Today, digital enterprises rely on information systems — such as customer relationship management (CRM) or enterprise resource planning (ERP) — to streamline operational processes. These systems record event data of all your company’s operations.
Using process mining techniques, you can exploit your data and glean functional insights from it to optimize your workflows and enhance process efficiency. This procedure is referred to as business process mining, and it helps your team uncover inefficiencies and make informed decisions.
What is Business Process Mining?
Process mining is a technique for monitoring and analyzing event log data with the intention of identifying existing process impediments. In gathering — or mining — the event log information, you're able to provide data-driven solutions and insights to facilitate real process improvements.
How Does Process Mining Work?
Process mining occurs in four stages:
- Stage 1: Your business information system captures your digital footprint. Systems capture all user activities and create a digital record. These are everyday activities such as ATM cash withdrawals, loan approvals, data entry, inventory management, or filling order submission forms.
- Stage 2: Process mining software creates event logs. Process mining tools convert the digital records into event logs in various formats such as eXtensible Event Stream (XES), Object-Centric Event Logs( OCEL), or Comma-Separated Values (CSV). The event log displays three vital attributes — activity, timestamp, and case ID.
- Stage 3: Process mining tools create a visual map from the event logs. These tools analyze the event logs and create a process map detailing the as-is processes of every business interaction as they occur.
- Stage 4: Your team processes analytics and monitors performance (with the help of machine learning). Data mining and ML techniques are applied to identify the bottlenecks, dependencies, and hidden patterns you can optimize to achieve optimum process efficiency and enhance business outcomes. You also set key performance indicators (KPIs) to help monitor performance.
Mining Methods and Tools of the Trade
As outlined in the Process Mining Manifesto, there are three mining methods:
- Discovery: Process discovery technique involves creating a process model from event log data without leveraging any preset data and information. With this process mining technique, you can uncover real processes by only prototyping event log data without referencing an existing process model.
- Conformance checking: With this method, you compare an existing process model with its event log data to check for discrepancies. The main idea is to confirm from the event logs if your current process model works as originally intended.
- Enhancement: Also known as performance mining or organizational mining, this technique focuses on improving an existing process model by applying information deduced from its event logs. Here, the main objective is to extend or modify your current model.
When performing process mining, you work with four different perspectives:
- Control-flow: With this perspective, you study the ordering of activities to find the most efficient way to perform tasks.
- Organizational: You focus on individual actors and resources constituting a process. These are the people, departments, roles, and systems involved in a process. The purpose is to structure all organizational units to achieve optimum process efficiency.
- Case: The goal here is to establish and define overlapping relations and dependencies between properties and develop a befitting solution. You do this by focusing on the inherent properties and corresponding data elements in different cases and processes.
- Time: This perspective is all about analyzing the timing and frequency of events to establish process bottlenecks, monitor resource utilization, and forecast the remaining processing times of running events.
How Have Process Mining Methods Evolved?
Top process mining experts like Neil Ward-Dutton point out that process mining has evolved significantly from its traditional days. The rapid growth of the digital universe and the advancement of artificial intelligence has fueled the evolution of process mining methods.
These are the areas wherein process mining has evolved most:
- Automation: AI and computers have automated process mining, making it more data-driven than before. Today, companies no longer use manual mining techniques such as process mapping and flowcharting.
- Application: Traditionally, process mining was mainly applied in the production and manufacturing sectors. Today it is used in many other industries, such as finance, healthcare, retail, and telecommunication.
- Integration: Today, process mining integrates numerous technologies, such as business process management (BPM) and robotic process automation (RPA).
- Accuracy: As machine learning and AI technologies grow, they boost the accuracy and efficiency of process mining.
- Speed: Today, you can perform process mining in real-time instead of waiting for periodic analysis as in the past.
What Process Mining Tools Are Available Today?
Since the globally-acclaimed computer scientist Wil van der Aalst first coined the term process mining in 1998, many mining tools have been developed. Some of the top-tier process mining tools applicable in multiple industries include:
- Celonis Execution Management System
- IBM Process Mining
- SAP Signavio Process Intelligence
- UiPath Business Automation Platform
- Automation Anywhere Process Discovery
- Abbyy Timeline
- Scout Platform
- MPM ProcessMining
- QPR ProcessAnalyzer
- Fluxicon Disco
- Microsoft Process Advisor
With the many options for process mining tools, you can find one that best suits your company’s operational processes.
How Can Process Mining Software Help Your Organization?
Process mining is part of Automated Process Discovery technology that helps organizations establish process inefficiencies and opportunities for optimization. These insights help steer your company’s automation initiatives. Regardless of your industry, your company can enjoy the following benefits of using process mining software:
- Foster process efficiency: Process mining helps you determine productivity lags through root-cause analysis, helping you reach peak productivity levels.
- Superior quality management: Process mining facilitates data-driven decision-making, helping you make more quality decisions regarding your workflows.
- Fulfill service-level agreement (SLA) requirements: In the age of customer experience, process mining helps you meet and exceed customer expectations by optimizing the customer journey.
- Round-the-clock improvement: Process mining allows you to optimize your business processes continuously to sustain optimal performance.
- Saves time and money: With intelligent automation, you can coordinate RPA, ML, and AI technologies to automate repetitive processes. This saves your time and resources.
Transform Your Business Operations with Process Automation
Process automation is a guiding step toward your company’s digital transformation. Modern companies increasingly rely on process automation to optimize their operational processes and achieve and maintain optimum productivity.
Fortunately, you can partner with BP3 to help you actualize your company’s process automation strategy. At BP3, we create uniquely intelligent solutions by blending digital process automation and an end-to-end business process perspective.
You may hear industry jargon like RPA, AI, IDP, generative AI, application modernization, workload automation, design thinking, and user research. At BP3, we’re simply in the business of finding a faster way to achieve your business objectives. All that technology sounds complicated, but at the end of the day, the approach is simple.