PEX Network’s key takeaways:
- Fraser Damoff from Independent Electricity System Operator (IESO) explains why process discipline, standardization, and continuous improvement must come before artificial intelligence (AI).
- Robotic process automation (RPA) and strong business process management (BPM) aren’t outdated stepping stones – they’re the critical foundation that makes any advanced technology worth deploying.
- Leaders must rethink ‘technology-led’ change and refocus on what truly drives long-term value: clear problems, stable processes, and an unwavering commitment to excellence.
At a time when AI dominates the business transformation conversation, it’s easy for organizations to chase the newest technology without first asking whether their processes are ready for it. Fraser Damoff offers a grounded, refreshingly practical perspective on why that approach so often backfires.
Drawing from his experience as supervisor, continuous improvement and head of the Lean center of excellence at IESO, Damoff argues that RPA and strong BPM aren’t outdated stepping stones – they’re the critical foundation that makes any advanced technology worth deploying in the first place.
In this interview, Damoff unpacks why process discipline, standardization, and continuous improvement must come before AI if organizations want sustainable results. Using vivid metaphors – from broken shopping carts with jet engines to golf courses with drainage issues – he explains how skipping the fundamentals can magnify inefficiencies, erode trust, and stall transformation efforts.
His insights challenge leaders to rethink ‘technology-led’ change and refocus on what truly drives long-term value: clear problems, stable processes, and an unwavering commitment to excellence.
You can hear more from Damoff when he speaks at All Access: Future of BPM 2026!
PEX Network: You’ve described RPA as the foundation of effective BPM. What makes it uniquely suited for that role compared to newer technologies?
Unlike emerging AI tools, which often depend on probabilistic outputs and large volumes of data, RPA thrives in rule based, repeatable workflows – precisely the areas where process discipline is first developed.
At IESO’s Lean center of excellence, we see RPA as a catalyst for building that foundational discipline. When a team documents workflows, eliminates waste, and defines clear decision rules, they gain the clarity necessary to automate responsibly. Newer technologies can accelerate performance, but without RPA-level structure, they often magnify underlying chaos rather than resolve it.
PEX Network: Why are organizations so eager to leap to AI before mastering basic process management and automation?
FD: AI can play a huge role in BPM, but we are setting ourselves and our clients up for failure if we don’t put our Kaizen hat on when it comes to AI implementations. My team and I always use the example of a golf course with drainage issues as great symbolism for AI.
In our golf course example, implementing AI supports into our golf course operations would be like installing automated sprinklers throughout the course to save time watering the grass. If we have an underlying drainage issue, then our fancy new sprinkler system isn’t really solving a true challenge. In fact, it is creating more work for us and making our true root-cause even worse.
I think many organizations are drawn to AI because it’s positioned as a shortcut or way to bypass slow, methodical process improvement work. The pressure to ‘keep up’ with digital trends is very real and AI carries a futuristic appeal that RPA or BPM might not.
At IESO’s Lean center of excellence, we consistently emphasize that strong foundations deliver the best long-term ROI. Without standardized processes and quality data, the value of AI is greatly diminished.
PEX Network: What typically happens when organizations layer AI on top of poorly designed or undocumented processes?
FD: AI layered on top of poor processes is like building a beautiful new house on a crumbling and cracked foundation. It can make existing inefficiencies even worse, it can increase operational risk, and worst of all it can create adoption fatigue where our clients lose trust in the overall business transformation journey.
It can make inefficiencies worse, increase risk, and send teams rushing into AI just because everyone else is. As process folks, we know what happens when you add new tech on top of hidden factories and silos – it’s like putting a jet engine on a broken shopping cart. It won’t solve any problems, it’ll just multiply them.
PEX Network: At what point in the BPM and automation journey does AI truly start to make sense?
FD: In my mind, AI is a natural third step in our continuous improvement business transformation journey. The key requirements we need to see are:
- A strong, repeatable process.
- Good quality data.
- Evidence of a highly successful RPA workflow.
AI becomes a force multiplier only when the first phases are strong.
PEX Network: What does ‘process discipline’ actually look like day-to-day in a mature BPM organization?
FD: In IESO’s Lean center of excellence, we take a bit of a different approach to ‘process discipline’ by focusing on our ‘commitment to excellence.’ As a big basketball fan, the quote from Michael Jordan is something our team tries to live by every day:
“Excellence isn’t a one-week or one-year ideal. It’s a constant. There will always be days where you don’t feel on top of your game, or meetings in which you aren’t at your best, but your commitment remains.”
For our work, our commitment to excellence looks like small, continuous, and data-driven improvements, whether that be in traditional process improvements or enhancements made to our RPA workflows.
Our goal is always to have processes that can run successfully, regardless of the process operator. What mindset shift do executives need to make to move away from ‘technology-led’ transformation toward ‘process-led’ transformation?
PEX Network: What mindset shift do executives need to make to move away from ‘technology-led’ to ‘process-led’ transformation?
FD: A conversation that my colleagues and I have all the time is how important it is to focus on problem solving and not on ‘this new tool can do X, Y, and Z.’ Looking for problems to solve should always be at the core of our business transformation work, not shopping for new tools.
One of the best leaders that I ever worked with always said that technology can accelerate a good process but it doesn’t fix a broken one. RPA and AI implementations are really just outcomes of mature, and stable processes.