navigate market uncertainties - Integrating advanced tech in cash flow management - Best practices for CFOs to master cash flow in uncertain times

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Akash reports on technology companies in the United States, electric vehicle companies, and the space industry. His reporting usually appears in the Autos & Transportation and Technology sections. He has a postgraduate degree in Conflict, Development, and Security from the University of Leeds. Akash's interests include music, football (soccer), and Formula 1.

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Arm Holdings plans to launch AI chips in 2025, Nikkei reports

SoftBank Group's Arm Holdings , plans to develop artificial-intelligence chips, seeking to launch the first products in 2025, Nikkei Asia reported on Sunday.

Watch CBS News

Social Security projected to cut benefits in 2035 barring a fix

By Aimee Picchi

Edited By Alain Sherter

Updated on: May 7, 2024 / 11:28 AM EDT / CBS News

The timeline to replenish Social Security is being extended. The federal retirement program said Monday it may not need to cut benefits until 2035, one year later than previously forecast, because of stronger performance by the U.S. 

The new projection, from the Social Security Board of Trustees' annual report,  amounts to "good news" for the program's 70 million beneficiaries, said Martin O'Malley, Commissioner of Social Security, in a statement. Even so, he urged Congress to take steps to shore up the program to ensure it can pay full benefits "into the foreseeable future."

Social Security relies on its trust funds to provide monthly checks to beneficiaries, with the funds primarily financed through the payroll taxes that workers and businesses provide with each paycheck. But the funds' reserves are drawing down because spending is outpacing income, partly due to the wave of baby boomer retirements and an aging U.S. population. 

Experts underscore that if the trust funds are depleted, benefits won't suddenly disappear. Instead, Social Security beneficiaries will face a cut to their monthly checks, with the agency on Monday projecting that recipients would lose 17% of their current benefits.

That would be painful for millions of retired and disabled Americans, but it represents a modest improvement from last year, when the Social Security Administration projected that benefits could be slashed by 23% if the trust funds reached the point of depletion.

Advocates for older Americans praised the improved outlook, while pressing Congress to take action on shoring up the program. 

"Congress owes it to the American people to reach a bipartisan solution, ensuring people's hard-earned Social Security benefits will be there in full for the decades ahead," AARP CEO Jo Ann Jenkins said in a statement. "The stakes are simply too high to do nothing."

Lawmakers have yet to take action despite being aware of the looming funding crisis, noted Maya MacGuineas, president of the Committee for a Responsible Federal Budget, a think tank that focuses on the federal fiscal policies, in a statement.

"Every year we get closer to the deadline, we seem to get further away from the solutions," she said. Without a fix, "Social Security's retirement trust fund will be insolvent when today's 58-year-olds reach the normal retirement age and today's youngest retirees turn 71."

Economic boost

O'Malley attributed the improved Social Security forecast to the stronger economy, pointing to what he called "impressive wage growth, historic job creation, and a steady, low unemployment rate." In other words, a healthy job market is resulting in more Social Security taxes going into the funds' coffers.

The report comes as Social Security's financial outlook has become a political lightning rod, with Republicans proposing that the retirement age be raised — effectively cutting benefits for millions of current workers — and former President Donald Trump indicating he would be open to cuts to Social Security and Medicare. 

Democrats argue that there are other ways to fix the program without cutting benefits, such as raising the cap on payroll taxes. Currently, individual income over $168,600 is exempt from the Social Security payroll tax. 

Medicare's "go broke" date

Meanwhile, Medicare's go-broke date for its hospital insurance trust fund was pushed back five years to 2036 in the latest report, thanks in part to higher payroll tax income and lower-than-projected expenses. Medicare is the federal government's health insurance program that covers people age 65 and older and those with severe disabilities or illnesses. It covered more than 66 million people last year, with most being 65 and older.

Once the fund's reserves become depleted, Medicare would be able to cover only 89% of costs for patients' hospital visits, hospice care and nursing home stays or home health care that follow hospital visits.

In a statement on Monday, President Joe Biden credited his administration's economic policies for Social Security and Medicare's stronger outlook. 

