Process optimization: process mining as a success factor of digital transformation

The next big thing: process mining

Companies realize the impact of optimized processes to support their digital transformation, yet a constantly growing IT landscape, legacy systems, unharmonized processes, process non-compliance, and a lack of automation all contribute to operational inefficiencies.

The data hidden in ERP and other underlying source systems offer vast potential for process optimization that is often unused. Decisions about process optimization are often based on manual, subjective, and biased process-gathering and documentation methods. Most often, these do not reflect real-time process variants, or address non-compliance, and require a considerable degree of effort and cost.

In contrast, process mining provides objective visibility across an entire organization. The market-leading process mining software from Celonis provides visualizations and deep insights by capturing three sets of process data from underlying source systems:

• Process identifiers: Every process instance has a corresponding unique identifier, and by capturing this number Celonis can trace each individual case from beginning to end.
• Process activities: These indicate the individual tasks and activities within a given case ID, thus ensuring all variations within the process are captured.
• Process time stamps: A record of the time tasks and transactions take place, which show in what sequence the various activities occurred and the throughput time between each step.

The combination of these three data points forms the digital footprint of every process, which can be visualized in real-time and improved rapidly to bring significant cost savings without resorting to manual efforts. This further eliminates process-mapping bias and subjectivity and removes the need to congregate in teams to determine process flow. Process mining delivers significant business value by allowing companies to discover inefficiencies, identify actions to streamline processes in real time, and continually monitor them to ensure optimal performance and improved customer experience.

To unlock the full potential of process mining and to improve business outcomes for organizations, the transparency and insights gained with process mining must be turned into actions by taking optimization steps.

Capgemini Invent’s methodology for process optimization

A critical phase of Capgemini’s process mining and optimization delivery method is the Process Deep-Dive Analysis. Here, in accordance with the 80/20 rule, we discovered that a limited number of process variants (processes that deviate from the happy path) account for most of the inefficiencies in the process. Therefore, the focus of the analysis is on these errant processes.

Another vital component of the Capgemini methodology is collaboration with the employees. By collaborating to examine and improve the recently discovered process variants, the delivery time is significantly reduced due to the following:

• High level buy-in of the process-mining technology
• Cross-sector subject-matter expertise
• Quick wins are identified and exploited with moderate effort.

ESOAR: a framework for process optimization

The ESOAR method provides the framework for transforming optimization potential into concrete use cases. The concrete procedure for process optimization is determined in a multi-stage procedure. The ESOAR method consists of the following steps.

• Elimination of unnecessary process steps: Elimination of activities that increase the workload without additional benefits
• Standardization: Establishing best practices, unification of formats and standardization of similar processes
• Optimization: Optimization of existing processes and systems, for example by restructuring workflows and using existing system functionalities
• Automation: Development of solutions for process automation within existing systems, both short term (workflow/quick wins) and long term (development in systems)
• Robotization (Robotic Process Automation – RPA): Automation of cross-system processes at the user-interface level.

The ESOAR approach is supported with customized templates in the process-mining tool. That may include, for instance, variant processes (E, S), root-cause analysis (O), analysis of process’ or individual process steps’ level of automation (A), and analysis of the RPA potential based on process volume and repetitiveness (R).

Capgemini Invent also introduces process-specific best-practice approaches such as process standards, KPIs, or use cases for the subsequent process automation using RPA. In addition, process mining is used within the company’s own business-process outsourcing, where Capgemini Invent combines the external consultant perspective with the internal application perspective.

The process optimizations realized with the ESOAR framework are monitored continuously. Monitoring ensures that initiatives are tied to KPIs and the business outcome.

Project examples show that, with process mining, clients can achieve up to 30% faster throughput times, up to a 25% reduction of manual-process steps, and upwards of 20% in process-cost savings. In order to realize these potential savings, organizations acknowledge the need for digitization and have stable support to overcome resistance. Capgemini Invent supports not only the technical implementation but also the integration of process mining into processes and functional areas and embedding of process mining into an organization.

Capgemini Invent and Celonis will share more on this topic on their upcoming webinar Leveraging process mining to enhance your RPA journey. Register to join us on May 19, 2020.

Co-author:

	Brian Finkel Digital Consulting Manager, Celonis
Celonis for Consulting digitizes process discovery and analytics on client engagements to create valuable, fact-based, and data driven process insights.