analyzing your hr landscape assignment

HR LANDSCAPE ASSESSMENT UNLOCKING THE FUTURE OF YOUR WORKPLACE

Presented by Alysha M. Campbell, Founder & CEO

In today's dynamic and rapidly evolving business environment, Human Resources (HR) is at the forefront of driving organizational success. As a fractional HR consultant specializing in Diversity, Equity, and Inclusion (DEI) strategies, I'm excited to embark on this comprehensive HR Landscape Assessment with you.

Our mission is to navigate the ever-changing HR terrain, uncovering valuable insights, and offering strategic solutions that empower organizations to build inclusive, equitable, and high-performing workplaces.

By leveraging my expertise in HR & DEI, I aim to provide a holistic view of your HR landscape, identifying trends, challenges, and opportunities that will shape the future of your HR practices and contribute to the overall growth and success of your organization.

THE ASSESSMENT COVERS THE FOLLOWING:

Hr leadership.

Every organization deserves a dedicated team to focus on all areas of HR.  We believe that our people are the heart of every organization.

HR Technology

HR-related technology plays a pivotal role in navigating the complexities of managing human capital.

Employee Engagement

In today's dynamic business landscape, employee engagement stands as the cornerstone of organizational success.

Diversity, Equity & Inclusion

Diversity, Equity, and Inclusion aren't just buzzwords; they're the foundation of a vibrant, innovative, and harmonious workplace

HR Ecosystem

What's working well, where are there areas that may need improvement, what opportunities for growth are there, and does your organization have a future vision plan?

Leadership Development

In the ever-evolving world of business, leadership development stands as a beacon of growth and progress.

WHO THIS ASSESSMENT IS FOR:

Our hr landscape assessment is specifically designed for forward-thinking organizations and hr professionals who are keen on driving growth and innovation. it's an ideal tool for:.

Executives & Business Owners:

Leaders who recognize the importance of effective HR in achieving business objectives and fostering a positive organizational culture.

Small to Medium-Sized Enterprises (SMEs):

Businesses seeking to establish robust HR practices and systems to support their growth.

HR Managers & Directors

Individuals responsible for overseeing the HR function and looking to enhance their HR strategy and operations.

Startups & Emerging Companies:

Organizations in the growth phase needing to establish solid HR foundations to support rapid expansion.

Companies Undergoing Change:

Businesses facing transitional phases, such as mergers, acquisitions, or significant restructuring, who require a reassessment and realignment of their HR strategies.

Diversity, Equity, & Inclusion Advocates:

Organizations committed to improving their DEI practices and fostering an inclusive workplace.

Let's unlock the full potential of your organization's HR landscape, one question at a time.

The investment.

At just $575 (USD), our comprehensive HR Landscape Assessment represents an outstanding investment for your organization. This assessment is not just a diagnostic tool; it's a transformative journey into the heart of your company's HR framework. It covers critical areas such as HR Leadership, Technology, Employee Engagement, Leadership Development, and Diversity, Equity, and Inclusion (DEI).

For this competitive price, you will gain:

In-depth Analysis : Receive a detailed analysis of your HR ecosystem, providing insights that are often overlooked but critical for organizational growth.

Customized Recommendations: Benefit from tailored strategies and actionable steps to enhance your HR functions and align them with your business goals.

Future-Proofing Your Business: Equip your organization with the tools and knowledge to adapt to evolving business landscapes, ensuring long-term success and resilience.

Enhanced Employee Experience: Improve engagement, development, and inclusivity, leading to a more motivated and productive workforce.

Expert Guidance : Our team of experts will guide you through the assessment report and will also provide ongoing support, maximizing the value of your investment.

The HR Landscape Assessment at $575 is not just an expenditure but a strategic investment in your organization’s most valuable asset - its people. Take this step towards unlocking the full potential of your HR landscape and driving your organization towards a successful future.