"Since I took office, my economic plan and strong recovery from the pandemic have helped extend Medicare solvency by a decade, with today's report showing a full five years of additional solvency," he said. "I am committed to extending Social Security solvency by asking the highest-income Americans to pay their fair share without cutting benefits or privatizing Social Security."

—With reporting by the Associated Press.

• Social Security

Aimee Picchi is the associate managing editor for CBS MoneyWatch, where she covers business and personal finance. She previously worked at Bloomberg News and has written for national news outlets including USA Today and Consumer Reports.

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Federal judge temporarily halts Biden plan to lower credit card late fees to $8

A federal judge in Texas temporarily halted a plan by the Biden administration to lower late fees on credit cards to $8 that was slated to go into effect next week

LOS ANGELES -- A federal judge in Texas temporarily halted a plan by the Biden administration to lower late fees on credit cards to $8 that was slated to go into effect next week.

The temporary nationwide injunction imposed by Judge Mark Pittman in the Northern District of Texas is a win for the big banks and major credit card companies, which collect billions in revenue each year in late fees and were looking to stop the proposal from going into effect. It is also a win for the U.S. Chamber of Commerce, which led the lawsuit on behalf of the banks.

The new regulations that were proposed by Consumer Financial Protection Bureau would have set a ceiling of $8 for most credit card late fees or require banks to show why they should charge more than $8 for such a fee.

The rule would bring the average credit card late fee down from $32. The bureau estimates banks bring in roughly $14 billion in credit card late fees a year.

White House spokesperson Jeremy Edwards said in a statement Friday night, “We are disappointed that a court sided with House Republicans, big banks and special interests to hit pause on a critical measure to save American families billions in junk fees.”

Banks had sued to stop the lawsuit earlier this year, but they had run into a roadblock when Pittman ordered the case moved to Washington, D.C., because of the fact that few banks operate in northern Texas. However, an appeals court reversed most of Pittman's decision and ordered him to rule on the bank's request for an injunction.

While Pittman did impose the injunction, he used a significant portion of his order to chastise the Fifth Circuit Court of Appeals for sending this case back to him after he had already ruled that the case should be handled out of Washington. Critics of the lawsuit have called the case the latest example of judicial “forum shopping,” where a company files a lawsuit in a friendly district in order to have a greater likelihood of getting a favorable ruling.

As part of his reelection campaign, President Joe Biden has tried to highlight his administration's push to clamp down on what he calls “junk fees,” which are bank-related fees like late fees, ATM fees and overdraft fees.

"Every month that the credit card late fee rule is blocked will cost Americans over $800 million," the White House said Friday.

Banks have seen the campaign as a political battle against their business model, while consumer advocates have seen these bank fees as excessive based on the amount of risk that banks and credit card companies are taking on.

“In their latest in a stack of lawsuits designed to pad record corporate profits at the expense of everyone else, the U.S. Chamber got its way for now -- ensuring families get price-gouged a little longer with credit card late fees as high as $41," said Liz Zelnick with Accountable.US.

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Money blog: Loud budgeting - the taboo-busting money hack you can do without giving up daily coffee

Created accidentally by a comedian, "loud budgeting" is breaking down the taboo of speaking about money. Read this and the rest of our Weekend Money features, and leave a comment, and we'll be back with rolling personal finance and consumer news on Monday.

Saturday 11 May 2024 20:15, UK

Weekend Money

• 'Loud budgeting': The money-saving trend that has nothing to do with giving up your daily coffee
• What is most in-demand period property?
• £12m tea advert, downsizing, £320 tasting menus and job interview mistakes: What readers have said this week
• Free childcare applications about to open for new age band
• Where has huge week for UK economy left us?

Best of the week

• How to avoid a holiday data roaming charge (while still using the internet)
• Mortgage rates up again this week - here are the best deals on the market
• My daughter discovered undeclared £600 management fee after buying her flat - can we complain?
• Best of the Money blog - an archive

Ask a question or make a comment

By Jess Sharp , Money team 

Money saving trends are constantly popping up on social media - but one in particular has been gaining huge amounts of attention.

