profitability case study pdf

6 Variants of Profitability Framework: Guide & Tips

The most popular case type across MBB firms is profitability and you will most likely encounter at least one. Understanding the framework specifically designed for that type of problem is crucial. In this article, I will show you how to use this framework in case interviews – from the fundamentals to instant-result tips to land one of the most prestigious job offers out there!

Table of Contents

What is the profitability framework?

Profitability framework is a special-designed issue tree to solve Profit problems in consulting case interview . The framework starts with a math equation: PROFIT = REVENUE – COST then consequently breaking down each branch (REVENUE and COST) down into smaller components such as: Price x Quantity or Cost/Unit x Quantity.

But hey, what is a case interview framework in the first place?

A case interview framework is a template used to break down and solve business problems in case interviews. A framework can be highly customized for specific cases or versatile enough for general problem-solving. Some popular frameworks are: Profitability, Market Entry, 3C&P, or the marketing 4P.

The most important thing to remember when using frameworks to solve a problem is to be FLEXIBLE. Consulting problems are complex and usually there are no clear-cut, ready-to-use frameworks to solve them. The interviewer looks for context-relevant frameworks, not complicated but inappropriate ones.

Hence, the more you master the “building-blocks” frameworks, the better you can draw specific frameworks suitable to each context. Learn more about frameworks.

Diving into the “profitability framework”

The nice thing about Profitability Framework is that it is entirely based on different Math equations. That allows for flexible use in case interviews with many different variants, allowing figures to be viewed from different angles for multiple insights. Moreover, most of the data are easily accessible from the company’s financial reports.

On the highest level, everybody agrees that: Profits = Revenues – Costs. But down to lower layers, there are a number of variants. But the main idea is to keep using math to break every branch down until the case shows its true self.

Here is one example of a variant. We will introduce to you 6 of them later in this post. Keep reading.

Understand the profitability cases?

Profitability case is one of the most popular case interview problem types, often given in the format of a client facing declining or negative profit. The consultant’s job is to analyze the situation, identify the root-cause, and propose solutions. Almost all Profitability cases start with a Profitability Framework and slowly transition themselves into qualitative issue trees.

Here are some examples of profitability cases:

• Profit problem: Alice’s hotel chain has been experiencing profit stagnation for 6 months despite an increase in customers, they want to understand why?
• Loss problem: Bob’s restaurant has been operating at a loss for 3 consecutive months despite having raised their menu price. They want your help to make the business profitable again.
• Revenue problem: Han’s marketing agency has seen total revenue decline for 2 years despite significant cuts in back-end costs, they want to know what’s causing it.

While the most popular Profit cases are asked in the form of “Problem – Find root-cause – Solutions”, occasionally the interviewer may also give you the “Yes/No” or “How-to” cases:

• “Boston Electric is planning to acquire a very expensive set of equipment to expand their production. Is this a good idea?”
• The Coffee House is planning to launch a new store in a nearby city. How to do it in the most Profitable way?

In this article, I will focus mainly on the “Problem – Find root-cause – Solutions” type. It is the most popular format and studying it will show you the big picture quickest. Once you grasp the format, you can easily apply the principles to other formats.

Six variants of the profitability framework

Variant 1: unit price/costs x quantity (both sides).

This is the most popular and rudimentary variant of the profitability framework, with a logically simple mathematical structure. This variant is often used for cases where the unit sale of ONE particular product is important (for example, in single-product businesses).

This variant has two drawbacks: it cannot be used for multiple product lines at the same time, and it’s not strictly MECE . (price and quantity are fundamentally related – lower price tends to increase quantity, and vice versa – that means the root cause from one branch may manifest in the other, making it harder to isolate).

Case Example

A local ice-cream business finds its profits deteriorating in the last two years. They have hired you – an independent consultant – to find the root cause of their problem and fix it.

Now, if this business only sell one type of ice-cream, this is how we can break down their profits:

Variant 2: Revenue/cost per customer x number of customers (both sides)

This one is a spin-off of Variant 1, with units of goods exchanged for customers. This variant is often used for businesses where the spending of each customer varies significantly (say, a supermarket or a restaurant).

In contrast to Variant 1 the business has one or many product lines is not important, and there’s less correlation between the two branches (more MECE ).

If the shop in the previous example has 3 types of ice-cream and also sells optional toppings to eat with the ice-cream – say, strawberries -it wouldn’t make any sense to put them all into one group. The price variations between each cup, with three types and toppings added, can be quite remarkable, so Variant 2 should be used:

Variant 3: Segments/business lines (both sides)

Variant 3 divides the revenue side into corresponding market segments or business lines in a MECE way (more so than the first two variants). If the case concerns many product lines or market segments , and you suspect the root cause comes from one of them, use this variant.

This variant and its spin-offs (4 and 5) tend to be more MECE than the first two, but it cannot answer “why” the problem is happening, only “where” – to answer that “why” question you need to revert to the first two variants to break down the data, then switch to qualitative frameworks to answer the case question.

In the ice-cream case, if the root cause of the business’ problem comes from competition in the chocolate ice-cream line, neither Variant 1 nor Variant 2 can isolate it. The below issue tree, on the other, would certainly reveal that problem:

Variant 4: Non-operating vs operating (revenue side)

Variant 4 is basically Variant 3 for businesses which regularly engage in activities outside their core services/products. It divides revenues into operating revenue generated from selling the business core products/services, and non-operating revenue from investments or sale of assets).

For example, if the ice-cream business also owns a few shop-houses for leasing to other businesses, here’s what their revenue would look like:

Variant 5: Functions/cost types (cost side)

Variant 5 is similar to Variant 3, using the source of cost as the basis for segmentation – but only applies to the cost side. This variant is useful for cases where the root cause comes from one particular function of the company (such as HR, Marketing, Sales, etc.).

Here’s Variant 5 applied to the ice-cream case given above:

Variant 6: Fixed vs variable

Variant 6 uses accounting concepts to break down the costs of a business, much like Variant 4 on the revenue side. The most popular form of this variant is “Costs = Fixed Costs + Variable Costs”, shown below; this form is fundamentally MECE and applicable for every business, however, each branch must always be divided into many sub-branches (using the previous variants).

Here’s Variant 6 applied to the ice-cream case given above:

Combinations, spin-offs, and qualitative frameworks

In real case interviews , you need to use a combination of the above variants – mostly because each variant has its own strong and weak points, and none of them can deliver an in-depth analysis of the problem on their own. Being creative enough to draw customized versions of the aforementioned frameworks is likewise crucial to passing the case interview.

However, many times numbers alone cannot get you to the root cause of the problem – and that’s where qualitative frameworks come into play. 

Switching to qualitative frameworks

Sometimes, quantitative frameworks like the profitability framework cannot take you to the root of the problem. In such cases, the solution is to switch to qualitative frameworks to find the root-cause. It’s like going on a picnic by a lake inside the forest: your car can only take you from home to the edge of the forest, you will have to navigate through the forest to the lake, on foot.

Case example

A major fashion retail chain has been operating without profits for the past 6 months. They hire you to investigate and deliver a solution.

Having applied the profitability framework, you determine that the problem comes from excessive HR costs. HR costs are a product of the number of employees and HR costs per employee (so they either hire too many or pay too much). After gathering more information, you found out that the company is over-hiring. At this point, you suddenly find yourself stuck. Now what? Why is the company overhiring? How can you fix that problem?

This is a typical “stuck” situation in profitability cases; in this section I’ll guide you through 3 simple steps to get out of it.

Step 1: Exhaust the math structure

In any profitability case, the first thing you need to do is to keep drilling down mathematically. Simple as it looks, it is a very effective tool to find root causes and deliver on-point solutions.

Most importantly, don’t be nervous when the math does not take you to the root cause just yet. In case interviews, focus on exhausting the framework really well at the beginning, because that’s where you’ll score most points. The interviewer will have made a decision in mind if you break down the issue really well. In tricky cases, he or she will give you a few hints to get to the bottom of the root cause.

In the given case, if you just stop at “over-hiring”, you can’t deliver a practical solution – because you haven’t broken down the case enough to reach the root cause. You don’t simply fire half your employees overnight indiscriminately.

Step 2: Gather as many insights as possible

The second step is to gather as many insights as possible about the company and the case context. This helps identify the most likely branches to contain the root causes.

Once you have reached the end of the quantitative framework, you will face what can be considered a mini case in itself. This mini case requires its own frameworks or systematic approach to find the root cause. For example, in the above case, the new mini case is: “How to reduce excess numbers of employees?”

The kinds of branches you draw next will entirely depend on the context and situation of the company you’re advising, which vary case by case. In other words, the qualitative traits of each company together determine how each framework will look like. That is what I mean by “qualitative framework”.

