How can organizations accurately measure and manage process complexity across different operational levels?

Host: Welcome to A.I.S. Insights — powered by Living Knowledge. I'm Anna Ivy Summers, and today we are tackling an issue that every single enterprise faces: process complexity. We're diving into an eye-opening study titled "The Many Faces of Process Complexity," which investigates how organizations conceptualize, measure, and actually manage the complexity of their business workflows. Joining me today to break it all down is our analyst, Alex Ian Sutherland. Welcome, Alex!

Expert: Thanks, Anna. Great to be here. This study really addresses a massive blind spot that executives and IT leaders grapple with every day when trying to streamline their organizations.

Host: Exactly. We always hear leaders say, "Our processes are too complex, we need to simplify them." But as this study points out, people use the phrase "process complexity" to mean completely different things. Why is that such a problem in practice?

Expert: Well, Anna, the fundamental issue is what researchers call the jingle-jangle problem. Different disciplines and managers use the exact same word, "complexity," to describe entirely different phenomena, or different terms like "variety" and "entropy" to describe the same thing. For example, if you implement a new ERP system, you might reduce the number of overall process variants across the company, which looks like you simplified the process at the macro level. But for the individual employee executing an order, that same system might add five new verification steps and extra data fields, making each sequence far more complicated. Depending on which ruler you pick, you could conclude your digital transformation either cut complexity or blew it wide open.

Host: That explains why so many digital transformation initiatives produce baffling results on the ground! So how did the authors tackle this messy landscape in their study?

Expert: The authors conducted a scoping review across three major domains: Information Systems, Organization Science, and Computer Science. They analyzed 58 core studies to uncover how complexity has actually been measured. Then, they synthesized all these scattered approaches into a unified mathematical notation built on three basic tiers: actions, sequences of actions, and entire processes. By translating everything into one shared language, they identified 21 distinct operationalizations of process complexity and mapped them cleanly across six levels of analysis.

Host: Six levels? Take us through how those levels break down.

Expert: Think of it as zooming in with a camera lens. At the highest level, you have the overall process level, looking at metrics like total event log size or the number of unique end-to-end paths. Zoom in one step, and you have between-sequence complexity, comparing how different two entire customer journeys or workflows are from one another. Step closer, and you get sequence-level complexity, measuring the internal variety, order variation, or entropy within a single execution. Zoom in further, and you find partial pattern complexity, which detects recurring multi-step routines, followed by action pair complexity, looking at two-step transitions and branching paths in a process network. Finally, at the closest zoom, you have single action complexity, looking at the internal configuration of an individual action—such as the digital tools, roles, and data inputs required to perform it.

Host: That makes total intuitive sense. It really shows that complexity isn't a single number on a dashboard. But the study also makes a crucial distinction between "complicated" and "complex." What’s the difference there?

Expert: That distinction is a game changer for leadership. "Complicatedness" refers to systems with many moving parts, but where the rules are linear, stable, and predictable—like a precision mechanical watch or a rigid, multi-step compliance checklist. It takes effort to analyze, but it is knowable. True "complexity," on the other hand, involves dynamic, non-linear interactions where people adapt, find workarounds, and respond to uncertainty in real time. Many tools that claim to measure process complexity are really just measuring complicatedness, like counting the sheer volume of tasks, while missing the emergent human adaptations happening beneath the surface.

Host: And that brings us to what I found most fascinating in the study: these multi-level trade-offs and transfer mechanisms. Complexity doesn't just vanish when you try to eliminate it, does it?

Expert: Exactly, Anna. It often just moves. If corporate management strictly standardizes a process at the sequence level to boost efficiency, frontline employees might find the rigid system impossible to use when unexpected customer edge cases arise. To get the job done, employees start inventing workarounds, juggling multiple spreadsheets, or making ad-hoc phone calls. You reduced sequence-level complexity on paper, but you dramatically increased single-action cognitive load and hidden operational friction. It’s like squeezing a balloon: if you press down on one end, it bulges out on the other.

Host: So how should business leaders apply the insights from this study to make better decisions?

Expert: First, stop treating complexity as an inherently bad thing. Following Ashby's Law of Requisite Variety, your internal process flexibility needs to match the complexity of the environment you operate in. If you run a nuclear plant or payroll, you want low variety, tight standardization, and minimal sequence complexity. But if you run an innovation lab, a creative design agency, or an agile software team, high process variety and dynamic action repertoires are what enable problem-solving and resilience. Second, leaders should use this study's framework as a toolkit: pick the specific metric that matches your actual goal. Use process-level metrics for high-level governance and KPIs, sequence and between-sequence metrics to detect standardization versus flexibility, and action-level metrics to ensure your tools and interfaces aren't overwhelming your staff.

Host: A brilliant perspective that turns complexity from a vague corporate buzzword into an actionable strategic lever. Alex, thank you so much for breaking down this foundational study for us today.

Expert: My pleasure, Anna.

Host: And thank you to all our listeners for tuning in to A.I.S. Insights — powered by Living Knowledge. Be sure to subscribe, and join us next time as we unpack the research shaping tomorrow's business and technology landscape. Until then, stay curious.