Created accidentally by a comedian, loud budgeting is breaking down the taboo of speaking about money.

The idea is based on being firmer/more vocal about your financial boundaries in social situations and setting out what you are happy to spend your money on, instead of "Keeping up with the Joneses". 

On TikTok alone, videos published under the hashtag #loudbudgeting have garnered more than 30 million views - and that figure is continuing to climb. 

We spoke to Lukas Battle - the 26-year-old who unintentionally created the trend as part of a comedy sketch. 

Based in New York, he came up with the term in a skit about the "quiet luxury" hype, which had spread online in 2023 inspired by shows like Succession. 

The term was used for humble bragging about your wealth with expensive items that were subtle in their design - for example, Gwyneth Paltrow's  £3,900 moss green wool coat from The Row, which she wore during her ski resort trial...

"I was never a big fan of the quiet luxury trend, so I just kind of switched the words and wrote 'loud budgeting is in'. I'm tired of spending money and I don't want to pretend to be rich," Lukas said. 

"That's how it started and then the TikTok comments were just obsessed with that original idea." 

This was the first time he mentioned it...

Lukas explained that it wasn't about "being poor" but about not being afraid of sharing your financial limits and "what's profitable for you personally". 

"It's not 'skip a coffee a day and you'll become a millionaire'."

While talking money has been seen as rude or taboo, he said it's something his generation is more comfortable doing. 

"I've seen more debate around the topic and I think people are really intrigued and attracted by the idea," he said. 

"It's just focusing your spending and time on things you enjoy and cutting out the things you might feel pressured to spend your money on."  

He has incorporated loud budgeting into his own life, telling his friends "it's free to go outside" and opting for cheaper dinner alternatives.

"Having the terminology and knowing it's a trend helps people understand it and there's no awkward conversation around it," he said. 

The trend has been a big hit with so-called American "finfluencers", or "financial influencers", but people in the UK have started practising it as well. 

Mia Westrap has taken up loud budgeting by embarking on a no-buy year and sharing her finances with her 11.3k TikTok followers. 

Earning roughly £2,100 a month, she spends around £1,200 on essentials, like rent, petrol and car insurance, but limits what else she can purchase. 

Clothes, fizzy drinks, beauty treatments, makeup, dinners out and train tickets are just some things on her "red list". 

The 26-year-old PHD student first came across the idea back in 2017, but decided to take up the challenge this year after realising she was living "pay check to pay check". 

She said her "biggest fear" in the beginning was that her friends wouldn't understand what she was doing, but she found loud budgeting helped. 

"I'm still trying my best to just go along with what everyone wants to do but I just won't spend money while we do it and my friends don't mind that, we don't make a big deal out of it," she said. 

So far, she has been able to save £1,700, and she said talking openly about her money has been "really helpful". 

"There's no way I could have got this far if I wasn't baring my soul to the internet about the money I have spent. It has been a really motivating factor."

Financial expert John Webb said loud budgeting has the ability to help many "feel empowered" and create a "more realistic" relationship with money.

"This is helping to normalise having open and honest conversations about finances," the consumer affair manager at Experien said. 

"It can also reduce the anxiety some might have by keeping their financial worries to themselves." 

However, he warned it's important to be cautious and to take the reality of life into consideration. 

"It could cause troubles within friendship groups if they're not on the same page as you or have different financial goals," he said.

"This challenge isn't meant to stop you from having fun, but it is designed to help people become more conscious and intentional when it comes to money, and reduce the stigma around talking about it." 

Rightmove's keyword tool shows Victorian-era houses are the most commonly searched period properties, with people drawn to their ornate designs and features.

Georgian and Edwardian-style are second and third respectively, followed by Tudor properties. Regency ranked in fifth place.

Rightmove property expert Tim Bannister said: "Home hunters continue to be captivated by the character and charm of properties that we see in period dramas.

"Victorian homes remain particularly popular, characterised by their historic charm, solid construction, and spacious interiors. You'll often find Victorian houses in some of the most desirable locations which include convenient access to schools and transport links."

