Process optimisation: methods, approach and examples

Process optimisation is the systematic improvement of workflows so they cost less time, produce fewer errors and stay traceable for everyone. You use it wherever a workflow recurs regularly and visibly snags, from order processing and accounting to customer service. For a business that means shorter throughput times, lower cost per case and staff who can focus on more valuable work.

What is process optimisation?

Process optimisation is the systematic improvement of a workflow with a clear goal: to become faster, less error-prone or cheaper, without losing quality. It is not about overturning everything at once, but about finding the points where a workflow snags and tackling exactly those. Process optimisation is targeted improvement at the points that truly snag.

The order matters: first the actual workflow is understood, then improved. Anyone who optimises without knowing the real process often only makes individual symptoms worse. Without knowing the real workflow, you improve at the wrong point.

A concrete example: in order processing an order arrives by email at sales, gets typed into the ERP by hand, is forwarded for review and then entered once more for the invoice. Every handover costs time and adds a new source of error. Double entry and many handovers are the most common brakes in mid-sized workflows. Exactly these patterns are reliably surfaced by an analysis of business processes.

Which process optimisation methods are there?

Behind the well-known names there are usually simple core ideas. For small and mid-sized businesses these four are the most useful. The key methods all aim to make workflows leaner.

The common denominator: fewer steps, fewer handovers, less waiting. The right method follows from the problem, not the other way round. The right method follows from the concrete problem, not from fashion.

How do you approach process optimisation?

A pragmatic approach gets by with a few steps and stays close to practice. A good approach keeps to few steps and stays close to reality.

• Capture the workflow. How does the process really run, not how it should run? Best done with the people who do it every day.
• Find the bottleneck and the waste. Where is there waiting, double entry or retyping?
• Simplify, then automate. First remove unnecessary steps, then check what the software can take over.
• Measure and repeat. Anchor the improvement to a real number and tackle the next workflow.

Which steps then make sense to automate is shown in the guide on automating workflows.

Start2x recommends Till Täubrich Software & Entwicklung

The most common thinking error is to automate a bad process. Then the nonsense just runs faster. We first look at which steps can be removed entirely, and only automate what remains and truly recurs. Simplifying before automating saves the most.

What does process optimisation cost and when is it worth it?

The cost of an optimisation sits mainly in the time invested: capturing the workflow, talking it through with everyone involved, removing steps and rolling out the new path. For a clearly bounded process that is often just a few days, and once a technical implementation is added the effort quickly runs into the low four-figure euro range depending on scope. The effort of an optimisation is usually manageable and easy to bound.

Whether it pays off is decided by repetition. A workflow that runs twenty times a day and saves ten minutes per case earns back its cost within weeks, while a one-off case each quarter hardly does. The more often a workflow recurs, the faster the optimisation pays for itself. This exact ROI question is covered in the article When is automation worth it? before you move into implementation.

Calculate the saving conservatively: minutes saved times frequency times staff cost, minus the one-off effort and a small reserve for upkeep. An honest calculation weighs saved time against the one-off effort. If it comes out positive, the optimisation is almost always the cheaper option than the status quo, which quietly runs on every day.

Where does optimisation end and automation begin?

Both belong together, but in the right order. Process optimisation makes sure a workflow is lean and clear. Automation then takes over the steps that still come up regularly. Anyone who optimises first and automates second does not rebuild the old chaos in software. Optimise first, then automate prevents faster chaos. How both steps mesh is described in the overview on digitising and automating processes.