A2 Radio: Turning Data Into Business Value

(Image: (vm/iStockphoto)

(Image: (vm/iStockphoto)

Small analytics projects that can lead to the biggest returns for organizations can also fall by the wayside when they must compete for attention with other priorities inside the business -- for instance other analytics organizations, roles, and data efforts.

That's according to Andrew Wells and Kathy Chiang, authors of the new book Monetizing Your Data. They should know. Both have worked with organizations for decades, helping them shepherd their analytics programs to turn insights into value.

"When we first started tackling this problem, one of the key challenges we noticed was the siloed approach to development and distribution of analytic information," the authors wrote in the preface to their book. These days more self-service efforts are helping improve the negative impact of some of these gaps. But gaps remain, and that means that organizations are not getting the full value out of their analytic investments.

So how do you fix it? Wells and Chiang compiled their approach in their new book, and will be talking about both the book and the approach on AllAnalytics radio on Wednesday, March 29 at 1 pm ET/10 am PT. (Register now for the show: Monetizing Your Data: Turning Insights Into Action.)

They bring their experience with real-world challenges in the field to their approach to analytics.

Wells is CEO of Aspirent, a management consulting firm focused on analytics. He's spent 25 years building analytics solutions for a wide range of companies, from Fortune 500s to small non-profits. Chiang is an established business analytics practitioner with expertise in guided analytics, analytic data mart development, and business planning. She currently serves as VP of business insights at Wunderman Data Management, and has also consulted with Aspirent on several projects with clients including IHG and Coca Cola.

Wells and Chiang's book arrives at a challenging time for analytics programs and projects.

Kathy Chiang

Kathy Chiang

"Making a quality decision is harder than ever before. We are flooded with information and are expected to synthesize this information into quality decisions in order to drive results," the authors write.

And yet when managers make decisions without analytics, they run other risks.

"Making decisions based on gut feel, intuition, or emotion leaves you vulnerable to the cognitive biases we all carry around with us."

Many organizations get stuck in an analytic maturity level of "reading the news," or the reports generated by their analytics efforts. But "reading the news" doesn't drive value in itself. Insights must be tied to action.

Wells and Chiang will discuss the Analytical Cycle, which they break down into four components -- measure, inform, diagnose, and action. But this cycle is not a straight line. It's a circle of effort and action.

Andrew Wells

Andrew Wells

"This analytical cycle is structured very similarly to that of a doctor or scientist trying to diagnose an issue," the authors wrote.

The goal of all of it is to connect the data you have to making better business decisions -- an effort that enables organizations to better monetize their data.

Register now, and join us on Wednesday, March 29 at 1 pm ET/10 am PT to learn about this approach and how it can be applied to your organization's data programs.

Jessica Davis, Senior Editor, Enterprise Apps, Informationweek

Jessica Davis has spent a career covering the intersection of business and technology at titles including IDG's Infoworld, Ziff Davis Enterprise's eWeek and Channel Insider, and Penton Technology's MSPmentor. She's passionate about the practical use of business intelligence, predictive analytics, and big data for smarter business and a better world. In her spare time she enjoys playing Minecraft and other video games with her sons. She's also a student and performer of improvisational comedy. Follow her on Twitter: @jessicadavis.

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Re: Big Issue
  • 4/5/2017 5:40:17 PM

Having a goal and turning that data will surely alleviate a lot of the problems as noted when "decisions based on gut feel, intuition, or emotion leaves you vulnerable to the cognitive biases." Our emotions will generally not get a great deal of business value compared to the hard data from our customers and sales results.

Re: Big Issue
  • 3/29/2017 5:40:45 PM

@tomsg, not only seeing the results is important but having a clear definition of what a successful initiative would look like.

Big Issue
  • 3/28/2017 2:04:33 PM

While I have seen many examples of analytics saving money or growing revenue, the biggest issue I run into is that companies ( especially the small ones) do not have good measurements so that thye can see the results. I think the first thing to do is to put a good set of metrics out with ways to measure them, then start the program.