Process Mining and Official Statistics - CBS
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Johan Lammers from Statistics Netherlands has been a business analyst and statistical researcher for almost 30 years. In their business, processes have two faces: You can produce statistics about processes and processes are needed to produce statistics. As a government-funded office, the efficiency and the effectiveness of their processes is important to spend that public money well. Johan takes us on a journey of how official statistics are made. One way to study dynamics in statistics is to take snapshots of data over time. A special way is the panel survey, where a group of cases is followed over time. He shows how process mining could test certain hypotheses much faster compared to statistical tools like SPSS.
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Feature Engineering for Electronic Health Record Systems
Feature Engineering for Electronic Health Record SystemsProcess mining Evangelist Oak Ridge National Laboratory (ORNL) is a leading science and technology laboratory under the direction of the Department of Energy.
Hilda Klasky is part of the R&D Staff of the Systems Modeling Group in the Computational Sciences & Engineering Division at ORNL. To prepare the data of the radiology process from the Veterans Affairs Corporate Data Warehouse for her process mining analysis, Hilda had to condense and pre-process the data in various ways. Step by step she shows the strategies that have worked for her to simplify the data to the level that was required to be able to analyze the process with domain experts.
How to Set Up Process Mining in a Decentralized Organization?
How to Set Up Process Mining in a Decentralized Organization?Process mining Evangelist
The history of a.s.r. begins 1720 in “Stad Rotterdam”, which as the oldest insurance company on the European continent was specialized in insuring ocean-going vessels — not a surprising choice in a port city like Rotterdam. Today, a.s.r. is a major Dutch insurance group based in Utrecht.
Nelleke Smits is part of the Analytics lab in the Digital Innovation team. Because a.s.r. is a decentralized organization, she worked together with different business units for her process mining projects in the Medical Report, Complaints, and Life Product Expiration areas. During these projects, she realized that different organizational approaches are needed for different situations.
For example, in some situations, a report with recommendations can be created by the process mining analyst after an intake and a few interactions with the business unit. In other situations, interactive process mining workshops are necessary to align all the stakeholders. And there are also situations, where the process mining analysis can be carried out by analysts in the business unit themselves in a continuous manner. Nelleke shares her criteria to determine when which approach is most suitable.
Analyzing the Customer Lifecycle - Total Gas & Power
Analyzing the Customer Lifecycle - Total Gas & PowerProcess mining Evangelist Analyzing the customer journey is all about shifting the focus from an internal department view to a customer perspective. To achieve that, Business Intelligence analyst Carmen Vermeer and Marketing Manager Noortje Groenendaal used process mining for their analysis of the customer lifecycle at Total.
The departments who are responsible for customer service, billing, sales, and marketing, are all involved in this customer lifecycle. Instead of looking at these individual departments one by one, Carmen and Noortje determined what a successful and what an unsuccessful customer journey looks like from a customer’s point of view. Then, they analyzed the effect of actions that were taken to increase customer satisfaction and the timing of these actions.
Theory of Constraints in Parts Repair - Lufthansa
Theory of Constraints in Parts Repair - LufthansaProcess mining Evangelist Christian Pohle is Head of Process at Lufthansa Technik. His process mining journey started off with an unusual situation: They had great data. Their ERP system collects very detailed and accurate information about all the steps that happen in the parts repair process. So, they were in an excellent position to use that data for their process mining analysis.
With his background in Lean Six Sigma, Christian could use the lean methodologies of continuous improvement and combine them with process mining. One interesting tool that they used is the Theory of Constraints, which is a technique that focuses on finding the biggest bottleneck and resolving it, then finding the next-biggest bottleneck and resolving it, etc.
Instead of working on individual transformation projects, they used an Agile approach to implement and review the improvements in sprints. This led to an openness and honesty that were appreciated throughout the company. In his remarkable story, Christian brings to life how process mining helps to move discussions “from the belly to the brain” through objectification of gut instinct.
