HR By Numbers: Did Marissa Miss An Opportunity To Do A Google On Yahoo?

People analytics isn’t just another catch phrase. It means using data and analytics to personalize and manage each employee in order to drive superior employee outcomes. Primarily that is done by using hiring, retention, diversity, and top performer identification algorithms. Further, individual abilities and tendencies towards job loyalty, leadership, collaboration, and innovation are identified as well as individual key motivators.

In other words, people analytics transforms HR from a relationship and reputation model to a scientifically data-driven one. In short, it takes the subjective guess-work out of the most costly of all business investments – people.

How do we know that people analytics can deliver on that big data promise? We need only look at Google’s success in using people analytics these past five years with Project Oxygen.

Marissa Mayer, a former Google executive and now the head of Yahoo!, was probably aware of such initiatives – so, did she miss a trick, slapping all Yahooligans with a “no WFH” rule? Or, was it actually a data-driven objective analysis that convinced her that this intervention was necessary to bring Yahoo back from the brink? We may never know the answer to that question but we do know that the science of analyzing data about people is here to stay.

HR Managers now have access to data beyond time and productivity metrics such as from surveys, participation in enterprise social networks, training, performance, ability to influence others, public profiles on blogs and social networks – all the multiple facets of their top talent that they can understand better through data.

Analytics can tell you a great deal about what holds meaning in your employees’ lives and therefore what motivates them and how you can go about maximizing their productivity. You may find that young programmers crave learning opportunities and for their managers to take genuine interest in them. They also like help with their mundane chores – so there could be substantial returns on those free laundry and free food perks after all!

Analytics might also alert you to segments of people with young families who highly value their work-from-home freedom so they can attend their kids’ activities or be there to supervise them at home while completing their deliverables. This group may be less interested in training and off-site meetings. Others in your organization may prefer to be valued for their experience and tenure. Healthcare benefits may matter more than anything else to this group.

Are money and boilerplate incentives then the best motivators? Probably not. Do understand, however, that none of this replaces the traditional motivational tools such as Autonomy, Mastery, Purpose, and Drive, as Daniel Pink laid out in his bestselling book ‘Drive.’ It simply quantifies these elements with data and manages them by the numbers.

With the tremendous amount of data available today, firms have a unique opportunity to borrow from the science of customer analytics and apply it to their large employee base. Such can then be segmented into homogenous groups initially and eventually to a personalized “unit of one.” The opportunity then is to relate every policy, process and action to outcomes that are meaningful for that particular business.

People analytics are an important tool with which to answer very simple questions about your people with data rather than rely on gut or intuition:
• Who are my best employees? How are they different from others?
• How can I quantify the potential value of each employee more accurately?
• How do I effectively segment my employee population?
• How do changes in compensation & benefits affect the performance metrics of different employee segments?
• What are the factors that drive employee performance?
• How can I tailor training and incentives to enhance the employee performance?
• How can I optimize my spend on an employee to maximize his/her performance?

By getting this math right, firms can readily develop data driven hypotheses and ideas, not to supplant human judgement but to enhance it. Intervention and motivation efforts are much more likely to succeed if they are founded on hard numbers.

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