The manufacturing industry, like any other industry, is not immune to data challenges. Sourcing data, wrangling it and ensuring it’s being used in a governed, standardized way are not uncommon problems. Particularly in manufacturing, issues surface with inventory management, within the supply chain and with logistics.
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We all know data is the new oil. Both data and oil are valuable resources and share a common quality; if unprocessed they cannot be used. Data and oil have to be broken down and built up again to create true value for the business. There is, however, one key difference. Whereas oil is tangible, data is not. This means that the flow of low-quality oil is traceable and will be noticed in the production process. But, what happens if there is a bad data flow in your organization?
The story of the last year+ is one of disruption and change across every aspect of our lives. As we all navigated a ‘new norm,’ businesses naturally had to pivot as well, with some sectors finding new opportunities while others scrambled to reimagine their entire go-to-market strategies.
“Data acumen” is a powerful new term. I heard it used recently in relation to a historically hard problem for the Department of Defense (DoD). The problem is the speed of data change. David Spirk, DoD’s Chief Data Officer, gave an historic keynote at GovCon Wire’s Data Innovation Forum, which was held in June 2021. He was joined by three key leaders in DoD data: Thomas Sasala (Navy), Eileen Vidrine (Air Force) and David Markowitz (Army).
Data and technology are often hailed as a magic ingredient that can help solve so many problems. But, as I discussed with Joe DosSantos on Data Brilliant – it’s just one piece of the puzzle. In order to truly navigate uncertainty, the key is widening your focus and opening up your information sources. It comes down to balancing breadth of perspective with depth of expertise.
In my previous blog posts, I’ve talked about how you can aggregate data depending on the data type, as well as how you can re-express your data to get more value from it. For this post, let’s look at some of the different ways of measuring your data.
