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Evan Miller joined Hertzler Systems Inc. (Goshen, IN) in 1984. For the next seven years he held positions within the company in sales, marketing, technical support and training. In 1991 when founder Paul Hertzler retired from the firm, Miller became president and is now co-owner of the company.

# What Is Your "Data Driven" Score?

August 17, 2009
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In last month's post, I asked if the term "data driven" is just another buzzword. Now I will point you to some actions that can help you become more data driven.

In last month's post I asked if the term "data driven" is just another buzzword. I argued that "data driven" deserves an operational definition, and proposed a simple two-by-two matrix that could help us develop a common understanding of what it means to be data driven.

While most people aspire to Quadrant A (low cost and high value data), most don’t live there in reality. Many actually live in Quadrant D (high cost and low value).

While the anecdotal descriptions of the four quadrants that I shared last month are useful, they don’t offer much guidance on what to do about your current reality.

For that reason, I developed a quick and dirty gap analysis that helps you quantify where you are today. Used properly, the gap analysis can point you to some actions that can help you become more data driven.

I use the term gap analysis because it helps you evaluate the gap in your current performance and your performance potential. Sometimes I like to say that your performance potential is how things would work if God ran the process.

Anyhow - here is the Gap Analysis Tool. Just answer the four questions below, then click Continue to answer four more questions. Then Click Results to see where you score.

Here are some questions that might help you develop a new strategy:
• Is your score better on the horizontal axis (data cost) or on the vertical axis (data value)? If you’re firmly in Quadrant C (low cost and low value) it is obvious that you need to work on increasing the value of your data. If both scores are low, look for the low-hanging fruit. Often this is found in data completeness and automation. Automation will free up time from the data shuffle so that you can work at making better use of the data that you’re collecting.
• Where are your lowest scores? Often bringing one score up from Never to Seldom or Seldom to Sometimes will do a lot to improve your performance.
• Are your scores balanced across all eight categories, or are some significantly better than others? As a rule, I’d encourage you to seek a balance across all aspects, rather than strive for excellence in one aspect at the expense of the others. These are just some of the ways you can use this data to become more data driven.

Copyright Hertzler Systems Inc, 2009. Used by permission.

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