Striking Gold in Your Data: A Process Mining Introduction
- Jeffrey Agadumo
- June 7, 2023
Enter process mining!
Deep within the caverns of your organization’s data lies hidden treasures, as precious as gold and as transformative as discovering a new resource. These treasures are the untapped potential of your business processes, waiting to be unearthed and refined to reveal invaluable insights.
In today’s rapidly evolving business landscape, organizations constantly aim to optimize their processes and gain a competitive edge. By leveraging the power of data, process mining enables organizations to analyze, understand, and optimize their operations with unprecedented precision.
This article delves into the fascinating process mining world, exploring its benefits, techniques, and applications across various industries.
Join us as we uncover the transformative potential of mining business data to reveal how it can unlock new levels of efficiency and innovation for your organization.
Business Process Management in a Digital Age
Every business needs to monitor its daily processes, whether they’re central to the company, support other activities, or help manage everything. And thanks to the many business software available today, it’s now easier than ever for organizations to track even the most granular details of their processes.
Business software can manage and streamline various aspects of an organization, from overseeing purchase orders and recording customer grievances to monitoring employee performance. In essence, we can group different types of business software into the following categories:
- Enterprise Resource Planning (ERP): It integrates various business functions into a single, unified system, typically including modules for finance, accounting, inventory management, procurement, human resources, and more.
- Customer Relationship Management (CRM): Helps manage customer interactions, track sales leads, and maintain customer data.
- Project Management: Assists teams in planning, organizing, and tracking projects. Features typically include task management, collaboration tools, resource allocation, and progress tracking.
- Human Resources Management (HRM): It streamlines HR functions, encompassing recruitment, employee onboarding, benefits administration, payroll, and performance management.
- Business Intelligence (BI) and Analytics: This is one of the most important on this list. It helps organizations analyze data, reveal hidden insights that can make or break a business, and make decisions based on insights.
By default, the administrators of these systems have access to their event logs. The event log is typically a tabular entry of every action that occurs in a system, including user activities, system errors, system warnings, and other important events. These event logs and all your business data come together to form a holistic picture of your business.
Process Mining: The Long and Short of It
Process Mining (PM) is a data-driven approach to analyze and improve business processes by extracting information from event logs generated by IT systems. It helps identify inefficiencies, bottlenecks, and deviations and enhances overall process performance using specialized algorithms. The goal is to provide valuable insights into processes’ operations and streamline them for better efficiency and effectiveness.
Generally, it divides into four stages.
This technique aims to automatically construct a visual representation of the underlying process model based on the event logs. As a result, the discovered process model captures the flow of activities and their relationships, clearly understanding the actual process execution.
Popular process discovery algorithms include:
- The Alpha Algorithm.
- Heuristic mining.
- Genetic process mining
- Fuzzy mining
- The Inductive Miner.
Conformance checking compares the discovered process model with a predefined, desired process model (often called a “reference model”). This technique helps identify deviations, non-compliance, and bottlenecks within the process.
Various conformance-checking methods, such as token-based replay, alignment-based replay, or trace equivalence, can measure the similarity between the discovered and reference models and highlight areas where the process execution deviates from the expected behavior.
Performance analysis focuses on evaluating the efficiency and effectiveness of the discovered process model. This technique leverages timestamp information from event logs to calculate performance metrics, such as cycle time, waiting time, throughput, and resource utilization.
Organizations can make data-driven decisions on process improvements and optimizations by identifying areas with high waiting times, low throughput, or other inefficiencies.
In optimization, we modify the discovered process model by incorporating additional information, such as resources, timestamps, or other contextual data. This process yields a more accurate and detailed representation of the process, which we can use for further analysis and optimization.
Enhancement methods may include adding resource information to visualize the allocation of tasks or incorporating time and cost data to enable more comprehensive performance analysis.
Some Obvious Benefits of Process Mining
Process Mining (PM) is excellent for companies aiming to understand their workflows better and make positive changes. Some of the top perks include:
- Increased process transparency: Process mining helps organizations visualize and understand their processes, uncovering hidden patterns, relationships, and inefficiencies. This increased transparency enables better decision-making and more effective process improvements.
- Enhanced process performance: By identifying bottlenecks, inefficiencies, and deviations from the desired process model, process mining allows organizations to optimize their processes and improve overall performance.
- Improved compliance: Conformance-checking techniques in process mining help identify deviations from regulatory requirements or internal policies, enabling organizations to address compliance issues proactively and reduce the risk of fines or penalties.