• How long does the HR Landscape Assessment take to complete? The HR Landscape Assessment is designed to be thorough yet efficient. On average, it takes about 25-30 minutes to complete. We’ve structured the assessment to be comprehensive in covering key areas such as HR Leadership, Technology, Employee Engagement, Leadership Development, and Diversity, Equity, and Inclusion (DEI), while also respecting your time constraints. This time frame ensures that you can provide thoughtful and meaningful responses without it being overly time-consuming. We recommend setting aside a quiet, uninterrupted period to complete the assessment, allowing you to reflect on each aspect of your HR landscape thoroughly. The insights gained from this time investment are invaluable for shaping your organization’s HR strategy and practices.
• Can the Assessment be Paused and Resumed? Once you start the assessment, you should plan to complete it in one sitting. The assessment will time out after about an hour and your progress will unfortunately not be saved.
• Is There a Discount for Multiple Assessments Within One Organization? Please reach out to us directly for more information: [email protected]
• Is the Assessment Confidential and Secure? Absolutely. We take the confidentiality and security of your information very seriously. Here's how we ensure this: Strict Access Control: Access to your assessment data is strictly limited to authorized personnel who are directly involved in the analysis and report generation process. These individuals are trained in data privacy and are committed to maintaining the highest standards of confidentiality. Privacy Compliance: Our processes are designed in compliance with leading privacy laws and standards. We regularly review and update our practices to stay aligned with the latest regulations and best practices in data protection. Anonymization of Data: When analyzing data for trends or insights, we ensure that it's anonymized. This means any identifying information is removed or altered to prevent the identification of individual participants. Secure Report Delivery: The final report is delivered through a secure platform. You will receive a unique, password-protected link to access your report, ensuring that only you and your designated team members can view it. No Third-Party Sharing: With the exception of sharing data with our Partner, PeopleGuru, we will NOT share your data with third parties without your explicit consent. Your information is used solely for the purpose of the HR Landscape Assessment and to provide you with customized recommendations. PeopleGuru equally shares our commitment to data protection and privacy. Regular Security Audits: Our systems undergo regular security audits to identify and rectify any vulnerabilities, ensuring continuous protection of your data. We understand the importance of trust in our services, and we are committed to upholding the highest standards of data privacy and security. If you have any specific concerns or questions about our data handling practices, please feel free to contact us for further information.
• How long will it take to receive the report after completing the HR Landscape Assessment? Once you have completed the HR Landscape Assessment, we commit to delivering your comprehensive report within 7-10 days. This timeframe allows our team to thoroughly analyze your responses and craft a detailed report that includes an in-depth analysis, customized recommendations, and strategic insights tailored to your organization's specific needs and goals. We understand the importance of timely and actionable feedback, so our team works diligently to ensure that you receive a quality report that provides valuable insights into your HR functions and strategies as quickly as possible. Rest assured, we are dedicated to providing you with a report that not only meets but exceeds your expectations, in a timeframe that allows for prompt and effective action.
• What if I Have Questions or Need Clarification on the Report? We understand that the HR Landscape Assessment report can contain comprehensive and detailed information. It's natural to have questions or require clarifications on some aspects of the report. Here’s how we support you in this process: Scheduled Follow-Up Meeting: We typically schedule a follow-up meeting post-report delivery. This meeting is an opportunity for you to discuss the report in detail with our team, ask questions, and seek clarification on any of the findings or recommendations. Email and Phone Support: You can reach out to us via email for any immediate questions or clarifications. Our team is committed to providing prompt and thorough responses to ensure your complete understanding of the report. Documentation and Additional Resources: Along with the report, we provide supplementary documentation that can help explain methodologies, terms, and concepts used in the report. These resources are designed to enhance your understanding and provide additional context. Ongoing Consultation Services: If you require more in-depth support or ongoing consultation to implement the recommendations in the report, we offer specialized services. These can be tailored to your specific needs and can range from one-off consultations to long-term advisory roles. Webinars and Workshops: Occasionally, we conduct webinars and workshops that delve into common themes and questions arising from our HR Landscape Assessments. These sessions are a great way to gain further insights and engage with our experts. Feedback Mechanism: We welcome your feedback on the report and our support services. If there’s anything you believe we could improve or clarify further, we are open to hearing your thoughts. This feedback helps us enhance our services continually. We are committed to ensuring that you derive the maximum value from your HR Landscape Assessment report. Our team is here to support you every step of the way, from understanding your report to implementing its recommendations effectively.
• How Can the Results Be Utilized? The results of the HR Landscape Assessment are designed to provide actionable insights and strategic guidance in various areas of your human resources function. Here’s how you can effectively utilize these results: Strategic Planning: Use the insights from the assessment to inform your HR strategic planning. The detailed analysis of areas like HR leadership, technology, and DEI can help you identify strengths to build upon and areas that need improvement. Targeted Interventions: The assessment pinpoints specific areas within your HR ecosystem that may require attention. This allows you to design targeted interventions, whether it's enhancing employee engagement, upgrading HR technology, or implementing more effective leadership development programs. Performance Benchmarking: Compare your current HR practices against the best practices identified in the report. This benchmarking can be a powerful tool for continuous improvement. Training and Development: Leverage the findings related to leadership development and employee engagement to tailor your training and development programs. This ensures that they are directly addressing the needs and gaps identified in the assessment. DEI Initiatives: Use the DEI insights from the assessment to enhance your diversity, equity, and inclusion strategies. This could involve revising policies, implementing new training programs, or setting new organizational DEI goals. Enhancing Employee Experience: Utilize the feedback on employee engagement to create a more fulfilling and productive work environment. This might include improving internal communication, employee recognition programs, or career development opportunities. HR Policy Review and Update: The assessment can highlight areas where your HR policies may be outdated or not aligned with industry best practices. Use this as an opportunity to review and update these policies. Future Workforce Planning: Insights into the current state of your HR ecosystem can aid in planning for future workforce needs, helping you anticipate and prepare for changes in the labor market or industry. Leadership Team Development: Utilize the assessment's findings on your HR leadership team to identify areas for further development and training, ensuring that your leaders are equipped to drive HR success. Feedback Loop: The results can also be used to create a feedback loop within your organization, where you regularly assess, implement changes, and reassess to ensure continuous improvement in your HR practices. By leveraging these results, your organization can make informed decisions, implement effective strategies, and continuously improve your HR functions to align with your overall business goals.

Next Steps and Follow-Up After Your HR Landscape Assessment

Thank you for completing our in-depth HR Landscape Assessment! As we process the insights and data gathered, here's what you can expect next:

Comprehensive Report Delivery : Within the next 7-10 business days, you will receive a detailed report. This report will provide a thorough analysis of your HR Leadership Team, HR Technology, Employee Engagement, Leadership Development, Diversity, Equity, and Inclusion (DEI), and your overall HR Ecosystems.

Tailored Recommendations : The report will include tailored strategies and actionable recommendations to enhance each aspect of your HR landscape. These suggestions are designed to align with your organization’s unique needs and objectives.

Scheduled Follow-Up Meeting : After you’ve had a chance to review the report, we will schedule a follow-up meeting, if desired. During this session, we'll discuss the findings in-depth, answer any questions, and collaborate on prioritizing the implementation of recommendations.

Feedback and Continuous Improvement: Your feedback is crucial for continuous improvement. We welcome your thoughts on the assessment process and the report, which will help us refine our approach and support your ongoing HR evolution.

We're excited to continue this journey with you, transforming insights into actions that foster growth, innovation, and success in your organization.

📝 Example of Report 📝

How to be great at people analytics

A decade ago, someone touting the benefits of “people analytics” probably would have been met with blank stares. Was there value to be gleaned from HR data? Absolutely. But firms were thinking more narrowly about the potential—focusing on core HR systems and gathering straightforward information, such as snapshots of regional head counts or the year’s average performance evaluation rating, rather than using analytics capabilities to manage talent and make evidence-based people decisions.

Today, however, the majority of large organizations have people analytics teams, 1 Innovation generation: The big HR tech disconnect 2019/20 report , Thomsons Online Benefits, July 24, 2019, thomsons.com. 70 percent of company executives cite people analytics as a top priority, 2 “How people analytics can change an organization,” Knowledge@Wharton, May 23, 2019, knowledge.wharton.upenn.edu. and there’s little argument that people analytics is a discipline that’s here to stay. What’s striking, though, is the different ways that firms have approached building their people analytics functions. Team size, composition, and organization vary widely, and priorities for capability development and maturation differ significantly.

Most companies still face critical obstacles in the early stages of building their people analytics capabilities, preventing real progress. The majority of teams are still in the early stages of cleaning data and streamlining reporting. Interest in better data management and HR technologies has been intensive, but most companies would agree that they have a long way to go.

Leaders at many organizations acknowledge that what they call their “analytics” is really basic reporting with little lasting impact. For example, a majority of North American CEOs indicated in a poll that their organizations lack the ability to embed data analytics in day-to-day HR processes consistently and to use analytics’ predictive power to propel better decision making. 3 Based on responses of participants at a McKinsey roundtable of 45 chief human-resources officers in the autumn of 2016. Frank Bafaro, Diana Ellsworth, and Neel Gandhi, “ The CEO’s guide to competing through HR ,” McKinsey Quarterly , July 24, 2017. This challenge is compounded by the crowded and fragmented landscape of HR technology, which few organizations know how to navigate.

So, while the majority of people analytics teams are still taking baby steps, what does it mean to be great at people analytics? We spoke with 12 people analytics teams from some of the largest global organizations in various sectors—technology, financial services, healthcare, and consumer goods—to try to understand what teams are doing, the impact they are having, and how they are doing it.

Stairway to impact

It helps to think about the growth trajectory of a people analytics team as a stairway with five steps (Exhibit 1). The best teams don’t climb directly from one step to the next one; they are constantly iterating—retracing their steps and climbing the same stairs again—at every level of the journey to the top.

