Organizations no longer see people analytics as separate from HR, but as an integral part of HR. Data-savvy HR professionals are seen as key enablers and companies are increasingly investing in training them to become more data-driven. But how does this look in day-to-day life?
In this article, I explore three practical case studies that show how people analytics is creating impact – while also transforming HR into a data-driven function.
A large restaurant chain was trending in a downward direction and was struggling to understand why. They had pieces of data, including an annual employee survey, but they were not sure where to start to figure out what was going wrong.
The team that was asked to look at the data to help this struggling restaurant, did not look at traditional HR outcomes. Instead, they identified three business outcomes that mattered most to the organization:
They decided to utilize one of the most advanced analytics techniques, Structural Equations Modeling (SEM), rather than regular correlation- and regression analyses. This allowed them to identify which employee survey categories were linked to the three business outcomes.
The next challenge was to relay the results in an impactful way, so that leaders would understand the results and knew which steps to take next. They created a heat map (as seen below), which showed where managers had to focus their time, attention, and money to provide the largest ROI.
For this restaurant chain, the most important drivers of outcomes were Senior Leaders, Teamwork, Management, Communication, Ethics, and Job Fit. If a manager increased their survey scores on those categories to above a 4.00, they were likely to see a 16% increase in customer satisfaction, 18,000 more customers a year, and 10% less staff turnover. With this analysis, HR was able to put a real dollar amount on its strategic initiatives and help the rest of the business make better decisions.
This organization was successfully able to leverage the power of its people data. They were able to effectively show where managers should focus to improve their business outcomes. By using people analytics, HR Leaders were able to serve as true business partners for the company.
This case study revolved around expats. More often than ever before, people are crossing their national borders for work-related purposes (BGRS, 2010-2017).
However, this increase is in different types of assignments. Where traditional assignments used to be planned for the long-term, these days expatriates often only stay abroad for short periods of times.
In this case, the analyst looked at two large multinationals to determine the impact of the expatriation process on employee turnover. The sample included the career paths of over 9,000 new young professionals. In his dataset, all kinds of HR and personal information about these individuals was included, which allowed him to isolate the effect of an international assignment. The analysis resulted in the figure below.
As can be seen, expat status significantly reduced the risk for turnover when compared to their non-assigned peers at home. However, “organization red” had a much higher turnover amongst employees who returned from their assignment abroad (repatriates).
The above results had multiple implications for these organizations. Organization blue should continue to assign their top talent abroad, as this seemed to improve their retention. Organization red should optimize their repatriation policies in order to retain their top talents, as it seemed as if short-term assignments were not helping their talent pipelines.
This People Analytics project turned the data these organizations already collected into insights that sparked a conversation regarding talent programs. Without a data-driven HR function, these companies could have potentially lost their top talent.
People Analytics can help you with more than just HR outcomes. In a project in Zimbabwe, analysts were asked to predict road traffic accidents (RTA) using psychometric tests. These insights would help deliver goods on time and reduce cost of accidents by hiring better drivers.
To do this, they tested 54 drivers from a local company in Zimbabwe using the Fitness to Drive plus Vienna Test System. Each driver’s test results were then matched with their record of road traffic accidents from 2014 to 2015. This allowed them to build a logistic regression model that distinguishes good drivers from bad drivers (see below).
As shown in the table above, only two of the dimensions had a significant relationship with a driver’s road traffic accident risk. However, the inclusion of all dimensions in the model lead to an improved classification of drivers’ accidents risk profiles.
This implies that, without any prior road traffic accident record, the company can use appropriate psychometric tests to decide whether or not they should hire a driver or machine operator.
The same approach can also be used to identify training needs among drivers who are already part of the organization. In the event that the model has identified a certain driver’s road accident risk as too high, the driver may be re-assigned to other areas of operation in the organization. Doing this will reduce the costs incurred as a result of accidents, giving a clear ROI on the work of HR.
The cases above show how people analytics can add value to both HR and to the business as a whole. Even if your company already has enough happy customers, doesn’t have expats, and has no use for road traffic accident data, there are still plenty of uses cases for people analytics in your organization.
To become a data-driven HR function, it is vital to understand and utilize the data that is present in your organization. The best approach to seeing where analytics can add value is by going through your talent management model and for each step in the model see where the greatest potential benefit is. Making these processes more efficient and effective though smart tools also enables the collection of data for these steps – which can then form input for further analysis.
Erik van Vulpen is founder of Analytics in HR (AIHR). He is writer, speaker, and trainer on people analytics. Erik is instructor for the HR Analytics Academy and has extensive experience in the application HR analytics.