Process Mining is an innovative data analytical approach to uncover and visualize any process in any company in an objective and exhaustive manner.
In traditional Business Intelligence reporting (BI), statistical tools have difficulties in revealing both the big and the very detailed picture of processes, while analyzing both levels of granularity together is the most efficient way to understand the real life situation.
Process Mining provides a visual representation of any process in all its detail and can be made graphically visible, thus focusing attention on details of the overall process.
Process Mining makes it possible for you:
1. To understand how a process is actually executed. Often, business process how and when their processes are supposed to run and who is supposed to do what. However, they usually do not investigate the actual processes as these are executed; what is really happening throughout the process lifecycle. When studying the actual process executions, one might find unknown variances, as well as as rework loops and bottle-necks.
2. Improve the process flow by knowing the actual flows, frequencies, rework loops, bottle-necks and delays in the process. The actual flows can be compared with normative models and external best practices, enabling identification of improvement opportunities.
3. To Benchmark and Harmonize processes in different parts of a company by understanding how people work in different ways to see what the best practices are and to align processes.
4. Compare processes between organizations supporting (pre-merger) Operational Due Diligence or acquisition feasibility.
5. Verify that implemented process changes have had the expected effect by comparing efficiency and effectiveness of old and new process.
6. Improve the quality and increasing the efficiency of auditing and compliance, by objective and full assessment of processes used.
As for all data driven technologies, data preparation plays an important role in realizing full benefit from process mining. This includes creating one or more consistent event logs of process activity.
There are 3 key required components to a Process Mining event log:
The prerequisites are the bare minimum, for more advanced analysis, other data attributes can be added. The most common are relevant elements such as resources, countries, departments, etc., as well as product characteristics and costs. Leveraging such additional data will enable more detailed investigations (territory specificities, products being treated differently depending on their category etc.)
An event log can be thought of as a spreadsheet:
Process mining is a discipline (not just a tool) that requires skills to detect and solve data quality issues, how to interpret the results, but also process experience and awareness and stakeholder management.
Next, the outcome of a technical Process Mining analysis can only reveal candidates for root-cause analysis; the process mining analysis is just a starting point for the discussion with domain experts. When starting with Process Mining one should consider:
Start small, think big:
Choose a (sub-)process where beginning and end are clearly defined. Take your business stakeholders from insight to insight. Stimulate them to ask questions. Explore, analyze and innovate. Time-box the intermediate results and the project. At the same time, keep an eye on the overall (end-to-end) process and value chain, preventing local improvements that could hurt the overall process. Eight weeks for the first project is usually a good aim.
Focus on the business value, set clear goals:
Define the business value in terms of effectiveness (customer experience and/or revenue), efficiency (costs) and risk (reliability). Determine the process aspects you want to focus on.
Make sure to communicate what process mining is not. Those working in the process should not feel threatened, as the Process Mining exercise should not be focused on people, but solely on the processes that are executed. By indicating clear boundaries, you can manage expectations and mitigate resistance.
Facts don’t lie, but don’t forget a sanity check:
Process mining allows you to analyze processes based on facts instead of subjective opinions. Speak openly and transparently about the data that you use and about the facts that come out of this analysis. Always use experts from the business process domain and the IT-domain for a sanity check of the data and the analysis. Use process mining as a constructive starting point to ask the right questions and avoid rushed judgments.
Obviously, there is a lot more to tell about this. Send us an email or give us a call if you want to know more about process mining and how it works in practice
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