To move from the first step of the stairway (poor data) to the second step (good data), an organization must focus on building a foundation of high-quality data. This usually means that data needs to be extracted from the transactional systems where it is entered and then reshaped, cleaned, and re-coded into a more manageable and easier-to-understand structure that is aligned to the goals of the people analytics team. The more that analysts and data scientists need to clean and recode data to make it usable for even simple analysis, the less efficient the analytics team will be and the longer it will take to develop its skills and capabilities. This is arguably the most difficult step to get right. Significant resources, time, and investment are required to identify and manage core HR data systems, establish a common language and consistent data structure, and determine a basic set of guidelines for data collection, processing, and engineering. These are iterative processes, with no definitive solutions; rather, the processes and their outcomes change as the internal and external talent environments shift, systems are retired and renewed, and links are established among HR teams such as recruiting, training and development, and employee benefits.

As the operating environment changes at an increasingly rapid pace, both capabilities and the technology used to manage and transform data need to be increasingly flexible. In people analytics, as in many other tech-enabled fields, taking an agile approach is now a fundamental requirement. People analytics teams must work together with their enterprise-wide technology groups in a rapid and nimble way to institute new technology platforms, evolve existing infrastructure, and maintain consistent enterprise-wide standards.

Once a strong data foundation is in place, the people analytics team can climb to the third step, making the useful data accessible to the organization and experimenting with new technologies to analyze and disseminate the data. The sophistication that organizations are able to achieve at this step is variable. At the simplest end of the spectrum, teams might focus on automating and visualizing HR dashboards via standard business-intelligence platforms such as Tableau, in order to generate standard reports or respond to ad hoc requests. More advanced teams might prioritize custom builds and software development for self-serve applications, perhaps using their own front-end developers.

It’s evident from our interviews that organizations arrive in different ways at the ability to put data and actionable insights into the hands of decision makers. At several points, organizations must make decisions related to technologies and platforms—decisions such as whether to use homegrown talent or third-party vendors—and the answers vary by organization. As one would expect, the ability to attain advanced automation and self-serve capabilities depends greatly on the quality and accessibility of the underlying data.

Teams that mastered descriptive and automated reporting at step three are ready to climb to step four and build advanced-analytics capabilities. Data scientists, rather than business-information specialists, use programming languages like R, Python, and Julia to join disparate sources of data, build models to help understand complex phenomena, and provide actionable recommendations to leaders making complex and strategic business decisions.

We spoke to people analytics teams at a handful of organizations that are experimenting heavily at this level of the stairway and still have significant room to grow as their companies become open to new statistical tools, scale their data-science talent bench, and pursue a wide range of use cases. While some companies employ “broad-spectrum” data scientists who work cross-functionally to support a wide range of business needs, we found that the most advanced teams have created specific subspecialties in data science (for example, natural-language processing, network analytics, and quantitative psychometrics). These allow people analytics teams to increase their impact on their organizations by providing the advanced insights necessary to support strategic decision making on diverse and complex types of talent issues.

No people analytics team we interviewed has been able to take a full fifth step to reach the top level of the stairway: creating reliable, consistent, and valid predictive analytics. Reliable predictions will enable people analytics teams to analyze and explore practical options for management action. While some organizations have built fit-for-purpose predictive models—mostly for workforce planning—implementing predictive analytics in the context of employee selection, development, or engagement decisions requires a substantially scaled-up data-science operation, massive amounts of highly accurate data (“very big data”), cutting-edge algorithmic technology, and organizational comfort with how to address the impact on fairness and bias.

Beyond the required resources and the complexity of the analytics techniques, the infrastructure also poses a challenge to scalability and could require the use of cloud services. Most of the teams we spoke with are still working from on-premise technological infrastructures and show few signs of migrating their data and analytics capabilities to cloud services in the near future.

Ingredients for success

Our conversations with people analytics teams in leading organizations reveal a set of six best-in-class ingredients that have helped to propel the teams’ impact, success, and continued growth. These ingredients fall into three main categories: data and data management, analytics capabilities, and operating models. If we were to build a leading people analytics team from scratch, this is what we would strive for.

Data and data management

All great analytics teams are enabled by strong data standards, engineering, and management, and our interviews confirmed that this is no different in people analytics.

Significant and dedicated data-engineering resources. We found that the greatest team differentiator was the level of dedicated data-engineering resources available to it for propelling data creation and quality control. The leading teams have full ownership of their own data repositories, allowing them to rapidly test new ideas, iterate, and reduce dependencies on enterprise-level technology resources.

An added benefit of dedicated data-engineering resources is that they enable strategic alignment. Data engineers who are steeped in the strategic context of their organization’s people analytics teams are able to design the data foundation and analytics solutions more thoughtfully and deliberately from the beginning.

Breadth and depth of data sources. Leading teams have invested heavily in a strong HR-data foundation but also have advanced ways of going beyond the core HR systems to use several additional internal sources of data. The most straightforward way might be seamlessly linking the HR data with finance data, though data priorities will differ depending on organizational context. A few teams have begun to step beyond relational databases to build graph databases 4 A type of NoSQL database, graph databases are able to model relationships within data in a powerful and flexible manner. For more, see Antonio Castro, Jorge Machado, Matthias Roggendorf, and Henning Soller, “ How to build a data architecture to drive innovation—today and tomorrow ,” June 3, 2020. for advanced network analytics. In addition, leading teams have a robust and flexible survey strategy for monitoring employee sentiment. They are also able to integrate their survey data with multiple other data sources to create multidimensional quantitative and psychometric models that help explain employee engagement trends and dynamics.

While it is common for people analytics teams to feel constrained by a lack of easily available data, leading teams are more creative with data, acquiring new sources or combining existing ones in new ways to attack the problem at hand. For example, time-sheet data could be transformed and loaded into a graph database and linked by activity or project codes to allow better analysis of teamwork and collaboration.

Analytics capabilities

Advanced people analytics projects can require both deep technical knowledge and the ability to integrate and translate across a wide array of expertise and input. The best teams are building their talent bench with breadth and depth.

Robust data-science function. As we expected, all the leading people analytics teams we interviewed have invested heavily in acquiring data-science talent, though their approaches differ. Some teams focus on hiring “all-around athletes,” while others prioritize specialized backgrounds such as quantitative psychometrics or natural-language processing. Leading teams have sizable data-science “pods” that span a wide range of advanced analytical methodologies, programming languages, and academic backgrounds. The best teams hire and develop specialists in specific disciplines of data science but nevertheless expect all of these individuals to operate in a nimble, cross-functional way in order to meet evolving needs.

Strong translation capability. Leading teams also complement their high-caliber technical talent with skilled “translators”: specialized “integrators,” who bridge the gap between business leaders and technical experts. They translate strategic challenges into analytic questions and use evidence-based practice to interpret insights derived from the analytics, engage stakeholders, and ultimately propel business changes. Translators often serve as an entry point to the people analytics team, helping to raise awareness of the team in the organization and build the team’s credibility. Some of the leading people analytics teams have built benches of internal consultants to partner directly with individual businesses on their specific problems.

