Turning the analytical talent gap into an analytical talent dividend

By Stephanie Robertson, SAS Insights Editor

How important is analytical talent to your organization? If you’re aiming to become data-driven and turn your data into important insights, it should be near the top of your priority list.

It comes as no surprise that organizations today are reporting increases in the amount of data they have and how easily it can be accessed. However, it is a bit surprising that recent studies indicate that despite having more data, organizations still struggle to turn their data into insights that drive value.

To understand what is driving that number down, MIT Sloan Management Review conducted its fifth annual survey of business executives, managers and analytics professionals around the world from a wide range of industries and sizes. Also interviewed were subject-matter experts. Participants included spokespeople from Coca-Cola, GE, General Mills and Google.

The 2015 data and analytic research report, “The Talent Dividend,” found that the biggest barrier to creating business value from data is the shortage of appropriate analytical skills – the so-called analytical talent gap. The survey also presents findings on how analytically savvy organizations have turned that gap into a talent dividend.

Download the full MIT Sloan Management Review Research Report, “The Talent Dividend”

Tips for building your analytical talent bench

Along with informative survey results on the state of analytics talent in organizations, the research report provides tips that some data-driven companies have found helpful for increasing their analytical talent dividend.

Tip #1: Look inside your organization

According to the report, one of the most successful strategies for ramping up analytical skill power is to search your own backyard. And, train in your own backyard. Having someone who understands your business and organizational culture can be crucial to creating business value from data and analytics. So much so that it may behoove you to provide existing employees with a formal training program. The survey indicates this is a very successful strategy. As the report says, “There is far more to the talent equation than the acquisition of skilled data workers.”

Tip #2: Integrate existing talent with new hires

This may be harder than it sounds. An amazingly low number of companies said they have successfully integrated new analytical talent with existing data workers. Even 50 percent of analytical innovators reported having trouble integrating new data workers and existing employees. Wayde Fleener, a data scientist hired by General Mills in 2013, says if you are one of the new hires, it helps to focus on the fact that you’re not trying to “take over.” You are there to help the organization improve. After six months of creating relationships, Fleener was able to say he has the support he needs from the organization’s IT department.

Tip #3: Buddy up and create a common core

It’s a fact. People are good at different things. Organizations are finding that pairing data scientists with business domain experts works. The survey also found that more organizations are training managers to understand analytics than they are training analytics professionals to understand the dynamics of the business.

How do you compare?

Today’s organizations understand the value of competing with analytics. But this understanding has triggered a demand for analytics talent that far exceeds supply. Many companies are struggling to attract and retain the talent needed to build competitive advantage. The "Talent Dividend" research report explores the success factors of data-oriented companies who are cashing in on their talent dividends. Discover the hallmarks of analytical maturity and see how your plan for developing, cultivating and retaining analytical talent stacks up.