When people hear the words data mining, they nowadays have an idea of what it means. We often define data mining as a process of analyzing data from several perspectives and summarizing it into useful information. With support from this information, we can then make decisions that affect the success of a company. However, even when data mining is familiar to people, process mining still seems to be a new topic for many. Very often, I encounter questions like, “What is process mining? How does it work?”.
Editor's note: This post was originally published in July 2017, and has been updated for accuracy and comprehensiveness by Saara Bergman in January 2021.
Process Mining vs. Data Mining
On a general level, we aim to do the same with process mining as with data mining. The goal is to analyze data from different perspectives and summarize it into useful information for making business decisions.
Combining Business Process Management with Data Mining
But this time, the context is the business processes of an organization. In other words, business process mining is a combination of business process management and data mining. We take the data that exists in the information systems of a company and use that to visualize the real-life execution of the company’s processes. Almost all IT systems store data in databases and create event logs. Process mining refers to these logs as "event data" required for process mining analysis.
The traditional methods of workshops, interviews, and manual documentation require a lot of efforts. But how else can you update the process documentation and make sure it actually describes the way things are really done?
Process mining software saves you a lot of time and effort. Just take the data, and visualizations of your processes are already on their way. The best part: they are based on facts and are completely objective.
Process mining tools visualize what kind of process flows take place in your organization and how different teams and units are performing. This empowers process professionals who are responsible for optimizing and improving operational performance with the means to spot inefficient processes or process steps, and find the best practices in use.
Process Improvement and Monitoring
Have you looked at processes from operations-driven or data-driven point-of-view? Business process improvement as a domain has been around for eons (well, for decades at least), but many companies are still doing it with traditional and subjective methods – workshops, interviews, manual documentation. If you work in one of these companies, you are overlooking the abundance of data in your own company’s IT systems and how you can use this data to conduct process mining to give a completely new angle to the improvement needs and actions of your organization.
To understand the differences and what to change, you need to be able to compare performance even on a very detailed level to dig out the real root causes. Process mining shows you a list of targets where to make changes, where the biggest need for improvement is, and most importantly, where the biggest and quickest benefits are to be achieved.
Once you identify the improvement needs and actions needed for your organization based on the results, process mining also gives you the means to easily follow up on the impact of changes in business processes. Not only does QPR ProcessAnalyzer visualize the actual process flows, but it also offers a variety of process analyses for organizations to understand their business processes, as well as attributes affecting the processes, and to monitor how improvement actions are changing the processes. With the help of the process mining software, you can easily identify where to target your improvement and development activities when new actions are required.
How much more efficient and in which areas? What are the cost savings? Do you know which units in your organization are doing best and why that is?
Companies need to have all possible information and support at hand to target decisions correctly. Regular KPIs will get you started, but to get down to individual orders or even order lines and process-oriented facts, you need to do more. Process mining reveals the untapped potential available in your organization.
If you recognized the need to increase process efficiency, you probably also acknowledge the importance of reducing process deviations. There might be trouble with lead times and automation degrees, for example. Customers aren’t getting what they requested when they requested it, and you aren’t really sure why that is the case when individual KPIs show acceptable levels.
You might think some actions are completely automated, but the company hasn’t really achieved the benefits expected through automation. There might still be plenty of hidden work done manually, such as changes to orders. With process mining, you can find out fact-based deviations that you can trust, and, with QPR's process mining software and ready-made Robotic Process Automation (RPA) presets, you'll easily identify the best processes for RPA, monitor automation levels, and get instant ROI calculations.
Why Process Mining?
Why not just stick to traditional BPM? To answer to the ever-growing pace of business transformation, you need to be able to react quickly and not build analyses that are outdated already before they are completed. The accumulation of data is making sure that your process analyses cannot be based on gut feelings: you need fact-based figures and evidence to back up your claims.
Saving Time and Releasing Working Capitals
Traditionally, managing and optimizing processes has been a very labor-intensive area that requires a lot of time from experts in the organizations. The growing demand for efficiency and being able to clearly showcase results is also hitting BPM professionals. Very often, I’ve heard them stating that when their situation analysis is ready, the data which they used to back their assumptions with has already changed, rendering the analysis all but useless.
When optimizing processes, the most time-consuming part is often data collection. With process mining, you get a head start by automating the data collection part. The basis for understanding the operational situation in an organization is to understand what is actually happening, not what is assumed to be happening. This is what you find out using process mining.
Locating Process Bottlenecks
Process bottlenecks are hard to uncover by hosting BPM and process mapping workshops. People have a gut feeling of what could be wrong or inefficient, but they lack fact-based proof. They need the data to back their assumptions, and this is where process mining comes to the rescue.
Replacing Opinions with Facts
One of the main goals in process mining is to be able to see the big picture of a company’s business processes and still be able to drill down to the root causes of deviations, bottlenecks, or process variations. With process mining, we don’t have to settle for averages - we dig out the reasons behind unwanted behavior. To bring this closer to organizations and to see what process mining means for different industries, I’ll give a couple of short examples.
What are typical Use Cases for Process Mining?
