Optimising the benefits of process mining

Companies of all types and sizes are increasingly turning to process mining to streamline core business operations, improve service delivery, and boost agility. However, successful implementation is not without its challenges. Dan French, CEO of Consider Solutions, highlights five common pitfalls and offers proven strategies to overcome them.

Process mining or technically ‘mining for data about process execution’ is an increasingly relevant tool for executives and process owners. It can provide effective support to process excellence, transformation and business change initiatives by exposing an understanding of the business reality – the real journeys beneath the end-to-end process.

Process mining detects bottlenecks, defects and variations in processes, developing factual understanding and identifying communications issues and training needs. It facilitates activities, projects and continuous improvement initiatives that streamline processes, improve customer satisfaction, reduce cost, improve KPI measures and generate better data quality.

However, there can be significant challenges in implementing process mining. Here are five process mining pitfalls to potentially be wary of – but also the best strategies to successfully address them:

1) Expectations and Received Wisdom

Process mining is more complex than it appears, requiring real business input and consideration – and not just about applying the technology but interpreting the outcomes. Here’s the reality check, as it needs an understanding of both the process and the IT system to extract the right data. It also takes multiple iterations to produce meaningful and correct results.

Don’t start the How before the Why, What and Who are agreed and engage process specific stakeholders before you invest and start – they will collectively make the value delivery happen. Consequently, it also needs to be managed with EQ (emotional intelligence) as well as IQ. Also communicate every step of the way and set realistic timelines for achieving business value.

2) Business Process Understanding

First stop and think about why you are doing process mining (e.g. output or cost ratio improvement), for whom (finance, functional lead, service, business process owner) and what (scope or manual/automated elements)?

Otherwise, you run the risk of getting a very shiny technical solution that does not deliver actionable results; a never-ending project that doesn’t cover the end-to-end processes, plus missed opportunities and dissatisfied stakeholders questioning investment and resources.

Process mining doesn’t necessarily give us process understanding, so take a more holistic view of what good looks like, what stakeholders believe a good outcome is, what this end-to-end process looks like and the journeys involved. Then map it all out as that will enable you to validate the data generated from process mining. It’s about combining people, process and data with the process mining technology to give a much better chance of success.

3) Performance versus Defects

KPIs mean different things to different people and can therefore conflict and skew business reality. Process defects – and how they can decrease productivity and confidence, increase dissatisfaction and influence non-productive outcomes – are a critical element of enhancing performance. There’s the risk of an isolated and blinkered view when relying simply on output indicators.

Rather, concentrate the process mining on exposing leading defects rather than what’s already good, because defect detection is the fuel for continuous improvement and reveals the barriers to, and opportunities for, longer-term positive results. This will also inform you how to navigate and where to make positive changes.

4) Hidden Meaning in Data

Data is everywhere and there are masses of it, but a common vacuum still exists between data expertise on the one hand and business expertise on the other. Different stakeholders view data from different perspectives and with different vocabularies, so you need data translators as well as analysts.

Only insight in data usage will give you the capability to change and optimise the process output. It is all-too-common for a process mining initiative to indicate massive cost saving opportunities, which later disappoint as awareness of ‘false positives’ increase.

Be sure to make deep business process and deep data thinking an integral part of your team and combine and augment it with technical data analysis and process mining expertise. Take a data lifecycle approach to understand the origins, what changes and the meaning of all the data. There will also be data quality gaps, but this synergistic approach will help interpret any deficiencies and prepare you on how to deal with them.

5) Time to Value and Opportunity Cost

Be patient and realistic because more often than not it takes longer to deliver process mining value than expected. Proof of concept projects tend to start with a specific focus, to generate data to see what can be done, but in doing so we miss some of the key process elements already highlighted that accelerate change and incremental value via a clear vision and accurate roadmap.

Everything else falls under time-to-value, so determine smarter process mining options that drive 80% of the value with 20% or less of the cost effort and cycle time – the Pareto Principle. But that’s not just about producing the process mining deliverable, it’s delivering the business outcome value of the process change that depends on it. This will also help sustain improvements by creating a new norm.

Conclusion

In summary, process mining technology alone is the least of your priorities in driving process excellence and financial improvements. Overarching leadership, stakeholder management and execution skills are the mission critical components in being able to clarify the why, map out the what, determining the whom, managing their time and effort, plus delivering the desired business outcomes and value.

Keep in mind that the ‘how’ is much bigger than the process mining technology itself.

About the author: Dan French is the Founder and CEO of Consider Solutions, a consultancy firm specialised in process excellence. He leads a team located in UK, the US, Europe and Asia.