Operating models

In a fast-developing field, people analytics teams need to deliver impact across the organization and stay ahead of the curve to maintain that impact into the future. The best teams align themselves well against organizational priorities while maintaining space for open experimentation and innovation.

Innovation as the norm. Members of leading teams are explicitly expected to explore and innovate beyond their day-to-day fulfillment of the needs of their clients. Some companies have rules of thumb for the percentage of time that teams spend on exploration as opposed to core foundational work. These expectations allow teams to fully experiment and build out proofs of concept.

This process can take a variety of forms, but the important distinction is that the areas of innovation need not directly support an existing business priority or client need; they might be purely exploratory. For example, some data scientists relish the extra time to play around in a sandbox and learn how analytic tools and services work in the cloud. Others might want to explore creative new ways to visualize data in order to equip business leaders with helpful insights. The goal is to ensure that all team members are constantly forming new ideas and looking for new ways to meet the analytic needs of the organization and thereby help it achieve its objectives.

Clear alignment with clients and organizational use cases. People analytics teams take different approaches to organizing themselves and aligning with different clients. What is consistent, however, is the presence of a mechanism for attaining an in-depth understanding of enterprise-wide priorities as well as the specific needs of individual clients. This mechanism creates feedback loops that enable continuous learning and iterative development, and it ensures that people analytics teams are working on the most pressing and high-impact topics.

A culture of trust, empowerment, and ownership is the critical foundation for ensuring that a people analytics team is aligned with its clients as well as the enterprise. People analytics teams routinely deal with urgent (and often ambiguous) client needs and questions, highly sensitive data, and challenges to extrapolating meaningful and actionable insights that will guide business decisions. The bar to entry for the best teams is high: members must own their work from end to end and be empowered to define the constraints of any analysis, protect privacy as well as fairness and equity, flag issues that arise, and use their own judgment to derive insights. Being reactive and incremental is not enough in human resources, where priorities change and the top ones require immediate attention.

Over time, as organizations become increasingly dependent on the quality of their insights, the best people analytics teams play a stronger role in shaping the HR agenda, influencing how the organization manages its talent at both a policy and a process level.

The pulse survey

The COVID-19 crisis provided a natural experiment for one large, global organization with a strong people analytics team to use the ingredients outlined in the previous section by rapidly creating a homegrown weekly pulse survey to track the opinions and feelings of tens of thousands of employees around the globe. This capability enabled the organization to better understand the best ways to support employees in a challenging time and a fully remote work environment.

Setting up the pulse survey required intensive collaboration between diverse, highly skilled individuals already embedded in the organization’s people analytics team as well as rapid and close collaboration with the leadership of the organization. Translators navigated the need to craft questions that engaged employees, gathered high-quality data to feed the analytic models, and communicated insights back to leaders who had urgent decisions to make about how to best support their workforce in an external environment that was highly unpredictable and changing week by week.

To speed the time to insights, data engineers established an automated and continuous link among weekly survey-response data, core HR data systems, and a broader set of additional data sources, including data sets that data engineers had developed and customized for this purpose. This process cleaned, tested, and prepared the data for analysis. In addition to rapidly providing analysts with weekly data to examine and synthesize, it fed these data to a prototype self-service reporting tool, which gave leaders the ability to directly investigate aggregated pulse data within six hours of the survey’s close.

The customized data sets supported both exploratory and targeted analyses and helped generate actionable insights for the leaders. Analyses were designed to build on the organization’s current understanding of the health of its employees, marrying new and existing information to yield new insights that guided various efforts. For example, specialists in natural language processing used structural topic modeling to identify and quantify topics in the free-text comments that employees submitted as part of the survey each week. Sentiment analysis was used to understand the emotion behind each topic. These results were then married to the demographic information prepared by data analysts, allowing managers, leaders, and other decision makers to understand how the conversations and associated feelings varied by subpopulation, such as parents and less tenured employees. The combination of data sources and analytic approaches ultimately revealed population-specific needs, which allowed the organization to target specific groups and tailor the type of support it offered to maximize impact.

Exhibit 2 is a view of the major topics generated from the free text of the employees who responded to the pulse surveys and how their emphasis on these topics changed over the course of two months of the crisis. At the beginning, employees were thankful for the health of their families and peers and had generic concerns about the developing situation, but as the crisis evolved, their thoughts crystallized into the more particular concerns of isolation, remote work, childcare, and work-life balance.

The ability to rapidly develop this capability, turn around a wide range of sophisticated analytics within 24 hours after the survey closed, and repeat the survey weekly did not come easily to the organization or the people analytics team. The capabilities required to pull it off were tightly rooted in the data, analytics, and operating-model ingredients that we have identified as the hallmarks of great people analytics teams.

Despite the vast differences that exist among organizations’ data quality, integration, and infrastructure, we all certainly have a lot to learn from each other. Answering the following questions will be helpful to leaders who want to identify where their organization’s people analytics is now and where they would like them to be:

• Where is the organization on the people analytics stairway? Where does it aspire to be in the next year, three years, and five years?
• How does the organizational context influence the mandate of the people analytics team?
• What ingredients does the organization possess today, and which does it need to build?
• How should the organization determine its priorities in building people analytics capabilities? For example, should it build to support certain specific internal use cases, or should it build a broad bench of capabilities to support an unpredictable or rapidly changing internal environment?
• If the organization had to get one thing right over the next 12 months, what would it be? What would get in the way of its getting there?

While no single model is the “correct” one for developing the capabilities of a people analytics team, leading teams seem to have a set of ingredients in common. While the past decade has brought about real change, even the best teams—those that iterate at each step of the stairway and learn as they ascend—have barely scratched the surface of what’s possible with people analytics.

Elizabeth Ledet is a partner in McKinsey’s Atlanta office; Keith McNulty is a director, people analytics and measurement, in the London office; Daniel Morales is a director of analytics in the Washington, DC, office; and Marissa Shandell is an alumna of the New York office.

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The Definitive Guide to People Analytics: How to Make Better HR Decisions

What you need to show up as a strategic partner at your business.

In today’s business landscape, people analytics offers HR a seat at the strategic table.

Just as other areas of the business bring a data-backed performance narrative to every board meeting, strategic call, and quarterly check-in, HR leaders are also harnessing the power of data through people analytics.

And it’s working.

HR teams that leverage data are 10x more likely to be effective at providing insights to top leaders. And companies that excel at analytics are 3.1x more likely to financially outperform their competitors.

What is People Analytics?

Labor costs

Employee engagement

And so much more

People analytics has evolved over the last few years as more businesses and industries try to make sense of how their people policies and strategies impact their business’s performance, specifically:

• Why employees leave jobs
• How to minimize turnover
• How to improve hiring practices
• The business impact of turnover
• How to boost employee productivity
• Employee wellbeing

When HR leaders leverage the employee data they’re already collecting to answer business questions, they shift into a strategic business partner capacity and increase the value they bring to their role..

