Power BI is a common business intelligence tool which enables organizations to explore their external and internal data to optimize strategies, improve customer experience and save costs. Process mining can serve as an alternative to business intelligence tools since it extracts and analyzes real-time process data to identify performance issues, root-causes, noncompliant cases, and automation opportunities. Yet, business leaders can leverage a higher volume of data and create interpretable visuals to obtain more insights and improve data-driven decision-making by combining these two tools.
1. Enhance Power BI infrastructure with PM
Power BI has difficulty working with a complex data structure because users may fail to refresh the dashboards and reports based on the larger datasets they imported. Thus, Power BI cannot automatically extract real-time data, which is why it can only offer static process models.
Process mining can disentangle this problem by seamlessly collecting and analyzing such complex and large datasets from the company’s IT systems. Users can discover the process models, create dynamic graphs, and obtain performance metrics with process mining.
Integrating Power BI with process mining allows BI analysts to advance their process analysis while saving the time dedicated to data cleaning.
2. Enrich process mining visuals with Power BI
Process mining users can model their processes with diagrams and workflow maps and zoom into the areas that require further improvement. However, these models are not always straightforward and intuitive for users.
Power BI can help process mining to generate interpretable maps and easy to understand visuals such as stacked bars or slicers. Power BI users can visualize and customize their data and company metrics to create captivating real-time reports and dashboards. They can also schedule reports in different formats with multiple recipients.
Such dashboards can be useful to:
- track performance,
- revise budgets,
- Make predictions,
- Improve decision-making
3. Generate data-driven strategies
Power BI requires a certain knowledge of processes and continuous interpretation. For instance, Power BI indicates the KPIs that do not perform well, but it cannot deliver root causes or make suggestions. Therefore, business intelligence analysts should decide the reason behind the issues and develop strategies to reduce these inefficiencies.
Process mining points out the stages where bottlenecks occur along with potential root causes. For example, process mining can help BI analysts detect the delays in your approval processes due to manual request submissions. Consequently, BI analysts do not need to interview anyone or rely on their guts while interpreting the insights they obtained and implementing data-driven strategies and action plans.
4. Improve efficiencies for a streamlined workflow
Power BI offers a higher level of understanding of process performance, which is why it cannot hint if the process does not comply with standards and rules.
On the other hand, process mining can allow analysts to focus on a specific activity or task to identify performance issues and their root cause with conformance checks. By digging into every single case, process mining allows users to detect performance issues that are not easy to uncover at first.
By combining Power BI and process mining, analysts can monitor their process performance KPIs at a higher level and dive into details in the process analysis with process mining to streamline an efficient workflow.
5. Implement RPA and workflow automation
Power BI cannot inform analysts of the root causes of process inefficiencies, so analysts who only leverage Power BI will miss automation opportunities.
Automation discovery is one of the top 5 use cases for process mining since process mining software can point out the manual activities that lead to higher costs and time for the company and lower customer experience.
Thus, process mining facilitates the implementation of process automation by
- calculating the ROI,
- identifying deviations in RPA projects,
- And predicting failure points that can be improved in these projects.
For example, Piraeus Bank solved the problems in its automation project and shortened its loan application process from 35 minutes to 5 minutes by employing process mining.
Explore other applications and IT systems that process mining can improve:
If you need help to choose a vendor, start reviewing our data-driven comprehensive vendor list for process mining.
Check out comprehensive and constantly updated list of process mining case studies to find out more process mining PowerBI real-life examples.
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