I was once appointed to work on a cross-functional team to support unlock the reverse logistics in my former organization. And one day, as I worked through some of the problems, thinking myself as a star for discovering the bottlenecks, a thought came to me. I thought, “why not check out some of the work that had been done on this challenge in the past?” I was surprised to find almost the same problem identification, the similar root causes and even similar solutions were being suggested.
It became apparent that something was wrong. We were not making the most of the data. The people on the cross-functional team kept changing year on year, but they all kept arriving at similar conclusions. Yet, the major problem remained unchanged. Instantly, I realized that there was a big problem in how the organization approached past data.
Why would everyone proceed to run the same reports, suggest the same landmark solutions and yet the problem remained unmoved? Now in hindsight, I realize that organizations must re-strategize on their data approaches. I don’t know how to drill this down, but data is the new capital, it will make or break organizations. And organizations must have strategies on how data is transferred from one team to the next, without compromising its integrity.
Some of the best data comes from failed projects. Yet, failed projects are the most ignored, they become untouchables. No one desires to investigate a failed project. Everyone simply states that this project failed, but data is never collected on why it failed. Organizations ought to borrow something from the aviation industry. The aviation industry gets safer from a prior accident. Because every accident is treated in such a way that it should never happen in the same manner, for the same cause.
Yet organizations continue to fail in the same way. Regimes change, structures change, but the way in which organizations fail remains constant. Why? Because organizations don’t treat data with the importance it deserves. They all talk about data, how it’s critical, but the culture in organizations proves that data is not a priority. Organizations must build a strong data culture. Without strong data cultures, organizations are bound to hit standstills.
Without a strong data culture, organizations will also miss out on the transformations that Artificial Intelligence is bound to usher in. Artificial Intelligence can only rest on a strong data foundation. Unfortunately, organizations have not built serious data foundations. This foundation starts with a pro-data culture. All data must be treated with the respect it deserves. That starts with data that points to why things failed!
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