Martin Beringer
After more than two decades in my career, I often reflect on how profoundly different my early professional life might have been if I had access to the technology we take for granted today. Before transitioning into the tech world as a serial entrepreneur leading innovative startups, I spent over ten years in food manufacturing, dedicating much of that time to driving continuous improvement as a Six Sigma Black Belt, immersed in the challenges and intricacies of process optimization.
Several of the companies I worked for were in the midst of implementing ERP systems, transitioning from outdated legacy platforms, and the seemingly endless maze of spreadsheets. While these systems resolved many manufacturing challenges—such as accurately capturing costs in real-time—they also introduced new hurdles. Often, the people implementing these systems couldn’t fully anticipate the long-term consequences of their decisions.
For instance, at one company, all product manufacturing specifications were entered into the long text field of SAP production orders. As anyone familiar with ERP systems knows, unstructured data like this doesn’t lend itself well to retrieving precise equipment setting variables. This became a significant barrier when we started implementing Statistical Process Control (SPC) to monitor real-time performance data. To gain meaningful insights into process capability, we needed a structured database for specification limits.
What ensued was a year-long project to create a custom ABAP program to house these specifications in a structured format. Once the database was set up, we began the laborious task of manually extracting data from unstructured specification sheets and entering it piece by piece. The payoff was worth it: we gained remarkable visibility into real-time process performance and could statistically benchmark it against specification limits. However, looking back, I can’t help but think how much easier that year would have been with access to generative AI.
Recently, we worked on an AI-driven data transformation project, helping a customer convert over 1,000 job descriptions in Word format into a structured data format for import into SuccessFactors. The parallels were striking: the same challenge of turning unstructured data into actionable insights, but this time, AI saved countless hours of manual effort.
Information technology has always been here to help us solve problems, but sometimes, it also creates new ones along the way. Take, for example, the advent of PDF forms. These forms were designed to collect information, only for that data to be often tucked away in file storage, rarely revisited or utilized. Similarly, business analytics tools have provided us with dashboards and elegant reports for over a decade, offering remarkable insights into metrics like “How much am I spending on maintenance for this production line?”
But there’s a glaring gap: the “why” behind the “how much.” In systems like SAP, unstructured data in long text fields of notifications and work orders remains a black hole, making it nearly impossible to discern underlying causes. Critical questions often remain unanswered because we’ve created so much data that we now require AI to decode all of it.
The sheer volume and complexity of modern data have brought us to a tipping point—one where AI isn’t just a nice-to-have but a necessity for uncovering patterns and trends that would otherwise remain hidden. Dashboards and reports are useful, but the future belongs to conversational business analytics, where insights are unlocked in real time and drive actionable decision-making.
We’ve arrived at another inflection point— one where those who “crack the AI nut” first will accelerate their improvement at a pace that leaves the fence-sitters behind. While some may hesitate, watching from the sidelines out of fear or analysis paralysis, waiting is no longer a viable strategy in the age of AI disruption.
For process improvement professionals, the message is clear: pivot toward AI now or risk being outpaced. The critical question isn’t whether AI will transform your industry—it’s how you’ll harness its power to solve problems in innovative ways. If you don’t ask these questions and take action, rest assured, someone else will—and they’ll leave you playing catch-up.
If you’re ready to get ahead of the curve, we invite you to schedule an introductory meeting and demo with us. During this session, we’ll showcase real-world examples of how we’ve helped organizations like yours achieve success with AI-driven solutions. It’s just an hour of your time—and with so much to gain, there’s truly nothing to lose.