- Reduced operational costs: Process mining can uncover areas of waste, inefficiencies, or duplication within processes, allowing organizations to streamline operations and reduce costs.
- Informed digital transformation: Process mining can inform digital transformation initiatives by identifying areas where automation or new technologies can be most impactful, leading to more successful and targeted investments.
Process Mining Possibilities: Relevant Use Cases
Here we will outline some possibilities of Process Mining(PM) business and include some case studies to help provide some context and give you an idea of how to use it to enhance your business processes.
- Purchase-to-Pay (P2P): Process mining can analyze the end-to-end procurement process, from purchase order creation to invoice payment. Such analysis helps organizations identify and address inefficiencies, leading to streamlined procurement processes and cost reductions.
- Order-to-Cash (O2C): Analyzing the O2C process using process mining helps organizations uncover bottlenecks, optimize order processing, and improve customer satisfaction by reducing order lead times and increasing order accuracy.
- Incident Management: In IT service management, process mining can be applied to the incident management process to identify inefficiencies, ensure compliance with service level agreements (SLAs), and improve response and resolution times.
- Supply Chain Management: Process mining can help organizations optimize their supply chain processes, identify inefficiencies in logistics, and improve the coordination between suppliers, manufacturers, and distributors.
- Claims Processing: In the insurance industry, process mining can be applied to the workflow to streamline claim handling, reduce processing times, and minimize fraudulent activities.
Some relevant case studies to further highlight the use cases are:
Siemens, a leading industrial manufacturing company, utilized Celonis’ Execution Management System (EMS) to drive digital transformation and process optimization across their organization. Through process mining, Siemens gained transparency in their complex Order-to-Cash process, enabling them to benchmark performance, increase automation by 24%, and reduce rework by 11% globally.
As a result, the implementation led to a reduction of 10 million manual touches annually. This significant improvement in efficiency, cost savings, and delivery times impacted multiple departments, including sales, operations, and procurement.
Vodafone, one of the world’s largest telecommunications companies, implemented Celonis Process Mining on their SAP S/4HANA infrastructure to gain transparency and standardize their global purchase-to-pay process. By leveraging process mining, Vodafone visualized real-time as-is processes, identified inefficiencies, and uncovered root causes of problems, enabling them to make data-driven decisions and optimize their operations.
This significantly improved process efficiency, automation, and compliance, positively impacting their business success and customer satisfaction.
Top 3 Process Mining Software Picks
The best software for process mining depends on various factors, such as your specific needs, budget, and the complexity of your business processes. However, here are some of the top process mining software available in the market:
Celonis is a leading process mining software that provides real-time visibility into business processes, enabling users to identify inefficiencies, bottlenecks, and other areas for improvement. It uses AI-powered technology to automate data collection and analysis, and it provides intuitive visualizations and dashboards to help users understand and optimize their processes.
Minit is another popular process mining software that offers a range of features and capabilities, including process discovery, process monitoring, and process improvement. It gives users real-time insights into their processes, enabling them to identify and eliminate inefficiencies and improve overall business performance.
ProM is an open-source process mining software with many tools and functionalities for process analysis and optimization. It supports a variety of process mining techniques, including process discovery, conformance checking, and performance analysis, and it can be customized and extended through plug-ins and add-ons.
Process Data Cleaning and Transformation with Datameer
Process mining collects data from various sources beyond event log data alone. Depending on the business structure and unique process use cases, data can originate from spreadsheets, databases accessed through ODBC drivers, sensory data from IoT devices, and many other sources.
To ensure data integrity, organizations should take steps to clean and transform all event logs and related data before feeding them into the process mining software.
Here is where Datameer truly excels!
Datameer is software that helps process mining by providing the necessary data preparation and analysis capabilities to make sense of complex business processes. It offers advanced data integration and preparation features that allow organizations to collect and combine data from various sources, including structured and unstructured data, and prepare it for process mining analysis.
In addition, Datameer provides a range of pre-built connectors that make connecting with process mining software possible, making it easy to export processed data for further analysis and visualization. Furthermore, Datameer can collaborate with third-party software like Amazon SageMaker to model custom algorithms for process mining, such as the alpha algorithm.
Overall, Datameer provides a user-friendly and efficient platform that streamlines the process of data preparation and analysis for process mining, leading to actionable insights that can improve business efficiency.
If you are considering using with Datameer, here’s a 14 Day free boost to get you started today.