Applying to the case above, some company-specific, insight-revealing questions you might ask are:

1. What are the sources of HR costs? 2. Among those sources of costs, which one is the main contributor? Suppose, for the first question, you find out that the two sources of costs are:

• Salaries of employees in office departments (office salaries overhead)
• Labor cost to operate day-to-day business activities in retail outlets (outlet labor costs)

For the second question, you might find two possibilities:

• Office salaries overhead is the main contributor
• Outlet labor cost is the main contributor

At this point, you need to dig deeper. Ask more questions and gather more facts

1. If office salaries overhead is highest, is the company having excess employees in one or more departments compared to our competitors?

2. If outlet labor cost is highest, how many employees does the company have per store? Is it optimizing its outlet workforce? What metric is it using to allocate employees

Step 3: Apply insights to the framework

At this stage, drawing qualitative issue trees is usually easier than the first stage, a.k.a using the quantitative framework to break down the problem at the beginning of the case. Here’ when you add gathered contextual insights into the framework and derive suitable qualitative variants.

To continue with the case above, suppose the source of high HR cost is hiring too many employees at store outlets. If this is the case, you need to determine which stores are having too many employees and why. In other words, you are looking for outlets in which labor is not being optimized and the reasons behind that.

There are several interrelated variables to consider when ranking all outlets to pinpoint ones where employees are not being allocated efficiently:

1. Store sales: what is the sales to employees ratio for each store?

2. Store size: what is the store size to employees ratio for each store?

3. Customer traffic: what is the customer traffic to employees ratio for each store? 

Five tips when using the profitability framework

Tip #1: strictly follow the problem solving methodology .

The Profitability Issue Tree is very easy to follow. So the interviewer can also easily catch it if you deviate from the standard Consulting Problem Solving Methodology. Here are some of the common mistakes that may sound silly but I keep seeing candidates making them over and over again:

Going to Layer #2 without testing Layer #1 first

For example: you break down the problem into Revenue and Cost (this is Layer #1), you decide to tackle Revenue first. And here, without confirming Revenue is problematic, you immediately go down into Price or #Unit. This is not logically sound. You can and you should only go down to Layer #2 (Price, #Unit) if you know the Root-cause IS in Revenue.

Going to Layer #2 even though the branch doesn’t contain the Root-cause

For example: you break down the problem into Revenue and Cost. You test Revenue and there is nothing wrong with it. You keep going down to Price and #Unit (Layer #2) … just for the sake of going down. If there’s nothing wrong with Revenue, don’t waste anytime. Move to Cost!

Moving to other branch without closing the deal with the current branch

For example: you are on the Revenue side and there are signs that the Root-cause is here. You break Revenue down to Price and #Unit. You analyze a bit, hit a deadend, and decide to go to Cost. This is not logically sound. Try to exhaust Revenue (a.k.a: identify the Root-cause in there or conclude Revenue is NOT the problem) before moving to Cost!

Tip #2: “Pretend” to be hypothesis-driven

The Problem Solving Methodology tells us to be “hypothesis-driven”. What does it mean? It means to look for the root-cause with some educated guesses in mind, a.k.a: to draw the issue tree that isolates potential root-causes. But isn’t it so obvious that we would almost always break down Profit into Revenue and Cost, right?

So the answer is to do whatever you need to do with the issue tree (a.k.a: breaking down Profit into Revenue and Cost). But as soon as you step into Revenue or Cost (the first layer =), say it’s the hypothesis that carries you there.

“I hypothesize that the Root-cause is in the Revenue branch. So I would like to test Revenue first. Here are some of the data I need … etc.”

Tip #3: Get a feel for the case and decide on the specific variant

The first Layer is quite straight forward but the deeper you go, the trickier it gets. You need to use business intuition and contextual insights to decide which variant to use.

Contextual insights can be gained by asking the interviewer – in fact that’s what you’re supposed to do in a case interview, as you are not allowed to bring outside knowledge into the case. That said, knowing how to ask is extremely important – you must always show a purpose when asking for context or any data. “To get a feel for the case and draw the most relevant issue tree” is a perfectly valid excuse – I tend to use it at the beginning of the case when there is hardly any data to make informed decisions.

However, context can only make sense with business intuition – which can only be gained through exposure. Read consulting and business news, do mock cases, slowly your intuition will build up. This part of case interview is covered by our Business Intuition package of the Case Interview End-to-End Secrets Program, which uses unconventional cases to prompt the development of intuition.

Tip #4: Use your good old math friend before flirting with qualitative ideas

Quantitative analysis is always easier than qualitative. For example: you figured out that there is definitely something wrong with employee cost. Don’t try to understand why yet. Don’t ask for company’s organization charts, don’t try to understand the human structure yet. Keep using math until you can’t anymore.

In this example, you can continue to break Employee Cost down into #Employees and Average Salary. Even if this breakdown doesn’t yield any important insights, it’s worth the try. Because when it does work, you save yourself a ton of hassle.

Tip #5: Have a personal script

You can save valuable Brain Power for what really matters the most. So if anything can be prepared beforehand, do it. This is so important that the whole next section will be dedicated to it. Keep reading!

See more helpful tips for the profitability framework in our Case Interview End-to-End Secrets Program . To know if you’re on the right track, you can also book a meeting with former consultants who have insider knowledge of what makes you fail in a case interview. They will give you a real life mock interview and quickly identify your improvement areas.

Developing a personal pcript

Organize what you are going to say into a script, and practice a hundred times.

Let’s be honest, sounding structured and professional in any case interviews costs a lot of brain power. Particularly, in profitability cases, you are better off maximizing your time and effort breaking down the problem, not smoothly translating from the math language.

Hence, I recommend practicing all the formulaic lines, such as the opening or data requests, using an interview script. Practicing is really the only way you can unconsciously sound structured and professional. With enough training, those lines will feel natural to you.

Here’s an example of a good practice script: 

This article will give insights into market entry framework, revealing how to apply it to market entry cases in case interviews.

A case interview is where candidates is asked to solve a business problem. They are used by consulting firms to evaluate problem-solving skill & soft skills

Case interview frameworks are methods for addressing and solving business cases.  A framework can be extensively customized or off-the-shelf for specific cases.

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Case Interview End-to-End Secrets Program

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DoorDash: In Search of Profitability

By: Arpita Agnihotri, Saurabh Bhattacharya

The chief executive officer and co-founder of DoorDash was facing various challenges. Based in San Francisco, California, DoorDash was the market leader in the US food delivery services industry. In…

• Length: 10 page(s)
• Publication Date: Apr 14, 2021
• Discipline: Strategy
• Product #: W21165-PDF-ENG

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The chief executive officer and co-founder of DoorDash was facing various challenges. Based in San Francisco, California, DoorDash was the market leader in the US food delivery services industry. In December 2020, despite ongoing losses, the start-up launched the largest initial public offering of the year in the United States. Market observers believed that intense competition in the US food delivery services industry and DoorDash's questionable business model fundamentals would make profitability difficult to achieve. Restaurants were raising objections to food delivery platforms, seeing profits shrink due to commissions paid to the platforms. Consumers were paying at least 40 per cent more on orders made through an online delivery platform compared to self-pickup. However, during the COVID-19 pandemic, consumer demand for food delivery services increased and DoorDash reported a profit for the second quarter of 2020. DoorDash was expanding rapidly, after several rounds of funding. Could the co-founder prove critics wrong about the business fundamentals of his food delivery platform? How could he create a sustainable profit for DoorDash?

Arpita Agnihotri is affiliated with Pennsylvania State University - Harrisburg. Saurabh Bhattacharya is affiliated with Newcastle University.

Learning Objectives

This case is intended for undergraduate- or graduate-level courses in business strategy, strategic management, creativity and innovation, and entrepreneurship. The case discusses the profitability challenges of companies in a highly competitive industry, where all stakeholders incur high costs due to a platform-mediated business model. The case further highlights how a company can become profitable through innovation and imitation strategies. After working through the case and assignment questions, students will be able to critically analyze how a business creates value for multiple stakeholders; examine the business model fundamentals of a platform-mediated business model; understand the overvaluation of start-ups due to a blitz-scaling growth strategy; and explore ways to make a company profitable in a competitive industry.

Apr 14, 2021

Discipline:

Geographies:

United States

Industries:

Accommodations, Restaurants and food service industry

Ivey Publishing

W21165-PDF-ENG

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The Profitability Case Framework: A Key to Solving Profitability Cases

Learn how to solve profitability cases with ease using the Profitability Case Framework.

Posted May 11, 2023

Consulting Week (Apr 15-18)

Monday, april 15.

