Is Your Company Ready for HR Analytics?
Although many companies have been investing heavily in big data and analytics, there have been few success stories in applying analytics to human resources. But that may be about to change.
Big data and analytics are omnipresent in today’s business environment. What’s more, new technologies such as the internet of things, the ever-expanding online social graph, and the emergence of open, public data only increase the need for deep analytical knowledge and skills. Many companies have already invested in big data and analytics to gain a better understanding of customer behavior. In fact, due to the introduction of various regulatory guidelines, some of the most mature analytical applications can be found in customer-focused areas in insurance, risk management, and financial fraud detection.
But what about leveraging big data and analytics to gain insights into another group of your company’s key stakeholders: your employees? Although we see many companies ramping up investments in HR analytics, we haven’t seen many success stories in that area yet. Because HR analytics is “the new kid on the block” in business analytics applications, we believe its practitioners can substantially benefit from lessons learned in applying analytics to customer-focused areas — and thus avoid many rookie mistakes and expensive beginner traps.
Based upon our research and our consulting experience with customer-focused analytics, we offer four lessons about how to successfully leverage HR analytics to support your strategic workforce decisions. More specifically, we will juxtapose some of our recent research and industry insights from customer analytics against HR analytics and highlight four important spillovers.
Lesson 1: Model, measure, and manage your employee network dynamics. In our own research, we have found that ties between customers (such as social ties, credit card transactions made with the same merchants, or board membership ties between companies) are very meaningful in explaining and predicting collective behavior such as customer churn, customer response to marketing outreach, or fraud. It is our belief that these principles can be easily used to harvest some low-hanging fruit in HR analytics. In particular, a network can be constructed — with employees as the nodes and with the links between them based upon factors such as (anonymized) email exchanges, joint projects, colocation, and talent similarity, and possibly weighted for how recent such connections were. This network can then be leveraged to understand how smoothly new hires will blend into your workforce network; it also can be used to quantify the optimal mix, from a performance perspective, between behaviors that bring cohesiveness to the employee network and those that bring diversity.