The other day I was showing a colleague the Data Cost / Value Matrix and describing the four aspects of data value.
He made a comment that got me thinking. I was explaining the fourth aspect of data value: Data Visibility and Transparency when he said: “For my customers, transparency isn’t the key issue. The biggest issue is that they are drowning in data they can’t use. If you can make the data they already have more usable then you’re providing value.”
My first impulse is that perhaps I need to relabel the graphic so that “Data Visibility & Transparency” reads “Data Visibility and Usability.”
The more I thought about it, however, the more I realized that all four aspects of data value have to do with making data more usable.
Product Release and Control is the minimal, entry level approach to making data more usable. Data for product release and control validates that our products are acceptable for shipment. It may be accept/reject type data, and may be based on either measurements or some other kind of pass/fail criteria, and is based on the voice of the customer. Product release and control is necessary, but not sufficient.
Process Control makes data more usable because we’re relying on statistical theory to help us understand when we should react and when we should leave things alone. Process Control empowers us to react immediately to instability and unexpected variation.
Using data for Continuous Process Improvement makes the data even more usable. When you can close the loop on processes and drive continuous improvement, you get significant returns on your efforts. Closing the loop means being able to find hidden sources of variation and correlation between key input and key output variables.
The last aspect – Data Visibility & Transparency – adds value because when data is readily visible across all levels in an organization, it changes the way people work. One engineer put it to me this way:
The real time part of it has been cool. I have walked into several meetings and said “As of 5 minutes ago, this week our first pass yield is 93%.”
In the past I would walk into a meeting and report on week-old data. So inevitably there would be questions on “Do we have this fixed?” and the answer would be “I think so.”
We are definitely making a lot more decisions based on data rather than gut feel or incomplete data. We feel like we are getting the entire landscape before we go down and make a decision on what we are going to do.
