Smarter use of analytics offers top competitive advantage

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Data and analytics are the new source of competitive advantage, but how do executives know the best analytics tools to invest in and how to apply data insights to business decisions? That's the focus of the new book from John K. Thompson and Shawn P. Rogers, “Analytics: How to Win With Intelligence.”

Information Management spoke with author John Thompson about the lessons to be learned in the book and how organizations can reap the full benefits of data analytics.

Information Management: What is the central message to the reader in your new book?

John Thompson: Non-technical C-Level executives hold the majority of the budgets and resources and will make the primary decisions regarding how companies invest and move forward with analytics. After recognizing that there was widespread trepidation and a lack of understanding of analytics in the executive ranks, I decided to write this book to give these executives a high-level overview of successful teams, projects, technologies and approaches in analytics.

IM: What is the meaning of the title of the book?

Thompson: The title is a description of the main message of the book. The book is a primer on analytics. The book is intended to provide context and a framework for the readers so that they can feel an increased sense of understanding and confidence when talking about and making decisions about investing in analytics.

IM: What was your inspiration for writing it?

Thompson: For the past three years I traveled the world meeting with a wide range of executives (technical and non-technical). I noticed that the majority non-technical executives had a sense that they did not understand the math, technology or people who were involved in making their analytics efforts successful. I wanted to reduce that knowledge gap and increase the level of confidence and communication between these groups.

IM: What is your background in data management and analytics?

Thompson: I have spent the last 30 years building software products and implementing analytic solutions in global corporations. I was fortunate enough to be part of the early days of business intelligence, data warehousing, data mining and now analytics. I have worked in the US, Latin America, Europe and Asia and have been involved in projects focused on fraud prevention, plant floor efficiency, marketing, pricing, advertising, and a wide range of intriguing projects.

IM: Analytics is tough stuff for many organizations. For those that don’t do it well, where do they go wrong?

Thompson: Analytics is definitely a complex proposition, you are correct in that assertion. The majority of failures that I have seen come in a couple areas:

First, teams or organizations try to solve a problem that they don’t understand or that they invented to try to vet analytics. Companies and groups have enough well-known problems that can be solved or improved with analytics, they do not need to invent new problems, but it is done over and over, so people must feel the need to approach the process in this manner.

Second, leaders let themselves be sold on projects that are unrealistic and the final results do not live up to expectations. Teams should set out to solve problems in small pieces. An example might be, trying to eradicate or eliminate fraud. This is a laudable goal, but hard to do. Look at one aspect of fraud, lessen or eradicate that and then move onto another aspect. With this approach, over time, the results can be staggering.

IM: What are some best practices of organizations that do analytics well?

Thompson: One of the most successful approaches that I have seen executed multiple times in a wide range of organizations in numerous countries is to build a Center of Excellence for Analytics (COE). The COE is a SWAT team for analytics. The COE is typically a distributed organization (ironic to name it a Center, when it has no center) that is the leads on major analytics initiatives. A range of options for COE teams and organizational structures and approaches are described in the book.

Another best practice is one that we already discussed, limiting the size, scope, team and time that a project is to exist. Small teams, projects and problems are more easily studied and solved. Start small and iterate.

IM: What are some of the top myths about what analytics can do for an organization?

Thompson: Well, there could be a book on this topic!

We can fall back to the beer and diapers fallacy or the story about retailers knowing more about individuals than their family members do. The more salient point here is that analytics is not magic. If you do not know what you are solving for or do not have the right data or team to build the solution, there is a very small chance that the project will produce positive and tangible results. Be realistic and results will follow.

You’ve heard about the million monkeys and typewriters, right? One of them will reproduce one of the great works of literature…. don’t approach your project in this manner.

IM: How should an organization best measure success when it comes to using analytics?

Thompson: In the beginning, on a project by project basis. Over time, on a functional area basis (i.e. results in marketing, manufacturing, etc.) and then finally on a portfolio basis.

IM: What would you like your readers to most take away from the experience of reading your book?

Thompson: That they have a better understanding of how analytics can help them win against their competitors and that they have a clearer view of where they want to invest their time and money to advance their goals. I want people to feel more comfortable in investing in and using data and analytics to advance their goals.

This is an easy to read book with an accessible and digestible message. I want this book to be their on-ramp to their analytics journey.

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