Process Mining BPM in '24: Explore 3 Easy Tips to Combine

Updated on Mar 1

3 min read

Table of contents

1. Shorten BPM cycle time 2. Establish effective BPM projects 3. Ensure data-driven BPM Further Reading

Business process management, BPM, increases effective process management by aligning business processes according to the company strategy and goals. Some BPM benefits include:

Increasing efficiency,
Managing change,
Assessing process performance,
Ensuring compliance and security,
Easing transfer of knowledge,
Enhancing customer satisfaction.

Process management can be automated with Business Process Management (BPM) Software or a process intelligence tool, such as process mining.

In this article, we’ll go over 3 ways process mining can facilitate BPM.

1. Shorten BPM cycle time

BPM has five main steps which are listed as:

Analysis
Design & modeling
Implementation
Monitoring
Optimization

However, completing each stage can prolong the time allocated for BPM projects because each step includes collecting and analyzing data and developing strategies and accurate models. As a result, improving and managing processes takes longer to realize.

Process mining can help users to complete each of these stages smoothly and in a shorter time. For instance, process discovery capability can automatically analyze the event log data to deliver a process model. Consequently, analysts can easily do the analysis, design and modeling, the most time consuming phases of the BPM, with one tool only.

With conformance check and process enhancement capabilities, analysts can compare the obtained model against process performance KPIs and learn the costs, delays or frequencies in their processes. Thus, they can identify deviations and bottlenecks along with their root causes. Based on such insights, process analysts can move to redesigning their operations and implementing changes to improve their processes.

Analysts can go over their updated processes with process mining to monitor if their changes have created the impact they aimed at and how to refine their strategy.

BPM life cycle has four phases: process modeling, process redesigning, process execution and monitoring, process strategy. For each of them there are key challenges which can be solved with a specific process mining capability.
For process modeling, it is a challenge to uncover the real process as it is and represent it in the model which can be tackled down with process discovery by taking the event log and producing the model, reducing the time spent on human judgments, subjectivity and arguments from personal experience.

Source: Process Mining and its impact on BPM

The figure above shows how process mining can tackle the challenges posed by BPM phases.

2. Establish effective BPM projects

Although it is important to meet the deadline for the BPM project, it is important to generate a project that can produce significant results for process performance. We already went over the five best practices to establish an effective BPM project.

We recommend utilizing process mining for each practice since the software can help analysts set realistic priorities or end goals and manage the project with the insights it provides. Process mining enables analysts to translate the process data into a visual workflow to spot bottlenecks in the workflow seamlessly.

Thus, some process mining vendors offer simulation and digital twins of an organization (DTO) capabilities to measure the change analysts want to implement. Such features enable experimenting with the strategies developed and ensure the effectiveness of the BPM project.

3. Ensure data-driven BPM

BPM aims to provide and sustain an ideal process which is why BPM analysts need both as-is and as-if models.

Process mining can provide BPM analysts with an as-is model and allow them to compare the discovered model against the ideal one. Based on the gap, analysts can understand what type of change the organization needs to implement, such as automation.

BPM also requires a focus on customer experience, which includes detecting primary and secondary processes that contribute to increased customer satisfaction. Analysts need to collect and dive into customer-related data such as CRM or customer feedback to understand the customer perspective.

Process mining can help analyze customer surveys, interviews and CRM data to determine processes that customers like the most. Process analysts can redesign process executions and set best practices based on such insight.

Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.