Turning Data into Action
A practical approach in your digital transformation journey regardless of where you are in it.
Businesses today know the importance of data to function effectively and efficiently. We have production data measuring operations, equipment data measuring health and utilization efficiency, time data to pay and manage staff, and a whole lot more.
We also acknowledged the effects of “bad” data - untimely, missing, incomplete and simply incorrect. Whatever the issue, it manifests in “Who made that decision? Why are we doing this? This report makes no sense! What a waste of time and money!”, and the “industrial noise” festers. Sound familiar?
To make matters worse, we did not see the train coming while we frantically lay network track. We are already pushing 5G-LTE and beyond. In the multi-billion-dollar frenzy of the “Internet of Things” or IoT deployment we amass vast repositories of data – “farms” of it.
“Data bloat” continues at an exponential rate, yet many organizations still have the same issues noted at the beginning of the article. The human brain simply cannot digest the data volumes that today’s system spew. Often, data is provided with insufficient context to properly assess it. However, businesses are adjusting to this new world order of collection and storage. Leading software vendors provide digital solutions offering better data access, reporting capability, faster processing and automation. But that was no different a half century ago. Perhaps there are new approaches in the digital transformation spectrum.
Shift from data exposure to actionable usage.
Today, successful organizations adopt automated systems to perform actionable tasks , or at the very least notify a human to do something. Consider the non-value-added employee expense process. Filling the report, scrutinizing, authorizing, remitting, and resolving discrepancies, etc. This process(es) can be almost entirely automated. The system prevents or alerts to non-conformance, triggers upstream reimbursement and other administrative processes effecting policy and procedure. In the least, is exposes lack of policy or other management issues if the problem is significant and persistent.
Whether a simple administrative task, or a complex production process, systems today either execute the task or prompt a trigger to act – appropriately and timely. Why show all production orders? Rather, show prioritized orders, emphasize critical data, and isolate non-conformance. Exposing staff to pertinent data keeps them more task-focused. This strategy does require more process rigor to identify critical business process and define tolerance limits; however, one can argue that the very process of documenting them is extremely beneficial to the team. As a team you get to ask, “is that important, why is that important, does it fit within our strategy and vision?” The more systematic the more efficient the process, and the more you align to your strategy and vision. Also remember, systems do not miss things, have bias, never take time off and do not leave.
Focus on business, not technology outcomes.
A data-driven system relies on clean, objective data to automate specific tasks. Again, the emphasis is to increase task-focus and reduce administrative burden. Embracing this strategy requires critical attention to a broader change management or business outcome. Roles can be significantly changed, shifted to others better positioned, or eliminated altogether. Also, realize and afford new opportunity given the “freed” time. Simply reducing staff tends to stifle further automation incentive and potentially diminish motivation and trust. Challenge and reward your staff that brave the outcome. As leaders, also be brave and supportive to the needs of your staff.
It’s clear the opportunity to increase capacity, improve bottom line, or elevate your customers’ experience is achievable with a more data-driven system and makes for a healthier and stronger organization overall. Isn’t that the end goal?