Process Mining in Action

Table of Contents

1. Frontmatter

2. Part I

   1. Frontmatter

   2. 1. Process Mining in a Nutshell

      Lars Reinkemeyer

      Abstract

      Fundamentals such as event logs, cases, activities, and process variants are explained. Concrete examples show how Process Mining can be used for business transparency and value. Allowing full transparency based on event logs, the implications of this important change—away from perception based towards a fact-based process management—are discussed. The metaphor of an MRT is used to explain possibilities, benefits, and limitations of Process Mining.

   3. 2. How to Get Started

      Lars Reinkemeyer

      Abstract

      One of the most common questions raised during discussions, presentations, and initiation of projects is the question “how to start a successful project?” Experience and market research show that many Process Mining projects fail. Exaggerated promises and unrealistic expectations, unspecific targets, reluctant teams, and insufficient digital traces can be some reasons for failure. While there is no silver bullet, experience shows that—besides the three factors Purpose, People, and Processtraces, which will be explained in the following chapters—ten general aspects, including quick start, expectation management, and which process to start with, are crucial.

   4. 3. Purpose: Identifying the Right Use Cases

      Lars Reinkemeyer

      Abstract

      Purpose implies a clear understanding of what Process Mining shall be used for, i.e., which use case shall be investigated. Like for any other tool, an idea is to be formulated first: what shall be achieved and how the tool can contribute. The chapter starts with typical questions from functional departments and reflecting challenges from process owners along the value chain. Examples for purpose, which Process Mining can support, are explained with 22 standard use cases.

   5. 4. People: The Human Factor

      Lars Reinkemeyer

      Abstract

      While innovative IT tools can be a great enabler, it is a key success factor to get the right people on board. All smart data, insights, and transparency will be useless if the process experts or process owners do not appreciate and support the approach. Similar to applying MRT technology, the affected people must be determined to pursue a therapy and strive for improvement. The chapter shares operational experiences, challenges, and organizational setups which have proven successful.

   6. 5. Processtraces: Technology

      Lars Reinkemeyer

      Abstract

      Processtraces are comparable to raw oil: they are hard to find, the collection causes technical challenges, and the refinement is laborious. But once all these obstacles have been overcome, it can be used in an amazing variety of forms and fuel impressive results. The chapter discusses not only best practices for identification and customization of processtraces from raw data, but also a structured approach, which includes technical aspects and challenges. The chapter covers technical architecture as well as user-related aspects such as data access, security, and user experiences.

   7. 6. Challenges, Pitfalls, and Failures

      Lars Reinkemeyer

      Abstract

      As the evolution of Process Mining has not always been on the happy path, the idea of learning from failure has been adopted as a guiding principle for this book, applicable to this chapter as well as to the use cases in Part II. This chapter presents ten samples, reflecting challenges which were posed, pitfalls which were learned hands on, and failures which have been experienced. Samples range from data availability to process conformance checking and shall help the reader to avoid similar experiences.

   8. 7. Process Mining, RPA, BPM, and DTO

      Lars Reinkemeyer

      Abstract

      With digital transformation being one of the hottest topics of today’s business, digital tools such as Process Mining and Robotics Process Automation (RPA) see a spike while Business Process Management (BPM) might be considered as a more established approach for operational efficiency. This chapter describes the differences between these technologies, how they correlate and can complement each other, e.g., with the RPA Scout, and touches on the concept of a Digital Twin of an Organization (DTO).

   9. 8. Key Learnings

      Lars Reinkemeyer

      Abstract

      As a summary for Part I, this chapter comprises the ten key learnings on one page.

3. Part II

   1. Frontmatter

   2. 9. Siemens: Driving Global Change with the Digital Fit Rate in Order2Cash

      Gia-Thi Nguyen

      Abstract

      Global change that sticks in a complex organization is not an easy task, yet this has been achieved in only 1 year with a lean team of three people within Siemens Digital Industries. Using the innovative technology of Process Mining and equipped with frontline experience as well as a distinct mindset, automation and digitalization have leaped forward tremendously on a global scale. This is the call for action, because everyone can achieve the same, as the secret sauce is simply the combination of head, heart, and hands.

   3. 10. Uber: Process Mining to Optimize Customer Experience and Business Performance

      Martin Rowlson

      Abstract

      Process Mining has allowed Uber’s Customer Support teams to uncover insights across their processes that touch more than 700 cities across 65 countries on 6 continents. This capability allows Uber to understand variation in customer support and target large-scale multimillion dollar efficiency gains through process harmonization and increased customer satisfaction though global process benchmarking. Internally, Uber has used the power of Process Mining to help foster a culture of continuous improvement by providing a deeper level of business process visibility.

