The Human Resources Fortune-teller: Using Data Analytics to Predict the Future of People in Your Organization

As 2019 comes to an end, everyone is busy planning for 2020. Certainly, people working in human resources have a thousand questions to answer and another thousand to ask. Some of these questions will be:

1. Who is going to resign?
2. Who is going to outperform others?
3. How long before an employee is ready to move up the ladder?
4. How many key positions will be at risk of departure?
5. What questions should I ask in my next engagement survey?
6. Which employee will benefit the most from online training?
7. Which employee will learn nothing from a training course?
8. Is our workforce diverse enough?
9. Does our workforce need diversification?
10. What keywords in my next job advertisement will attract the right candidates?

These questions are by no means exhaustive and the list can go on forever. As you may have noticed, all these questions are about the future. Are you supposed to be a fortune-teller? The answer is: definitely yes. Why? Because all other department heads are. A marketing manager knows which client will buy the company’s products. A sales manager knows how much revenues a salesperson will generate. A finance manager knows where investing money will make more money. So why can’t HR professionals do the same? It is time to mine people’s data, looking intensively into the information just like we gaze into a crystal ball. It is time to start seeing people’s future.

It all starts with a hunch, a feeling, or a theory that does not necessarily have solid proof. As you sit down in your office late one night, thinking how to retain critical employees and stop the leakage in your high potential pool, you notice that the last three employees who resigned are all males who studied in the same university, got married recently, and are managed by a male who is at least 15 years older than they are. And by the way, they all like their steak well-done.

Although a little perplexing, you decide to venture into a data analysis exercise to try to connect these variables. Fortunately, you just started an HR modeling exercise. You ask your team to gather data about all employees who have resigned in the past 5 years and you gather the information on a data sheet and start looking for trends. For curiosity’s sake, you kept a column representing how those who resigned like their steak – again as strange as it seems.

This is called data mining. As you look deeper into your data, you notice that the bigger the age gap between an employee and his or her manager, the faster these employees tend to resign. Hence, you decide to run a correlation amongst your variables to confirm your hunch. Surprisingly, you find that any relationship between resigning (your dependent variable) and the employee/manager age gap (one of your independent variables) is only due to chance and therefore, your hypothesis is incorrect. This is what we usually call data analysis. Interestingly though, how employees who resigned like their steak has shown a significant correlation. This is a little surprising and very intriguing. Should you start probing for that in your recruitment interviews? You think that it is probably too soon for such a solid conclusion.

On the other hand, one independent variable has shown a very high correlation: marriage expectancy, or the probability that your employee is to be married soon. This is insightful. You decide to analyze further the resignation behaviors for another year. You identify six employees who just got married and then you send the general manager a sealed envelope with a sticky note saying: “Do not open before August 2020”. On August 1st, the general manager opens the envelope as she was reading the turnover report and is astonished by the fact that five names out of six mentioned in your note resigned! You have a new nickname: the fortune-teller.

By the way, you have suggested a very innovative flexible attendance policy for newly wed employees that reduced turnover dramatically. But you’re still trying to find out why they all like their steak well-done. This is not a fairy tale. Rather, it is a sneak-peak into the enormous power of data analysis in the HR realm. The process below explains how you can use data analysis to inform sound people decisions:

• Step 1: Link business strategies to people strategies
• Step 2: Identify business challenges
• Step 3: Form your business hypothesis
• Step 4: Gather your data
• Step 5: Choose analysis tools and strategies
• Step 6: Turn data into insights and articulate findings and decisions
• Step 7: Communicate your conclusion with storytelling and visualization
• Step 8: Evaluate your analytical intervention

If you are interested in knowing more, register for the Certified HR Analyst program and become your organization’s next fortune-teller. Details about the course can be found using the following link: https://www.meirc.com/training-courses/human-resources-training/certified-hr-analyst.