Organizations are typically managed through functions and departments. The work that produces an outcome for the customer or the organization, however, rarely begins and ends inside one department.
Customer onboarding may involve sales, operations, risk and IT. A purchasing request may move through the business, procurement, finance and suppliers. An IT request may cross several support teams.
Process management looks at this work from start to finish.
Why does end-to-end thinking matter?
Every team in a process can meet its own KPI while the overall process still performs poorly.
Three teams may each complete their own work in one hour. But if the case waits two days between teams, the customer still experiences a slow process.
This is why it matters to look not only at the performance of individual activities, but also at the flow between them.
Efficient departments do not automatically create an efficient end-to-end process.
What does lean thinking question?
Lean is not simply a cost-reduction method.
The core question is whether an activity creates necessary value.
Common sources of waste in processes include:
- Waiting
- Rework
- Unnecessary approvals
- Unnecessary handoffs
- Manual data transfer
- Excessive controls
- Errors and correction
- Unnecessary process variants
The objective here is not to remove every control or step.
Some controls are necessary because of risk, quality or regulation.
Lean thinking tries to separate what is necessary from what is not.
Why do processes become complex over time?
Most processes were not designed to be as complex as they eventually become.
An audit finding adds a control. A new product adds another approval. A new system introduces another step into the existing workflow. An exception creates an alternative path.
Each addition may have made sense at the time.
But over the years, as these accumulate, the process can end up with more steps, systems, approvals, manual intervention and exceptions than it started with.
Process management therefore includes reviewing accumulated complexity on a regular basis, not just designing new processes.
Simplify before automating
Process automation is a powerful tool, but it may not create the expected value when applied to the wrong process.
Digitizing all eight approvals in an eight-approval process can speed it up. But if four of those approvals are genuinely unnecessary, the better approach is to simplify the process first.
A practical sequence is:
Understand → Question → Simplify → Standardize → Automate → Measure
Doing unnecessary work faster does not remove the unnecessary work.
How should performance be considered?
A single KPI is often not enough.
A process should be viewed across several dimensions together:
- Time
- Quality
- Cost and effort
- Customer outcome
- Conformance and control
Reducing lead time while increasing errors, for example, is not a real improvement.
What role do Process Mining and Task Mining play?
Process owners' experience and process models matter.
Process mining can complement that view with system evidence.
Task mining can expose manual work that does not appear fully in event logs.
This can make simplification decisions rest not only on workshop outcomes, but also on actual process and task behavior.
Continuous improvement
Processes are not static.
As customer expectations, products, organizational structures, regulation and technology change, even a well-designed process needs to be reassessed over time.
Process management is therefore better treated as an ongoing discipline of measurement and improvement than as a one-time project.
← All articles