The book is written by practitioners to share industry best practices and hands-on experiences. It provides more than 200 pages with guidance how to start a project, key learnings and challenges, pitfalls & failures. Twelve operational use cases are presented by experts from multiple industries and functions.
Lars Reinkemeyer (Editor)

“If your organization cares about operational performance and has a culture that thrives on transparency, Process Mining is the answer to your prayers. And there is no better source than this book to learn about what Process Mining is, how it’s being used in leading companies, and where it might go in the future.”
Thomas H. Davenport
The book is written by practitioners to share industry best practices and hands-on experiences. It providers more than 250 pages with guidance how to start a project, key learnings and challenges, pitfalls & failures. Twelve operational use cases are presented by experts from multiple industries and functions.
Lars Reinkemeyer (Editor)
“If your organization cares about operational performance and has a culture that thrives on transparency, Process Mining is the answer to your prayers. And there is no better source than this book to learn about what Process Mining is, how it’s being used in leading companies, and where it might go in the future.”
Thomas H. Davenport

Chapters & Abstracts (Click2Read)

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.

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 such as quick start, expectation management and which process to start with are crucial.

Purpose implies a clear understanding, 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.

While innovative IT tools can be 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.

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 different 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.

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 as well as failures which have been experienced. Samples range from data availability to process conformance checking and shall help the reader to avoid similar experiences.

With digital transformation as 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 traditional 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).

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

Global change that sticks in a complex organization is not an easy task, yet this has been achieved in only one 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 a distinct mindset, automation and digitalization had 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.

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 six continents. This capability allows Uber to understand variation in customer support and target large scale multi-million 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.

It has been about three 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 for the example of production processes.

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 global and complex 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.

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.

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 dept cycle includingonboarding, billing, debt management and customer care. It provides insights in real-world activities and customer behaviorsthat 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.

ABB is a global technology company in the sector of Power and Automation and is using Process Mining technology for improving its performance towards fourkeyperformance 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.

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

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, Schukat is now amidst a data driven continuous changing process which affects the whole organization.

Process Mining applications were adopted in the already productive business intelligence platformto 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.

Internal Audit at Bayer AG was an early adopter of the innovative Process Mining technologythough - 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.

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 up 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 have now a flexible and powerful reporting solution at hand.

Written by Wil van der Aalst, this chapterreflects on the adoption of traditional process mining techniquesand the expansion of scope, discussed with five trends.An inconvenient truth explains, why – despite a 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, Wil coins the term of “Process hygiene” to make Process Mining the “new normal”.

The business outlook is written by the editor andconsiders 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.

10 Key Learnings

#1    Transparency is a prerequisite for digital Transformation
#2    Process Mining allows full Transparency based on Event Logs
#3    Purpose, People and Processtraces are essential (“3Ps”)
#4    Start with Simplicity to fight Complexity
#5    Purpose comes First
#6    It’s all about the People
#7    Processtraces are comparable to raw Oil
#8    Provide an open platform and build a strong community
#9    Fail fast or Scale fast

#10  Process Mining and RPA can complement each other

Testimonials

“This book, written by practitioners for practitioners, provides an excellent overview on Process Mining principles and a broad variety of use cases. Each practitioner shares individual experiences and the multitude of outlooks from practitioners and academics will foster future development, innovations andincrease business value. Thus, leaving Process Mining as an academic and innovative field that could well be one of the key technologies driving the Digital Transformation.“
Hannes Apitzsch (CEO Global Business Services, Siemens AG)

“Important in the Process Mining environment is the how and what of the implementation. This book with many pragmatic and operative examples gives a guideline and a framework for the utilization in different branches and organizations. It shows all of us, that this new technology will be not a short time hype. It will be a foundation technology for digitalization of organizations. Take this book as a basic description of Process Mining for the next years. Get advantages out of these examples.”
Klaus Straub (CIO: 2014-2019 BMW, 2004-2012 AUDI, 2002-2004 SiemensVDO)
“If your organization cares about operational performance and has a culture that thrives on transparency, Process Mining is the answer to your prayers. And there is no better source than this book to learn about what Process Mining is, how it’s being used in leading companies, and where it might go in the future.”
Thomas H. Davenport (Distinguished Professor, Babson College and Research Fellow, MIT Initiative on the Digital Economy); Author of Process Innovation, Competing on Analytics, and The AI Advantage
““Unlike the traditional plan-execution process improvement, Process Mining allows full transparency of actual processes and activities. Process Mining in Action describes principles, challenges and learnings from years of practice.”
Seungjin Whang (Professor of Operations, Information & Technology at Stanford Graduate School of Business)
“This is a timely book that presents operational experiences and brings Process Mining application problems to academic research communities. It inspires researchers to further develop frameworks and techniques to tackle broader process analytics challenges over multiple application domains in order to complement the fast growing operational community.”
Jianwen Su (Professor of Computer Science at University of California, Santa Barbara)

