In Part 1 of this four-part series, Frank Costanzo and Dr. Dave Solot discussed how the Big Data revolution has changed the way we hire and develop top performers. In Part II, they talk about People Analytics for recruitment and selection. Dr. Dave continues the story…
Part II: Building Your Team; Hiring with Analytics
I recently worked with a company that was looking to hire a new Sales Leader. They had experienced moderate growth for the past decade, but sales numbers had begun to decline in the past year. As a result, ownership decided to confront a problem that had been bothering them for a while—a dysfunctional culture. Historically, the sales organization had very little accountability beyond top-line revenue growth. This allowed them to operate however they wanted, so long as growth was positive. The result was small increases in the top line year over year, but also a back-office mess and an inconsistent experience for customers. Essentially, short-term sales were growing at the expense of long-term customer satisfaction.
The organization reached out to me to help them identify a new Sales Leader who would bring both growth and a sense of order to the organization.
We started with the most important part of any People Analytics selection engagement—building a model of success. In the Big Data world, this is called the “predictive model.” As we’ve discuss in all of our People Analytics work, the quality of your answer is only as good as the model you build to answer it.
We defined a model that included the traditional predictors of success in a sales leadership role: leadership ability, the need for results, negotiating skills, business acumen, and a few others. Then we modified this model to include process focus and organizational citizenship. These qualities would address the company’s need to bring structure and responsibility to a disorganized sales culture.
With the model in place, the company assessed their candidates. Using our Caliper Analytics engine, we compared each applicant against the predictive model. For each one, we were able to show the percent likelihood of success, along with the specific areas of strength and weakness. Furthermore, we displayed the overall strengths and weaknesses of the entire applicant pool so the organization could assess how well their strategy aligned with the available candidates.
With the assistance of People Analytics, the company hired an individual who is not only effectively transforming their sales culture but also driving the sales force to deliver significant growth.
The key takeaway from this story is the role that People Analytics plays in a best-practices selection process. In the past, hiring was largely a guessing game of attempting to match observed strengths with the assumed needs of the organization. With the advent of Big Data, we bring precision and efficiency to the process of quantifying company needs relative to applicant ability.
And in today’s ever-changing business landscape, that’s an essential component of success.