What Is Process Mining?

Process mining is the deep-dive analysis, discovery, monitoring and improvement of as-is processes, revealing the to-be efficiencies your business benefits from. It takes all of the process data within a company's walls and "mines" it for insight on potential improvement, focusing on finding better, more efficient pathways in operations. The goal is finding "touchless" process paths that require minimal human intervention. This allows businesses to increase speed and accuracy, allowing teams to focus on doing what they do best as efficiently as possible.

How does process mining work?

Every time a process is completed, it creates data. For example, any time a customer service request is received, you know when the call was received, who handled it, how long it took, whether the issue was resolved, just to name a few It could also include time-stamped logs of purchases made at a register. Or invoices sent on a particular date.

Common business processes leave digital footprints in enterprise systems like SAP, Salesforce and Oracle. When using simple analytics tools, you can look at this data for processing, mining the information to understand some general trends - how long things take, the total volume of processes completed, who is handling what, etc.

This is where a process mining solution comes in. Using a process mining platform, you can upload all of this data - both historical and real-time - to take these insights to the next level.

What is process mining software?

Identifying and analyzing processes could require a massive amount of manual work, especially considering the amount of process data that needs to be examined. This is where process mining software can help.

Process mining software is a tool that quickly analyzes all of your process data from various systems like an ERP, CRM or MES. It helps to identify the bottlenecks and opportunities for improvement. It makes sense of the data, which allows you to understand and identify their dependencies to find patterns, anomalies and opportunities for optimization.

Why is process mining important?

Because process mining discovers, monitors and improves processes, it is important for improving day-to-day business operations. But on a wider scale, process mining is important as it can support business operations in driving resilient growth.

According to a recent Gartner report, process mining supports the creation and maintenance of business operations resilience, which is a key driver of resilient growth. It does this by enabling people, processes and information systems to adapt to changing patterns, such as new competitors, products, services, channels, business models or operating technologies.

The ability to alter operations with fact-based insights, continuously or on-demand, is monumental if driving efficiency, operating with agility and achieving growth is important to your business. Below are some of the ways that process mining can benefit a business’s operations:

  • Discover hidden behavior in massive amounts of data
  • Drive Process Transformation Projects
  • Check if processes behave like you expect them to
  • Enhance your Process Description with real-world data

Process mining for root cause analysis

Using machine learning, process mining applications help with root-cause analysis - identifying the best and worst of all processes based on this data. What is slowing down important business tasks? What are the so-called "happy paths" that complete a full process flow as quickly as possible? Based on these insights, you can revise the full end-to-end process and reallocate resources to better align with these happy paths.

Process mining for conformance checking

Once these new, improved processes are in place, process mining benefits conformance checking on an ongoing basis. Process mining companies can run real-time analysis on processes as they are being executed and then identify gaps between the as-is processes and the ideal case (to-be process). Once you identify those gaps, you can develop a concrete plan to close them so that as-is and to-be processes, over time, become one and the same.

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Gartner® Critical Capabilities for Process Mining Tools
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Process mining use cases

The potential applications for process mining sweep across industries and departments. Anywhere there is a process in business, process mining can help. However, there are a few use cases where process mining is currently being used to improve business operations:

  • Customer experience: Use process mining to ensure you are provide the best possible customer experience possible. Identify any customer process that takes longer to resolve than others and make sure you are providing the right information to the customer at the right time.
  • Supply chain management: Analyze logistical operations to identify the weak links in your supply chain, and become more resilent and less vulnerable to disruptions.
  • IoT process improvement: Identify so-called happy paths in your production to increase throughput and efficiency, and lower cost.
  • Procure to pay: Optimize procurement by eliminating payment term discrepancies and maverick buying.
  • Order to cash: Maximize touchless orders, reduce order-to-delivery cycle time and ultimately speed up payment collection.

What are the five keys to process mining?

  • SEE IT
    Data is just 'data': a string of numbers, and sometimes it can be extremely overwhelming -- unless you know why you're looking at all of it. What does it all mean? What's the point? How do you make sense of all of it?
    Once you understand what the data's telling you -- delays, bottlenecks, increased scrap, lack of product quality, etc. etc. -- you can mock up those event logs alongside goals to visualize and achieve the differentiation.
  • FIX IT
    This is where process mining really shines: the goals you want to achieve then set the framework for how processes get mined and then mapped as a visualized mockup for what your operations should look like.
  • RUN IT
    The ideal process mining software will integrate seamlessly with any system for fast execution and rollout. Once the "happy path" has been discovered, it's all downhill from there with operations flowing that much easier.
    One big advantage of process mining software is that as your business operates, processes are continually monitored to ensure goals have been reached. That continuous flow of data is priceless.

