Where's the Human Element in People Analytics?

Where's the Human Element in People Analytics?

A recent chat with a couple of data analytics professionals inspired me to consider what I have done so far in the area of People Analytics. Analytics has been a buzz word in recent years but the area of People Analytics seems to have a lot of room for exploration. As a former HR and Learning business partner, I came across consulting firms promoting analytic-driven solutions for company sales team, organization learning or HR insights. However, how many of these solutions have fully considered the Human Element in People Analytics? Putting solutions-providers or data analytics technologies aside, what makes an analytic-driven HR intervention more accepted by all stakeholders?

To answer the latter question, here are 5 considerations:

1) What's the HR business case we are trying to solve with Analytics?

A clear and concise HR business case is needed to scope the scale of the people analytics project. There are times when the HR business case seems obvious (for eg. Why is the attrition so high in a particular year?) but there might be instances when the HR may take some time to build or may even require an external consultant to identify the issues (for eg. What accounts for the low trust in a team/organization?).

Having an external People Analytics professional, preferably with substantial experience in Human Resource, is also helpful to quickly pinpoint the HR business case with more objectivity and free from any internal politics. Nevertheless, the assumption here is that any HR-related gaps can be addressed with analytics.

2) Which analytics model is best for solving the particular HR business case? Why?

Ideally, this consideration should be addressed by the same person. However, I have yet to meet an expert HR professional who is also a full-stacked data scientist. This question has to be worked out between the HR professional who's tasked to helm the People Analytics project and the data analytics subject matter expert.

3) What are the stages of each analytics model? How can each stage of the analytics model contribute to answering the HR business case you are trying to solve?

Although the HR business case statement has been identified, data analytics professionals may get engrossed with creating algorithms to interrogate data but lose sight of the business case they want to solve. HR professionals who are leading People Analytics projects could also get distracted with all the fanciful features of data manipulating or visualization software and as a result, waste a lot of time.

Prepare to account to project stakeholders how each stage of your chosen analytic model could help you answer the HR business case.

4) What's the degree of flexibility allowed to accommodate changes to the HR business case in the project?

Sometimes, a change in HR business case would require more data from the same data source that had supplied data to your project or data from other data owner(s). This happened to me (as a HR and Learning business partner overseeing the project) before when key stakeholders revisited and rewrote the HR business case statement repeatedly. They also requested to insert more variables into the data metrics that could potentially disrupt the earlier formulas. Thankfully the stakeholders stopped shifting the goal post after a handful of revisits. How would you react if you were in my portfolio then?

5) Who's the best person to communicate and deliver the analytic-driven HR intervention? Why?

I have no hard and fast answers for this but I would get an external person who could explain, in layman's terms, the art and science of People Analytics to all stakeholders in a town-hall setting. Since this is essentially a HR intervention, the same person should also have acquired substantial internal HR experience to consider the impact of the intervention on HR-related factors such as staff hygiene and office politics while partnering the HR in the particular organization to deliver the solution.

Finally

The need to consider the Human element, to me, makes People Analytics a more sophisticated type of business analytics to master. What I've presented above are based on my limited experience with People Analytics and I'm still growing in this field of specialization. Let's take this People Analytics conversation further. What are your thoughts? Feel free to comment or share this post.

This article was originally published on LinkedIn

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