Think of your employee data like kindling—something easily available, often overlooked, but holding immense strategic power when paired with the spark of analysis. Analysis and reporting illuminate the untapped potential of the employee data you’re already collecting.

What data does HR need to track for people analytics?

If you’re just getting started with people analytics, it can seem daunting to report on and analyze every piece of employee data. Here’s the good news—you’re likely already collecting much of the data you need to uncover good insights.

The first step is to start with the employee data you have available.

Employee data (e.g., employee records or personnel files) is the most basic building block needed for people analytics. And luckily, it’s information businesses already collect for payroll and legal compliance.

People data is the difference between paper pushers and powerhouse advocates. In HR, if we truly believe that employees drive the customer experience, we would want to be as rigorous around our employee data as we are around our go-to-market and customer data.

Anita Grantham | Head of HR at BambooHR

• Pay history
• 401(K) & HSA contributions
• Job evaluations
• Peer evaluations
• Performance improvement plans
• Disciplinary action
• Employee comments
• Absence rate per manager
• Voluntary turnover
• Involuntary turnover
• Reason for departure
• Professional licensure & certification
• Training completion
• Employee wellbeing survey
• PTO & sick leave taken
• Enrollment rate by plan/program
• Usage rate by plan/program
• Annual recurring revenue (ARR)
• Monthly recurring revenue (MRR)
• Year-over-year growth
• Seasonality
• Revenue goals
• New products
• Release dates
• Customer engagement

What questions should HR ask to find the right metrics?

Not sure what data to review first on your people analytics journey? Think of a strategic HR or business goal that matters to your leadership team, then look at your current HR initiatives to see if you can find a way to connect them.

The best people analytics insights come from strategic HR leaders asking the right questions—more importantly, are the actions you’re taking helping the business reach its goals? And if not, what do you need to change to get you there?

Here is a list of questions to get you started. Remember to keep an open mind for other metrics you can use to answer your people analytics questions.

• Employee surveys with questions specific to company objectives and goals to understand if company objectives and goals are connected to department and team goals
• Employee absenteeism
• Employee turnover
• Overtime hours
• Self assessments and manager assessments

What HR initiatives or programs are helping the business save costs or boost revenue?

What HR programs are or are not working?

• Quarterly revenue numbers compared to specific employee engagement initiatives
• Employee benefit usage compared against employee productivity and quarterly revenue numbers
• Employee wellness benefit usage

How can we improve our recruitment efforts to save the HR team time?

How can we get roles filled faster?

How can we ensure a better match between new hires and open roles?

• Time to hire
• Quality of hire
• New-hire turnover rate
• Offer letter acceptance rate
• New hire onboarding effectiveness surveys

How can we motivate employees and to increase engagement?

How well do employees understand and contribute toward company objectives and goals?

• Employee satisfaction surveys (eNPS)
• Employee productivity—self assessments and manager assessments
• Employee benefits usage, especially those categorized as wellbeing benefits like EAP usage.

Is our employee retention rate high, flat, or low?

Are there specific departments with strong or poor numbers?

• Employee retention rate
• Voluntary vs. involuntary turnover rate
• Turnover rate by manager and department (How much employee turnover per manager is too much?)
• Number of internal promotions vs. new hires in a quarter or a year
• Number of internal promotions vs. new hires in a quarter and a year
• Total top performers compared against total internal promotions vs. new hires

If connecting HR metrics to business initiatives feels like the wrong process for your team, consider working backward with these questions:

• What is it that you want to know?
• Do you have the information to find the answer?
• If you don’t have the correct information, how can you find new data to help answer the question?
• What is the human story behind the numbers?

For example:

• How do employee benefits impact employee retention?
• Do you have data that shows employee satisfaction and engagement in regards to benefits? Do you have data on employee turnover?
• Do you need to do an employee survey?

People Analytics in Action

The scenario:.

You notice higher employee turnover for high performers. You know this is costing the business money and time, but don’t know exactly why these employees are leaving.

The problem to solve:

How can we reduce employee turnover, especially for top performers?

Key reason to review the people analytics:

Employee turnover can cost businesses up to 33% of an employee’s annual salary. Every employee who leaves means more work for the business, including:

• Sharing the load of that employee’s job with other employees
• Posting a new job description
• Interviewing potential candidates
• Hiring a new employee
• Onboarding the new employee

Key metrics to analyze:

• Top performer turnover
• Onboarding effectiveness
• Time to productivity for new hires
• Impact of unfilled headcount
• Turnover by team, department, and job type
• Turnover data: How many top performers leave each year, and what is their average time with the company?
• Exit interviews: Why are top performers choosing to leave? Are they getting better offers elsewhere? Did the role not live up to what they thought they were accepting?
• New hire survey for onboarding effectiveness: How well were new hires prepared for their new roles with onboarding training?
• New hire manager input: What is the time to productivity of new hires—how soon were new hires able to do their jobs without supervision, hit quota, etc.? Did new hire performance match expectations based on their resume, interview, references, etc.?
• Number of employees taking on extra work while headcount is replaced: How many hours of additional work are they completing, and how many employees are impacted?

Once you identify key data, you need to analyze to understand why top performers are leaving your business by looking for patterns and trends.

For example, if top performers consistently rate your onboarding program as ineffective in their new hire surveys, or they are leaving within the first six months, it’s time to review how well your onboarding program is preparing new hires for their roles.

Before you can jump in and make changes, you’re going to need to convince business leadership that the investment of time and money is going to be worth it.

To make a convincing business case to update your onboarding program, look at the impact the turnover is making to existing teams. Review the following:

• Number of extra hours of work
• Lost productivity on stalled projects
• Total number of employees (and their salaries) who are picking up extra work

Connecting the HR impact of a better onboarding program to lower turnover, less disruption to other employees, and less revenue lost creates an easy argument for more HR resources.

What tools can HR use to track HR metrics?

The data you need to get started with people analytics—while typically available—may be spread across multiple spreadsheets, tools, or platforms that aren’t always connected. If it’s hard to find basic information because of inefficient, manual, or time-consuming processes, organizing it in a way that will glean important insights or trends can feel overwhelming.

If you’re ready to start digging into your data to find real insights for your business, especially if you’re ready to see how your HR initiatives are impacting your business’s bottom line, you need to get your data ducks in a row.

The simple truth is, if your HR data isn’t easily accessible and accurate, you won’t be able to deliver timely or reliable insights.

Find yourself wondering if your data is accurate or how you can move forward with disconnected systems? Here’s what you can do:

• Confirm your current data accuracy. Ask employees to confirm the accuracy of the employee data you already have available. You can do this in one-on-one meetings with managers or through your HR system.
• Consolidate your HR systems (or connect disconnected systems) so you have a single source of truth.
• Gather missing employee data. If your business is behind on collecting important employee data (especially data that’s critical for payroll or legal compliance), start collecting that information today.

