Data Mining Interview: Jeanne Harris

Jeanne_Harris2newAfter reading the excellent Analytics at Work, I had the opportunity to ask a few questions to one of its author, Jeanne Harris. She kindly accepted to answer my questions for the readers of Data Mining Research. Here are her answers.

Data Mining Research: Could you please introduce yourself and explain to the readers how you have been interested in analytics?

Jeanne Harris: My name is Jeanne Harris. I am an executive research fellow and a senior executive at the Accenture Institute for High Performance in Chicago. I lead the Institute’s global research agenda in information, technology, analytics and talent.  In my 33 years at Accenture, I’ve had a lot of roles.  I previously led Accenture’s business intelligence, analytics, performance management, knowledge management, and data warehousing consulting groups. So as a researcher I have always been interested in how managers make decisions and how those decisions contributed to achieving better business performance.

DMR: “Analytics at Work” is your second book in this domain. The first one was “Competing on Analytics”. Can you explain how they are different?

JH: In our previous book, “Competing on Analytics,” we described companies that build their business strategies around their analytical capabilities. Analytics were how they distinguished themselves in the marketplace. As we talked to executives around the world, we realized that many companies didn’t aspire to become analytical competitors, but the executives at these firms did want to help their organizations become much better at using analytics to make better decisions and to improve business performance. And they wanted some pragmatic advice on how to build their analytical capabilities over time. If a robust, enterprise-wide, analytical capability could be accomplished by executive fiat, we would not have needed to write another book. But like anything worthwhile, putting analytics to work takes effort and thought. So “Analytics at Work” is for anyone who thinks that their organization ought to make more decisions based on facts (not unaided intuition or prejudice) or wants to unleash the potential buried in their company’s data. And new Accenture research shows how important this has become. In a recent survey of 600 senior managers at more than 500 blue-chip organizations in the United States and the United Kingdom & Ireland (UK&I), nearly half (46 percent) of respondents said that among the long-term goals of their senior management teams are applying analytics in useful areas of the business and becoming more analytical in decision-making styles and methods across their businesses (Coleman Parkes Research, “Accenture Analytics Project: Summary Report”, 2009.)

DMR: In your new book, you introduce the DELTA methodology. Can you explain what it is?

JH: To help managers understand how to assess and improve their analytical capabilities over time, we came up with the acronym DELTA-the Greek letter that signifies “change” in an equation. Together these five factors need to be addressed in any analytical initiative:

  • D for accessible, high-quality data
  • E for an enterprise orientation
  • L for analytical leadership
  • T for strategic targets
  • A for analysts

To improve an organization’s analytical capabilities, you’ve got to move forward with all five DELTA elements in rough proportion. But organizations have very different starting points, different mixes of capability, and different rates of progress with analytics. To help you sort all this out and to plan and manage your development of analytical capabilities, we developed a five-stage model of progress, which we discuss further in the book.  The model helps managers assess their organizational current strengths and weaknesses, and offers specific advice for each stage of analytical maturity.

DMR: What is the most important lesson you have learned in the period that separated the two books?

JH: We are all headed towards a more analytical future as organizations realize that decisions based purely on gut feel are no longer good enough.  But it is no longer sufficient to have the trappings of analytics – to have data, technology and smart analysts. The real challenge is to have a fact-based analytical culture and to embed analytics into critical business processes.  All the analytics in the world won’t help unless managers use them to make and execute better decisions. So ultimately we need to become a lot smarter about how we make and execute decisions.

DMR: Jeanne, thanks a lot for your answers and all the best in the analytics world!

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Comments Icon3 comments found on “Data Mining Interview: Jeanne Harris

  1. Hi,
    I am working as a Associate Professor in engineering college. My interested area is Datamining.i am doing ph.d in andhra university visakhapatnam.I am interested in data mining .my guide suggested to do the data mining techniques using neural net works. he suggested one related ieee paper also.Now i want to continue my work. How can i proceed my work. Do you have any suggestion or any new ideas on this.please help me.
    thanks
    venkat

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