Responsible Data Science for Process Miners
Responsible Data Science for Process MinersProcess mining Evangelist Wil van der Aalst gave the closing keynote at camp. He started with giving an overview of the progress that has been made in the process mining field over the past 20 years. Process mining unlocks great potential but also comes with a huge responsibility. Responsible data science focuses on positive technological breakthroughs and aims to prevent “pollution” by “bad data science”.
Wil gave us a sneak peek at current responsible process mining research from the area of ‘fairness’ (how to draw conclusions from data that are fair without sacrificing accuracy too much) and ‘confidentiality’ (how to analyze data without revealing secrets). While research can provide some solutions by developing new techniques, understanding these risks is a responsibility of the process miner.
Process Mining Meets Football - JADS (Hadi Sotudeh)
Process Mining Meets Football - JADS (Hadi Sotudeh)Process mining Evangelist Sometimes, an application of process mining comes along that nobody thought of before. Hadi Sotudeh, PDEng student at JADS, had such an example when he applied process mining to data from the 2018 World Cup in football.
After transforming the data into an event log suitable for process mining, he was especially interested in how a football team possesses the ball on the pitch. This would give coaching staff great insights into interesting patterns of play to develop counter strategies for an opponent, or for a team to learn from mistakes.
The challenge is that the football interactions do not follow a typical (standard) process. Therefore, finding the right perspective is not easy. Hadi shows that there is not just one perspective, but that the same data can be molded to explore many different angles. Each of these perspectives can give different insights. For example, next to sequences of types of actions, he also looked at interactions between individual players, zones in the field, and patterns for particular outcomes (e.g., goal or throw-in).
Process Mining in Logistics - Vanderlande
Process Mining in Logistics - VanderlandeProcess mining Evangelist Vanderlande is the global market leader for value-added logistic process automation at airports, and in the parcel market. The company is also a leading supplier of process automation solutions for warehouses.
Boris Nikolov is a Process Improvement Engineer at Vanderlande. He supports customers by solving problems and by implementing new systems for baggage handling or parcel sorting and routing.
One of the customers in the parcel distribution center called Boris to solve a problem of recirculating parcels. Normally, parcels entering the system are scanned and routed to the right locations. However, a percentage of parcels kept circulating. Using the standard checks, he was not able to find the problem quickly. So, he tried process mining and found out that the root cause was that the lookup of the location of the parcels in the ERP was delayed. He also used process mining in the design stage of new baggage handling systems for airports.
Process wind tunnel for improving business processes
Process wind tunnel for improving business processesProcess mining Evangelist With roots that trace back to 1919, AIG is a global insurance company with operations in more than 80 countries and jurisdictions. Sudhendu Rai is a Lead Scientist and Head of Data-Driven Process Optimization in the COO Office of AIG’s Investments organization.
Sudhendu presents their ‘Process Wind Tunnel’ framework to evaluate and optimize process structure and parameters prior to committing to a final process design. In the same way as wind tunnels are used to test the aerodynamics of a physical object, a discrete-event simulation can be used to explore alternative “What-If” scenarios for a process without implementing them (yet) in the real world.
A big problem of using simulation is that the initial model needs to reflect the reality as closely as possible. Process mining is a great way to discover the key steps and process flows that need the be part of the simulation model. Furthermore, process mining helps to determine the probabilities of transitions and the distribution of the process times to populate the model. Based on this initial model, alternative process re-designs of the current process can be tested in the simulation tool. After finding the best scenario, Sudhendu could reduce the cycle time from 12 days to 5 days, increasing the throughput by over 30%.
Building Operational Profiles for Philips MRI Machines
Building Operational Profiles for Philips MRI MachinesProcess mining Evangelist Philips Healthcare is a global maker of many healthcare products, among which are imaging systems such as X-Ray, CT, Fluoroscopy and Magnetic Resonance Imaging (MRI) machines. ESI is an independent research organisation for high-tech embedded systems design and engineering.
Carmen Bratosin is a research fellow at ESI and Mark Pijnenburg is a Clinical Verification Lead at Philips Healthcare. Mark and Carmen showed how process mining can be used to analyze the system usage of an MRI machine. Understanding the actual usage patterns in the field is especially interesting to improve the system requirements and to increase the test coverage based on real-life behavior for these machines.
