A Manufacturing Company’s Journey Beyond Traditional Reporting
A few years ago, I had a conversation with a local business leader of a manufacturing company that had heavily relied on predefined, analytic reports to metric their operations. They shared with me a problem they were facing – a succession planning issue for their reports. The power users of their reports were retiring and they had several thousand operation performance reports that were going to lose their report owners. This posed a serious challenge for the company as they had to figure out who would take the reporting mantel and continue the operational legacy of these reports.
At that time, retaining the predefined reports seemed to be the safest option for the company. They believed this approach would maintain business performance by backfilling report ownership with smart people. I was still surprised that the problem turned into a data analytics succession planning exercise, when it could have been an opportunity to employ the power of data science to optimize resource utilization and operational outcomes.
Today, organizations have even more impactful solutions towards organizational process improvement beyond “retaining predefined reports”. Data analytics has evolved beyond predefined reports, thanks to the power of algorithms and AI. By utilizing AI-driven analytics, businesses can not only identify and address anomalies in real-time but also uncover hidden patterns and correlations that lead to process optimization. This shift offers numerous benefits, including proactive issue resolution, deeper understanding of data, enhanced efficiency, process optimization, and reduction of predefined reports that require support staff.
Embracing AI-driven insights is a transformative step towards a more data-driven and agile future for businesses.