Solution ideas usually appear quickly in process improvement work.
“Let's automate this step.”
“Let's remove an approval.”
“Let's implement a new system.”
“Let's add more capacity.”
Any of these may be the right answer. But unless the underlying problem is clear, they may not create a real improvement in the process.
Define the problem first
The first question should not be “what should we do?” but “what are we actually trying to fix?”
For example:
- Is the process taking too long?
- Is waiting high?
- Are errors or rework excessive?
- Is manual effort high?
- Is the customer experience poor?
- Is SLA being missed?
- Is there a conformance risk?
- Are too many variants occurring?
Each of these questions requires a different analysis and a different solution.
Process improvement starts with defining the problem clearly enough, not with selecting a solution.
Choose the right process
Trying to improve every process at the same time is not realistic.
Good starting candidates often have:
- High transaction volume
- Long completion time
- Significant manual work
- Rework and returns
- Multiple teams or systems
- Measurable customer or cost impact
- Sufficient data
But choosing only the “most problematic” process is not always right either. There needs to be a realistic ability to act on the findings once the analysis is complete.
Understand the current state
It is worth not relying on a single source.
Interviews with process owners, existing process models, procedures, KPIs and reports, system data, process mining and task mining can all be used together.
What people know about a process and what the systems show as actual behavior complement each other.
Separate symptoms from root causes
Finding the slowest step in a process is not the same as root cause analysis.
An approval stage may show a three-day wait, and the problem may look like the approving team.
But the real cause could be missing documentation, incorrect routing, bad data created earlier or an unnecessary approval rule.
The place where a problem is most visible is not necessarily where the problem originates.
Simplify the process
Improvement does not always require a technology investment.
Sometimes the most effective change is to:
- remove an unnecessary step,
- combine two controls,
- clarify responsibility,
- run work in parallel,
- reduce unnecessary handoffs.
Technology tends to create more value on top of a process that has already been simplified.
Evaluate improvement scenarios
In more complex processes, it is useful to evaluate the potential effect of a change before implementing it.
Simulation or what-if analysis can model how total process performance might change if:
- an approval is removed,
- resource capacity is increased,
- two steps are run in parallel,
- certain work is automated.
Measure the result
After an improvement is implemented, the same indicators should be measured again.
Time, waiting, rework, effort, SLA and customer outcome show whether the change actually worked.
Process improvement does not need to begin with a large transformation program. A measurable improvement in one well-chosen process can be a solid foundation for broader work.
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