Preparing the data for process mining is not easy, because the logging produced by the MRI machines is only available on a technical log level used for debugging. Furthermore, each physician has their own preferences regarding the machine setup for certain exams, which adds to the complexity. They started by selecting the key activities in the technical log and then aligned them with the user interface elements. Finally, they matched the logged events with the steps described by the American College of Radiology to get them on the abstraction level that a radiology expert would understand. In this way, they were able to compare the actual usage of the MRI system with the expected (and designed) behavior.
How to make impact with process mining? - PGGM
How to make impact with process mining? - PGGMProcess mining Evangelist PGGM is a non-profit cooperative pension administration organization. They are founded by social partners in the care and welfare sector and serve four million participants.
Bas van Beek is a process consultant and Frank Nobel is a process and data analyst at PGGM. Instead of establishing process mining either in the data science corner or in the Lean Six Sigma corner, they approach every process improvement initiative as a multi-disciplinary team with people from both groups.
The nature of each initiative can be quite different. For example, some projects are more focused on the redesign or implementation of an IT solution. Others require extensive involvement from the business to change the way of working. In a third example, they showed how they used process mining for compliance purposes: Because they were able to demonstrate that certain individual funds actually follow the same process, they could group these funds and simplify the audit by using generic controls.
Process Mining as Enabler for Digital Transformations
Process Mining as Enabler for Digital TransformationsProcess mining Evangelist Raiffeisen Bank International (RBI) is a leading Retail and Corporate bank with 50 thousand employees serving more than 14 million customers in 14 countries in Central and Eastern Europe.
Jozef Gruzman is a digital and innovation enthusiast working in RBI, focusing on retail business, operations & change management. Claus Mitterlehner is a Senior Expert in RBI’s International Efficiency Management team and has a strong focus on Smart Automation supporting digital and business transformations.
Together, they have applied process mining on various processes such as: corporate lending, credit card and mortgage applications, incident management and service desk, procure to pay, and many more. They have developed a standard approach for black-box process discoveries and illustrate their approach and the deliverables they create for the business units based on the customer lending process.
Process Mining Machine Recoveries to Reduce Downtime
Process Mining Machine Recoveries to Reduce DowntimeProcess mining Evangelist
ASML provides chip makers with everything they need to mass-produce patterns on silicon, helping to increase the value and lower the cost of a chip. The key technology is the lithography system, which brings together high-tech hardware and advanced software to control the chip manufacturing process down to the nanometer. All of the world’s top chipmakers like Samsung, Intel and TSMC use ASML’s technology, enabling the waves of innovation that help tackle the world’s toughest challenges.
The machines are developed and assembled in Veldhoven in the Netherlands and shipped to customers all over the world. Freerk Jilderda is a project manager running structural improvement projects in the Development & Engineering sector. Availability of the machines is crucial and, therefore, Freerk started a project to reduce the recovery time.
A recovery is a procedure of tests and calibrations to get the machine back up and running after repairs or maintenance. The ideal recovery is described by a procedure containing a sequence of 140 steps. After Freerk’s team identified the recoveries from the machine logging, they used process mining to compare the recoveries with the procedure to identify the key deviations. In this way they were able to find steps that are not part of the expected recovery procedure and improve the process.
Skills for Successful Process Scientists
Skills for Successful Process ScientistsProcess mining Evangelist The final speaker at Process Mining Camp 2018 was Wil van der Aalst, the founding father of process mining. In his closing keynote, Wil talked about the updated skill set that process and data scientists need today. Since process mining research was starting up in Eindhoven in the late 90s, the availability of suitable data has increased tremendously, which makes it even more important that this data can and will be used in an appropriate and responsible manner.
This requires dedicated capabilities from the process miner in each stage of the analysis pipeline: Processing and analyzing data, being responsible about the effects on people, and on business models. When you look for people who are skilled in all of these technical areas, as well as in soft skills like communication and ethics, you start looking for (as they would say in the Netherlands) a “sheep with 5 legs”, or something that is very rare. Becoming a data scientist requires a lot of effort to learn all the skills that are needed to live up to these high expectations.
