The People Operations, or Human Resources, field has changed dramatically throughout my career. The most impactful change has been the move toward analytics-driven decision making. Leaders in People Operations have been using data for years to make budget and spending decisions based on traditional measures like cost-per-hire or percentage-based salary increases. While these basic metrics are crucial to a company’s success, progressive leaders must now drive their businesses with more advanced, analytics-based decision-making. Leaders like Laszlo Bock, famous for driving data analytics into Google’s People Operations’ function has stated that the goal of People Analytics is to “complement human decision makers, not replace them.”
What if you could measure colleague engagement and happiness in a way that told you, with precision, when your teammates were most likely to put in their notice? How can talent acquisition teams project their ability to fill roles with quality candidates based on data already available? What schools’ graduates are most likely to relocate to your market and stay for more than two years? All of this is possible to predict in today’s ‘Big Data’ world. The data exists. The question is whether you can access it, utilize it, and begin to make predictions based in the data.
For a small business like Kinney Group, working in the IT Operations Analytics world, we help our clients use their data to solve business issues every day. Like the fable of the cobbler’s children; however, our internal People Operations’ team does not always have the internal tools and resources to best access and utilize this internal data to its fullest extent. By Q1 2017, my team will have full access to all of our internal data in a dashboarded, usable format. In the meantime, we are manually correlating data to find trends, make business decisions, and predict our 2017 successes and failures.
A current example of our ability to solve Kinney Group issues using data was our quick response to an identified colleague morale data change. Using real-time feedback gained from our business partner, OfficeVibe, we were able to address a significant mood change in the office with our Leadership team. Within two weeks, our scores had recovered because we had addressed specific issues within teams. As we gathered information, it seemed the change in scores was based on misinformation among teams. Without addressing this or being notified of the mood change through our data, we could have missed an easy opportunity to communicate the right information at the right time for our colleagues.
Every situation in which we are able to present data to a hiring manager or Executive rather than ‘go with our gut’, is a situation in which we can gain trust and share our expertise to best meet the needs of our business. Whether it be compensation data, colleague engagement, turnover predictions, or simply the best times of day to reach valued candidates on the phone, we are using data to improve results across the talent acquisition and People Operations’ functions. I look forward to sharing our successes here and learning what is working for other teams in our space. Happy correlating!