People Analytics in the Pandemic: With Great Data Comes Great Responsibility
I have a news app on my smartphone that pushes the number of positive COVID-19 tests in the Netherlands on a daily basis. In the same message, they mention the absolute difference with the day before. Those numbers can be pretty frightening. What the message does not mention is the number of tests of that day or the day before. So we don’t know if there is actually a relative increase or decrease when it comes to people testing positive.
On top of this, the number of positive tests is pretty debatable. Our national COVID-19 rules are specifically aiming to avoid crowded intensive care units and don’t focus on the number of positive tests (although the relationship is not irrelevant to assume). My point here is that these numbers do not tell the full story. In other words: the storytelling is off.
This made me think about our internal information flow during the pandemic. It is pretty clear that in an operational company like Dutch Railways (NS), the number of sick people has an impact on productivity. But we should never forget to put things in perspective.
One of the things we did in our People Analytics department is presenting the absenteeism we are facing now compared to the pre-COVID period. The effect we see is that we have people not working because of absenteeism, but not a lot more than usual. And absenteeism is a challenge for a lot of companies in general; it is not a specific COVID issue. The addition to our story is subtle but does not take the focus away from the issue. In that way, we try to have an impact on our businesses and decision-makers.
People analytics and future-proofing organizations
A lot of companies are struggling because of the pandemic. And many of them will have to become smaller in order to even have a future. People Analytics should have an important role when it comes to making decisions about the future workforce.
The Dutch workforce, in general, is aging. And our legal retirement age is slowly moving towards 70 years. Knowing how many people retire in the years to come is the first step to understanding whether you will be able to get smaller without firing people. Instead, you would rely on natural employee attrition. And what department other than People Analytics should know everything there is to know about the workforce?
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Finance departments tend to take the actual retirement dates to calculate the number of people retiring. But many people in the Netherlands are in the financial position to retire way before that date, sometimes up to three years or more. You have to take that into account when you look at this specific sort of information.
You can imagine that there is a big difference between an average retirement age of 67 or 64 and the impact that has on your workforce planning and succession management. Predicting the number of leavers and which department they work in helps you decide where to train the successors. Or when there are no successors within the tough labor market, you can redesign your company and see if certain roles can be made obsolete.
It makes quite a difference whether you will need to recruit 50 finance specialists or 50 truck drivers. Your retirement predictions will help you understand future training and recruitment objectives. To summarize: knowing who will retire when, in what department, and in which role is essential data that People Analytics can provide to make better decisions.
People Analytics can do this because they are at the heart of the basic people administration. They have direct access to the data. They also can combine data. For instance: they do not only know when people leave, but also why they leave (at least they should know). So determining the number of future retirees can be modeled best by People Analytics.
In that way, People Analytics also has a significant impact on decision-making during and post-COVID-19. The implication here is that your data has to be of good quality. The pandemic has also made it even more important to know the costs of your current and future workforce: again, something that People Analytics should be working on with Finance.
People Analytics is becoming more and more strategic in their tasks, helping organizations increase their effectiveness and improve performance. (Image source)
Data-fueled strategic workforce planning
In general, not just because of the pandemic, it is clear that People Analytics has a critical role in strategic workforce planning. Next to technology, there are loads of factors that might bring change to your company. The context of most companies is that they have to be more flexible, efficient, and effective.
Think about what economic uncertainty, growing competition, and scarcity in the labor market might mean for your company. All these factors implicate that ‘business as usual’ only exists for so long. This all means we need to get ready for these changes. We need to transform our company and make it future-proof.
People Analytics plays a key role in this process. HR has to translate the business strategies into people strategies. You will have to determine the gap between the current and desired situation and what actions both HR and business need to take to be ready. And again, storytelling and high-quality data make the difference here. The same data mentioned before about retirement, age of the workforce, absenteeism, and reason for leaving the company are essential. Performance scores and training data can be added.
Let’s imagine that our data analysis tells us that 20 people will leave over the next five years in a particular department. The business should know whether the work stays the same, both the actual work in terms of responsibilities and the amount of work. Then you know if you need to recruit 20 people, fewer, or more of them. And when to recruit them.
By having the right data, you will know whether your workforce has successors available in the company. That gives you an objective for Learning & Development and a different recruitment objective: hiring someone for the current role of the successor. New employees are likely to be needing training when they come in, so that’s in the analysis as well.
And it does not stop there.
By doing this right, you can also predict how many people you need in your Recruitment and Learning & Development teams, as you will be predicting the amount of (extra) work for these departments. Eventually, the outcome will be a specific objective for Recruitment or Learning & Development—all to get ready for the future.
A final word
It feels pretty cool that our still-growing People Analytics community has been able to get a seat at the table. And not at the far end of that table, but getting closer and closer to the middle where other people can actually hear us.
That means we have an impact. Great impact.
Let’s keep doing it right: with great data comes great responsibility.