As ambassadors of process mining, we also have the responsibility to use the right terms. Wil sees a clear a distinction between Artificial Intelligence (AI), machine learning, and data mining. At the same time, one could argue that process mining is data mining, but the underlying techniques are very different. So, saying that process mining is part of data mining, or AI, doesn’t make any sense.
There are incredible expectations around AI and Big Data, which is very dangerous as we have seen in past “AI winters”. We should be careful not to overpromise and try to be realistic. The incredible successes of machine learning techniques like deep learning are, for example, still limited to very specific fields.
Some in the media and big technology companies use terms like Artificial Intelligence, Machine Learning, and Deep Learning interchangeably. They might argue that you don’t need process mining as you can just put an event log into a deep neural network and a process model will come out. There is, however, not one deep learning algorithm that can discover a process model. Instead, when we look at process mining it combines the fields and methods of ‘process science’ and ‘data science’. This makes it even more challenging for us to cover all required skills.
But do you, as a professional, need to know how a car works internally in order to drive it? It depends on what you want to accomplish. For example, if you need to drive fast around the Nurburg Ring, it can be very useful. Also, if you need to select a car then it would certainly be useful to know about its internals. Process mining is a relatively young technology. Therefore, it is useful to know how it works in order to select the right tool, and to use it to maximum effect.
So what kind of skills do you need as a process miner? You need to be able to extract and clean the data, spend time on the analysis, and interpret the results. This is not easy.
Process Mining and Jira - Air France KLM
Process Mining and Jira - Air France KLMProcess mining Evangelist
The sixth speaker at Process Mining Camp 2018 was Marc Tollens, a digital product owner at Air France KLM. In order to compete in the aviation market, KLM focuses on providing an excellent customer experience. They adopted the agile methodology to be able to reduce the time to introduce new touch points in the traveler’s journey. The performance of the agile teams is crucial to get the most out of each sprint.
As a Sunday afternoon project, Marc collected data from Jira, a project management software for (agile) software development, to see how process mining could be applied to help the teams learn from each other. Surprisingly, the flow of each team was quite different.
Marc started comparing the flows of the three teams to identify key differences in behavior and the resulting effects. In this way he could see if a team was able to deliver what they promised and whether they started testing too early or too late. He shared his observations with the teams during the retrospective and returned for the next sprint to see how the improvement worked out.
Understanding Complex Development Processes
Understanding Complex Development ProcessesProcess mining Evangelist The fifth talk at Process Mining Camp was given by Olga Gazina and Daniel Cathala from Euroclear. As a data analyst at the internal audit department Olga helped Daniel, IT Manager, to make his life at the end of the year a bit easier by using process mining to identify key risks.
She applied process mining to the process from development to release at the Component and Data Management IT division. It looks like a simple process at first, but Daniel explains that it becomes increasingly complex when considering that multiple configurations and versions are developed, tested and released. It becomes even more complex as the projects affecting these releases are running in parallel. And on top of that, each project often impacts multiple versions and releases.
After Olga obtained the data for this process, she quickly realized that she had many candidates for the caseID, timestamp and activity. She had to find a perspective of the process that was on the right level, so that it could be recognized by the process owners. In her talk she takes us through her journey step by step and shows the challenges she encountered in each iteration. In the end, she was able to find the visualization that was hidden in the minds of the business experts.
Controlling Financial Processes at a Municipality
Controlling Financial Processes at a MunicipalityProcess mining Evangelist
The fourth speaker at Process Mining Camp 2018 was Wim Kouwenhoven from the City of Amsterdam. Amsterdam is well-known as the capital of the Netherlands and the City of Amsterdam is the municipality defining and governing local policies. Wim is a program manager responsible for improving and controlling the financial function.
A new way of doing things requires a different approach. While introducing process mining they used a five-step approach:
Step 1: Awareness
Introducing process mining is a little bit different in every organization. You need to fit something new to the context, or even create the context. At the City of Amsterdam, the key stakeholders in the financial and process improvement department were invited to join a workshop to learn what process mining is and to discuss what it could do for Amsterdam.
