Process Mining vs Business Intelligence (BI)

I get asked the question of what is the difference between process mining and BI a lot, so I hope to address and answer this question in this blog post.

Over the past ten years, I've had the privilege to gain extensive experience through several large-scale BI projects in different industries and among many customers. As a member of an analytics delivery team at Accenture, I’ve come in touch with multiple BI solutions. For the last three and a half years, I’ve familiarized myself with the process mining methodology and the process mining technology - QPR ProcessAnalyzer, as a Process Intelligence Consultant at QPR Software.

Process Mining vs BI

As humans, we are perceptible to subjectivity. This obstructs our ability to draw an exact and precise picture of a business process when defining the ‘as-is’ state. Whereas given that computers are very good at executing millions of operations per second, can be automated to our needs. And we’ve got good at getting them to do so.

Then, if you could put a combination of human intelligence and computer’s ability to perform complex tasks, analyzing business processes to generate detailed reports from the data collected in your organization’s databases to get crucial insights about your large enterprise.

Does that sound like business intelligence? Perhaps process analytics?


Process analytics and business intelligence can seem to overlap each other in terms of expectations. Although their underlying methodologies and results stand in stark contrast, nevertheless it demonstrates an important co-relation.

From a management perspective, BI enables you to collect business data, find information primarily through reporting, operational processes, and various standard channels. Whereas process analytics, on the other hand, uses statistical and quantitative tools allowing diagnosis functionality via process mining methodology.

Process mining enables you to perform process analyses, such as influence, variation, flowchart analysis, aided with real-time operational modeling. The process analyses are derived from factual data to identify locked performance potential, allowing operational efficiency and cost saving optimizations.

This enables the organization to drive fact-based decision making to improve processes, learn about bottlenecks, minimize costs to improve efficiency, understand unpredictable delivery chains or unreliable partners.

These are clear and concise actions when executed deliver concrete benefits. This is a huge step up from merely measuring and monitoring targets as part of BI activities.

Data Preparation

BI projects often last for several months. The ETL part, where data is first extracted from a source system, transferred to reportable format, and finally loaded into a reporting data warehouse, is heavy and time-consuming.

Thus, I was surprised by how fast you can get the relevant data from different ERP systems to QPR ProcessAnalyzer and start performing interesting process analyses.

Process-oriented, Locate Root Causes

I would say that process mining and QPR ProcessAnalyzer are a powerful combination. Not only can you get a high-level understanding of your company’s processes, but you can also drill deeper down to the possible root causes of process-related problems.

QPR ProcessAnalyzer is easy-to-use and visualizes business processes neatly. Whereas millions of rows of process data might prove difficult to tackle using traditional BI methods, you can get an understandable, visualized overview of your processes using QPR ProcessAnalyzer.

One of the most sophisticated features of the software is the root cause analysis. QPR ProcessAnalyzer helps you to identify a bottleneck in your process, where you can examine the root causes using the statistical method based Influence Analysis.

Process Analysis with Drill-down

QPR ProcessAnalyzer is integrated with QPR Metrics which means that combining traditional BI dashboard reporting with intelligent process analytics is fast and agile – something that’s fully lacking in traditional BI software.

QPR ProcessAnalyzer also takes care of the two questions I’ve often run into:

  • How can we export the data from our BI tool for further analysis?
  • How can we be sure that the data in the report is correct?

Conveniently, QPR ProcessAnalyzer is available through the web or it can be installed as an Excel add-in, and thus you have the data automatically in Excel for your own calculations. BI solutions typically aggregate data at the warehouse level before it is in a reportable format. For this reason, it’s impossible to drill down to the source data level. In contrast, not only does QPR ProcessAnalyzer give you insights of high-level aggregated data, but it also lets you drill all the way down to single case IDs and verify the values in your ERP system.

Data-driven & Predictive Analytics

As a “statistics geek”, I’ve enjoyed playing around with QPR ProcessAnalyzer and analyzing real-world customer data starting from my very first month here at QPR. I look forward to crunching some more process data, understanding our customers’ processes better, and learning more about the advanced features of both QPR ProcessAnalyzer and the whole QPR Suite. And of course, I’m super excited about developing predictive analysis features for QPR ProcessAnalyzer.

Thanks for reading this far, and if you’re interested in learning more about the benefits of process mining in relation to traditional BI, please connect with me on LinkedIn and let’s chat!

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Jaakko Niemi

Process Intelligence Consultant

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