10:00 PM UTC · 60 minutes

Profitability cases are one of the most common business problems that consultants and analysts encounter today. Understanding how to solve these cases is essential for business leaders and consultants alike. In this article, we will introduce the profitability case framework and cover all the key components that can be used to solve profitability cases successfully.

Understanding the Profitability Case Framework: An Introduction

The profitability case framework is a powerful tool that can be used to solve business problems efficiently. It consists of five key components, including market analysis, industry trends, KPIs, cost structure, and revenue stream evaluation. By examining each of these components in detail, analysts and consultants can identify key issues, determine potential solutions, and make data-informed decisions that drive business success.

One of the key benefits of using the profitability case framework is that it allows businesses to identify areas where they can improve their profitability. For example, by analyzing their cost structure, businesses can identify areas where they are overspending and make changes to reduce their costs. Similarly, by evaluating their revenue streams, businesses can identify opportunities to increase their revenue and improve their bottom line.

Another advantage of using the profitability case framework is that it provides a structured approach to problem-solving. By breaking down complex business problems into smaller, more manageable components, analysts and consultants can develop a clear understanding of the issues at hand and develop targeted solutions. This can help businesses to save time and resources, while also improving the quality of their decision-making.

Importance of Profitability Cases in Business Strategy

Profitability cases are a crucial part of business strategy, as they can help companies identify areas for growth and improvement. By solving profitability cases, businesses can establish competitive advantages, enhance their operations, and achieve long-term success.

Furthermore, profitability cases can also assist businesses in making informed decisions about resource allocation and investment. By analyzing the profitability of different products, services, or business units, companies can determine where to allocate resources and invest in areas that will generate the highest returns. This can lead to increased efficiency, profitability, and overall success for the business.

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How to Identify Profitability Cases in Business Scenarios

The ability to identify profitability cases is essential to resolving them. In general, profitability cases emerge when businesses experience a decline in profits or struggle to generate sufficient revenue. For example, if a company's sales have decreased for no explicable reason, or if its expenses have increased with no clear explanation, a profitability case might emerge.

One way to identify profitability cases is to conduct a thorough analysis of the company's financial statements. This can involve examining the income statement, balance sheet, and cash flow statement to identify any trends or anomalies that may be impacting profitability. Additionally, it may be helpful to compare the company's financial performance to industry benchmarks or competitors to gain a better understanding of how it is performing relative to others in the market.

Another important factor to consider when identifying profitability cases is the company's overall business strategy. If the company is pursuing a strategy that is not aligned with its core competencies or market demand, it may struggle to generate profits. In these cases, it may be necessary to reevaluate the company's strategy and make adjustments to better align with market demand and the company's strengths.

The Five Components of the Profitability Case Framework

Now let us examine the five key components of the profitability case framework in detail.

1. Analyzing Market and Industry Trends for Profitability Cases

The first component of the profitability case framework involves analyzing current market and industry trends. This includes examining factors such as market size, customer behavior, and competitive landscape. By analyzing these trends, businesses can identify new opportunities and develop strategies that improve their profitability.

2. Identifying Key Performance Indicators (KPIs) in Profitability Cases

The second component of the profitability case framework involves identifying KPIs that are relevant to the business. These KPIs are used to evaluate the effectiveness of different business strategies and can include metrics such as sales revenue, market share, and customer satisfaction.

3. Understanding Cost Structures and their Role in Profitability Cases

The third component of the profitability case framework involves understanding the cost structure of the business. This includes examining factors such as fixed and variable costs, and analyzing the impact of changes in cost structures on the overall profitability of the business.

4. Evaluating Revenue Streams and their Impact on Profitability Cases

The fourth component of the profitability case framework involves evaluating revenue streams. This involves examining how the business generates revenue and identifying any potential weaknesses or inefficiencies in the revenue generation process. Examining revenue streams can help businesses identify new opportunities for growth and improve their overall profitability.

5. Techniques for Conducting a Thorough Analysis of Profitability Cases

The final component of the profitability case framework involves techniques for conducting a thorough analysis of profitability cases. This includes techniques such as benchmarking, data analysis, and financial modeling. By using these techniques, businesses can gain a deeper understanding of their profitability cases and develop effective strategies to solve them.

It is important to note that the profitability case framework is not a one-time process, but rather an ongoing one. Businesses must continuously analyze market and industry trends, identify relevant KPIs, understand their cost structures, evaluate revenue streams, and use techniques for conducting a thorough analysis of profitability cases in order to stay competitive and profitable.

Additionally, businesses must also consider external factors that may impact their profitability, such as changes in government regulations, economic conditions, and technological advancements. By staying aware of these external factors and adapting their strategies accordingly, businesses can ensure long-term profitability and success.

Case Studies: Real-Life Examples of Implementing the Profitability Case Framework

One of the best ways to understand how the profitability case framework can be used in practice is by examining real-life case studies. For instance, one company used the profitability case framework to identify a decline in sales in one of its key regions. Using market analysis and KPI evaluation, the company was able to identify a shift in customer preferences and develop a new marketing strategy that improved sales in the region.

Another example of the profitability case framework in action is a company that used it to evaluate the profitability of its product lines. By analyzing the costs and revenue of each product line, the company was able to identify which ones were not generating enough profit and make the decision to discontinue them. This allowed the company to focus its resources on the more profitable product lines and increase overall profitability.

Additionally, a third company used the profitability case framework to evaluate the effectiveness of its pricing strategy. By analyzing the pricing of its products and comparing them to competitors, the company was able to identify areas where it could increase prices without negatively impacting sales. This resulted in a significant increase in revenue and profitability for the company.

Common Mistakes to Avoid When Solving Profitability Cases

While the profitability case framework can be a powerful tool for solving business problems, there are common mistakes that businesses and consultants should avoid when using it. These include failing to conduct in-depth analysis, ignoring key factors and overlooking the importance of data analysis.

Another common mistake to avoid when solving profitability cases is failing to consider external factors that may impact the business. For example, changes in the economy, industry trends, and government regulations can all have a significant impact on a company's profitability. It's important to take these factors into account when analyzing the case and developing a solution.

In addition, it's important to avoid making assumptions without sufficient evidence. Consultants and businesses may be tempted to make assumptions based on their own experiences or preconceived notions, but this can lead to inaccurate conclusions. Instead, it's important to gather and analyze data to support any assumptions or hypotheses made during the case analysis.

The Future of Profitability Cases: Trends and Predictions

The profitability case framework continues to evolve as new trends emerge and technologies become available. For instance, the use of artificial intelligence and machine learning may allow businesses to more accurately identify profitability issues and develop effective solutions. However, despite these changes, the core components of the profitability case framework remain essential to resolving profitability cases effectively.

Another trend that is expected to impact profitability cases in the future is the increasing focus on sustainability and social responsibility. As consumers become more aware of the environmental and social impact of their purchases, businesses will need to consider these factors in their profitability analysis. This may involve incorporating sustainability metrics into their financial analysis and developing strategies to reduce their environmental footprint while maintaining profitability.

In conclusion, the profitability case framework is a powerful tool that can be used to solve a range of business problems. By examining market trends, identifying KPIs, understanding cost structures, evaluating revenue streams, and using effective analysis techniques, businesses can identify key issues, develop effective solutions, and achieve long-term profitability.

One of the key benefits of using the profitability case framework is that it allows businesses to make data-driven decisions. By analyzing financial data and market trends, businesses can identify areas of opportunity and make informed decisions about where to invest resources. This can help businesses to avoid costly mistakes and maximize their return on investment.

Another advantage of using the profitability case framework is that it encourages collaboration and communication within organizations. By involving stakeholders from different departments and levels of the organization in the analysis process, businesses can gain a more comprehensive understanding of their operations and identify areas for improvement. This can lead to more effective decision-making and a more cohesive organizational culture.

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Profitability Framework: Master This Case Interview Structure

• Last Updated June, 2023

Rebecca Smith-Allen

Former McKinsey Engagement Manager

When you first start preparing for consulting case study interviews, coming up with a structure for analyzing the problem can seem intimidating. It doesn’t have to be. The profitability case framework is a simple yet flexible framework that you can apply to many types of case interview questions. S tart your practice here, and you’ll soon have the confidence to expand to other case interview frameworks and begin creating ones that are all your own. In this article, we’ll discuss:

What is a Framework?

• Why You Want to Use a Framework to Answer a Case Interview Question,
• The Profitability Equation – the Basis of the Profitability Case Framework,
• A Profitability Framework Example,
• Types of Case Interview Questions that Can Be Answered Using the Profitability Case Framework, and 
• Tips on Using the Profitability Framework.

Let’s get started!

A framework is the high-level set of topics that must be addressed when answering a case question or business problem. Frameworks break down a business problem into the component parts that need to be analyzed in order to:

• Identify the root cause of the issue that needs to be solved, and
• Develop a solution that will work for the client’s business.

