Data. Lots of it. When I first learned that I had cancer in January 2013, I knew nothing about cancer. My wife and I immediately started a crash course learning as much as we could. The first time it was prostate, the second time it was renal, and the third time colon cancer. I can’t begin to tell you how much information there is available about cancer. To the neophyte (not even a novice) the data was overwhelming. So many sources, that in the end, one of our first priorities was to talk with credible professionals with lots of experience. We also learned that many internet sites were not credible (Now isn’t that a shock? HA!) So we stayed with the trusted sources like MD Anderson, Johns Hopkins, Mayo, and others. Today, I have five teams of doctors at MD Anderson that have my back and help us sort through our questions and provide us insight to make our own choices – do something with the data. In the end, you are your own best advocate. But today we still sort through so much data to be informed and make good decisions.
That takes us to the dictionary…
Forget spellcheck or using Google. Remember the dictionary? Yes, the book. Now think for a minute. What does a dictionary do?
Back in 1995, I had the opportunity in Manchester, England to make a presentation on e-commerce to over 1000 supply chain, sourcing and procurement professionals. The focus of the presentation was how the information being shared using e-commerce was going to change the industry. My team had been instrumental in implementing a major UK retailer’s first e-commerce system. It even was the focus of a Financial Times special report. Prior to taking the stage, a crazy idea struck me. It was either going to be impactful – or make me look quite crazy.
I took a large book and walked on stage. I had no clue what the book was – it was big. I started the presentation without slides, held the book high in my hand, and asked “What does a dictionary do?” The audience started to get quiet as I got their attention. I asked again “What does a dictionary do?” As the room got quiet, a few people raised their hands. I picked one person who answered “It gives us definitions of words!” Another answered “It tells us how to pronounce words!” HA! Just what I hoped would happen.
I threw the book on the stage with a loud THUMP. I yelled at the book “Give me the definition of ‘computer’.” The book did nothing – of course. I then made the pronouncement that “This book does nothing!” The audience laughed…
Today, instead of e-commerce, there is much discussion about digitization, Internet of Things (IoT), business analytics, etc. The foundation for these technology driven business approaches is that data is being made available from many more sources around the world. This is a tremendous opportunity for insight and discovery. But, like the dictionary, the data does nothing. (Yes, we can also discuss at length the difference of data and information…)
Like the dictionary, it takes a person who knows what the book (data) is and how to use it. Someone with the skills, experience, and knowledge of how to use the book and then do something with what they find. Someone must apply the data to have a business impact and provide some kind of value to the business. That is the key.
One of my personal interests of late has been the recent focus on business analytics. Many of the consulting studies, board meetings, and executive discussions I have participated in has been focused on do you build the infrastructure to collect the data first then find the problem? Or do you define the problem then collect the data? It seems that if the initiative is driven by IT, then the data is collected first, then they search for a problem to solve. If driven by the business, the problem is defined first. Even a major university I have discussed this with has two separate approaches. The IT department and Supply Chain department are taking these same different approaches, when indeed they should be integrated for maximum impact and value.
The other business analytic topic discussed at length is the lack of data scientists to analyze the data. In the end, the skills and experience needed to solve business problems goes far beyond those of a data scientist. Experts in business process (sourcing/procurement, manufacturing operations, etc.), program management, and other skills along with a data scientist are required to take the data and do something with it.
In the end, technology is a game changer. Today tons more data is being accessed by new technology. This data does nothing until you provide it context by applying it to a business process and having a skilled, experienced human do something with it. That is the business relevance of technology. Otherwise we are destined to use technology to make bad decisions faster.
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