Bringing People Analytics Back Down to Earth
Consider the following analytics initiatives pitched at this year’s HR trade conferences:
Outfit your entire workforce with Fitbits to monitor the sleep patterns and fitness levels of your workforce. Track the lifestyle habits of top performers and push employees with unhealthy habits to follow suit.
Use text mining to study employee emails and determine which employees have the broadest network of relationships within the company. Encourage less-connected employees to expand their networks.
Use wearable heart-rate monitors to measure employee engagement during meetings.
The crowd’s reaction to these ideas was skeptical at best. There were the obvious concerns around privacy and intrusiveness, but also around elaborate expenses and questionable payoffs. Does a dedicated employee who pulls the occasional late night really need to be scolded for missing her bedtime?
So why this flirtation with Orwellian overreach? Not long ago, most HR departments were seen as laggards in the field of data analytics. While the early adopters – generally found in Finance and Marketing departments– had eagerly embraced new technologies in data science and evidence-based decision making, HR continued to rely on gut instinct and guesswork. Thought leaders in the field saw the need to modernize and learn how analytics could inform key decisions related to the hiring, development, and retention of human capital. The field of “People Analytics” was born.
Now, with a firm foothold in America’s top HR departments, People Analytics has passed through its infancy and entered into a thriving adolescence. Practitioners are in full brainstorm mode and thinking big. In this exuberant climate, there are bound to be some misfires.
Fortunately, in real worlds of most organizations, there is no need for the experimental grandiosity on display during this year’s conference circuit. If you’re just starting out with People Analytics, there is a likely a wealth of untapped data right at your fingertips, and a tried-and-true set of techniques to mine that data for immediate value. In most HR departments, there’s still plenty of low-hanging fruit to be had. Here’s a few tips on how to get it:
Focus on Existing Data
“Data in the new oil” has become the analyst’s rallying cry. If data is an abundant raw material that can be exploited for value, there’s no need to go generating more of it. The collection of new data (using such dubious techniques as Fitbits and email snooping) can be an expensive and high-risk proposition; but with the right expertise, existing data can be easily mined for a handsome payoff. Most companies collect and store information on the following fields: employee performance, employee demographics, job-related events, customer satisfaction, sales volumes, manager and team characteristics. The combination of these indicators can create a very powerful basis for studying employee behavior and learning how to improve on key outcomes.
Establish a Use Value up Front
It’s essential that the end users – managers and HR specialists – be involved in defining goals and implementation strategies before an analytics project is undertaken. Due to the anxiety associated with math and statistics, many stakeholders are tempted to hand their data over to a specialist and tell them to “have at it.” But this type of open-ended approach can lead to a lot of wasted time. You don’t want to end up with project deliverables that you didn’t want or can’t use. Here are some examples of user-driven deliverables that we’ve provided to Vemo clients.
Retention Application: A bi-monthly push report sent to all managers within the organization, informing each manager of his or her ten employees with the highest likelihood of resigning in the upcoming year, along with evidence-based actions that might be undertaken to retain these individuals.
Compensation Assessment: A cross-country report across for a large multinational corporation, using historical data to identify the necessary compensation packages for motivating high retention and performance within each country. Used to refine compensation policy and make workforce allocation decisions.
Diversity Application: A comprehensive review of which branches within a company might show evidence of race or gender bias, and a list of data-driven strategy to improve female and minority retention within these branches.
Tie Analytics into an Established Planning Infrastructure
The output of an analytics project can be rather unwieldy – often a constellation of excel-style spreadsheets, PowerPoint slides, graphs, and descriptive tables. Once these deliverables are handed off, distributing them to the right stakeholders, and helping these stakeholders put them to optimal use, can be a daunting task. One way to solve this problem is to integrate analytics into an established planning software, where managers and planners can access and apply data-driven insights using an intuitive user interface, and where the fruits of data science can be integrated into broader workforce planning initiatives. The latest version of our software, Vemo6, is designed for this exact purpose. With the help of our new data science team, our long-established planning and dashboard modules have been upgraded to make optimal use of new developments in predictive analytics.