Framework Example: The 3Cs – Company, Customers, and Competition

For more on the 3Cs framework as well as other frameworks such as the BCG 2 x 2 Matrix, SWOT analysis, the 4Ps, or other frameworks, see our Case Interview Frameworks article.

Why You Want to Use a Framework to Answer a Case Interview Question

Every client is different and so the solutions to their problem are different. Because of this, consulting interviewers aren’t looking for candidates to have an immediate solution to the business problem. 

Instead, they’re looking for candidates who are good at structured problem-solving.

Structured problem-solving allows someone who has general knowledge of business to direct their analysis to the relevant aspects of the client’s problem so they can solve it. 

A framework is a useful tool to help you structure your problem solving because it highlights the key topics to be addressed in your analysis.

The Profitability Equation – the Basis of the Profitability Case Framework

At the highest level, the profitability framework is a simple equation:

Profits = Revenues – Costs

Quantity sold is the amount of goods or services sold in a period of time. The pounds of bananas, hours of personal fitness coaching, or number of cell phone screen repairs sold to customers.

Price is the amount of money charged for the product or service sold.

Fixed costs are the costs that don’t change based on the quantity of goods sold (or at least don’t change quickly). They include things like: property costs (rent for offices, factories, warehouses, or retail space), depreciation of equipment needed to make the product or provide the service, the cost of salaried employees/management, property taxes, etc.

Variable costs are the costs that depend directly on the quantity of goods or services sold. Example: if you sell more cars, you need to buy more tons of steel and more tires in order to manufacture the cars. Variable costs include: materials used to make the product, the cost of hourly employees (those directly involved in making the product or producing the service), shipping, credit card transaction costs, etc.

To use the profitability equation to solve a case interview question, you start with either cost or revenue and ask questions about how the components of each are changing until you find the issue(s) which is(are) hurting profitability. 

Once you know what is causing the profitability problem, you can move on to brainstorming how to fix it.

Using  the Profitability Framework to Drive Deeper Analysis

There are several ways you can dive deeper into a profitability case. They involve segmenting the business into its component parts or benchmarking. Segmenting: Comparing one segment of a client’s business to another for the purposes of identifying key differences. You can segment a businesses financial performance by comparing:

• One business segment to another,
• One geographic unit to another,
• One distribution channel to another, or
• One customer type to another.

Benchmarking: Compare the client’s business or a segment to:

• Key competitors, or
• The client’s own performance in prior periods.

Here’s how.

Breaking Down Profitability by Business Segment, Geography, Distribution Channel or Customer Type

Breaking down profitability by business segment.

Some case questions will involve the relative profitability of different parts of a company such as by business segment,  geographic unit, distribution channel, or customer type. 

Suppose a computer company is competing successfully in the retail market but losing business to the competition in the corporate and education markets. To better understand the business problem they face, you should look at the profitability of each business segment separately.

Retail PC Profits = Retail PC Revenues – Retail PC Costs

Corporate PC Profits = Corporate PC Revenues – Corporate PC Costs

Educational PC Profits = Educational PC Revenues – Educational PC Costs

When you dive into the revenues and costs of each division separately, you may find that the cost structure that allows the company to be successful in the retail market does not provide the level of standardization needed by corporate IT departments, resulting in lost sales to those clients. Or the client might not be able to hit the price point needed to compete in the price-sensitive educational market.

Nail the case & fit interview with strategies from former MBB Interviewers that have helped 89.6% of our clients pass the case interview.

Breaking Down Profitability by Geography

Now suppose this same computer company sells computers all over the world. To understand whether the heart of their profitability problem stems from with differences in the geographic markets it competes in, you can compare the profitability of the different geographic units and analyze what is driving the differences you see.  North American PC Profits = North American PC Revenues – North American PC Costs Latin American PC Profits = Latin American PC Revenues – Latin American PC Costs European PC Profits = European PC Revenues – European PC Costs Asian PC Profits =Asian PC Revenues – Asian PC Costs African PC Profits =African PC Revenues – African PC Costs By drilling down into the revenues and costs by region, you may find that the cost structures in the different markets are fundamentally different due to differences in government regulations, labor rates, and pricing/the level of competition, etc. Looking at each segment of the business separately helps to identify what makes one part of the company profitable and others unprofitable. You can look at profitability by sales channel of customer type as well as by business unit or geography.  The best comparison to you depends on the individual case. You might need to break down profitability a couple different ways to find the one that is most relevant to solving the case.

Benchmarking Profitability Relative to the Competition

Sometimes the change in a business’s profitability isn’t caused by the actions of the company itself. It’s caused by actions the competition has taken. This can happen if the competitor takes actions to increase demand for their products and services such as:

• Reduces its costs,
• Reduces prices, 
• Increases advertising spending,
• Increases sales staff, or
• Opens new store locations.

Benchmarking Profitability Over Time

If a client’s competitors haven’t changed their business strategy and the profitability problem isn’t focused on any one product segment or geography, the next thing to analyze is the client’s cost and revenue structure over time. Costs that aren’t carefully managed will increase over time. New employees will be hired, head office facilities expanded, or component costs increasing with inflation. Flat revenue combined with rising costs will put pressure on profits.  Even if revenue isn’t  flat, cost increases outpacing revenue increases will cause a profitability problem. If profits are squeezed by continually rising costs, the client can resolve its profitability problem by:

• Managing costs better,
• Raising prices,
• Gaining market share, or 
• Doing all of the above.

How Do You Know Which Profitability Analysis Is Right to Use?

Sometimes you’ll get a hint in what type of profitability benchmarking you should do from the case question. If the question says that a North American company is experiencing low profitability in its sales in China – compare the cost structure of the North American business unit to that of the Chinese business unit. If you identify differences that explain the problem and help you find a solution, that’s the right comparison. If there are no differences in the cost or revenue structure of the 2 geographies, look at the profitability of the Chinese business unit to competitors in China or to its own past performance. Try different benchmarks until you find differences that explain the problem with profitability. If the question asks about how to improve the profitability of a particular product, compare that product’s cost and revenue structure to the profitability of their other major products.

Profitability Framework Example: Frozen Heaven Ice Cream

Case introduction:.

Our client, Frozen Heaven, makes small-batch ice cream. They serve the ice cream in the company’s restaurants as well as selling pints and quarts to go. Frozen Heaven has been experiencing a decline in profits and wants to turn this trend around.  What should they do?

Start by exploring either costs or revenues.  Question: How have revenues been trending over time? Revenues are down by 5% versus the prior year. Question: I’d like to understand what’s going on with revenue by looking at price and the quantity of ice cream sold. First, has the price of Frozen Heaven’s ice cream changed? There’s been no significant change in either the pricing of either the packaged ice cream or the ice cream served in the restaurants. Question: So the problem has been with the quantity of ice cream sold.  Yes, the quantity of ice cream sold is down 5%. The decline has been about the same across both the packaged and restaurant-served products. Question: I’m interested in understanding possible causes for the decline in ice cream sales. Are there any new competitors in the market? No. Question : Have existing competitors changed anything about their business? Price, advertising, opening new restaurants? Both our client and the competitors have added new stores over the last 12 months at about the same rate. Pricing and advertising haven’t changed. Question: Has our client’s product changed? The client hired a new head of operations 15 months ago. She has over ten years of experience with one of the biggest mass-market ice cream manufacturers in North America. She was given latitude to make changes to improve the company’s efficiency and profitability. In fact, she’s reduced costs but 3%. Unfortunately, that’s not enough to offset the reduction in revenue. Question: I’d like to understand the change in costs. Was the cost reduction in fixed costs, variable costs, or both. Variable costs. Question: Was the reduction in labor, the cost of ingredients, or something else? The cost of ingredients. Question: What ingredient costs went down?  Dollars spend on milk have been in line with the reduced quantity of ice cream sold, as were the costs of flavorings like chocolate, vanilla, etc.  The biggest change has been in the cost of mix-ins to the ice cream. The client creates specialty flavors by adding in things like chocolate chips, caramel, and crushed up Oreos and Heath Bar, etc. These costs are down 30%. Question: Has the reduction in mix-ins made a difference to the client’s customers? That’s a good question. We haven’t studied this, but a quick review of the client’s reviews on Yelp shows there are comments from customers suggesting that they’ve noticed the reduction in mix-ins and don’t like the change.

