People Analytics Projects: Do NOT start with the data

HR professionals and company executives believe that data is the “golden chalice” in their pursuit of supreme knowledge.

However, the truth is that no matter how advanced your analytics skills and data governance infrastructure are, your data will not provide you with a ready-made solution unless you ask it specific questions regarding data analysis.

Why should we always start with asking specific questions?

1.      Asking the right questions means that we have identified an important business challenge that requires immediate understanding.

A lot of our HR clients know that we love helping them with their employee turnover challenges with our prediction analytics solutions. Some months ago, one of our clients approached us initially because they wanted to implement our turnover algorithms to the scholarship program they were running with a number of universities. Every year they provide to very competent individuals highly competitive and generous university scholarships. After finishing their studies, the scholars have to work for the company that funded them for a number of years. Our client therefore wanted to predict which scholar would choose not to work for them after the end of their studies. They had lots of data that we could use for the development of a very sophisticated algorithm but the problem was that they did not have any “turnover issue” AT ALL. All their scholars, and I mean ALL, after their graduation, were choosing to work for the company that funded their studies for a considerable amount of years!

Having realized the context of the analytics project, we talked our clients out of the specific project because we did not want to waste their money and time. We started to explore together what was the real issue that was challenging them. Please do not forget: “the most important aspect of people analytics is actually the value proposition: does it make sense to spend time and resources on a given business problem?” The truth is that managers intuitively had realized that something was bothering their scholars, and with the proper analytical thinking we managed to identify a relevant project purpose and relevant research questions that could add value to their business.

2.      Asking the right questions means that we have identified a number of significant and relevant solutions for addressing an important business issue and bring value to the business.

During my first meeting with a new HR client I was informed that they wanted to do a segmentation analysis to understand employee turnover. Even though I enjoy doing segmentation analyses, when the client started talking about the data they have available, I immediately realized that this is not the right place to start. They wanted to link survey data and demographic data to turnover because this type of data was readily available without considering whether this type of data could actually provide meaningful answers.  

So, we tried, together with the client, to identify some of the crucial drivers for employee turnover, such as promotion wait time, compensation ratio, pay increases, tenure, training opportunities, performance and management onboarding effectiveness. This type of data (together with the data that were readily available) allowed us to effectively target and fine tune our client’s retention strategies rather than develop a “one-size fits all” employee retention solution.

Next, we worked with our client to identify the main objective of the specific turnover project. When our client was certain that they wanted to develop strategies for employee retention based on the analysis, we further asked: “Is all turnover bad? Should your retention program also cover low performers in non-critical positions?” Such analytical thinking led us to the formulation of a very significant question that could truly create business success: “What is the employee segment that has a high impact on business outcomes and is at highest risk of leaving?”

In this way, people analytics does not just validate existing knowledge, but by asking the right questions based on the development of a framework that understands and interprets employee turnover it can become business relevant and add value to business decisions.

3.      Asking the right questions means that a business strategy is inherent in the design of the analytics and algorithmic solution.

Working with many HR clients on workforce planning, through which companies align their workforce supply with their business demand, made me realize that one of the advantages of asking the right questions is to incorporate from the beginning the strategy of the business into an analytics solution.

Most HR clients still treat workforce planning as a finance-driven process in which personnel spending is managed as a cost without taking into consideration the skills needed to meet strategic business objectives. HR and business units have little insight about the adequacy and appropriateness of employee skills in order to achieve their business goals. Some of the critical questions we always ask our clients to start building workforce planning before any algorithmic solution are: “What’s the situation with employee turnover and how do we manage talent acquisition and why?” “What roles or skills are needed to meet strategic objectives?” “How is our business plan being implemented through our workforce plan?”

And if you want some even more introductory questions: “How many people will I have at the end of the year?” “Which are the characteristics that drive success in sales roles (or any role that is crucial for meeting your business objectives)?”.

Such analytical thinking could then help us develop algorithmic models and future workforce scenarios by applying different criteria and optimizing workforce costs.

4.      Asking the right questions means that we are not doing analysis for the sake of analysis.

Analytics for the sake of analytics is not helpful and especially when they are meaningful only to HR but not to the business. For example, prediction that links the number of training classes to attrition or correlates performance review rating with how long someone would last in their role is an HR issue and not a business critical issue. We might also be able to identify very precise algorithms for such issues after a lot of work and use sophisticated frameworks, but I am afraid they often have very little practical value. Just like the point we made before, it is just as if we managed to develop a very precise prediction algorithm for employee turnover without having a turnover problem in our company!

People analytics should focus on the most important issues for the business. Ask yourself: “What are the biggest challenges our business will face within the next 3 years?” “How can HR support the business to achieve its objectives?”  

5.      Asking the right questions will guide you through the process of data collection and will ensure that you have some standard KPIs in place to measure the achievements by the end of the analytics project.

We don’t want to start a people analytics project without having any metrics to evaluate the success of the project. In this sense, you always need to ask yourself: So what? What do you want to achieve by the end of the project? You need to identify measurable achievements and the research questions are your ultimate guide in developing such quantifiable metrics. If the metrics are not available you need to design processes for feasible data collection in order to make sure that you can measure the outcomes of your people analytics project.

Thank you for reading. I hope this article helped you understand the importance of starting any people analytics exercise with the right research questions that meet a concrete business challenge and not simply with data.

If you have any comments, please feel free to leave your feedback below. See you in the next post!

About the Author

Olivia Kyriakidou is in the mission of making analytics accessible to HR professionals and helping HR professionals get a seat at the table of strategic decision-making. She is helping companies and HR professionals to make better people and business decisions through actionable data and analytics-driven insights. Olivia is also known for her academic work, having written many articles for academic and practitioner journals and taught at both the undergraduate and graduate levels. She is the founder of ImasterPA that provides educational and consultancy services in all aspects of HR, analytics, digitalization, workplace technology and development of management and leadership soft skills.

You can connect with her on LinkedIn and Twitter.