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Overview of Process Mining

Process Mining, Automation, Business Operations, Intelligent Process Automation

Process Mining is “the utilization of specialized data mining algorithms to analyze processes, isolate trends and patterns, and highlight factors that can be modified, in the form of process maps, to improve business process understanding and management as a whole.”

Any organization, big or small, local or global has one thing in common – It is constantly looking for tools and techniques to improve business procedures.

Traditionally, identifying roadblocks in plan execution has been a painstaking event. Even at an individual level, identifying errors and creating a new plan to eliminate the scope of a recurrence is extremely tedious.

Visualizing the big picture and discrepancies between plans and reality has left many visionaries stumped. The actualization of a complex procedure is often full of deviations caused by real-time challenges that employees face. The disparity between what is forecasted and what happens, is often so wide that a departure from the prescribed plan of action becomes absolutely necessary.

Primarily due to the manual labor involved in reviewing actions and identifying the problem areas, the rectification of such issues, is very often ignored or delayed. Manually detailing a process can be extremely time consuming and take time away from other important tasks. Analyzing Big Data manually is nearly impossible and if it were to be done, would require an entire dedicated workforce. Since planned operations often do not account for delays, errors, unprecedented circumstances and worst-case scenarios, what the organization believes is happening, is rarely the complete picture.

Process Mining promises to become the new-age technological solution to this age-old business process management problem.

The software algorithms function using a collection of raw data generated during normal functioning of an organization which is compiled into event logs. They can provide detailed insight into processes as mundane as invoice generation to something as complex as generation of tax audits.

Breaking the functioning of a process mining software into miniscule steps, we get a list that looks roughly like:
  1. A data mining algorithm collects data from the user’s system, digging deep into low-level processes. Additionally, it may also collect data from external vendors that an organization may avail services from.
  2. It collects detailed, factual data based on real events and charts out how an organization really performs. In most cases, it creates a real-time log of all back-end and manual functions being carried out. This facilitates identification of
    a) What is happening
    b) Who is doing it
    c) whether protocol is being followed
    d) where the errors lie
    e) where the delay arises
  3. In collaboration with an analytical algorithm, KPIs (Key Performance Indicators) are created and mined data is compared to these KPIs.
  4. This comparison helps business process managers to identify spaces that require attention and improvement and formulate a modified business operation model.

Many process mining tools present data visually instead of graphically or in text. This allows managers to identify bottlenecks or low productivity areas and prioritizing areas of improvement becomes easier for managers. Organizations are enabled to exercise control on employee activity allowing them to create smarter workflow models. Re-engineering business processes widens the scope of Operations Management excellence. Data collected by data mining algorithms can also provide detailed insight into the designing of alternative operation architectures.

Process Mining not only allows improvement of existing operation models but can also assist in the creation of a model where no prior model exists. Based on the existence of a preceding model and how it is utilized by the tool, Process Mining techniques can be systemized into two modes:

Performance Mining focuses on evaluating different factors like waiting time, delays and processing time to identify where and when the existing model can be improved. Deviation from a prior model is not a factor in this technique and processes are evaluated based on “Can it be improved?”

Conformance Checking focuses on comparing real events to planned action and identifying the differences between the two. Therefore, this technique attempts to answer the questions “What are the shortcomings of the business plan?” and “Where is the business plan not being followed?”. As the name suggests, this mode checks whether employees conform to an existing process map and how deviations and delays affect the overall performance of the system.

Process mining has various applications that include

  • Evaluating process performance
  • Identifying areas of improvement
  • Monitoring modified operation models.

It encourages data-driven decision making and implementation of business solutions like robotic process automation and machine learning to boost performance in areas of deficiency. It also highlights the most beneficial and effective ways to implement automation.
Since it is a tool that can extract data and draw attention to obvious solutions, it can be employed to continuously evaluate the workings of an organization and provide a scale of performance and improvement over time. Process mining can be used in almost any industry to assess the operations of most functional fields. It is slowly gaining popularity in the banking, insurance companies, financial services, telecommunication, retail and even healthcare sectors.

With the realization of its multi-fold benefits, compliance capabilities and rapidly growing potential, Process Mining is emerging as a multi-faceted boon for process-management teams across the globe.