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Process Mining Tableau: 3 Reasons to Leverage them Together in '24

Process Mining Tableau: 3 Reasons to Leverage them Together in '24Process Mining Tableau: 3 Reasons to Leverage them Together in '24

Although it is a preferred tool, it experiences certain difficulties in incorporating operational aspects of the business, which can be easily solved by using process mining tableau. But keep in mind that using process mining alone also means that Tableau users might miss interactive and personalized dashboards. 

Tableau overcomes this predicament and allows business users to have the best of two worlds by having  a process mining extension. In this article, we’ll see three ways Tableau and process mining advance each other for business leaders and analysts to accelerate their organization!

1. Include process data in your analytics

Tableau can gather data from Excel, SQL databases and cloud-based applications, such as Salesforce, with one click. By bringing various data sources into the analysis, Tableau allows users to see their business holistically. 

However, Tableau lacks one critical aspect of business intelligence: understanding operational excellence, because Tableau cannot extract and analyze process data without an initial data cleaning and wrangling period. Such a challenge can be tackled with the help of process mining. 

Process mining allows business analysts to collect, analyze and visualize the process data recorded in their IT systems. By deploying Tableau with process mining, analysts can gain a more comprehensive understanding of their business. 

For example, suppose a financial institution aims to understand its credit card management in detail. By pairing Tableau with process mining, this firm can pour the digital footprints of potential leads and create a process flow. The process analysis can identify how many leads deviated and indicate the gaps in the flow, causing people to abandon the process. 

2. Use Tableau interactivity 

Process mining tools continuously develop dashboards and modeling capabilities to provide users with straightforward flows. Yet, such simple process models tend to ignore crucial information, negatively affecting the full comprehension of processes. Thus, they may not be so easy to construct for granular or multi-levelled data.  

One way to avoid this issue is to leverage Tableau to filter and dig into specific cases, process steps or arrows (connections) while investigating the workflow generated by process mining. Moreover, Tableau allows users to change the models by moving arrows and process steps in order to clarify models. By using this interactivity, analysts can obtain insights about each sub-process, important outliers and deviations or process bottlenecks for the given subprocesses.  

For example, patient journey mapping is an emerging application of process mining in healthcare. Process mining illustrates the steps patients go through, from the diagnosis to the treatment. It can also allow users to compare different patient journeys to identify variations in these journeys to determine optimal paths. However, healthcare is a fast-changing, multi-disciplinary, heterogeneous and often heavily manual field, challenging process mining

At this stage, Tableau’s interactive flows can be an efficient solution in which analysts can dive into each step and focus on different employees’ execution practices.   


3. Create personalized KPIs

Process mining offers common process KPIs, such as cost and time metrics. These KPIs are useful to track process performance and look for ways to improve operations. Although these metrics apply to many sectors, each business is unique, requiring slightly more relevant KPIs.   

Tableau can allow users to develop KPIs based on their preferences and transfer them to the process mining extension. This way, analysts can compare their process performance with the metrics that their business needs.  

For instance, a marketing team can develop a conversion rate on Tableau and use it on process mining to track the performance of their campaign management.   

What is process mining?

Process mining is a data-driven methodology that analyzes event logs from various business processes, like logistics processes, HR processes, or mortgage processes, to create objective insights into process efficiency.

By utilizing a process mining extension, such as those compatible with Tableau, it can generate an interactive process map from such complex processes. Such an integration enhances the understanding of valuable customer journeys and enable the detection of compliance-related issues. Whether it’s order to cash or purchase to pay, process mining Tableau desktop facilitates the exploration of many business processes, offering continuous insights to streamline and optimize operations.

Further reading

Explore more on process mining and its integration to other BI tools:

If you want to deploy process mining, check out our list of process mining software vendors to sort & filter vendors according to criteria like their location, popularity or maturity.

Check out comprehensive and constantly updated list of process mining case studies to find out more process mining tableau real-life examples.

And, if you have more questions about process mining, we can help:

Find the Right Vendors


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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Hazal Şimşek
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.

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