A Story About Data Quality

Let me start with some background information. A few weeks ago, I received an email from a former chair of the Baldrige Judges Panel and long-time friend, Kathy Herald-Marlowe. We hadn't communicated in several years, so my curiosity was immediately piqued. Kathy wrote she has been binge watching old episodes of the television series West Wing and had a simple question: Did I ever make a cameo appearance in an episode of West Wing? In particular, did I appear in season 4 episode 15, "Inauguration: Part 2 - Over There." In the inaugural ball there is a couple briefly on the screen (in the background) and Kathy was sure I was the male partner in that couple. Furthermore, she was curious how I got the bit part and do I include it in my resumé? 

Do I have a doppelganger?

My first reaction was to look at the old episode. I had to freeze the scene to get a look at the person, who I had no problem spotting, since I was focused on finding him. How she found me I will never know, but there to my surprise I was. Well, not exactly me, but a perfect doppelganger. 

My second reaction was to wonder what the chances are of a person having a doppelganger. University of Adelaide School of Medicine researcher Teghan Lucas used a database of almost 4,000 individuals to search for duplicate faces. She was unable to find any two faces that matched. Furthermore, through mathematical analysis, she discovered that by using a combination of eight facial metric traits, the probability of finding two faces with the same measurements in the general population was less than one in a trillion. I don't think I will search for my facial double.

My third (more geeky) reaction was to think about the challenges of social media and image data interpretation in the burgeoning field of data analytics. I assume my facial image is an example of why achieving accurate/worthwhile results requires large volumes of data and not anecdotal data, like my facial image alone. Of course Kathy had the advantage of being able to validate her data interpretation by going straight to the source.

What do the Baldrige Criteria ask about data?

This simple example of qualitative data interpretation added new meaning for me to the questions and concepts in the Baldrige Excellence Framework. How do you ensure data and information quality and accuracy? These are the questions in Item 4.2a(1) related to data and information quality:

• "How do you verify and ensure the quality of organizational data and information? How do you manage electronic and other data and information to ensure their accuracy and validity, integrity and reliability, and currency?"

Data and information are of increasing strategic importance. In the area of strategy considerations, in Item 2.1a(3), the Criteria ask the question:

• "How do you collect and analyze relevant data and develop information for use in the strategic planning process?" The detailed considerations include the potential risk of blind spots in your information.

A Baldrige core value is management by fact. In the description of this core value there is a discussion of the many types of data and information needed to effectively manage organizational performance. These data and information may come in many forms, such as numerical, graphical, or qualitative, and from many sources, including internal processes, surveys, and the internet (including social media). The challenge of reliable data interpretation and use is immense.

So, here I sit without a tuxedo and dancing shoes, never having been to an inaugural ball, but with apparent data saying otherwise. How do you ensure the accuracy and validity of data you can't track back to a conversation with the source of the individual data points?
 

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