The term “Process Intelligence” is often used in process mining documentation and vendor information.
The definition of “Process Intelligence” varies from vendor to vendor, but there is no clear definition, therefere many people are confused about how it differs from process mining.
In this article, I would like to explain the relationship and differences between “process mining” and “Process Intelligence”, explaining “Business Intelligence” at the same time.
In fact, the relationship between the two is clear, as illustrated in the “process mining manifest” published in 2011.
As you can see, the largest frame is the “Business Intelligence”, inside which is the “Process Intelligence”, and inside which is the “process mining”. They are nesting relationships.
Business intelligence is literally the collection and analysis of all the business related data and information. The analysis is often conducted using so-called BI tools, typically starting from financial data such as sales and profits, we look at trends by fiscal year, month, and week, and drill down by area and product to delve into the areas and product categories that contribute to sales and profits, as well as the factors that are hindering them. This is business intelligence.
“Process Intelligence” is a type of business intelligence analysis that focuses on data and information related to business processes. Furthermore, “process mining” is an analytical method based on the flow of business process, or “Control Flow” in process intelligence.
Some people say that since process mining is basically included in business intelligence, can it be replaced by business intelligence?
However, the basic function of process mining, “(automatic) Process Discovery” requires a special algorithm that BI tools typically do not equipped with. And it is not practical to build algorithms for process mining based on BI capabilities from scratch (Even if you could build an elementary one, the process model that you reproduced would be unreliable.)
Therefore, if you want to do process mining, you need to use a dedicated process mining tool, which BI cannot replace.
So where does process intelligence cover?
In addition to process discovery using special algorithms, the Process Mining Tool calculates various statistical values and presents them in various tables and graphs.
For example, the number of issues involved in the process being analyzed, the throughput from start to finish of the process (cycle time), the number of activities per activity, the processing time, the transition time (path time) from one activity to another, or the wait time. The average, maximum and minimum, median, and standard deviation of these values can also be checked.
These statistics can be calculated on the basis of simple arithmetic operations without the need for special algorithms. It’s easy to do with BI. That’s where “Process Intelligence” covers.
In the process mining analysis, based on the “process model” (as is process model) discovered through the algorithm, various variations are verified “variant analysis”, and comparative analysis with ideal processes (to be Process), that is, conformance checking, is performed.
In addition, identify problem activities where processing time exceeds KPIs and bottlenecks where waiting time is too long. Basic statistics such as number of processes, processing time, and waiting time are important.
In other words, process mining involves drilling down into process intelligence figures from various perspectives in conjunction with process models.
The major process mining tools have standard process intelligence capabilities with dashboards that visually represent various numbers, as well as algorithms for creating process models. In this sense, it is safe to say that the current process mining tools are “process intelligence tool”.