While finding the right tools for people analytics can be challenging, the good news is many human resources management systems (HRIS) eliminate the need to clean, track, store, measure, and report data yourself. Instead, the right HR software will deliver automated, digital, real-time reports.

As you review your options for people analytics tools—like an HRIS—look for the following:

• Use a tool that generates reports automatically using data stored in your system. This saves your team time and reduces the need to hire an HR employee with specific analysis skills.
• Select a tool that prioritizes simplicity, security, and ease of use (especially with reporting). This makes the tool more accessible and usable for everyone on the HR team, regardless of analytics skills, and makes adoption easy for everyone else.
• Choose a tool that is built for HR. Retrofitting other reporting tools for HR’s specific needs often doesn’t work and misses out on important HR-specific reporting needs.

Look at the ROI for what you’re paying an HR person to do: is it data entry or could they be offering more? The sheer magnitude of paper work that comes with movement in hiring or exits inside your population absent technology is super inefficient without an HRIS.

What to look for in an HRIS

HR data and documents often live in multiple systems, platforms, or spreadsheets. This leads to time-consuming redundancies when you’re double entering data, trying to pull data from multiple systems into a single report, or checking multiple tools for different data sets.

Add in the significant security risks and tedious upkeep of storing information in massive spreadsheets and it’s clear why the better route is a digital solution—like an HRIS—with a central repository for all of your employee data. With one digital tool for all of your employee data you’ll save time and keep all the data safe and secure.

It can be hard to meet executive reporting demands or even start your people analytics journey if your HR toolset doesn’t include some basic or advanced reporting functions. Trying to cobble together an analysis of multiple data points is challenging for even the most practiced analytical team.

Instead, consider an HRIS that has robust-reporting capabilities built in. With reports already built-in to a system that’s designed for HR, you can easily gain insights into the people analytics questions you’re ready to start answering.

HR teams are often interrupted by ad-hoc employee requests or shoulder-taps to check basic employee information. These time-consuming tasks and the other HR workflows that are often manual—approvals, recruiting workflows, etc.—can make it challenging to find the time to do true people analytics research and analysis.

Look for an HRIS that can automate basic HR tasks (e.g., approvals) and streamline data management to free up your time for the more important and strategic work of people analytics.

A quick note about security and compliance

An HRIS can help your HR team by eliminating the compliance and security risks associated with keeping employee data and documents on your computer, on your server, and in spreadsheets. And, by bringing reporting in-house to the HR team, there’s no concern over providing access or sharing data with an analysis team that might not have the right authority to view private employee data.

How BambooHR Helps You Collect and Analyze Your People Data

Data shows that when teams focus on HR analytics by using HR software, they’re 5x less likely to have trouble collecting data. A single source of truth—a centralized solution for all of your HR data and documentation where everything works together—eliminates the need to log in to multiple systems, keep information in multiple places, and worry about safety and security of your information.

“A centralized system that can automate our onboarding and offboarding frees up a ton of time within my team that we can now use to really meet the important part of HR, which is working with our people, developing and growing them. And that allows me in my role to [focus on] strategy and the bigger picture.”

—Tracy McDonald, Thinkific, BambooHR customer

“Instead of always reacting, [BambooHR helps us have] an opportunity to be more strategic. Now the HR team can actually do ‘looking forward’ work, which impacts engagement and retention.”

—Jane Jaxon, Wistia, BambooHR customer

“...I would say ultimately that [BambooHR] probably saved us another hire because that was where I was getting to. [I was thinking] I need to hire another person to just track all the paperwork that’s going along with this. So when we brought on BambooHR it was like bringing on a new hire.”

—Ben Brubaker, Assure Services, BambooHR customer

Powerful data insights are only a click away.

With BambooHR ® , you can manage and report on all of your sensitive people data with an organized, secure database—no technical experience required.

Get a Free Demo Today!

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About BambooHR:

Serving more than 30,000 organizations and over three million employees worldwide, BambooHR® is the only HR software designed for small and medium-sized businesses. BambooHR makes it easy for growing companies to manage essential employee information in a personalized, cloud-based, and secure system. BambooHR customers include innovators like Asana, Foursquare, Stance, Change.org, Jane.com, and Postmates. With customers in 100 countries, BambooHR’s goal is to set HR professionals and organizations free to do great work. BambooHR also hosts more than 30,000 HR professionals at its annual HR Virtual Summit. To find out more, visit bamboohr.com or follow @bamboohr on social media.

Predictive Analytics for HR: How to Use it

Elizabeth Parker

• July 29, 2023
• Reporting and Analytics

In today’s fast-paced and competitive business landscape, Human Resources (HR) departments play a crucial role in driving organizational success. However, traditional HR practices often rely on reactive approaches to address workforce challenges, leading to missed opportunities and inefficiencies. Enter Predictive Analytics for HR – a game-changing methodology that leverages advanced data analysis and artificial intelligence to forecast future HR trends and make informed, proactive decisions.

Predictive Analytics empowers HR professionals to move beyond conventional guesswork and intuition, tapping into the wealth of data generated within an organization. By analyzing historical HR data and identifying patterns, correlations, and trends, HR teams can predict employee performance, attrition rates, training needs, and workforce demand, among other vital aspects. This enables HR leaders to anticipate potential issues, optimize talent management strategies, and foster a more engaged and productive workforce.

This article delves into the fascinating realm of Predictive Analytics for HR, exploring its applications, benefits, and implementation challenges. By adopting this transformative approach, organizations can unlock the full potential of their human capital and elevate HR’s strategic impact within the company.

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Table of Contents

Understanding HR Data

In the realm of human resources (HR) , harnessing the power of predictive analytics begins with a comprehensive understanding of HR data. This crucial step forms the foundation upon which effective predictive models are built. HR data encompasses a wide array of information, ranging from employee performance metrics and recruitment statistics to training and development records. It is imperative to identify the relevant data sources and ensure their accuracy and completeness before embarking on the analytical journey.

To collect HR data, organizations can employ various methods, such as surveys, employee feedback, performance evaluations, and time tracking systems. Integrating data from disparate sources can present challenges, but this step is essential for gaining a holistic view of an organization’s workforce.

Once the data is gathered, data preprocessing is essential to clean and prepare it for analysis. This includes handling missing values, outlier detection, and data normalization to ensure data quality and consistency. Exploratory data visualization techniques can then be utilized to gain insights into patterns, correlations, and trends within the data, providing valuable context for the subsequent analysis.

By laying a solid groundwork of comprehending HR data, organizations can move towards building predictive models that offer actionable insights to optimize talent management, improve employee retention, identify skill gaps, and enhance overall HR strategies. Harnessing the potential of HR data through predictive analytics has the potential to revolutionize how organizations approach human resources, fostering data-driven decision-making and ultimately driving success in the modern workplace.