Throughout the week Money blog readers have shared their thoughts on the stories we've been covering, with the most correspondence coming in on...

• A hotly contested debate on the best brand of tea
• Downsizing homes
• The cost of Michelin-starred food

Job interview mistakes

On Wednesday we reported on a new £12m ad from PG Tips in response to it falling behind rivals such as Twinings, Yorkshire Tea and Tetley....

We had lots of comments like this...

How on earth was the PG Tips advert so expensive? I prefer Tetley tea, PG Tips is never strong enough flavour for me. Shellyleppard

The reason for the sales drop with PG Tips could be because they increased the price and reduced the quantity of bags from 240 to 180 - it's obvious. Royston

And then this question which we've tried to answer below...

Why have PG Tips changed from Pyramid shape tea bags, to a square? Sam

Last year PG Tips said it was changing to a square bag that left more room for leaves to infuse, as the bags wouldn't fold over themselves.

We reported on data showing how downsizing could save you money for retirement - more than £400,000, in some regions, by swapping four beds for two.

Some of our readers shared their experiences...

We are downsizing and moving South so it's costing us £100k extra for a smaller place, all money from retirement fund. AlanNorth

Interesting read about downsizing for retirement. We recently did this to have the means to retire early at 52. However, we bought a house in the south of France for the price of a flat in our town in West Sussex. Now living the dream! OliSarah

How much should we pay for food?

Executive chef at London's two-Michelin-starred Ikoyi, Jeremy Chan, raised eyebrows when he suggested to the Money blog that Britons don't pay enough for restaurant food.

Ikoyi, the 35th best restaurant in the world, charges £320 for its tasting menu. 

"I don't think people pay enough money for food, I think we charge too little, [but] we want to always be accessible to as many people as possible, we're always trying our best to do that," he said, in a piece about his restaurant's tie up with Uber Eats... 

We had this in... 

Are they serious? That is two weeks' worth of food shopping for me, if the rich can afford this "tasting menu" then they need to be taxed even more by the government, it's just crazy! Steve T

If the rate of pay is proportionate to the vastly overpriced costs of the double Michelin star menu, I would gladly peel quail eggs for four-hour stints over continuing to be abused as a UK supply teacher. AndrewWard

Does this two-star Michelin star chef live in the real world? Who gives a toss if he stands and peels his quails eggs for four hours, and he can get the best turbot from the fishmonger fresh on a daily basis? It doesn't justify the outrageous price he is charging for his tasting menu. Topaztraveller

Chefs do make me laugh, a steak is just a steak, they don't make the meat! They just cook it like the rest of us, but we eat out because we can't be bothered cooking! StevieGrah

Finally, many of you reacted to this feature on common mistakes in job interviews...

Those 10 biggest mistakes people make in interviews is the dumbest thing I've ever read. They expect all that and they'll be offering a £25k a year job. Why wouldn't I want to know about benefits and basic sick pay? And also a limp handshake? How's that relevant to how you work? Jre90

Others brought their own tips...

Whenever I go for an interview I stick to three points: 1. Be yourself 2. Own the interview 3. Wear the clothes that match the job you are applying Kevin James Blakey

From Sunday, eligible working parents of children from nine-months-old in England will be able to register for access to up to 15 free hours of government-funded childcare per week.

This will then be granted from September. 

Check if you're eligible  here  - or read on for our explainer on free childcare across the UK.

Three and four year olds

In England, all parents of children aged three and four in England can claim 15 hours of free childcare per week, for 1,140 hours (38 weeks) a year, at an approved provider.

This is a universal offer open to all.

It can be extended to 30 hours where both parents (or the sole parent) are in work, earn the weekly minimum equivalent of 16 hours at the national minimum or living wage, and have an income of less than £100,000 per year.

Two year olds

Previously, only parents in receipt of certain benefits were eligible for 15 hours of free childcare.

But, as of last month, this was extended to working parents.

This is not a universal offer, however.

A working parent must earn more than £8,670 but less than £100,000 per year. For couples, the rule applies to both parents.