Process mining example:

There are many, many different applications for process mining across industries and business functions. Anywhere there is a process in your business, process mining can help.

One example where we at Software AG have used process mining is to improve the performance and flow through our sales pipeline. We noticed that leads weren't progressing through the pipeline as quickly as they had in the past, and we wanted to make sure that we were helping prospective customers as quickly as possible.

We turned to our process data to try and understand the root cause of the slowdown. Using ARIS Process Mining, we analyzed more than 750,000 Salesforce cases to (1.) identify the root cause of the delays, (2.) find the “happy paths” where we could better automate processes and (3.) compare as-is processes to to-be processes to see potential improvements.

The result? We found that the leads we responded do quickly were 7x more likely to progress in our sales funnel than those that were delayed. With this insight in mind, we rethought the processes and resources allocated to the initial follow-up and improved conversions by 20% in key markets.

Read the full case study

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"Seamless integration with ease of managing changes and relevant workflows."
“Ease of use and feasibility of the relevant workflows and its dependencies”
"Best tool for process mining"
“It is very user friendly, you don't have to roam across multiple things you will get what you want at your place. Easy to use. The best part is it is smooth.”
"ARIS process mining helps to find bottlenecks & improve the efficiency of processes."
“Makes process more efficient, find opportunities to increase throughput using process mapping”
"Best tool to Analyse and improve processes"
“Ease of integration, analysis, flexibility”
"Indepth Process analysis resulting in identification of improvement areas & automation opportunities"
“Process Discovery – View of actual Process on-ground (Process Flow for different variants)”

What is the future of process mining?

Business conditions are continuously evolving, and organizations are under intense pressure to adapt to changes in customer expectations, competition, regulations and expenses—the COVID-19 pandemic only increased this pressure to evolve constantly and quickly. Organizations are finding that their traditional ways of operating no longer thrives in today’s business landscape.

This led leaders to confront broken internal processes and ways of working, as well as external processes involving clients, partners and supply chains. On a smaller scale, people now collaborate in a variety of different ways, increasing the need for systems to adapt to changing patterns and newly composed capabilities.

As a result of an ever-changing and disruptive environment, there’s a demand for organizations to become more resilient and agile in order to survive in the future. Therefore, organizations are increasingly leveraging process mining technology, with a fact-based approach to process discovery and analysis, to reconstruct operations efficiently and accurately—now and into the future.

Glossary of process mining terms

Task Mining
The granular technology of capturing all sorts of user interaction data for analysis and improvement, which is at the heart of what process mining is.

Enterprise Mining
On a much wider scale, democratizing process improvement via a centralized process optimization location, or a "center of excellence" designed to provide the exact process discover and analysis for an entire enterprise.

Data Mining
A computerized process to identify and describe patterns, discovering new trends. Process mining does this, but with unique algorithms to analyze and break down data for better understanding and visualization.

Big Data
The implementation of BI methods on large datasets, providing those datasets for processing and the technical platform.

Business Process Discovery
The basic process mining method and approach for process detection, allowing easy visualization and grasping of details to optimize outcomes.

Process Analysis
The basis for increased business understanding, process improvement and optimization, analyzing in-depth all structures, displaying performance.

Process Improvement
Optimizing existing business processes to strengthen competitiveness in industry or vertical.

Conformance Checking
The basic process mining technique to determine compliance of event logs according to expectations with cases simulated in models either selected as "conform" or "varying."

Root-Cause Analysis
Detection of potential defects, determining the root cause of those defects and possible solutions toward taking measures to eliminate them.

Process Excellence
Delivering consistent positive output, creating and delivering value to the customer.

Operational Excellence
Delivering consistent positive output with not only internal processes, but other aspects, such as culture, people, resources and systems, showing how they optimally cooperate.

Process Optimization
Improving internal business procedures, examining documents to optimize workflow, reveal weaknesses, reduce cost and increase quality.

Robotic Process Discovery
A method of process discovery software applications automate, mapping processes, evaluating their automation suitability and generating workflows.

Robotic Process Automation
Commonly known as RPA with software applications learning, automating and optimizing processes with recurring, rule-based criteria that mimick human interaction.

Business Process Optimization Strategy
The framework and direction toward improvement and optimization of processes to increase workflow productivity, which can include omitting, combining or even disassembling sub-processes upon analysis completion.

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