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One further alternative would be to use the two approaches together, and combine the advantages of both.
For example, you could use process modelling techniques to build momentum, involve stakeholders, and identify the main bottlenecks. You could then verify this against the analysis from process mining to complete the picture, establish priorities, and set baselines to measure your improvement. From here, you could go a step further and use process simulation to see how the improved process would perform. The three aspects might work together as follows:
Process simulation: How would this work in practice?
Closing the loop in this way helps to rule out one of the potential pitfalls of process improvement: causing unintended side effects elsewhere. It’s important that the picture includes the entire process from end to end, seeing how the proposed improvements to various sub-processes work in relation to each other. There are other possible pitfalls that, handled well, can become success factors as you improve your process.
First, there is a danger of expecting process mining tools to automatically deliver insights by themselves. In fact, the information needs to be examined carefully to see what business value it offers – whether it’s improving efficiency and effectiveness, or reducing risk. It’s also important to choose improvements carefully, to build momentum within your organisation. Based on the data alone, you could be tempted to change the primary process – when in fact you might achieve success faster by working on a process with a defined beginning and end, and clear workflow support.
Another temptation is to try and answer every question at once. Your initial analysis will often raise further questions, so it’s important to separate the issues clearly based on the business value you want to achieve, and tackle them individually. One good way to address this is to propose a hypothesis for each question you want to answer, and use process mining to prove or disprove them in turn. Remember, however, to let the facts speak for themselves; don’t fall into the trap of trying to justify a subjective opinion.
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