Building a Predictive Analytics Model for HR

Building a predictive analytics model for HR involves harnessing the power of data to make informed decisions about the workforce. This process begins with clearly defining HR metrics and objectives, aligning them with the organization’s strategic goals. Identifying the right set of data variables is crucial, encompassing diverse aspects such as employee performance records, recruitment sources, training outcomes, employee demographics, and more.

Data preprocessing is a critical step in ensuring data quality, addressing missing values, outliers, and standardizing data formats. Once the data is prepared, exploratory data visualization techniques help gain insights into patterns, trends, and relationships that can guide the model-building process.

To perform meaningful analysis, HR professionals need to understand various types of analytics . Descriptive analytics helps in summarizing historical data, while diagnostic analytics enables identifying reasons for past events. However, the real power of predictive analytics lies in its ability to forecast future trends and outcomes. By applying statistical and machine learning models like regression, classification, and time series analysis, HR teams can anticipate employee performance, attrition, and even future workforce demands.

Prescriptive analytics goes a step further, suggesting optimal actions based on predictions to address potential challenges or capitalize on opportunities. By integrating these analytical insights into their decision-making processes, HR professionals can proactively align talent strategies with business goals, enhance employee satisfaction and engagement, and optimize resource allocation. As organizations increasingly rely on data-driven approaches, building and refining predictive analytics models become essential for shaping a successful and competitive workforce for the future.

Data Analysis and Interpretation

Data analysis and interpretation are crucial components of predictive analytics for HR, as they provide meaningful insights that guide decision-making processes. In this phase, HR professionals leverage various analytical techniques to make sense of the collected data and extract valuable knowledge. There are four main types of analytics: descriptive, diagnostic, predictive, and prescriptive.

Descriptive analytics involves summarizing historical HR data to gain a comprehensive understanding of past trends and events. This step helps identify patterns, anomalies, and general statistics, laying the foundation for more sophisticated analyses. Diagnostic analytics, on the other hand, delves deeper into the data to explore the reasons behind specific outcomes or trends. Understanding the “why” behind the observed patterns enables HR professionals to address underlying issues effectively.

Predictive analytics takes the analysis to the next level by forecasting future HR trends and potential outcomes based on historical data and statistical models. These predictions provide HR departments with valuable foresight, allowing them to proactively prepare for challenges or capitalize on opportunities.

Finally, prescriptive analytics offers actionable recommendations by simulating different scenarios and assessing the potential impact of various decisions. This empowers HR leaders to make well-informed choices, optimize workforce strategies, and improve overall organizational performance.

By combining these analytics techniques, HR teams can make evidence-based decisions, identify talent gaps, predict turnover, optimize workforce planning, and create more effective employee development programs. It is essential for HR professionals to interpret the results responsibly, considering ethical implications and ensuring data privacy and security throughout the process. With the power of data-driven insights, predictive analytics in HR can revolutionize the way organizations manage their human capital and drive sustainable success.

Selecting the Right Predictive Models

In the realm of Human Resources (HR), choosing the appropriate predictive models is critical for deriving meaningful insights and making informed decisions. Different HR objectives necessitate various analytical techniques, and selecting the right model can significantly impact the accuracy and effectiveness of predictions. Here, we explore some common predictive models and their applications in HR:

Regression Analysis for Predicting Employee Performance:

Regression analysis is valuable for HR professionals seeking to understand the relationship between employee performance and various factors, such as training, experience, and job satisfaction. By analyzing historical data, regression models can help forecast future performance levels, enabling HR to identify high-potential employees and design tailored development plans.

Classification Models for Employee Attrition Prediction:

Classification models, such as decision trees or logistic regression, are instrumental in predicting employee churn or attrition. By utilizing variables like job satisfaction, salary, and work-life balance, HR can proactively identify flight-risk employees, allowing for targeted retention strategies and reducing costly turnover.

Time Series Analysis for Workforce Demand Forecasting:

Time series analysis is paramount in HR workforce planning. By examining historical workforce data and external factors like market trends, seasonal patterns, or economic indicators, organizations can anticipate future workforce demands. This ensures a well-prepared HR strategy, minimizing talent shortages and surplus.

Clustering Analysis for Employee Segmentation:

Clustering analysis assists HR in categorizing employees into distinct groups based on similarities in attributes, performance, or behavior. This segmentation can lead to better-targeted HR policies, benefits, and training programs, improving employee satisfaction and engagement.

In conclusion, the judicious selection of predictive models in HR analytics empowers organizations to make data-driven decisions that optimize workforce management, talent development, and overall organizational success. Understanding the strengths and applications of each model is essential for leveraging predictive analytics effectively in the HR domain.

Implementing Predictive Analytics in HR

Implementing predictive analytics in HR requires a strategic and well-structured approach to leverage the full potential of data-driven decision-making. HR professionals must actively embrace data analytics and transform traditional practices. Here’s a comprehensive guide to successful implementation:

Overcoming Challenges in Data Integration and Privacy:

Integrating data from various HR systems and sources can be challenging. HR departments must collaborate with IT teams to ensure seamless data integration. Moreover, preserving data privacy and security is paramount. Strict protocols and compliance with data protection regulations should be established to safeguard sensitive employee information.

Developing Data-Driven HR Strategies:

HR leaders must align their analytics efforts with organizational goals. Identifying key HR metrics that align with business objectives is critical. By focusing on talent acquisition, performance management, retention, and workforce planning, HR can deliver data-driven insights to support informed decision-making.

Training HR Professionals for Data Literacy:

To unlock the true potential of predictive analytics, HR teams need to be equipped with data literacy skills. Providing training and workshops on data analysis tools, techniques, and methodologies will empower HR professionals to navigate through complex datasets and derive meaningful insights.

By embracing predictive analytics, HR can optimize recruitment processes, reduce employee turnover, identify skill gaps, and enhance workforce productivity. The integration of analytics-driven decision-making in HR practices will foster a data-driven culture within organizations, leading to better talent management and improved overall performance. However, ethical considerations, such as data privacy and fairness, must be at the forefront of every decision to ensure responsible and unbiased use of predictive analytics in HR.

Case Studies and Real-World Examples

In this section, we delve into real-world case studies and practical examples that demonstrate the successful implementation of predictive analytics in HR. These case studies offer valuable insights into how organizations have leveraged data-driven approaches to transform their human resources strategies and enhance overall business outcomes.

Through carefully chosen examples, we showcase various applications of predictive analytics in HR, such as predicting employee attrition, identifying top-performing candidates during recruitment, optimizing workforce planning, and improving employee engagement. These case studies illustrate how predictive analytics has enabled companies to make proactive decisions and preempt potential HR issues, ultimately leading to improved organizational performance and increased employee satisfaction.

Additionally, we examine key learnings and challenges faced during the implementation of HR analytics projects. We explore how organizations have navigated data integration complexities, addressed privacy concerns, and tackled issues related to algorithmic bias and fairness. Understanding these challenges helps HR professionals and decision-makers anticipate potential roadblocks and adopt ethical practices when utilizing predictive analytics to avoid adverse impacts on employees and organizational culture.