Step 2: Learn
As Wim put it, at the City of Amsterdam they are very good at thinking about something and creating plans, thinking about it a bit more, and then redesigning the plan and talking about it a bit more. So, they deliberately created a very small plan to quickly start experimenting with process mining in small pilot. The scope of the initial project was to analyze the Purchase-to-Pay process for one department covering four teams. As a result, they were able show that they were able to answer five key questions and got appetite for more.
Step 3: Plan
During the learning phase they only planned for the goals and approach of the pilot, without carving the objectives for the whole organization in stone. As the appetite was growing, more stakeholders were involved to plan for a broader adoption of process mining. While there was interest in process mining in the broader organization, they decided to keep focusing on making process mining a success in their financial department.
Step 4: Act
After the planning they started to strengthen the commitment. The director for the financial department took ownership and created time and support for the employees, team leaders, managers and directors. They started to develop the process mining capability by organizing training sessions for the teams and internal audit. After the training, they applied process mining in practice by deepening their analysis of the pilot by looking at e-invoicing, deleted invoices, analyzing the process by supplier, looking at new opportunities for audit, etc. As a result, the lead time for invoices was decreased by 8 days by preventing rework and by making the approval process more efficient. Even more important, they could further strengthen the commitment by convincing the stakeholders of the value.
Step 5: Act again
After convincing the stakeholders of the value you need to consolidate the success by acting again. Therefore, a team of process mining analysts was created to be able to meet the demand and sustain the success. Furthermore, new experiments were started to see how process mining could be used in three audits in 2018.
Mining a Global Trade Process with Data Science - Microsoft
Mining a Global Trade Process with Data Science - MicrosoftProcess mining Evangelist
The third speaker at Process Mining Camp 2018 was Dinesh Das from Microsoft. Dinesh Das is the Data Science manager in Microsoft’s Core Services Engineering and Operations organization.
Machine learning and cognitive solutions give opportunities to reimagine digital processes every day. This goes beyond translating the process mining insights into improvements and into controlling the processes in real-time and being able to act on this with advanced analytics on future scenarios.
Dinesh sees process mining as a silver bullet to achieve this and he shared his learnings and experiences based on the proof of concept on the global trade process. This process from order to delivery is a collaboration between Microsoft and the distribution partners in the supply chain. Data of each transaction was captured and process mining was applied to understand the process and capture the business rules (for example setting the benchmark for the service level agreement). These business rules can then be operationalized as continuous measure fulfillment and create triggers to act using machine learning and AI.
Using the process mining insight, the main variants are translated into Visio process maps for monitoring. The tracking of the performance of this process happens in real-time to see when cases become too late. The next step is to predict in what situations cases are too late and to find alternative routes.
As an example, Dinesh showed how machine learning could be used in this scenario. A TradeChatBot was developed based on machine learning to answer questions about the process. Dinesh showed a demo of the bot that was able to answer questions about the process by chat interactions. For example: “Which cases need to be handled today or require special care as they are expected to be too late?”. In addition to the insights from the monitoring business rules, the bot was also able to answer questions about the expected sequences of particular cases. In order for the bot to answer these questions, the result of the process mining analysis was used as a basis for machine learning.
Process Mining at Deutsche Bank - Journey
Process Mining at Deutsche Bank - JourneyProcess mining Evangelist Niyi started with process mining on a cold winter morning in January 2017, when he received an email from a colleague telling him about process mining. In his talk, he shared his process mining journey and the five lessons they have learned so far.
Deciding Surgery Room Allocations in a Hospital
Deciding Surgery Room Allocations in a HospitalProcess mining Evangelist The first speaker at Process Mining Camp 2018 was Fran Batchelor from UW Health in the United States. Fran is a Nursing Informatics Specialist who supports the surgical services at three of UW Health’s hospitals. She used process mining to analyze the flow of urgent and emergent surgical cases added to the schedule. What did she find?
The operations for most cases are scheduled and planned well in advance. For these patients the room is being prepared and the patient is transported to the room and after the operation the patient is transported to the recovery room. At the hospital they have 27 operation rooms available.
