Business Process Audit: Why More Companies Are Asking for One — and Where to Start

Over the past few months, several companies have approached us with requests for business process audits. And honestly, it feels like a very understandable signal of the moment we are in.

First, almost every economy today is experiencing growing pressure around efficiency. When businesses need to understand where resources are being lost, why execution speed is lower than expected, why teams are overloaded, and why results are no longer proportional to effort — business processes naturally become one of the key areas of focus.

Second, the world is changing too quickly. And here we increasingly see two common scenarios.

• The first: a company grew fast, launched new products, teams, and workflows “on the go.” Over time, a significant amount of operational chaos accumulates: duplicated functions, misaligned processes, complex coordination, excessive communication layers, and too many approval loops. Eventually, all of this starts slowing down the very business that once benefited from speed and flexibility.

• The second scenario is almost the opposite: a company has been operating for a long time, and the accumulated layer of legacy processes no longer matches current reality. Customers have changed. Partners have changed. Market speed has changed. Team structures, tools, channels, and expectations around efficiency have changed as well.

And then there is the third major driver: AI. On one hand, AI can genuinely simplify, accelerate, or even redesign many workflows — especially in sales, marketing, product management, analytics, recruiting, operations, and internal communication.

But an even more important shift is happening beneath the surface: technology is beginning to change the very possibility of certain processes existing in their previous form.

For example, in one of our current projects, redesigning the company’s customer data workflow is effectively removing one of the most painful operational blocks in terms of organizational complexity and human effort — with the potential optimization of 1,200+ human-hours per year.

And this is a fundamental shift. AI is increasingly changing not just the speed of existing processes, but the economics of coordination, information transfer, and decision-making inside organizations. At the same time, there is also a separate factor: FOMO. When everyone around is talking about AI, companies start feeling pressure: “We need to implement something as well.” One of the roles of a proper process audit today is to separate real value opportunities from chaotic attempts to “do AI for the sake of AI.”

That is why our approach never starts with technology. Technology is secondary. Business comes first.

We start by understanding the company’s strategy: where the business is heading, what its ambitions are, how the business model works, where the constraints and growth opportunities are, and which changes actually make sense in the current context.

Separately, we look at the company’s value creation flow — the path through which value moves from the very first customer signal, request, or interaction to the final outcome delivered to the customer. Where delays happen. Where duplication appears. Where approvals become excessive. Where information gets lost. Where teams become overloaded. Or where the system gradually starts serving itself instead of serving customers and business outcomes.

Then we analyze the objective side of operations: metrics, interaction structures, bottlenecks, decision-making speed, operational dependencies, and areas where efficiency is being lost.

And separately, we look at the subjective side: how people inside the organization actually perceive the system they work within. Because leadership teams and operational teams almost always have a very accurate internal understanding of where processes are already breaking down, where coordination is weak, where logic conflicts appear, or where overload and inefficiency are accumulating.

Usually, it is precisely at the intersection of strategy, value flow, operational reality, and people’s lived experience that the few truly important transformation points emerge — whether through simplification, process redesign, operating model changes, or the implementation of technologies, including AI.