Conclusion/Recommendation:

Frozen Heaven has seen a decrease in profitability resulting from a reduction in the quantity of ice cream it sells both in packages and served to customers in its restaurants. Frozen Heaven’s variable costs have gone down. That would seem to be good for profitability at first glance, but the cost reduction resulted from smaller quantities of mix-ins being used in the ice cream.  From a quick scan of Yelp, it sounds like the customers don’t like the changes to Frozen Heaven ice cream. I’d recommend using customer focus groups to gain a deeper understanding of what Frozen Heaven’s customers want in their ice cream. If it turns out that the mix-ins are important to their customers’ buying decision, they should return to former mix-in levels even if it means spending more money. It will be worth it in terms of increased sales. It’s possible the client’s head of operations won’t like this recommendation because she made the change to the amount of mix-ins used, probably because she thought that it would increase profitability. But the results of focus groups will persuade her that this recommendation will improve profitability.

Types of Case Interview Questions that Can Be Answered Using the Profitability Framework

• A retail apparel client’s profitability has declined over the last year. What is the source of the decline and how can we turn it around?
• An airline outsourced the food service on its planes several years ago. Now they are unhappy about the quality of the food served to customers and are thinking of bringing it back in-house. How would that impact the cost of food service? The cost structure of the airline overall?
• A client that makes and markets beauty products through department stores has seen sales decline in the European market. How can they reverse this decline?
• The public school system in a city is facing a significant budget shortfall. How can they reduce costs to close the budget gap?
• A hospital supplies provider is experiencing a rise in the cost of its products. This has resulted in a squeeze on margins. How can it improve its profitability?
• A restaurant holding company recently launched a new brand of restaurants in a few test markets. These new restaurants are popular with customers but not as profitable as their existing restaurants. What should they do?

6 Tips on Using the Profitability Framework: Segmentation & Benchmarking Options

1. segment by business unit..

Identify key business segments. If the profit margin differs substantially from one business unit to another, analyze their individual revenue and cost structures to identify the problem.

2. Segment by Geography.

Identify the geographies the business operates in. If profitability differs substantially from one geography to another, dive deeper into this to identify the problem.

3. Segment by Sales Channel.

If a company has more than one sales channel, such as a direct sales force and sales through distributors, compare the profit margin of one to the other to identify problems.

4. Segment by Customer Type.

Compare profits of products sold to different industries or of specialized/high-end products to mass market/low-priced products to look for differences and opportunities for improvement.

5.  Segment by Product or Service Line.

Analyze profitability across different product or service lines. Identify underperforming or high-potential areas to allocate resources effectively.

6. Comparison to Key Competitors.

Look for differences in the cost structure and pricing between the client and key competitors. If there are differences, look for opportunities to correct disadvantaged cost structures or raise prices.

7.Comparison Over Time.

Analyze cost and revenue trends over time to see if they have been moving against the client and find opportunities to improve results7

In this article, we’ve covered:

• What a Framework is,
• Types of Case Interview Questions that Can Be Answered Using the Profitability Framework, and

Still have questions?

If you have more questions about the profitability framework, leave them in the comments below. One of My Consulting Offer’s case coaches will answer them.

Other people prepping for the profitability framework found the following pages helpful:

• Case Study Prep
• Case Interview Frameworks
• Market Entry Framework  

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3 Top Strategies to Master the Case Interview in Under a Week

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Profitability Case

Profitability case - a framework for the most common case type in consulting interviews.

As you already know, there are several common case types that occur in case interviews you should familiarize yourself with. Profitability case interview questions are the most frequently used case types during case interviews for management consulting roles. Make sure to be prepared for them by internalizing our five steps to crack profitability cases. 

Profitability Questions – The Number 1 Reason For Most Consulting Projects

The most common reason why firms instruct consulting firms with their projects is that they struggle with their profitability. You will have to find out the root cause of their declining profitability. Examples are  falling sales ,  rising costs,  or  both . Your task will be two-fold: performing a structured and quantitative analysis of the data to  isolate the problem,  and then finding a promising solution for the problem .

Solve the Profitability Case Using This Case Example

We will explain the procedure along with a profitability case example just like the one you might encounter in a consulting interview: Your client is a chewing gum manufacturer (you can find the entire premium case here ). The CEO of the manufacturing company is concerned because his company is experiencing  declining profitability . Please investigate the reasons for the decline and give suggestions for improvement.

The Five Steps to Crack a Profitability Case Problem

1. Clarify the problem

Remember  the 4 commandments !

Take notes! Start with restating the problem: “Just so we are on the same page, our main objective is to determine the reasons behind the decline in profitability for a chewing gum manufacturer and provide recommendations to improve the profitability of the business, is that correct?”

2. Prepare your structure

“Thank you, may I take a minute to prepare my structure?” 

As mentioned in the introduction, the terms “ declining profitability ,  falling sales  or  rising costs ” hint at a profitability case. You now have to  isolate the problem  and  quantify it . A good start to analyze a profit problem is by using the  profitability equation:

When profits go down, you either have a  decline in revenue ,  rising costs, or both . The best way to find the root cause is to sketch the problem as an  issue tree . Start with the more promising part, for instance, revenues - because the market is highly competitive . Obviously, you would share that thought with your interviewer and be on the lookout for hints. E.g. ‘ I am going to look at revenues first, since in a competitive market like the market for chewing gums, I’d expect this to be a big driver.'  

You can further break down the profit tree like below:

Now you can start with one of the branches. Let's take the revenue side.

3. Analyze the revenue side

Whenever you get the information that something has changed:  quantify it!  Ask by  how much  and  in what time period . And very importantly: SEGMENT the revenue streams! You can ask the interviewer whether you can segment the revenues into its component parts. If the interviewer prompts you to do the segmentation, you can think about different  customer segments  (small business / large business, etc., age group, sex, etc…), product lines, or regions (South America, Asia, etc.). This segmentation will help you isolate the root of the problem. You'll be able to develop better and more targeted analyzes.

For example, when helping a chewing gum manufacturer improve his profitability, you may ask: “What are the revenue sources?”. The interviewer tells you that all revenue comes from two products: Flavored and non-flavored chewing gums. At this point, you might want to know the development of sales over the past couple of years. “How have sales figures developed over the years for both products?” He shares the following diagram with you:

It now becomes clear that revenue is not the problem because it has grown steadily in recent years. Therefore, it must be costs that rose significantly, leading to a drop in profitability.

If you’ve found the biggest driver of the problem, you oftentimes have to switch to a more qualitative framework like the 4 Cs to find the underlying root cause! For example: when you have less revenue, but the price is the same and units sold dropped, you have to find out why. Is there a  new competitor  on the market? Do you have  quality problems , or did you just stop a marketing initiative that you ran for years prior to this drop? 

4. Analyze the cost side

Now explore the cost side. You know that costs can be broken down into direct and indirect costs . You can then inquire about the breakdown of costs: "Please tell me about the direct/indirect cost split for the products.” The interviewer hands you the following graph:

As we know that there are two different product lines, it is advisable to calculate their  margins to check if there is a more profitable product line. You calculate the margin for both products based on the following formula:

“I'd like to calculate the margins for both products; do you have information on the different prices and costs for each of them?” The interviewer hands you the following graph:

Based on this, you calculate the margins:

5. Close the profitability case

“Analyzes show that the product whose sales have increased (flavored chewing gum) is also the one with lower margins due to the added flavor. Therefore, total profit margins have decreased while sales have increased.”

After you have determined the root cause, you must develop a good logical solution  (e.g., developing a competitive response , starting a marketing initiative, etc.)

It is important to stay structured even if you think you have reached the final stage. Therefore, categorize your approaches, for instance by short-term/easy to implement solutions and long-term ones.

• Negotiate with current suppliers.
• Look for other suppliers (form partnerships or buy greater amounts with batch discounts).
• Vertical integration.
• Release new products with better margins (e.g., low-calorie flavor gum or tooth cleaning gum).
• The client could also increase the price of the flavored gum, risking decreasing sales if customers do not see any added value with the price rise (high price sensitivity ).

1. MBB Final Round Case – Non-Profit Museum Revenue Increase

Style:  Interviewer-led (McKinsey style)

Topics:  Pricing ,  Profitability analysis

Your client is  ‘Muse 19’ , a Museum in Paris with a large collection of 19th-century artifacts, predominantly paintings, and sculptures. The museum is run by a non-profit organization based in France. The museum is quite popular amongst students, artists, and tourists. Last year, the museum attracted almost 2 million visitors. Despite this, the museum’s  revenue has been declining  for the last three years. Surprisingly, other museums of similar nature have been doing much better than Muse 19. The museum director has approached you for advice. Read the whole profitability case .

2. Caribbean Island – MBB Final Round

Style:  Candidate-led (usual style)

Topics:  Brain teaser ,  Market sizing ,  Profitability analysis ,  Valuation

A wealthy client has recently  bought an island in the Caribbean . She has engaged us to identify possible uses for her new island. Read the whole case .

