8 steps to serving up an analytics culture

On July 13, I attended one of the most interesting business events of my 30 year career, The SAS Power Series in Chicago. What made it so interesting is that the attendees, senior executives from a variety of industries, provided most of the content.

The interactive half-day session focused on how to build an analytics culture, drawing on the challenges and successes of the attendees. Tom Davenport (Competing on Analytics, Analytics at Work) and SAS CMO Jim Davis provided color commentary. Miguel Ares (Bloomberg BusinessWeek) and I also shared some highlights of a recent research study we co-sponsored on business analytics. After listening to all the discussions, there seemed to be a food theme going on. So here are my top observations:

  1. You are not dining alone. While the adoption of analytics is widespread—Jim Davis noted that “analytics have gone mainstream”—effective application is a different story. Our recent research study shows that only one in four businesses feels that its use of analytics is “very effective” in driving decisions. Companies haven’t yet turned the corner on their investments in analytics and are struggling to integrate it into their decision making.
    • How do we get people in the organization to understand and adopt analytics?
    • How do we get analytics to drive business impact?
    • How do we get to a point where we are making decisions at the speed of business?
    • How do we get our arms around customer insights and stay relevant to our customers?
    • How do we get a single source of the truth?
  2. This was echoed in the sessions when participants shared their challenges with analytics. Some examples:

    Let me note here that all of the participants in the session are analytics evangelists—they understand the value in analytics and are working to spread the good news to the rest of their organization.

  3. Whet their appetites. Our study shows the importance of data in the recipe for effective use of analytics. Most companies are stifled in their efforts because of data quality and access issues—further compounded by the increase in the amount and types of data available. Participants in the session reiterated the importance of getting your data in order: develop strong data stewardship and cross functional business intelligence.
  4. “Data will never be perfect,” was a comment from the members of a breakout session on data quality. The purpose of analytics is to help make informed decisions, they said. So start right away by wetting the organization’s appetite with what can be done now with the data you have. Tie analytical outcomes to the strategic issues of the business. This will fuel the analytics appetite, and as it grows, companies will invest more in resources and infrastructure to address data issues, paving the way for enterprise analytics deployments.

  5. Feed Them Saltines. The breakout discussion I observed focused on the challenges of building an analytical culture. The guys in this group were really sharp—they’ve used some innovative approaches to advancing analytics in their companies.
  6. I particularly like the notion Jayson Tripp and Brian O’Connor from Redbox had. “When someone is in the desert starving,” Brian said, “if you feed them a saltine, it tastes like steak.” Brian, responsible for the business intelligence function, initially fed Jayson, in charge of strategic planning, “saltines” of information as Jayson worked to gain acceptance of analytics at Redbox. Jayson took this information and boiled it down to three PowerPoint slides showing the financial impact to the company—and made inroads in analytics adoption. Getting “quick wins” in using analytics is important to winning over decision makers.

  7. Show them how the sausage is made. One issue in gaining the acceptance by executives is the notion that the analytic software is a “black box” where data goes and is mysteriously transformed into “answers.” Bruce Bedford at Oberweis Dairy recommended positioning analytics to decision makers who don’t have a statistical background. “Take them through a few simple examples like a t-test or chi-square,” he said. Then show them how it translates into a business decision. Bruce commented that the impact is amazing.
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  9. Hire a top chef. People, the right people, are a critical component to effectively using analytics, according to our survey. This was also a key component of the group discussion on driving an analytics culture. Participants recommended hiring a Chief Analytics Officer (CAO) to lead the analytics charge in the organization. This person should be a change agent to win over the reluctant decision makers. Tom reiterated the importance of influence. “If you want to make decisions better,” he quoted from one of his mentors, “it’s not about the math; it’s about the relationships.” You have to be able to clearly communicate the value proposition of analytics and what it means to the business. You have to be able to sell ideas.
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  11. Sell more lobsters. Everyone enjoyed the insight Tom shared about expanding the use of analytics and moving back and forth from the tactical to the strategic. Early on, he said, companies often start out addressing a single issue, or they begin at the tactical level. For example, a retailer Tom works with wanted to know: Do lobster tanks sell more lobsters? So they did a lot of testing at different store locations using analytics. The answer: Yes, lobster tanks do sell more lobsters, but only in stores where customers are inclined to buy lobsters anyway. With a tactical decision under its belt, the retailer can now advance to more strategic issues like store location and merchandise configuration.
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  13. Teach them to fish. Jim Davis talked about the four components of information maturity in the effective use of analytics: people, process, infrastructure and culture. “Of these, culture is the biggest challenge,” he said. He also told us that there is definitely a movement to stop looking at analytics as a tool or a product, but as a component of the business process. With analytical talent at a premium, Jim is an advocate of the analytics competency center, where data and analytics are managed as strategic assets with a view across the organization, and where decision makers can go to get business value from analytics.
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  15. Eat a balanced diet. For the last of my “food” references—I shared the concept of “Analytics Equilibrium” during the session. Again, I drew on findings from the business analytics research, which indicate that – on average – companies use 60 percent intuition based on business experience and 40 percent analytics to make their decisions. As companies mature in their use of information, this ratio tends to shift in favor of analytics. Companies that say that analytics are “very effective” in aiding decision making report using 53 percent intuition and 47 percent analytics to drive decisions.What’s the right mix? Of course that depends on the decision and the decision maker. Jayson Tripp shared an example of a fast food chain executive who counted the number of containers of milk for sale in a grocery store – to estimate the number of children in the area – in order to help choose location of restaurants.The session participants view analytics as a tool in the decision making process, which will never fully replace sound business experience. After all, the choice of analytical tools and the selection of data that goes into them are decisions people have to make. So I challenged the attendees to think about their own businesses and the decisions they are facing to determine what their own “Analytics Equilibrium” might be.

It was a great session. I’m looking forward to the next one in San Jose on September 7th. In the meantime, I feel a craving for lobster and saltines.

tags: all analytics, analytic culture, analytics, power series

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