With data we can make your processes financially measurable

Where is and should your time be allocated?

In Business Process Management, it has historically been difficult to understand how much time is required to execute a process in a specific information system. Leveraging our newly developed Effort Mining capability, you can distinguish between work time spent on an information system and compare it to the time spent on «non-system» activities. This makes it possible to quantify process optimization potential more thoroughly and leads to an increased understanding of where time is allocated.

Process and effort mining

Business process management has been revolutionized with the advent of Process Mining. Process Mining is a method that leverages the existing data in your Enterprise Resource Planning (ERP) system to build a digital twin of your process management system.

Effort Mining takes the data used in process mining to the next level. It provides insights into lead and execution times and combines them with process automation metrics for each action in relation to your specific process. In contrast to other methods, Effort Mining does not need to be installed or turned on. Like Process Mining, it uses pre-existing data, avoiding the need for additional data gathering or additional computing power.
 
Using state-of-the-art process analytics tools, such as Celonis or Process Gold, easy-to-consume dashboards are generated that provide detailed and ongoing insights gathering along a multitude of dimensions, such as users, materials or entities.

«Effort Mining significantly reduces subjectivity in assessing ERP automation and optimization potential, making it possible to address and quantify realistic improvement opportunities.»

Matthias Leybold, Partner Data & Analytics, PwC Switzerland
Effort Mining

Effort Mining reports and dashboards typically include:

  • A detailed list of actions executed during the process, their automation rates and the number of users and departments involved;
  • Analysis of time spent on processes  vs. activities outside the system and the «degree of system usage»;
  • Metrics broken down by function, department or process step;
  •  Translation of the time spent on processes into monetary values, by leveraging Human Resource Information System (HRIS) data, ERP data or SME estimations and organizational data points;
  • Identification of high-potential opportunities qualification and solution proposals  the knowledge of our Process Analytics and Cognitive Automation teams;
  • Customized, detailed, ad-hoc analysis of your process effort, including additional data sources, such as Task Mining, if needed.
Process Mining

With the data and insights obtained from these analyses, a clearer roadmap for effort reduction can be outlined. While your process improvements are being implemented, you can continue to use Effort Mining to monitor the success of your changes.

Details of this novel method for Process Mining and its use to address work time spent are published in the BPM Conference Industry Track proceedings as a scientific contribution to the topic of Process Mining.

In a nutshell

Effort Mining is a novel methodology for translating data into financially measurable spending for process executions. Thereby, Effort Mining significantly contributes to the identification of opportunities for process improvements, redesign and automation.

Details of this novel method and its use to address work time spent are published in the BPM Conference Industry Track.

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Get in touch with our Data & Analytics Team

We would be pleased to learn about your process and effort mining and discuss your open points and questions in a personal meeting.

https://pages.pwc.ch/core-contact-page?form_id=7014L0000004ysoQAA&embed=true&lang=en

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Contact us

Matthias Leybold

Matthias Leybold

Partner Technology & Data, PwC Switzerland

Tel: +41 58 792 13 96

Peter Blank

Peter Blank

Director, Analytics and Automation, PwC Switzerland

Tel: +41 79 179 47 20

Wolf-Dietrich Zabka

Wolf-Dietrich Zabka

Senior Consultant, Data-driven Process Analytics , PwC Switzerland

Tel: +41 76 78 567 89