Sustainability

In addition to economic value Process Mining can also contribute to ecologic benefits. As environmental challenges prevail it is time for a sustainability revolution and technological innovations such as
Process Mining must play a significant role, e.g. to identify process inefficiencies, reduce energy consumption and support the reduction of material waste.
Process Mining can support the transition towards a more efficient and sustainable economy for example in the field of supply chain by allowing to increase transport
efficiency, avoidance of empty transports, optimization of Inventories and reduction of waste. Insights are also used for an optimized transport modal-change, thus leading not only to economic but also ecologic value.
Uber: Traditional reporting methods such as scorecards only go so deep in terms of uncovering process inefficiencies. They typically notify someone when a key metric degrades. Process Mining allows us
to uncover unknown process wastes that scorecard metrics wouldn’t uncover. Such issues like inefficient contact handling due to multiple hand-offs and typical LEAN transport wastes.
Process Mining can support the transition towards a more efficient and sustainable economy for example in the fiSiemens O2C: Process Mining will continue to emerge into such pressing matters as
sustainability as well. New business models will arise around the reduction of waste and other inefficiencies of resources, be it energy, CO2 emission or plastic usage. Just as companies like the Plastic Bank is turning plastic into cash for the poor, Process Mining can help such companies to monitor the flow of plastic cradle to cradle in order to better understand where in the value chain waste can be reduced, e.g. by improving recycling infrastructures, less consumption by alternative products or the usage of recycled plastic. I personally see Process Mining as an independent and universal companion to create data-driven but process-centric transparency on any use case, yet especially in the still underdeveloped area of our most pressing questions around sustainability. It would be my personal wish to see more and more concrete use cases around efficiency of monetary activities from donations or grants; usage of natural resources or consumption of waste; or achievement of sustainability development goals.eld of supply chain by allowing to increase transport efficiency, avoidance of empty transports, optimization of Inventories and reduction of waste. Insights are also used for an optimized transport modal-change, thus leading not only to economic but also ecologic value.
EDP Comercial, the Portuguese electricity and gas seller from group EDP, that is committed to creating a more sustainable world, is using Process Mining to kickstart a digital transformation. With 74%
of its generation capacity coming from renewable resources, EDP offers its customers energy solutions that are digital, decentralized, and decarbonized. Using Process Mining, EDP Comercial analyzed over five million transactions and one million customer-facing operations with newfound transparency, enabling to pinpoint root causes of issues that could be solved to optimize operations.
Schukat: Many organizations are nowadays orientated to minimize their negative impact on nature and environment by reducing their energy and resource consumptions. A Process Mining system able to do
process cost calculations could do energy and resource calculations as well, either based on direct measurements by IoT devices or on external data. Thus it will enable us to get a differentiated and detailed view on the amounts of consumption for each and every process step. When having very broad process models, far reaching in- and outbound in the supply chain, we can attribute and balance consumptions. These insights will be an optimal, facts-based foundation for actions to reduce them
A Sustainability Revolution can be supported by technological innovations such as Process Mining, but also affects everybody. Think about process inefficiencies in your immediate environment
and how better process efficiency could support sustainability: from traffic congestions to waiting times in hospitals, from wasted times in call center queues to waiting times for bureaucratic decisions, from delayed goods deliveries to delayed flight arrival. Process inefficiencies are omnipresent, producing friction, waste and avoidable emission. Understanding the e2e processes allows to track down inefficiencies and reduce waste in time and resources. While SCM is probably the primary field, where Process Mining can support a sustainability revolution, CRM and other functions can equally support as ecological driver. The management of resources in ERP systems (financials, materials, assets and HR) will become more efficient with Process Mining, thus allowing to optimize scarce resources. In a world with more than 7.5 billion people and increasing issues due to limited resources this may become a strong purpose.

Authors

Gia-Thi Nguyen
Siemens AG, Digital Industries, Head of Operational Excellence
Martin Rowlson
Uber, Global Head of Process Excellence, Community Operations
Dr. Patrick Lechner
BMW Group, Head of Process Mining & Robotic Process Automation (RPA)
Khaled El-Wafi
Siemens AG, P2P Service Manager
Corey Balint
Athenahealth, Business Process Improvements Manager, Process Mining Insights
Ricardo Henriques
EDP Comercial, Deputy Director of Business Enablement & Transformation
Heymen Jansen
ABB Group VP Global Business Services – Head of Advanced Process Analytics
Christian Buhrmann
Bosch Group, Director Bosch Management Consulting
Georg Schukat
Schukat electronic, Co-owner and Co-CEO
Jutta Reindler
Siemens Healthineers, Innovation Manager for Business Intelligence
Arno Boenner
Bayer AG, Head of Audit Intelligence of Internal Audit
Gerrit Lillig
Telekom Deutschland GmbH, Head of program Digital and Agile Transformation of Finance and VP Steering Instruments Consumer business
Prof. Dr. Ir. Wil van der Aalst
RWTH Aachen University

Editor

Dr Lars Reinkemeyer is a visiting scholar at the University of California, Santa Barbara and senior executive of Siemens AG. Since 2014 he leveraged Process Mining technology in close collaboration with Siemens’ functional departments like sales, logistics, procurement, accounting and has established a global community in excess of 6.000 active users around the world, supporting the company’s digital transformation. As head of the Global Process Mining Services at Siemens Corporate IT he has built a team of experts located in Germany, Portugal and India providing cross-functional Process Mining services.

Dr. Reinkemeyer joined Siemens AG in 1994, right after he earned a Master degree in Business Administration and a PhD from the University of Cologne, from which he graduated summa cum laude. He joined Siemens as Product- and Regional Manager and was delegated to Siemens Australia as International Account Manager in 1996. In 1998, he signed on as General Manager at Oztrak Europe GmbH, gaining some hands-on start-up experiences. In 2000, he joined Atoss Software AG as a Director of International Sales. Dr. Reinkemeyer rejoined Siemens AG in 2001, where he held various international leadership positions in strategy, compliance and IT. He is a guest speaker at Stanford Graduate School of Business and regular speaker on international conferences.