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Bill is Founder and President of King Innovative, an advanced analytics and data privacy management practice. Bill has been in technology services for over twenty four years and specializes in helping others build better businesses. As a seasoned translator, he’s able to bridge the gap between business and technology by communicating complex issues in simple terms.

For our listeners, Bill sent over Fender Guitar’s story of how they used data to better understand the market and drive greater value to the customer. The video is really good too!

What’s not mentioned in either, Bill says, is Fender used data to transform, while their competitor, Gibson Guitars, was diversifying into home audio and filing chapter 11 bankruptcy. As Fender gains traction, Gibson loses it and uses diversification to stem the tide.

The moral of this story: the future will go to those who are good at leveraging data.

Some Misperceptions About Data

Successfully leveraging data is rarely a quick hit high return proposition, Bill says, which means it requires key stakeholder buy-in and ongoing support. Data, by its nature, is a continual learning process that never stops asking “why.” Continual learning requires a culture of continual improvement, open mindedness and comfort with change.

Cultures that think they know it all, are closed minded, not open to change or do not hold themselves accountable to improvement, and rarely leverage data to its fullest potential, he says. The perception of knowledge is the enemy of learning. Bill offers some common data misperceptions in the data graphic below.

Data Graphic


  • Data is about product/technology selection
    • Product A, B or C promises to turn data into insights, intel, etc.
    • i.e. a “solution looking for a problem” approach
  • We simply need a data analyst position
    • i.e. spans strategic to tactical, creative to analytic
    • Job description combines multiple roles into one
  • We need quick data “wins” to gain buy-in
    • Projects prioritized by
    • i.e. mis-alignment with strategic business requirements
  • Data is a support role
    • Provides insights, decision support, etc.
    • i.e. a “data last” approach
  • Data isn’t about company culture
    • Getting the right training/analyst will produce results
    • i.e. focuses accountability on support role
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