3. Incos Pens

Topics:  Market entry ,  Market sizing ,  Profitability analysis

Incos is a global manufacturer of writing products with divisions in North America, Europe, and South-East Asia. Their global sales are  $60 m  and their profits amounted to around  $30 m . Their European division who manufactures and sells  disposable pens  is experiencing  flattening sales and a decreasing profit.  The client hired you to help him come up with  suggestions  to get profits back on track. Read the whole case .

4. Espresso, Whatelse?

Topics:  Market analysis ,  Operations strategy ,  Pricing ,  Profitability analysis

Espresso Whatelse  is an Italian company that produces coffee and espresso machines since 1908. It is the Italian market leader and has a strong presence overall in Europe. In 2019,  Espresso Whatelse has increased its revenues, but it has seen  declining profit margin . Your client wants to understand the root causes of this 2019 trend and how to increase its profit margin again. Read the whole case .

5. DHL Consulting case: Books & Codes

Topics:  Operations strategy ,  Profitability analysis

A friend of yours recently got promoted to the position of  director of a university library . Yesterday, your friend received a call from the Ministry of Education, who offered him to be part of a national  RFID pilot  with his library. As your friend is unsure if he should pursue this option, he asks you for your advice. Your task is to  assess  the RFID technology for his library. How would you  approach  such a request? Read the whole case . 

Key takeaways

Profitability problems are frequent in consulting case interviews. To solve a profitability problem:

• find the root cause using the  profit formula
• use a  tree structure
• go down one branch at a time and  segment it
• quantify and look for trends
• locate the  biggest driver
• find out why through  qualitative analysis  and additional analysis (e.g., using the 4 Cs  Framework).

Questions on This Article

Excise tax to be dealt properly, related cases.

Bain Case: Old Winery

Oliver Wyman Case: Setting up a Wine Cellar

Oliver wyman case: on the right track.

zeb case: Quo vadis, customer?

EY-Parthenon Case: Virtual Marketplace

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Mastering the Profitability Framework for Case Interviews

Table of contents.

Consulting firms have a unique way of interviewing candidates. They use a case interview , where they present a real business problem that you need to break down and solve.

These interviews give consulting firms a direct indication of whether you would be a good consultant, as they test both hard skills (like problem-solving) and soft skills (like communication).

As a candidate, it is crucial that you have a clear and structured approach to tackling these case interviews. In other words, you should be familiar with frameworks and methodologies to solve different business problems.

One common case interview is a profitability case. So in this article, I will teach you how to use the Profitability Framework to confidently solve profitability cases.

Understanding the Profitability Framework

What is a case interview framework.

Let’s start with the concept of a framework…

A framework is a template that can be applied to break down and solve case interview questions. As a candidate, it gives you a clear starting point and a generic process to follow.

But frameworks are just a starting point. You will need to customize your approach based on the specifics of the case question you are given.

What is the Profitability Framework?

The Profitability Framework is a simple equation used to solve any profitability case interview question. The equation is: Profits = Revenue - Costs.

I’m sure this resonates with you all very well, as this is just how we calculate any profit in real life too, and consulting cases are no different!

However, during a case interview, you are expected to further break down the equation until you’ve identified to root causes of the company’s profitability issue.

Types of profitability case interview questions

It’s important that you’re able to quickly determine that your case interview question is a profitability question — and that’s not always obvious!

There are three main forms that profitability case interview questions may take:

• Profit problem:  For example, a client company has hired you as a consultant to increase profitability or profitability growth. This is the most straightforward and easy-to-identify profitability case interview question.
• Loss problem:  For example, a client company has been losing money for the last 3 years and wants you to identify and fix the issue.
• Margin problem:  For example, a client company has seen tightening margins over the last 2 years and wants you to address the issue.

Download 183 practice case interviews and over 851 pages of interview guides

The ultimate case study preparation package. Download practice cases from McKinsey, BCG, Bain, Harvard, Kellogg, Columbia, INSEAD, Cornell, and more!

How to apply the Profitability Framework

Once you’ve identified that your case interview question is a profitability question, you need to apply the Profitability Framework.

Fortunately, there’s a simple process that you can follow:

Step 1: Identify the specific profitability issue

First, you need to identify the profitability issue that the company is facing.

You will get some information from the interviewer when they read out the case scenario. But it’s also likely that you’ll need to ask questions to uncover more information.

Some examples of things to look for include:

• Profit is lower than competitors
• Profit is lower than historical levels
• Profit growth has changed
• Margins are shrinking

Step 2: Break down the revenue side of the equation

Next, you’ll need to figure out whether the profitability issue is due to falling revenues. To do this, you’ll need to break down revenue into its drivers .

There are multiple ways to break down a company’s revenue. You’ll need to figure out the most appropriate way, based on the case interview question that you’ve been given.

Some common revenue breakdowns include:

• Number of sales x revenue per sale:  This breakdown is useful for businesses that sell multiple products or SKUs, and where revenue per sale is highly variable.
• Number of customers x revenue per customer: This breakdown is useful for businesses that offer a limited range of solutions, such as subscription-based products or services businesses.
• Break down revenue by business unit or  geography: You can also breakdown revenue by function or location to identify performance differences in different parts of the business

Step 3: Break down the cost side of the equation

Now you must break down the cost side of the equation. Again, you’ll need to determine the most appropriate way to break down costs.

Some common breakdowns include:

• Fixed vs variable costs:  Understand whether there are issues with variable costs that scale with output (e.g. raw materials, packaging, production labor, etc) or with fixed costs (e.g. rent, utilities, etc)
• Operating vs non-operating costs: Understand whether there are issues with the operating costs associated with running the business (e.g. salaries, supplies, materials, etc) or non-operating costs (e.g. debt interest, taxes, etc).
• Break down cost by business unit or geography:  Just like you did for the revenue side, you can also segment costs by function or location to identify whether the underlying issue is unique to part of the business.

Step 4: Confirm any hypotheses that you have

By this stage, you should have uncovered one or more causes of the profitability issue outlined in the case study.

For example, you may have come to know that the average revenue per sale has dropped and variable costs have increased, confirm the same with the interviewer.

Test these with the interviewer and make sure you’ve identified the main hypotheses. If you’ve missed something, the interviewer will usually steer you in the right direction.

Step 5: Summarize your understanding of the problem and recommendations

After you’ve narrowed down your hypotheses, it’s time to think about solutions.

Ask the interviewer whether you can take 1-2 minutes to synthesize your findings and formulate recommendations (they will always give you this time).

First, focus on identifying the underlying issues with the biggest influence on profitability and prioritize those. You want to show that you can identify the “absolutely important” from the “merely interesting”.

Now think of potential solutions to those problems that you have identified. But don’t just think of generic solutions, you should think from the point-of-view of your specific company and include industry context.

For instance, if your client is an aviation company, include some industry-specific detail in your summary (maybe airline regulations, aviation fuel prices, etc.).

Tips for acing a profitability case interview question

There are a few things that can do to ensure you answer the case interview question well:

• Learn how to identify profitability questions:  Candidates often overlook the fact that profitability questions aren’t always obvious. Practice identifying which case studies are profitability questions to ensure that you’re applying the correct framework.
• Master the math: Profitability questions are all about breaking down using mathematics, so ensure that you’re confident in breaking down the question using the profitability equation.
• Don’t be afraid to ask questions:  Case interview questions are designed to be complex and ambiguous. Always ask the interviewer if you need more information or want to clarify your understanding.
• Prioritize the biggest drivers:  Most case studies will have multiple issues — but not all issues will be important. Show that you have practical business sense and prioritize the most important problems over the others.

Example profitability case interview questions

Example 1: global retailer.

Your client is a US-based fortune 500 company. It is one of the retail chains in the world. It was profitable and growing through the 1990’s. In 1999, it’s revenues were $14.1 billion. Since then revenues have been declining and the net income has been inconsistent. Help advise the company on how to improve profits.

Example 2: Chemical manufacturer

A major chemical manufacturer produces a chemical product used to preserve foods in containers. Despite an increase in market share, the manufacturer has experienced a decline in profits. The CEO of the company is worried about this trend and hires you to investigate.

Example 3: Cable TV company

A cable TV company from Canada, World View, had recently entered the US market in the northeast to expand its market share. World View saw this move as an opportunity to capture a large part of the US market (4MM consumers) in a market with very little competition.

However, in the last couple of years, much to the surprise of management, World View has been unable to make a profit. You have been hired to figure out why and advise them on their next move.

Example 4: Auto service chain

A major auto service chain, Wheeler Dealer, has enjoyed healthy returns on its 30-store operation for the past 10 years.

However, management feels that the chain needs to expand, as the current geographical areas in  which they are based have become saturated.

