Mining Your Organization's Hidden Gold

Published May 2012

While I remember little of various episodes, one of the more enduring memories of my childhood was the weekly introduction to "The Beverly Hillbillies" TV series.

    Then one day he was shooting for some food

    And up through the ground came some bubbling crude

I can still see the puzzled look on Jed Clampett’s face as he begins to comprehend his great fortune.

    Oil that is, black gold, Texas tea

Many organizations are likewise unknowingly sitting on a treasure trove … the data they generate each and every business day. Properly mining and analyzing this information can result in dramatic improvements in almost every area of your business. This includes dramatic increases in sales, better utilized advertising dollars, lower employee turnover, or remarkable improvements in quality.

Online retailers such as Amazon are especially skilled at this, immediately suggesting other potential products to shoppers which have been appealing to others with similar purchasing habits. The suggested products are not a wild guess on Amazon’s part, but are based on carefully studied sales data.

On the production side, a seemingly endless array of input factors may appear to impact the output quality of a complex process. When data on a finite number of key factors is captured and properly analyzed, however, the “magic” of the process can often be converted to science.

A reasonable analogy is a police detective trying to solve a crime. Whereas there may be an almost infinite number of suspects, when quantifiable data such as a fingerprint is fed into a good database, a culprit can be quickly and accurately identified.

Unfortunately, mining business data isn’t as easy as Jed Clampett simply missing a critter with his rifle. Rather, utilizing data to improve your business is a strategic decision with expense and resource implications. Success requires a well thought plan and careful execution.

  • What data will we collect? (Amassing unused data is as silly as ignoring valuable data)
  • How will we consistently and cost effectively capture it?
  • How will we keep data current?
  • How will we keep our data secure?

Fortunately, an array of software tools and technology solutions is available to fit any organization’s budget from a simple Excel spreadsheet to massive Enterprise Resource Planning (ERP) systems.

A perfect database is perfectly useless without the skills to efficiently and correctly analyze the data so that accurate conclusions can be drawn. For example, it’s important to understand if an observed “improvement” between last month’s output and this month’s output following a controlled change to a suspected input parameter is truly an improvement because it resulted in a statistically significant change or is merely the product of random chance.

Here again, there are a range of options available to match the size and needs of any organization. Smaller businesses may be fine with someone who knows Excel inside and out (including pivot tables), a good understanding of basic statistics provided with a software package like Minitab and a proven problem solving process such as A3 or 8-D. A large organization would do well to dedicate a small portion of its workforce – say one percent – as full-time, high-powered problem solvers taking on the company’s toughest issues and using a more sophisticated tool such as Six Sigma.

While it is not necessary for senior managers to be experts in using the above tools, it is vital that they understand the theory behind their use and insist on data-based decisions and statistically analyzed results from their troops. I once visited a boardroom with a plaque which stated, “In God we trust, everyone else better bring data.”

The evolution of technology to mine data to provide order and understanding to previously complex portions of business is as dramatic as the advancement of automation. Whereas the latter is more apt to elicit “oohs” and “aahs” during tours, the former is much more likely to offer a competitive advantage because it’s much more difficult to duplicate.

Today, if your organization isn’t effectively harvesting and analyzing its data to really understand what it does, you’re the equivalent of a corporate Clampett.

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