Nine months old

In September, this same 15-hour offer will be extended to working parents of children aged from nine months. From 12 May, those whose children will be at least nine months old on 31 August can apply to received the 15 hours of care from September.

From September 2025

The final change to the childcare offer in England will be rolled out in September 2025, when eligible working parents of all children under the age of five will be able to claim 30 hours of free childcare a week.

In some areas of Wales, the Flying Start early years programme offers 12.5 hours of free childcare for 39 weeks, for eligible children aged two to three. The scheme is based on your postcode area, though it is currently being expanded.

All three and four-year-olds are entitled to free early education of 10 hours per week in approved settings during term time under the Welsh government's childcare offer.

Some children of this age are entitled to up to 30 hours per week of free early education and childcare over 48 weeks of the year. The hours can be split - but at least 10 need to be used on early education.

To qualify for this, each parent must earn less than £100,000 per year, be employed and earn at least the equivalent of working 16 hours a week at the national minimum wage, or be enrolled on an undergraduate, postgraduate or further education course that is at least 10 weeks in length.

All three and four-year-olds living in Scotland are entitled to at least 1,140 hours per year of free childcare, with no work or earnings requirements for parents. 

This is usually taken as 30 hours per week over term time (38 weeks), though each provider will have their own approach.

Some households can claim free childcare for two-year-olds. To be eligible you have to be claiming certain benefits such as Income Support, Jobseeker's Allowance or Universal Credit, or have a child that is in the care of their local council or living with you under a guardianship order or kinship care order.

Northern Ireland

There is no scheme for free childcare in Northern Ireland. Some other limited support is available.

Working parents can access support from UK-wide schemes such as tax credits, Universal Credit, childcare vouchers and tax-free childcare.

Aside from this, all parents of children aged three or four can apply for at least 12.5 hours a week of funded pre-school education during term time. But over 90% of three-year-olds have a funded pre-school place - and of course this is different to childcare.

What other help could I be eligible for?

Tax-free childcare  - Working parents in the UK can claim up to £500 every three months (up to £2,000 a year) for each of their children to help with childcare costs. 

If the child is disabled, the amount goes up to £1,000 every three months (up to £4,000 a year).

To claim the benefit, parents will need to open a tax-free childcare account online. For every 80p paid into the account, the government will top it up by 20p.

The scheme is available until the September after the child turns 11.

Universal credit  - Working families on universal credit can claim back up to 85% of their monthly childcare costs, as long as the care is paid for upfront. The most you can claim per month is £951 for one child or £1,630 for two or more children.

Tax credits -  People claiming working tax credit can get up to 70% of what they pay for childcare if their costs are no more than £175 per week for one child or £300 per work for multiple children.

Two big economic moments dominated the news agenda in Money this week - interest rates and GDP.

As expected, the Bank of England held the base rate at 5.25% on Wednesday - but a shift in language was instructive about what may happen next.

Bank governor Andrew Bailey opened the door to a summer cut to 5%, telling reporters that an easing of rates at the next Monetary Policy Committee meeting on 20 June was neither ruled out nor a fait accompli.

More surprisingly, he suggested that rate cuts, when they start, could go deeper "than currently priced into market rates".

He refused to be drawn on what that path might look like - but markets had thought rates could bottom out at 4.5% or 4.75% this year, and potentially 3.5% or 4% next.

"To make sure that inflation stays around the 2% target - that inflation will neither be too high nor too low - it's likely that we will need to cut Bank rate over the coming quarters and make monetary policy somewhat less restrictive over the forecast period," Mr Bailey said.

You can read economics editor Ed Conway's analysis of the Bank's decision here ...

On Friday we discovered the UK is no longer in recession.

Gross domestic product (GDP) grew by 0.6% between January and March, the Office for National Statistics said.

This followed two consecutive quarters of the economy shrinking.

The data was more positive than anticipated.

"Britain is not just out of recession," wrote Conway. "It is out of recession with a bang."

The UK has seen its fastest growth since the tailend of the pandemic - and Conway picked out three other reasons for optimism.

1/ An economic growth rate of 0.6% is near enough to what economists used to call "trend growth". It's the kind of number that signifies the economy growing at more or less "normal" rates.

