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FASTforward: Competing on Analytics

by Sandy Kemsley

Tom Davenport presented on competing on analytics — he published an article with this title in 2006 in HBR. He believes that the planets are aligned for analytics:

  • Powerful IT, and a new model for IT use
  • Data critical mass: ERP, POS and web data
  • Skills sufficiency, at least for the individual pieces
  • Business need: a differentiated, personalized, well-informed easy use experience

He makes a distinction between reporting and analytics, and sees analytics as a way for companies to find the best customers and charging them the right price, or analyzing search logs to design a better website.

He sees the following attributes of a user-centric analytical strategy:

  • Analytics are used to design and modify the customer experience
  • Analytics are used to measure and maximize user engagement
  • Analytics are used to determine what the user wants, and personalize to the user
  • Analytics are employed across all customer channels
  • Analytics are made available to the user

This includes companies such as Amazon and Netflix through their targeted recommendations, Google with customized ads and do-it-yourself analytics, eBay with behavioral targeting, Harrah’s and Marriott with loyalty programs, and Royal Bank of Canada and Capital One with targeted cross-selling across channels. Analytics can also be used for public service: New York City reduced crime through predictive analytics of where crimes were most likely to occur.

He stepped through what’s required for competition grade analytics: data (which he envisions in a data warehouse, counter to Weinberger’s arguments about the more serendipitous discovery of data), enterprise (widespread access to a centralized data store), leadership (executive commitment), targets (focusing analytic activity), and analysts (professional, semi-pro and amateurs, using all levels of analytical tools).

He finished up with the next steps for analytics, from the pursuit of new data types to search/BI combinations to better model management.

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