   4. 11. BMW: Process Mining @ Production

      Bringing Innovation to Production Processes and Beyond Patrick Lechner

      Abstract

      It has been about 3 years since BMW Group first started using Process Mining—besides several other fields—in an area where probably no other company had used it in such depth and with such an impact before: in manufacturing/production. When Nicolas Größlein and I introduced Process Mining at BMW Group with the great support of our former CIO, Klaus Straub, and our Vice President Connected Vehicle, Digital Backend and Big Data, Kai Demtröder, we were not driven by the desire to be particularly innovative or creative. Our main driver was to ensure world class production and the best possible quality of our cars for our customers. Because premium products require premium production processes!

      But is Process Mining at production really a new driver for innovation that can bring production processes to the next level? Or is it just a hype, a buzzword that will be replaced by the next one pretty soon? For BMW Group it has turned into a game changer, as it is shown in this use case.

   5. 12. Siemens: Process Mining for Operational Efficiency in Purchase2Pay

      Khaled El-Wafi

      Abstract

      Purchase-to-Pay (P2P) Process Mining has the objective to visualize process flows, identify process weaknesses, and support process improvements. It allows to monitor and manage any process in complex, global organizations in an unprecedented form and efficiency. This includes:

      • Visualization of P2P processes based on live data from SAP ERP systems. Time stamps for duration between relevant process steps.
      • Identification of P2P process weaknesses, e.g., with low degree of automation or multiple approval steps.
      • Support process improvements with immediate review of process adjustments and interactive remediation.

      In a nutshell, P2P Process Mining provides the answers to “how can I increase operational efficiency?” and “how can I optimize my working capital by reducing cash out towards external suppliers?” within the P2P process.

   6. 13. athenahealth: Process Mining for Service Integrity in Healthcare

      Corey Balint, Zach Taylor, Emily James

      Abstract

      athenahealth’s Technology-Enabled Services—Service Outcomes team is responsible for the optimization and scaling of healthcare administration transactions—one in which we complete millions of transactions each day on our customers’ behalf. athenahealth was looking to create technology tooling to gain a better understanding of total process workflows across these service lines—both legacy and new services included. With the legacy service lines, the processes were more set in place (well-known happy paths, built out homegrown tooling, known pain points and exceptions, etc.) and with the newer service, developments were shifting frequently. From all of this, athenahealth turned to Process Mining as the tool to gain clean process insights, to help improve our customer’s experience, and bring more value to their practice.

   7. 14. EDP Comercial: Sales and Service Digitization

      Ricardo Henriques

      Abstract

      Energias de Portugal (EDP) is aiming to become a digital utility provider. Process Mining plays a pivotal role in the digital transformation journey and helps to transform the sales to debt cycle including onboarding, billing, debt management, and customer care. It provides insights into real-world activities and customer behaviors that help to reshape the way to do business. Customer experience visualization and cross-silo transparency allows new ways to analyze actual processes and provides a foundation to boost business efficiency.

   8. 15. ABB: From Mining Processes Towards Driving Processes

      Heymen Jansen

      Abstract

      ABB is a global technology company in the sector of Power and Automation and is using Process Mining technology for improving its performance towards four key performance indicators: Care, Customer, Cost, and Cash. In order to get the maximum out of this, our ultimate goal is to use Process Mining not just for analytics purposes, but ultimately to use it as a technology, supporting the business in early identification of opportunities and risks, so moving from Mining processes towards Driving processes.

      Starting with lead times and on-time deliveries, Process Mining has expanded at ABB towards hundreds of analytics cases: from logistics to finance to manufacturing. This innovative technology is used extensively throughout the organization and supported with an elaborate governance model, assuring continuous improvements.

   9. 16. Bosch: Process Mining—A Corporate Consulting Perspective

      Christian Buhrmann

      Abstract

      As a large corporation and global player, Bosch has several Process Mining use cases implemented, in different business divisions, across different continents, and in various process types, e.g. P2P, O2C, production, and ticketing. The Bosch Process Mining setup can be characterized as a top-management-driven central approach. Planning and execution is steered by a cross-divisional team consisting of the in-house consultancy, central IT, and divisional coordinators of the participating business units.