2/ 0.6% means the UK is, alongside Canada, the fastest-growing economy in the G7 (we've yet to hear from Japan, but economists expect its economy to contract in the first quarter).

3/ Third, it's not just gross domestic product that's up. So too is gross domestic product per head - the number you get when you divide our national income by every person in the country. After seven years without any growth, GDP per head rose by 0.4% in the first quarter.

GDP per head is a more accurate yardstick for the "feelgood factor", said Conway - perhaps meaning people will finally start to feel better off.

For more on where Friday's figures leaves us, listen to an Ian King Business Podcast special...

The Money blog is your place for consumer news, economic analysis and everything you need to know about the cost of living - bookmark news.sky.com/money .

It runs with live updates every weekday - while on Saturdays we scale back and offer you a selection of weekend reads.

Check them out this morning and we'll be back on Monday with rolling news and features.

The Money team is Emily Mee, Bhvishya Patel, Jess Sharp, Katie Williams, Brad Young and Ollie Cooper, with sub-editing by Isobel Souster. The blog is edited by Jimmy Rice.

If you've missed any of the features we've been running in Money this year, or want to check back on something you've previously seen in the blog, this archive of our most popular articles may help...

Loaves of bread have been recalled from shelves in Japan after they were found to contain the remains of a rat.

Production of the bread in Tokyo has been halted after parts of a "small animal" were found by at least two people.

Pasco Shikishima Corp, which produces the bread, said 104,000 packages have been recalled as it apologised and promised compensation.

A company representative told Sky News's US partner network, NBC News, that a "small black rat" was found in the bread. No customers were reported to have fallen ill as a result of ingesting the contaminated bread.

"We deeply apologise for the serious inconvenience and trouble this has caused to our customers, suppliers, and other concerned parties," the spokesman said.

Pasco added in a separate statement that "we will do our utmost to strengthen our quality controls so that this will never happen again. We ask for your understanding and your co-operation."

Japanese media reports said at least two people who bought the bread in the Gunma prefecture, north-west of Tokyo, complained to the company about finding a rodent in the bread.

Record levels of shoplifting appear to be declining as fewer shopkeepers reported thefts last year, new figures show. 

A survey by the Office for National Statistics shows 26% of retailers experienced customer theft in 2023, down from a record high of 28% in 2022.

This comes despite a number of reports suggesting shoplifting is becoming more frequent. 

A  separate ONS finding , which used police crime data, showed reports of shoplifting were at their highest level in 20 years in 2023, with law enforcements logging 430,000 instances of the crime.

Let's get you up to speed on the biggest business news of the past 24 hours. 

A privately owned used-car platform is circling Cazoo Group, its stricken US-listed rival, which is on the brink of administration.

Sky News has learnt that Motors.co.uk is a leading contender to acquire Cazoo's marketplace operation, which would include its brand and intellectual property assets.

The process to auction the used-car platform's constituent parts comes after it spent tens of millions of pounds on sponsorship deals in football, snooker and darts in a rapid attempt to gain market share.

The owner of British Airways has reported a sharp rise in profits amid soaring demand for trips and a fall in the cost of fuel.

International Airlines Group said its operating profit for the first three months of the year was €68m (£58.5m) - above expectations and up from €9m (£7.7m) during the same period in 2023.

The company, which also owns Aer Lingus, Iberia and Vueling, said earnings had soared thanks to strong demand, particularly over the Easter holidays.

The prospect of a strike across Tata Steel's UK operations has gained further traction after a key union secured support for industrial action.

Community, which has more than 3,000 members, said 85% voted in favour of fighting the India-owned company's plans for up to 2,800 job losses, the majority of them at the country's biggest steelworks in Port Talbot, South Wales.

Tata confirmed last month it was to press ahead with the closure of the blast furnaces at the plant, replacing them with electric arc furnaces to reduce emissions and costs.

In doing so, the company rejected an alternative plan put forward by the Community, GMB and Unite unions that, they said, would raise productivity and protect jobs across the supply chain.

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