Creating an advanced data analytics business culture: Tips and advice

Data analytics can help drive better business decisions, according to users and analysts. But creating an analytics business culture usually requires high-level executive support.

Our four-part series on setting up and managing data analytics programs concludes with an article on fostering...

an internal business culture that’s oriented toward fact-based decision making and the use of analytics tools.

Table of Contents

Analytics skills in demand – and analytics pros demanding top salaries
Data analytics team’s needs: a business home, leeway on tools and data
Getting ready for an advanced business analytics software project
Creating an advanced data analytics business culture: Tips and advice

The quickest, and potentially most successful, way to create an internal business culture that thrives on advanced data analytics technology and fact-based decision making is to start at the top of an organization, according to some IT professionals and industry analysts.

Just ask Bill Robinette, manager of business intelligence (BI) systems at Advance Auto Parts, a Roanoke, Va.-based retailer with about $5 billion in annual revenue. Two years ago, Robinette bore witness to the fact that a change in senior management can clear the way for the development of a data analytics business culture and a data warehousing, BI and advanced analytics program.

At a recent event held in Cambridge, Mass., by The Data Warehousing Institute (TDWI), Robinette said that when he joined Advance in 2006, business decisions were typically based on data stored in spreadsheets and Excel-generated cubes.

“Basically, we were running the business on gut feel,” he said, adding that more sophisticated BI and analytics investments were a tough sell because company higher-ups were mainly focused on redesigning Advance’s retail stores.

Going from ‘gut feel’ to an analytics business culture
Things changed in early 2008, when a former Best Buy executive took over as Advance’s CEO and put a priority on improving the mix of parts in different stores based on local demand. Instead of the previous one-size-fits-all approach to merchandise planning, the company now uses data mining and predictive analytics tools to help automatically set plans for populating individual stores with parts, Robinette said.

In addition, an analytics business culture has been firmly established within the retailer, he said. “My big cultural challenge now is that I have people who want [analytics] and I can’t deliver it fast enough.”

Operational improvements enabled by the analytics tools have helped to solidify those tools’ place in the company. For example, in the past, about 20% of the parts stocked in stores didn’t sell within a year. Advance has used analytics to lower that figure to 4% – a reduction that is “worth millions of dollars to our bottom line,” Robinette said. The company also uses performance metrics generated via its analytics applications to set growth targets for store managers and foster internal competition among stores.

Analysts say that Advance’s experience with analytics technology is becoming more common these days. A technology-savvy CEO, often someone brought in to replace the previous top executive, pushes a company to use advanced data analytics software and methodologies to generate deep data insights that can support better business decisions.

To help an analytics initiative succeed, senior executives need to drive an internal emphasis on optimizing business performance through quantitative measurements, TDWI analyst Wayne Eckerson said. They also have to put the company’s money where their mouths are by funding and prioritizing analytics projects, he added.

Analytics software doesn’t equal an analytics business culture
But new analytics software and high-level executive support – while a good start – aren’t enough to foster and maintain an analytics business culture. Companies also need to make sure that their employees have the ability to make the right decisions based on information gleaned from analytics technology, said Dan Vesset, an analyst at Framingham, Mass.-based IDC.

“I think that was part of the problem, for instance, with the financial crisis,” Vesset said. “The systems correctly identified risks, but the humans overrode those signals because they were incented to do so.”

A recent IDC survey of 1,100 organizations found that analytics programs tend to work best when employees are truly willing to let their actions be influenced by the technology. The survey also found that companies with successful analytics programs tend to be more successful in general. “The more analytically oriented a company was, the more competitive they were in their industry,” Vesset said.

He added that education and training are two of the keys to creating a long-lasting data analytics business culture. But that means more than simply teaching employees how to press buttons, click icons and read data on executive dashboards, he cautioned.

“We don’t just mean training on the tools but also training on analytics techniques,” Vesset said. “There is a lack of people who are knowledgeable on the different ways of analyzing data.”

Employees should also be educated about the meaning of data as it pertains to their company’s specific key performance indicators and performance metrics, he advised, while noting that such training is currently lacking at most companies.

Using an analytics group to help create an analytics business culture
Another potential way to help foster an analytics business culture within an organization is to set up a dedicated data analytics group, according to Eckerson, who put cultural issues at the top of a list of analytics challenges during a presentation at the TDWI event in Cambridge.

While most companies haven’t gone that far yet, he said, an analytics group with its own director could develop an analytics strategy and project plan, promote the use of analytics within the company, train data analysts on analytics tools and concepts, and work with the IT, BI and data warehousing teams on deployment projects.

One more point to keep in mind: Don’t go overboard on the use of analytics tools. For example, Advance Auto Parts tied information gleaned from analytics software into a performance dashboard application that was rolled out last year. The dashboard gives store employees a quick view of key performance metrics – a capability that Robinette said reinforces the importance and value of analytics without requiring front-line workers to delve deeply into it themselves.

“We didn’t want to turn our store managers and associates into data analysts,” he said. “We want them out front in the stores, selling products.”

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