By analyzing real-world success stories and setbacks, this section equips readers with practical knowledge and actionable insights to effectively adopt predictive analytics in HR. As the business landscape continues to evolve, embracing data-driven decision-making in HR will become increasingly vital for organizations seeking a competitive edge in attracting, retaining, and developing their talent pool.

In conclusion, predictive analytics has emerged as a powerful tool for HR professionals, revolutionizing the way they approach talent management and decision-making. By leveraging data-driven insights, organizations can make more informed and strategic HR choices, leading to improved employee retention, performance, and overall workforce efficiency. Ethical considerations, such as data privacy and fairness, must be prioritized to ensure responsible use of HR analytics. As technology continues to advance, the future holds even greater potential for HR predictive analytics, enabling businesses to optimize their human capital and create a competitive advantage in the ever-evolving global marketplace. Embracing this transformative approach is key to staying ahead in the modern HR landscape.

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What is predictive analytics in the context of HR?

Predictive analytics in HR involves using historical and current HR data to develop models and algorithms that forecast future HR trends, employee behavior, and performance.

Why is predictive analytics important for HR professionals?

Predictive analytics enables HR professionals to make data-driven decisions, optimize talent management, identify high-potential employees, predict attrition, and align HR strategies with organizational goals.

What types of HR data are commonly used for predictive analytics?

HR data used for predictive analytics may include employee performance metrics, recruitment data, training records, employee engagement surveys, and demographic information.

How can HR professionals collect and prepare data for predictive analytics?

HR professionals can gather data from various sources, such as HRIS systems, performance management tools, and employee surveys. Data preprocessing involves cleaning, transforming, and organizing the data for analysis.

What are some common predictive analytics models used in HR?

Common models include regression analysis for predicting performance, classification models for attrition prediction, time series analysis for workforce demand forecasting, and clustering for employee segmentation.

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Preparing to Manage Human Resources

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Description

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan . 

• Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
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About this course: One way or another, all employees are managed. But approaches to managing employees varying from employee-to-employee, job-to-job, manager-to-manager, organization-to-organization, and country-to-country. This course provides a foundation for developing your own approach to skillfully managing employees by illustrating alternative human resource management (HRM) strategies, introducing the importance of the legal context, and thinking about what motivates employees. This will then give you the factual and conceptual basis for developing specific, critical HRM skills in subsequent courses on hiring employees, managing performance, and rewarding employees. Don't know an…

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Didn't find what you were looking for? See also: English (FCE / CAE / CPE) , Agile / Scrum , M&A (Mergers & Acquisitions) , C/C++ , and French .

About this course: One way or another, all employees are managed. But approaches to managing employees varying from employee-to-employee, job-to-job, manager-to-manager, organization-to-organization, and country-to-country. This course provides a foundation for developing your own approach to skillfully managing employees by illustrating alternative human resource management (HRM) strategies, introducing the importance of the legal context, and thinking about what motivates employees. This will then give you the factual and conceptual basis for developing specific, critical HRM skills in subsequent courses on hiring employees, managing performance, and rewarding employees. Don't know anything about HRM? That's OK! Leave this course with a new-found understanding of the range of options available for managing employees, a grasp of what makes workers tick, and the readiness to develop your own HRM skills.

Taught by:   John W. Budd, Professor and Director

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

• Video: Video: Welcome to the HRM Specialization!
• Video: Video: Embrace Your Role as a Manager (Course Introduction)
• Video: Video: About the Instructor
• Video: Video: Human Resources? That’s Not Very…
• Practice Quiz: Course Readiness and Personal Goals
• Video: Video: HR Basics
• Video: Video: The Historical Evolution of HRM
• Video: Video: Contrasting Organizational Strategies
• Discussion Prompt: Discussion: Your Experience with a Good or Bad HR Strategy
• Video: Video: Alternative Managerial Styles
• Practice Quiz: Lesson 2 Practice Quiz
• Video: Video: External Influences on HR Strategies
• Video: Video: The Importance of Organizational Strategy for HR Strategy
• Video: Video: Speed Dating with HR Executives
• Video: Video: Ideas Matter
• Reading: Will the Real HRM Please Stand Up
• Practice Quiz: Lesson 3 Practice Quiz
• Video: Video: Why Worry about Why Employees Work?
• Video: Video: The Many Meanings of Work
• Video: Video: Working for Money
• Video: Video: The Daily Grind
• Practice Quiz: Lesson 1 Practice Quiz
• Peer Review: What Work Means to Me...and Others
• Video: Video: Opportunism and Shirking
• Video: Video: Incentives, Incentives, Incentives
• Reading: HR Pros Ignore Economics at Their Own Peril
• Video: Video: Information Signals and Screens
• Video: Video: The Commodification of Work
• Video: Video: Labor Supply and Demand
• Video: Video: Labor as than a Commodity
• Reading: Everything You Need to Know About the Employment Relationship in One Tweet
• Video: Video: Work is About Than Money
• Video: Video: Seeking Fulfillment from Work
• Video: Video: Finding Identity in Work
• Video: Video: Society Expects Me To Work
• Discussion Prompt: Discussion: Social norms that influence work in your culture.
• Video: Video: Caring for Others
• Video: Video: Serving Others
• Reading: The Metaphor of the Octopus Worker
• Video: Video: Fairness and Justice
• Video: Video: The Power and Limitations of Theories of Human Behavior
• Video: Video: Work Complexities Mean Managing is Complex
• Reading: To Tip or Not to Tip, That is the (HR Policy) Question
• Video: Video: The Goals of Every People Manager
• Video: Video: You Can’t Always Do What You Want
• Video: Video: Managing Unionized Employees
• Reading: Labor Relations 101 as Told Through the Musical Newsies
• Video: Video: The Front Stage, Backstage Manager
• Video: Video: The Employment-at-Will Baseline
• Video: Video: But True Employment-at-Will Doesn't Exist
• Video: Video: Disciplining and Dismissing Employees for Just Cause
• Video: Video: It’s a Complicated Legal World for Managers
• Reading: Thank You Wells Fargo...For Reminding Us of the Nature of the Employment Relationship
• Video: Video: U.S. Employment Law
• Video: Video: U.S. Labor Law
• Video: Video: Employment and Labor Law: Non-U.S. Examples
• Video: Video: Pay Attention to the Law, But Don't Be Paralyzed By It
• Discussion Prompt: Discussion: Important Work-Related Laws in Your Country?
• Video: Course Re-cap: Putting it All Together
• Video: Video: Interview with HR VP
• Video: (Optional) Video: Careers in HRM
• Video: Video: Looking Ahead to the Other Courses
• Reading: Reflection Exercise: Create a Mad Lib (optional, quick, and hopefully funny)
• Practice Quiz: Looking Back

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