What It Really Takes to Be Ready for Operational Intelligence, Part 1
100 Days, One Idea, and a New Way to Think About Operational Intelligence Readiness with Rob Bansek and Devon Keane
The demo was flawless. Every chart lined up, every recommendation made sense, and everyone in the room walked out thinking the same thing: this can’t miss. Months later, the pilot has stalled, the team has moved on, and nobody can quite explain what went wrong.
If that sounds familiar, you’re not alone. It’s the same frustration that led Rob Bansek to pick up the phone and call Devon Keane about 100 days ago. “I didn’t have a job. I had an idea,” Rob recalls. That call has since become the new Operational Intelligence practice at the InSource Solutions Group, now led by Devon. In the latest episode of our podcast, the two sit down to talk about why so many operational intelligence (AI) efforts fall short and what organizations can do differently.
Two Paths to the Same Problem
Rob and Devon came at the problem from opposite sides of the table. Rob spent six months asking vendors, customers, consultants, and integrators why new AI tools weren’t delivering. His first thought was that it was a data migration problem: should the data go to the AI tool, or the tool to the data? Then he realized migration was only one piece of a bigger data readiness question. Did people trust the data? Was it high quality? Did it have the right structure and context to be useful? The more conversations he had, the clearer it became that readiness was the problem, but it wasn’t just about data.
Devon had lived it from the inside. Over a career that started in aerospace and defense and led to a manufacturing conglomerate spanning everything from building materials to mining, he watched smart, well-funded teams struggle to turn new technology into real results.
That contrast is what makes the episode worth your time. Rob is the big-picture thinker who has watched the industry go through more than one technology wave. Devon is the product manager who wants to walk the process, talk to the people doing the work, and define what good looks like before anything gets built. One asks the big questions, and the other has the stories to answer them.
We’ve All Fallen for the Shiny Tool
Few people are immune to a great demo, Devon included. “I want to get my hands on them. I want to play with them myself,” he says of new tools. When everything works perfectly together in a demo, it’s easy to believe a tool can’t miss. But wanting a tool isn’t the same as having a problem for it to solve. It’s the classic “hammer looking for a nail.”
This isn’t a new problem, and InSource has seen it before. About 15 years ago, tools for downtime tracking, OEE, and SPC were the shiny new thing. Many manufacturers bought them expecting the software to fix the problem on its own, and not every project got the rigor it needed. “We’re just seeing the next iteration of that shiny tool,” Rob says.
So where should an organization start? With the problem, and with the right people in the room. Devon’s product management background shapes how he approaches it: you have to walk the process with the people who do the work, and understand where their pain is felt, how they make decisions, and what they’re constrained by. Leadership, engineering, operations, quality, and maintenance often see the problem differently. The episode also points to one person who is left out of that conversation far too often, even though they may understand the problem better than anyone in the building. Once you hear who it is, you may start wondering whether they’re in the room at your organization.
Technology Is the Easier Part
It may be surprising to hear from someone leading a new technology practice, but Devon believes that “technology is, more often than not, the easier part in this journey.”
Organizations bring real rigor to a historian or MES implementation, then often rush into AI without the same discipline. The harder part is adoption, governance, and whether an organization is truly ready to solve the problem in front of it. Devon calls this organizational will, and it has become central to how the new practice thinks about readiness.
That idea becomes very real once AI starts making recommendations. As Rob puts it, “These tools are only as good as the data we feed them.” At some point, a suggestion has to reach an operator on the floor. Does that person have the authority to act on it? What happens if the recommendation is wrong? Can the decision be reversed? None of these are data questions. They’re questions about people, process, and who gets to make the call, and they often decide whether a project succeeds.
Are You Ready? The Questions Worth Asking
If there’s one takeaway from the episode, it’s that readiness comes before the tool. Throughout the conversation, Rob and Devon keep returning to the same set of questions, and they’re a good gut check for any organization considering its next operational intelligence initiative.
It starts with the problem statement. What problem are you trying to solve, and is it truly worth solving? What is the value of solving it, and what does good look like? Devon stresses defining success from the very beginning, including the leading indicators that show a project is on track long before the financial results show up.
Then comes the harder question: are you actually ready to solve it? If you’re not, what’s standing in the way? It might be a data problem, a process problem, or an architecture problem. Or it might be an organizational will problem, where the technology works but the people and processes around it aren’t prepared to act on what it tells them.
If you can’t answer those questions with confidence, you’re not alone, and that’s where the real work begins. As Rob puts it, the goal is to make sure that when organizations do invest in the next shiny tool, “they’re getting it for a reason.”
Listen to the Full Episode
Hear Rob and Devon’s full conversation on what it really takes to make operational intelligence work, from the shiny tool to the people who make the final call.