For the past couple of years, they have aggressively pursued a growth strategy, opening an additional 15 stores. However, it seems that this approach has had negative returns. For the first time in over a decade, the chain’s profits dropped into the negative zone. You were hired to figure out why.

Example 5: Travel agency

A travel agency makes a 10% commission on all of its travel bookings. Their current profit  before taxes is $1MM, while the industry average ranges from $2MM to $3.5MM. Why are they making less than the industry average?

Example 6: Hospital

Our client is a 350-bed hospital in a mid-size city. The organization has historically exhibited  strong financial performance, and had a 1-3% operating gain each year for the last five years.

However, they are projecting a $12 million operating loss this year, and expect this situation to worsen in the future. As a result, the CFO believes that they will be out of cash within five years.

They have asked us to identify the source of this sudden downturn, and to come up with alternatives to restore them to a break-even position. They are one of the largest employers in the market, and will not consider layoffs as a possible solution.

Example 7: Fast food chain

Six months out of HBS, a frustrated classmate calls you to complain that the fast food burger joint that he bought has been steadily losing money for the last 3 months. He wants to know what you think he should do about it. Where do you start?

A generative AI reset: Rewiring to turn potential into value in 2024

It’s time for a generative AI (gen AI) reset. The initial enthusiasm and flurry of activity in 2023 is giving way to second thoughts and recalibrations as companies realize that capturing gen AI’s enormous potential value is harder than expected .

With 2024 shaping up to be the year for gen AI to prove its value, companies should keep in mind the hard lessons learned with digital and AI transformations: competitive advantage comes from building organizational and technological capabilities to broadly innovate, deploy, and improve solutions at scale—in effect, rewiring the business  for distributed digital and AI innovation.

About QuantumBlack, AI by McKinsey

QuantumBlack, McKinsey’s AI arm, helps companies transform using the power of technology, technical expertise, and industry experts. With thousands of practitioners at QuantumBlack (data engineers, data scientists, product managers, designers, and software engineers) and McKinsey (industry and domain experts), we are working to solve the world’s most important AI challenges. QuantumBlack Labs is our center of technology development and client innovation, which has been driving cutting-edge advancements and developments in AI through locations across the globe.

Companies looking to score early wins with gen AI should move quickly. But those hoping that gen AI offers a shortcut past the tough—and necessary—organizational surgery are likely to meet with disappointing results. Launching pilots is (relatively) easy; getting pilots to scale and create meaningful value is hard because they require a broad set of changes to the way work actually gets done.

Let’s briefly look at what this has meant for one Pacific region telecommunications company. The company hired a chief data and AI officer with a mandate to “enable the organization to create value with data and AI.” The chief data and AI officer worked with the business to develop the strategic vision and implement the road map for the use cases. After a scan of domains (that is, customer journeys or functions) and use case opportunities across the enterprise, leadership prioritized the home-servicing/maintenance domain to pilot and then scale as part of a larger sequencing of initiatives. They targeted, in particular, the development of a gen AI tool to help dispatchers and service operators better predict the types of calls and parts needed when servicing homes.

Leadership put in place cross-functional product teams with shared objectives and incentives to build the gen AI tool. As part of an effort to upskill the entire enterprise to better work with data and gen AI tools, they also set up a data and AI academy, which the dispatchers and service operators enrolled in as part of their training. To provide the technology and data underpinnings for gen AI, the chief data and AI officer also selected a large language model (LLM) and cloud provider that could meet the needs of the domain as well as serve other parts of the enterprise. The chief data and AI officer also oversaw the implementation of a data architecture so that the clean and reliable data (including service histories and inventory databases) needed to build the gen AI tool could be delivered quickly and responsibly.

Creating value beyond the hype

Let’s deliver on the promise of technology from strategy to scale.

Our book Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI (Wiley, June 2023) provides a detailed manual on the six capabilities needed to deliver the kind of broad change that harnesses digital and AI technology. In this article, we will explore how to extend each of those capabilities to implement a successful gen AI program at scale. While recognizing that these are still early days and that there is much more to learn, our experience has shown that breaking open the gen AI opportunity requires companies to rewire how they work in the following ways.

Figure out where gen AI copilots can give you a real competitive advantage

The broad excitement around gen AI and its relative ease of use has led to a burst of experimentation across organizations. Most of these initiatives, however, won’t generate a competitive advantage. One bank, for example, bought tens of thousands of GitHub Copilot licenses, but since it didn’t have a clear sense of how to work with the technology, progress was slow. Another unfocused effort we often see is when companies move to incorporate gen AI into their customer service capabilities. Customer service is a commodity capability, not part of the core business, for most companies. While gen AI might help with productivity in such cases, it won’t create a competitive advantage.

To create competitive advantage, companies should first understand the difference between being a “taker” (a user of available tools, often via APIs and subscription services), a “shaper” (an integrator of available models with proprietary data), and a “maker” (a builder of LLMs). For now, the maker approach is too expensive for most companies, so the sweet spot for businesses is implementing a taker model for productivity improvements while building shaper applications for competitive advantage.

Much of gen AI’s near-term value is closely tied to its ability to help people do their current jobs better. In this way, gen AI tools act as copilots that work side by side with an employee, creating an initial block of code that a developer can adapt, for example, or drafting a requisition order for a new part that a maintenance worker in the field can review and submit (see sidebar “Copilot examples across three generative AI archetypes”). This means companies should be focusing on where copilot technology can have the biggest impact on their priority programs.

Copilot examples across three generative AI archetypes

• “Taker” copilots help real estate customers sift through property options and find the most promising one, write code for a developer, and summarize investor transcripts.
• “Shaper” copilots provide recommendations to sales reps for upselling customers by connecting generative AI tools to customer relationship management systems, financial systems, and customer behavior histories; create virtual assistants to personalize treatments for patients; and recommend solutions for maintenance workers based on historical data.
• “Maker” copilots are foundation models that lab scientists at pharmaceutical companies can use to find and test new and better drugs more quickly.

Some industrial companies, for example, have identified maintenance as a critical domain for their business. Reviewing maintenance reports and spending time with workers on the front lines can help determine where a gen AI copilot could make a big difference, such as in identifying issues with equipment failures quickly and early on. A gen AI copilot can also help identify root causes of truck breakdowns and recommend resolutions much more quickly than usual, as well as act as an ongoing source for best practices or standard operating procedures.

The challenge with copilots is figuring out how to generate revenue from increased productivity. In the case of customer service centers, for example, companies can stop recruiting new agents and use attrition to potentially achieve real financial gains. Defining the plans for how to generate revenue from the increased productivity up front, therefore, is crucial to capturing the value.

Upskill the talent you have but be clear about the gen-AI-specific skills you need

By now, most companies have a decent understanding of the technical gen AI skills they need, such as model fine-tuning, vector database administration, prompt engineering, and context engineering. In many cases, these are skills that you can train your existing workforce to develop. Those with existing AI and machine learning (ML) capabilities have a strong head start. Data engineers, for example, can learn multimodal processing and vector database management, MLOps (ML operations) engineers can extend their skills to LLMOps (LLM operations), and data scientists can develop prompt engineering, bias detection, and fine-tuning skills.

A sample of new generative AI skills needed

The following are examples of new skills needed for the successful deployment of generative AI tools:

• data scientist:
• prompt engineering
• in-context learning
• bias detection
• pattern identification
• reinforcement learning from human feedback
• hyperparameter/large language model fine-tuning; transfer learning
• data engineer:
• data wrangling and data warehousing
• data pipeline construction
• multimodal processing
• vector database management

The learning process can take two to three months to get to a decent level of competence because of the complexities in learning what various LLMs can and can’t do and how best to use them. The coders need to gain experience building software, testing, and validating answers, for example. It took one financial-services company three months to train its best data scientists to a high level of competence. While courses and documentation are available—many LLM providers have boot camps for developers—we have found that the most effective way to build capabilities at scale is through apprenticeship, training people to then train others, and building communities of practitioners. Rotating experts through teams to train others, scheduling regular sessions for people to share learnings, and hosting biweekly documentation review sessions are practices that have proven successful in building communities of practitioners (see sidebar “A sample of new generative AI skills needed”).

It’s important to bear in mind that successful gen AI skills are about more than coding proficiency. Our experience in developing our own gen AI platform, Lilli , showed us that the best gen AI technical talent has design skills to uncover where to focus solutions, contextual understanding to ensure the most relevant and high-quality answers are generated, collaboration skills to work well with knowledge experts (to test and validate answers and develop an appropriate curation approach), strong forensic skills to figure out causes of breakdowns (is the issue the data, the interpretation of the user’s intent, the quality of metadata on embeddings, or something else?), and anticipation skills to conceive of and plan for possible outcomes and to put the right kind of tracking into their code. A pure coder who doesn’t intrinsically have these skills may not be as useful a team member.

