Process Mining - Change Is Inevitable Growth Is Optional?

Business excellence is a product of excellent processes. Excellence requires the ability of continuous optimization. Transparent processes are essential to identify optimization potentials.

But the reality is that there is a large volume of data to handle. Digital transformation requires a new method to analyse processes. This new method is called Process Mining. Process Mining delivers insights into processes and provides the necessary transparency.

What is Process Mining?

A process is a series of actions or steps repeated in progression moving from a defined or recognized ‘start’, to a defined or recognized ‘finish’. The purpose of a process is to establish and maintain a commonly understood flow that allows a task to get completed as efficiently and consistently as possible.

Every step in the process leaves a digital footprint in your transactional systems in the form of event log data. Process mining involves using this data to create a living picture of what your processes actually look like — which does not always match the definition of that particular process. It mines data from various IT systems to reconstruct what really happened in the end-to-end process based on actual data. It then moves from what, where and whom, to understanding why things are happening.

How Does it Work in Real-Time?

Process mining is different from mainstream machine learning, data mining, and artificial intelligence techniques. Classic data mining problems such as classification, clustering, regression, association rule learning, and sequence/episode mining are not process-centric.
However, process mining can be used to generate machine learning, data mining, and artificial intelligence problems.

Process discovery often provides new and surprising insights. These can be used to redesign processes or improve management. Conformance-checking can be used to see where processes deviate.

PROCESS MINING SPECTRUM BASICS

1. DATA – Process mining aims to precisely analyze business and production processes to identify weaknesses and find opportunities for improvement. With this, you derive a strategy for targeted optimization.To achieve this, however, any process mining tool first needs input. Information is required, which the software can use to understand the processes. Log files come into play here. They contain data on specific process activities, time stamps for these activities and several other so-called “attributes”, such as costs, location or responsible business units.
2. PROCESS DISCOVERY – THE NEXT STEP: FROM LOG TO SIMULATION – The log files of your IT systems now form the fodder for the process mining tool. The first thing the software does with the process data is to make what is known as a Discovered Model. In this virtual model, your process gets visualized in the exact way it takes place in the actual operating sequence. Insights into bottlenecks, weak points and optimization opportunities can be obtained.
3. CONFORMANCE CHECKING – Process mining is not limited to process discovery. The discovered process is merely the starting point for deeper analysis. For conformance checking, modelled behaviour and observed behaviour, i.e. event log, is compared.
4. MODEL ENHANCEMENT – DEEP LEARNING: It is also possible to extend or improve an existing process model using the alignment between the event log and the model.

KEY BENEFITS OF PROCESS MINING

• All AS-IS processes at a glance
• Data-based decision-making
• Uncover hidden process potentials
• Immediate increase in efficiency
• Provide Insights
• Enable Prediction
• Improve Reliability
• Show Variability
• Ensure Conformance

Today, many data sources are updated in (near) real-time, and sufficient computing power is available to analyse events as they occur. Therefore, process mining is not restricted to offline analysis; it can also be used for online operational support. For a running process instance, it is possible to make predictions, such as the expected remaining flow time. All this is achieved in a non-intrusive manner, which means business-as-usual for your IT department.

Over the last decade, there has been a spectacular growth of data. Moreover, the digital universe and the physical universe are getting more and more aligned. Therefore, business processes should be managed, supported, and improved based on event data rather than subjective opinions or obsolete experiences.

Now is the time to interpolate the heading – yes, you read it right. Process Mining enables a paradigm shift where Organization may be willing to rework/revisit existing workflows as Change Is Optional but once adapted Growth Is Inevitable.

By Velmurugan Kumarasamy

Solution Architect- Appian