What Is Process Mining? (Benefits and Types)

Updated September 30, 2022

Many organizations and departments benefit from regularly analyzing their workflows and operational processes to turn insightful key data into actionable plans. Process mining can help companies objectively evaluate their workflows and optimize their processes to make operations more efficient and cost-effective. By understanding how this works, you can better incorporate these strategies into the organization and software of your operations. In this article, we define what process mining is, discuss its benefits, explore how the process works, and explain the different types of this mining.

What is process mining?

Process mining uses data science and analytics to discover, validate, and improve workflows within a company. It's a multidisciplinary technique that combines strategies of data mining and business process management. Data mining extracts and identifies patterns in large data sets to analyze relationships within the sets and solve problems. Business process management handles discovering, analyzing, modelling, measuring, optimizing, and automating systems within an organization. Using this technique, companies can improve workflows for employees, departments, and operational tasks that help them grow.

Many organizations use these mining strategies and software to understand the efficiency of their current operations and discover bottlenecks and areas for improvement. Process mining software helps companies develop algorithms that can log data sets and store them for future analysis and manipulation. These algorithms are responsible for detecting patterns you can use to create strategies that help increase profit, reduce waste, and save on costs.

Benefits of process mining

There are many benefits to this technique. Here are a few of the advantages you might experience:

Better data-driven decision making

Data-driven decisions enable companies to make choices that are more relevant to organizational problems and that help them create long-term and short-term goals. One of the biggest challenges companies might face is the lack of data availability, transparency, and quality. Large companies especially might encounter data challenges because of the large and complex data sets with which they work.

These strategies and software can help businesses gain better insight into their data sets and visualize them in a transparent and understandable way. These tools analyze the raw data and operation logs to extract process sequences and relationships between elements in the data set. Once a company has better access to this information, it can quickly analyze the data to identify efficiencies and inefficiencies within the organization. This helps employees make more informed choices about business strategies, spending, and resource delegation.

Improved performance management

Tools help organizations automate the collection of data, metrics, and KPIs that are important for assessing performance and success. Companies use this data to determine the performance of employees and business strategies to decide whether they're spending money and resources efficiently. It also allows them to figure out how they can improve their operations and train their employees to increase performance. For example, organizations can look at customer service calls to determine whether employees are meeting customer satisfaction benchmarks and providing quality service.

Enhanced process automation

Using event logs from these tools, businesses can better see exactly how various operational systems run. They also have a better understanding of how departments and algorithms make operational decisions. This allows them to create bots and algorithms that can automate these operations based on current processes.

Reduced costs and resolved bottlenecks

With the visibility, automation, and transparency of data available, you can track how long and how many resources the company spends on each part of a process. You can then analyze whether they are spending money and resources effectively along the operational chain. Not only does it reduce the time it takes for the organization to spot inefficiencies and bottlenecks, but it also improves the accuracy of the data collection and trend analysis. As a result, you can quickly resolve any bottlenecks that slow productivity and better allocate resources to save costs and increase profit and growth.

How does this mining process work?

There are typically four steps involved in this technique. Below are the steps listed with a description of each one to help you understand:

1. Analyze and manipulate the organizational data

Most businesses already track and store large and complex data sets in a secure area, such as a database in the cloud. Related tools allow these organizations to take these secure data sets and transform them into event logs that they can analyze for each operational process that exists. The software typically assigns a timestamp, case ID, and activity to each piece of data. It uses these elements to analyze aspects of the workflow and determine which tasks to prioritize and which ones are efficient or require improvement.

2. Evaluate each process

Using the event logs, the software analyzes and creates graphs of every step in each workflow. The software then compares these graphs with the ideal ones that display how you might like the system to operate. By comparing your current graphs with the ideal ones, you can easily see the organizational efficiencies and inefficiencies within your operational processes.

For example, your current workflow for tracking inventory might involve many steps to help ensure you ship, transport, and deliver products to customers. With graphs that outline every step, you can identify small inefficiencies and improve upon them to optimize the system.

3. Prioritize the fixes required

Once you've graphed and analyzed all steps within your current workflow and determined how it differs from your ideal graph, you can identify the steps required to improve it. Based on the severity and urgency of the changes you want to make, it's important to prioritize the fixes. As software allows you to identify the exact time needed to complete each step and all the steps involved, you can quickly determine which issues require immediate remediation.

For example, you might prioritize fixing inefficiencies in your current workflow, or you might also consider fixing the bottlenecks that cost the most resources or money for the business.

4. Continuously track the workflows

Programs for this technique continuously monitor the operational systems and create event logs to gather information about the steps and metrics involved. This provides ongoing real-time data regarding whether your workflow is efficient and delivers the results you want to see. It also allows you to identify whether the improvements you've made successfully reduced previous inefficiencies and waste.

Different types of this technique

Here are common types of these strategies:

Process discovery

Process discovery involves manually or automatically documenting a company's current business processes and major variations. The set of tools and techniques involved in process discovery uses algorithms to make recommendations about automation and improvements to the system. It also helps design the workflow for automation, such as planning, mapping, and implementation. This makes it quicker and easier for the organization to automate parts of the workflow.

Process re-engineering

Business process re-engineering is a management strategy that identifies how to reduce organizational costs and redundant processes. Companies typically rely on specific systems to operate and ensure their success, which eventually becomes legacy processes. With the help of process re-engineering, organizations can objectively re-evaluate the workflows and address any bottlenecks that reduce improvement and cost savings.

Conformance checking

Conformance checking is the method of comparing an event log generated by the software with the process model and graph. This helps businesses determine whether their current system corresponds with the ideal one. If it doesn't, they can analyze the discrepancies and create strategies to make the current process as close to the target as possible. Workflows that are closest to the target model aren't only efficient but also cost-effective.

What Is Process Mining? (Benefits and Types)