Why You Need to Make the Leap from Predictive to Prescriptive Analytics
It's no secret that human resources have been slow to adopt analytics. While finance and marketing are now big data machines, HR is still in the rudimentary stages of data analysis.
But the industry is reaching a turning point. According to a recent report from PricewaterhouseCoopers, creating or improving "people analytics" is a strategic priority for 86 percent of organizations in the next one to three years, and nearly half have already implemented a dedicated program. In other words, analytics has moved from a nice-to-have to a must-have when it comes to making workforce decisions.
As both executive interest and investment in people analytics increase, HR leaders are faced with pressure to mature their analytics capabilities quickly — moving from simply diagnosing talent problems to finding solutions for them.
The Stages of Workforce Analytics
Before your organization can advance its analytics efforts, it is crucial to understand where you are on the analytics learning curve.
When organizations first embark on a workforce analytics journey, the work is mainly reactive, according to Bersin by Deloitte's Talent Analytics Maturity Model. Queries are based on requests from HR or other department leaders and tend to focus on identifying current trends. This first stage can also be referred to as the "descriptive and diagnostic analytics" phase, where companies report on current trends, such as low retention.
As organizations advance and build out their analytics teams, analytics efforts become proactive and begin to provide more strategic value for the company. Instead of simply identifying current talent management trends, organizations can use "predictive analytics" to determine future trends and test "what-if" analyses in order to understand the impact of decisions before implementing them: "What if we offered overtime pay, how would that impact retention?"
But in order to truly provide actionable insights, HR teams need to engage in the most advanced form of data analysis: "prescriptive analytics." While predictive analytics provides forecasts for what may happen, prescriptive analytics reveals what actions should be taken, such as finding that just one to three hours of overtime a week increases tenure. Due to the actionable recommendations it provides, prescriptive analysis is the most valuable type of data analysis for organizations to aspire to.
How to Implement a Prescriptive Strategy
For HR departments still struggling to kick-start descriptive and diagnostic analytics, however, prescriptive analytics may sound daunting — or even impossible. Our upcoming webinar, "Why Predictive Workforce Data Is No Longer Enough and Why You Need a Prescriptive Solution," on Tuesday, November 10 is designed to ease any apprehensions by providing best practices and how-tos for implementing prescriptive analytics.
Attendees will learn about each stage of the analytics maturation process, the differential value of descriptive, diagnostic, predictive and prescriptive solutions and how one industry leading company leveraged prescriptive insights to drive business change.
Register today to hear Max Simkoff, VP of Analytics at Cornerstone, explain how you can use prescriptive analytics to drive a deeper understanding of your workforce and align your HR initiatives to business goals.