How we reduced operational exceptions by 42% in six months

The hidden cost of exceptions

Every organization has exceptions to its processes. A client who needs a different format. A supplier who delivers outside of hours. An order that doesn’t fit the standard flow. Exceptions are inevitable. What isn’t inevitable is letting them grow unchecked until they consume more resources than standard processes.

In our experience with abemonFLOW clients, the average exception rate before implementation ranges between 25% and 45% of operational volume. That means between a quarter and nearly half of all work an organization processes doesn’t follow the designed process. It’s managed with workarounds, manual interventions, “special case” emails, and ad hoc decisions.

The cost is threefold: time (exceptions take 3-5x longer to process), errors (without a standard process, the error rate multiplies), and opacity (exceptions aren’t measured, aren’t reported, and aren’t improved).

The diagnostic: measuring the invisible

The first step was making the invisible visible. Before abemonFLOW implementation, the client didn’t measure their exceptions. Not because they didn’t want to, but because they had no way to do it. Processes were executed across a combination of ERP, spreadsheets, emails, and verbal conversations. Nobody had a complete picture.

We implemented a simple classification system that tagged each unit of work as “standard process” or “exception,” with a subcategory identifying the exception type. In the first four weeks of measurement, data revealed that 38% of operational volume was managed outside the standard process.

The most frequent exception types:

• Incomplete data (34%): The flow was interrupted because information was missing that should have been provided by another department or the client
• Undocumented rules (28%): Special agreements with clients that existed only in specific people’s heads
• Broken handoffs (22%): Work got “stuck” between departments due to lack of notification or protocol
• Input errors (16%): Incorrectly entered data generating cascades of manual corrections

The intervention: three levers

With a clear diagnostic, the intervention focused on three levers:

Lever 1 - Input data standardization. 34% of exceptions came from incomplete data. We implemented validations at the entry point that don’t allow a flow to advance without the mandatory fields complete. It’s not a longer form. It’s a smart form that asks only for what’s needed based on the operation type, but doesn’t let anything through without it.

Lever 2 - Executable documentation of business rules. 28% of exceptions existed because rules were in people’s heads. We extracted those rules, encoded them in the orchestration engine, and turned them into automatic decisions. The system now automatically applies the 5% discount for client X without anyone needing to remember or request it.

Lever 3 - Handoff automation. 22% of exceptions occurred at department boundaries. We implemented automatic handoffs with notifications, SLAs, and escalation. When department A completes their part, department B automatically receives the task with all necessary information. If they don’t act within the defined timeframe, it escalates.

Results at six months

The exception rate went from 38% to 22%. A 42% reduction. The remaining 22% corresponds to genuine exceptions: truly unique cases that require human judgment. Those can’t and shouldn’t be eliminated.

The impact on productivity was immediate. The operations team processed 28% more volume with the same number of people. Not because they worked more hours, but because they stopped losing time on workarounds.

Errors decreased by 55%. Without incomplete data, memory-based rules, and lost handoffs, the most common sources of error disappeared.

Key lesson

Operational exceptions are not a people problem. They’re a system problem. When the system lacks clear rules, adequate validations, and automatic flows, people invent workarounds. The solution isn’t asking people to follow the process. The solution is designing a system where following the process is easier than not following it.