   10. 17. Schukat: Process Mining Enables Schukat Electronic to Reinvent Itself

       Georg Schukat

       Abstract

       As a medium-sized distributor for electronic components, Schukat electronic must leverage technological innovation to stay competitive. Operational efficiency is crucial to stay competitive and secure a position as distributor in the value chain. For a better understanding of actual processes, Process Mining was deployed to gain transparency regarding actual order processing. Process Mining providing unprecedented transparency and insights, and Schukat is now amidst a data-driven, continuously changing process which has impact on the whole organization.

   11. 18. Siemens Healthineers: Process Mining as an Innovation Driver in Product Management

       Jutta Reindler

       Abstract

       Process Mining applications were adopted in the already productive business intelligence platform to support the constantly developing Computed Tomography (CT) product and service portfolio. The approach was driven by innovation management, recognizing the unique opportunity to optimize the CT product design and software workflow based on the real interaction between human and machine. For typical questions such as “how performant and user-friendly are the CT devices in clinical routine?”, “are programmed/predefined workflows accepted?” or “does the new innovative tablet control improve patient workflow?” Process Mining provides unprecedented transparency and thus the basis for strategic improvement.

   12. 19. Bayer: Process Mining Supports Digital Transformation in Internal Audit

       Arno Boenner

       Abstract

       Internal Audit at Bayer AG was an early adopter of the innovative Process Mining technology though—at first glance—an audit organization does not seem to be predestined to be the typical point of entry. Two factors favored this step: On the one hand, Bayer AG has been using SAP globally in its core processes for many years; this systemic homogeneity is not to be underestimated for the implementation of a Process Mining application. On the other hand, the majority of the audits performed by Internal Audit at Bayer AG, particularly in the commercial area, are strongly process driven. Although proven and extensive table-based toolboxes were available, it is very difficult to describe and interpret a global e2e process using tabular analyses and to audit it in a risk-oriented manner. Intense search discovered visual Process Mining as the perfect solution. In the start-up hall of the international IT-Fair CEBIT in 2012, the first meeting with an innovative young company took place. On the personal wish not to endure PowerPoint presentations, but only to see live data of real existing systems, it quickly became clear that the product came very close to what we had been looking for since many years. Our use case outlines the challenges of implementing Process Mining and how it drove the digital transformation of Internal Audit at Bayer.

   13. 20. Telekom: Process Mining in Shared Services

       Gerrit Lillig

       Abstract

       In 2016, Deutsche Telekom Services Europe decided to improve the analytics capabilities in one of the most important internal e2e processes. As a shared service center is typically focused on e2e process performance, one major attempt was the implementation of a Process Mining software in order to further improve the efficiency. The idea was to investigate our core processes, to find out where to shorten lead times, reduce complexity, and make the processes more efficient. During the implementation it then turned out that our shared service could benefit far more from this technology: We built operational steering capabilities, which led to concrete savings. We were able to bring our reporting and analytics capabilities on a new level. And we helped to position our shared services internally as a driver for digitalization. Of course, the road towards this was paved with a lot of challenges like workers’ council negotiations, internal constraints, and technical challenges—just to mention a few of them. At the end that all paid-off—we saved a lot of money in our operations, were able to establish a new digital steering solution, and we now have a flexible and powerful reporting solution at hand.

4. Outlook: Future of Process Mining

   1. Frontmatter

   2. 21. Academic View: Development of the Process Mining Discipline

      Wil van der Aalst

      Abstract

      This chapter reflects on the adoption of traditional Process Mining techniques and the expansion of scope, discussed with five trends. An inconvenient truth explains why—despite considerable progress in Process Mining research—commercial tools tend to not use the state-of-the-art and make “short-cuts” instead that seem harmless at first, but inevitably lead to problems at a later stage. Seven novel challenges provide an outlook on open research topics. In a final appeal, the term of “process hygiene” is coined to make Process Mining the “new normal.”

   3. 22. Business View: Towards a Digital Enabled Organization

      Lars Reinkemeyer

      Abstract

      The business outlook is written by the editor and considers the dimensions business expectations, potentials and benefits, technological developments, market trends, and developments of a digital workforce. The chapter has been structured on a timeline from present trends to short-, mid-, and long-term outlook, concluding in a Vision of a Digital Enabled Organization. The chapter aims to initiate thought processes, stir discussions, stimulate technical developments, and further enhance the power of Process Mining.

5. Backmatter