While current upskilling is largely based on a “learn on the job” approach, we see a rapid market emerging for people who have learned these skills over the past year. That skill growth is moving quickly. GitHub reported that developers were working on gen AI projects “in big numbers,” and that 65,000 public gen AI projects were created on its platform in 2023—a jump of almost 250 percent over the previous year. If your company is just starting its gen AI journey, you could consider hiring two or three senior engineers who have built a gen AI shaper product for their companies. This could greatly accelerate your efforts.

Form a centralized team to establish standards that enable responsible scaling

To ensure that all parts of the business can scale gen AI capabilities, centralizing competencies is a natural first move. The critical focus for this central team will be to develop and put in place protocols and standards to support scale, ensuring that teams can access models while also minimizing risk and containing costs. The team’s work could include, for example, procuring models and prescribing ways to access them, developing standards for data readiness, setting up approved prompt libraries, and allocating resources.

While developing Lilli, our team had its mind on scale when it created an open plug-in architecture and setting standards for how APIs should function and be built.  They developed standardized tooling and infrastructure where teams could securely experiment and access a GPT LLM , a gateway with preapproved APIs that teams could access, and a self-serve developer portal. Our goal is that this approach, over time, can help shift “Lilli as a product” (that a handful of teams use to build specific solutions) to “Lilli as a platform” (that teams across the enterprise can access to build other products).

For teams developing gen AI solutions, squad composition will be similar to AI teams but with data engineers and data scientists with gen AI experience and more contributors from risk management, compliance, and legal functions. The general idea of staffing squads with resources that are federated from the different expertise areas will not change, but the skill composition of a gen-AI-intensive squad will.

Set up the technology architecture to scale

Building a gen AI model is often relatively straightforward, but making it fully operational at scale is a different matter entirely. We’ve seen engineers build a basic chatbot in a week, but releasing a stable, accurate, and compliant version that scales can take four months. That’s why, our experience shows, the actual model costs may be less than 10 to 15 percent of the total costs of the solution.

Building for scale doesn’t mean building a new technology architecture. But it does mean focusing on a few core decisions that simplify and speed up processes without breaking the bank. Three such decisions stand out:

• Focus on reusing your technology. Reusing code can increase the development speed of gen AI use cases by 30 to 50 percent. One good approach is simply creating a source for approved tools, code, and components. A financial-services company, for example, created a library of production-grade tools, which had been approved by both the security and legal teams, and made them available in a library for teams to use. More important is taking the time to identify and build those capabilities that are common across the most priority use cases. The same financial-services company, for example, identified three components that could be reused for more than 100 identified use cases. By building those first, they were able to generate a significant portion of the code base for all the identified use cases—essentially giving every application a big head start.
• Focus the architecture on enabling efficient connections between gen AI models and internal systems. For gen AI models to work effectively in the shaper archetype, they need access to a business’s data and applications. Advances in integration and orchestration frameworks have significantly reduced the effort required to make those connections. But laying out what those integrations are and how to enable them is critical to ensure these models work efficiently and to avoid the complexity that creates technical debt  (the “tax” a company pays in terms of time and resources needed to redress existing technology issues). Chief information officers and chief technology officers can define reference architectures and integration standards for their organizations. Key elements should include a model hub, which contains trained and approved models that can be provisioned on demand; standard APIs that act as bridges connecting gen AI models to applications or data; and context management and caching, which speed up processing by providing models with relevant information from enterprise data sources.
• Build up your testing and quality assurance capabilities. Our own experience building Lilli taught us to prioritize testing over development. Our team invested in not only developing testing protocols for each stage of development but also aligning the entire team so that, for example, it was clear who specifically needed to sign off on each stage of the process. This slowed down initial development but sped up the overall delivery pace and quality by cutting back on errors and the time needed to fix mistakes.

Ensure data quality and focus on unstructured data to fuel your models

The ability of a business to generate and scale value from gen AI models will depend on how well it takes advantage of its own data. As with technology, targeted upgrades to existing data architecture  are needed to maximize the future strategic benefits of gen AI:

• Be targeted in ramping up your data quality and data augmentation efforts. While data quality has always been an important issue, the scale and scope of data that gen AI models can use—especially unstructured data—has made this issue much more consequential. For this reason, it’s critical to get the data foundations right, from clarifying decision rights to defining clear data processes to establishing taxonomies so models can access the data they need. The companies that do this well tie their data quality and augmentation efforts to the specific AI/gen AI application and use case—you don’t need this data foundation to extend to every corner of the enterprise. This could mean, for example, developing a new data repository for all equipment specifications and reported issues to better support maintenance copilot applications.
• Understand what value is locked into your unstructured data. Most organizations have traditionally focused their data efforts on structured data (values that can be organized in tables, such as prices and features). But the real value from LLMs comes from their ability to work with unstructured data (for example, PowerPoint slides, videos, and text). Companies can map out which unstructured data sources are most valuable and establish metadata tagging standards so models can process the data and teams can find what they need (tagging is particularly important to help companies remove data from models as well, if necessary). Be creative in thinking about data opportunities. Some companies, for example, are interviewing senior employees as they retire and feeding that captured institutional knowledge into an LLM to help improve their copilot performance.
• Optimize to lower costs at scale. There is often as much as a tenfold difference between what companies pay for data and what they could be paying if they optimized their data infrastructure and underlying costs. This issue often stems from companies scaling their proofs of concept without optimizing their data approach. Two costs generally stand out. One is storage costs arising from companies uploading terabytes of data into the cloud and wanting that data available 24/7. In practice, companies rarely need more than 10 percent of their data to have that level of availability, and accessing the rest over a 24- or 48-hour period is a much cheaper option. The other costs relate to computation with models that require on-call access to thousands of processors to run. This is especially the case when companies are building their own models (the maker archetype) but also when they are using pretrained models and running them with their own data and use cases (the shaper archetype). Companies could take a close look at how they can optimize computation costs on cloud platforms—for instance, putting some models in a queue to run when processors aren’t being used (such as when Americans go to bed and consumption of computing services like Netflix decreases) is a much cheaper option.

Build trust and reusability to drive adoption and scale

Because many people have concerns about gen AI, the bar on explaining how these tools work is much higher than for most solutions. People who use the tools want to know how they work, not just what they do. So it’s important to invest extra time and money to build trust by ensuring model accuracy and making it easy to check answers.

One insurance company, for example, created a gen AI tool to help manage claims. As part of the tool, it listed all the guardrails that had been put in place, and for each answer provided a link to the sentence or page of the relevant policy documents. The company also used an LLM to generate many variations of the same question to ensure answer consistency. These steps, among others, were critical to helping end users build trust in the tool.

Part of the training for maintenance teams using a gen AI tool should be to help them understand the limitations of models and how best to get the right answers. That includes teaching workers strategies to get to the best answer as fast as possible by starting with broad questions then narrowing them down. This provides the model with more context, and it also helps remove any bias of the people who might think they know the answer already. Having model interfaces that look and feel the same as existing tools also helps users feel less pressured to learn something new each time a new application is introduced.

Getting to scale means that businesses will need to stop building one-off solutions that are hard to use for other similar use cases. One global energy and materials company, for example, has established ease of reuse as a key requirement for all gen AI models, and has found in early iterations that 50 to 60 percent of its components can be reused. This means setting standards for developing gen AI assets (for example, prompts and context) that can be easily reused for other cases.

While many of the risk issues relating to gen AI are evolutions of discussions that were already brewing—for instance, data privacy, security, bias risk, job displacement, and intellectual property protection—gen AI has greatly expanded that risk landscape. Just 21 percent of companies reporting AI adoption say they have established policies governing employees’ use of gen AI technologies.

Similarly, a set of tests for AI/gen AI solutions should be established to demonstrate that data privacy, debiasing, and intellectual property protection are respected. Some organizations, in fact, are proposing to release models accompanied with documentation that details their performance characteristics. Documenting your decisions and rationales can be particularly helpful in conversations with regulators.

In some ways, this article is premature—so much is changing that we’ll likely have a profoundly different understanding of gen AI and its capabilities in a year’s time. But the core truths of finding value and driving change will still apply. How well companies have learned those lessons may largely determine how successful they’ll be in capturing that value.

The authors wish to thank Michael Chui, Juan Couto, Ben Ellencweig, Josh Gartner, Bryce Hall, Holger Harreis, Phil Hudelson, Suzana Iacob, Sid Kamath, Neerav Kingsland, Kitti Lakner, Robert Levin, Matej Macak, Lapo Mori, Alex Peluffo, Aldo Rosales, Erik Roth, Abdul Wahab Shaikh, and Stephen Xu for their contributions to this article.

This article was edited by Barr Seitz, an editorial director in the New York office.

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