Process mining is beneficial for many situations in large organizations. I can think of a few areas where the process mining methodology has been applied actively, although other areas also can gain immediate benefits from using the same process mining models. Read more about the most common process mining use cases:
Robotic Process Automation - Understand the actual processes, variations, and automation opportunities in order to succeed in RPA projects
Process KPI Reporting - Create complete process KPIs and dashboards for any given process
Digital Transformation - Understand the "big picture" - how organizations work, what to prioritize, and what to transform
Auditing and Compliance - Drive compliance with agreed processes, rules, and regulations
Process Improvement - Identify bottlenecks, rework, and other symptoms of inefficient processes
IT & ERP Development - Support ERP consolidation, new deployments, and major version upgrades
Applying Process Mining to Specific Processes
Typically, people have some idea how the process is running - or how it is designed to run - but the reality revealed with data can prove to be quite different.
Common findings are changes in order-to-cash and purchase-to-pay processes: a single order is delivered several times, or an invoice is sent more than once or left completely uninvoiced. For various reasons, the cases go through several changes that affect the efficiency of the end-to-end process.
In the order-to-cash process, end-to-end lead times or lead times between process steps deserve some scrutiny - check, for example, the lead time from delivery to invoice creation.
In the purchase-to-pay process, the challenges can start already at the beginning of the process, when a PO is created without a purchase requisition or a frame agreement.
Process mining shows you out-of-the-box how many nonconformant cases you have in your order-to-cash process and root causes for the nonconformance.
Process Mining helps in reaching better on-time delivery and a wider geographical reach. It also helps to cut down logistics and warehousing costs.dentifies exceptional and unwanted process steps and validates if the escalation rules are effective. Typical incident management KPIs are generated, such as SLA breach rate, Average Time to Resolution, and first call resolution rate.
Applying Process Mining to Specific Industries
In the manufacturing industry, timely and accurate delivery to a customer is the ultimate goal. If a company has several factories in different regions, there usually are differences between the reliability of deliveries. It’s quite easy to see that they exist, but harder to understand exactly where or why they happen. Also, very often, people with the loudest voice gets the most attention regardless of whether their problems are the biggest. With process mining, we can compare the performance of different regions down to individual process steps, including duration, cost, the person performing the step, and many more. All event data available in the systems is suitable for use in process mining and this way, you'll bring the facts to the table without debates.
- Case Studies: Metsä Board, Terumo, Patria Land System, Ruukki, Vaisala. Kemira
- Example: Metsä Board succeeded to increase order lines and volume by 60% without changes in their supply chain headcount as well as increase the number of conformant order lines from 40% to 80% - by focusing process improvement activities to the right areas and improving their geographical reach.
Banking and Financial Services
In the financial sector, it is crucial to follow the rules and regulations and to be able to prove you have done so. By using the event data from the systems, we can visualize even individual cases as a process flow. We can also show how often deviations and variations occur and what has been the reason causing this non-conformance. With process mining, we can both prove our actions but also pinpoint the improvement needs in the business processes.
- Case Studies: KBC, Komerční Banka, Piraeus Bank, Bridge Loans
- Example: Piraeus Bank cut their loan application process from 35 minutes to 5 minutes on average, by fixing their automation initiatives.
Telecommunication is a highly competitive sector globally. The ability to improve operational processes is key to success and profitability. Process Mining helps telecom companies in creating visibility to geographically disperse operations, identifying bottlenecks and ensuring that customers receive products and services on time.
- Case Studies: Nokia, Ericsson
- Example: Nokia improved business process lead times in Order-to-Cash and Purchase-to-Pay processes. Moreover, they got the needed transparency into their M&A of Alcatel & Lucent and harmonized processes.
Consulting companies play a major role in the development of organizations. Large, medium and small-size consulting companies are using process mining to achieve data-driven improvement which is based on facts instead of assumptions.
- Case Studies: Implement Consulting, EY
- Example: EY UK got a holistic view of all business processes, with 100% coverage of all transactions and root causes of inefficiencies, allowing them to predict errors and prioritize actions based on risk
The success of retail companies comes from efficient business operations. Logistics, warehousing, forecasting, order management, supplier management form the bases for the excellent end customer experience over the whole end customer life cycle. Process Mining gives visibility to all these interlinked processes providing an understanding of bottlenecks and failing interfaces. Data-driven fact-based Process Mining findings focus the development effort into those areas that matter most and give highest business results.
- Case Studies: Stark
- Example: Stark managed to dig deep into their IT systems and processes in order to streamline and digitize their business processes.
Utility companies have a high demand for robust and reliable services for their end customers. Process Mining provides visibility to complete end-to-end processes identifying process bottlenecks and root causes.
- Case Studies: Fennovoima, L&T
- Example: Lassila & Tikanoja used process mining to support their ERP implementation: they gained visibility into data and were able to develop internal capabilities from a process and data driven perspective.
Business logic of service companies is to achieve higher operational excellence (ie. lower costs) than their customers for the particular processes they outsource. Process mining is an important tool for improving the efficiency of a service company by ensuring harmonized operations, finding root causes for process issues and inefficiencies:
- Caverion, Barona
- Example: Caverion reduced the average time for delivery to invoicing by 50%, harmonized processes across the many different countries in which it
operates, and continuously monitors the process to ensure operations remain on track.
Summary: Visualize Processes, Make Findings and Discover Root Causes
In process mining, we use the event data in the company's IT systems (such as ERP, CRM and BPM) to bring insights into the company’s business operations. The insights are provided by automatically visualizing data with process flowcharts and creating analyses that give information on needed improvements and deepen the understanding of what is going on in the business processes. We can show both the big picture as well as the detailed ground-floor view on process execution.
Get started with QPR's process mining software, QPR ProcessAnalyzer.