There are other patients that require urgent care, for which additional ‘hold’ rooms are reserved. However, sometimes there are more emergent cases than available operating rooms, such that schedules need to be adjusted. The smooth flow is critical for emergent cases and the challenge is to allocate the operating space for these patients.
At the hospital, two additional operation rooms were to be opened for the emergent cases and a project was started to determine how these rooms could be best allocated. Neurosurgery had made a case for all available new space and was in line to receive it. However, Peripheral Vascular also voiced a need. A team was assembled to provide information regarding the decision making. How many add-on cases are there without a dedicated hold room being available? How are they moving through the process and are they still meeting the internal performance metrics?
From the database the team extracted the data for each step in the process and developed the logic to identify the add-on cases. By visualizing the process using process mining they were able to see how add-on cases behave. They were able to see that 70% of the cases were scheduled and of the 30% unscheduled cases 12% didn’t have dedicated hold rooms.
When looking at the flow of the add-on cases, they realized that not all cases have the same urgency. By giving the cases a priority, they were able to distinguish between the different levels of urgency. Especially when focusing on the emergent cases of Neurosurgery and Peripheral Vascular they found that 43% of the cases that took longer than 1 hour to get to the operating room belonged to the Peripheral Vascular surgery (a higher volume compared to Neurosurgery). So, it was most logical to allocate the additional rooms for both of these procedures.
Process mining reduced the political and emotional components when taking these decisions. By looking at the data and the visualization it was possible to tell the story more easily. Without process mining it would not have been possible to make such a clear-cut case and the decision would have been made differently.
However, it was not easy and took two years to get to this point. First of all, it was a challenge to set up the project and get access to the right data.
Mining the Customer Journey, accelerating New Product Introduction
Mining the Customer Journey, accelerating New Product IntroductionProcess mining Evangelist Mick is a supply chain manager at Veco, a precision metal manufacturer. With process mining, Mick found a technique to radically accelerate the New Product Development cycle and convert this to an opportunity for faster growth.
Veco had started using process mining three years ago as an addition to their Lean Six Sigma methodology, which helped them to reduce the lead time of production orders significantly. However, you often see that when you solve one problem, you uncover another.
As part of their growth strategy, Veco wanted to expand to new and existing customers outside of their existing part portfolio. When customers request a new product that they have not ordered before (so, it does not yet exist in the product catalogue), additional steps take place in the sales process: A sample first needs to be engineered, produced, and shipped to the customers before larger quantities are ordered.
To be able to close new deals quickly, Veco has the ambition to produce and deliver these samples within 15 days. However, by extracting data from the CRM and ERP system and analyzing it with process mining, they saw that it in fact took on average 52 days to deliver the samples to the customers. The longer the sample production process takes, the higher the risk that they may be losing these orders to the competition.
To understand the root cause of the delays, Mick and his team identified a new process ‘From Engineering to Order’ that was not managed before. In contrast to the production process of their regular catalogue parts, these sample parts required the involvement of the engineering department before they could be produced.
By involving members from both engineering and production, a “fast lane” was created for the engineering and production of these samples to speed up the ‘Engineering to Order’ process. By experimenting with this new process for a few weeks they were able to get “jaw-dropping” results. Within weeks, the director gave them the green light to implement this new way of working as the standard process, paving the way for future growth.
Lean & Process Mining - have fun and add value at the same time
Lean & Process Mining - have fun and add value at the same timeProcess mining Evangelist Roel Blankers and Wesley Wiertz work at VGZ. The health insurance cooperation VGZ is using operational visual management to track process performance every day. Lean has been adopted as the problem-solving methodology.
However, it took Roel a lot of time to map the existing processes during brown paper sessions before they were able to understand the real problem. When they analyzed the non-routine dental care claims process they decided to try a different approach: Process mining.
After extracting and preparing the data, they discovered that this process took 28 days to complete. In the discovered process maps they could see that a lot of the requests were being forwarded from the administrative teams to the medical advisors. Just by sharing the discovered process and asking why these claims needed to be forwarded to advisors, they found that a lot of these cases could actually be handled by the administrative teams. Therefore, it was proposed to set up an experiment to transfer the knowledge between the medical advisors and the administrative teams. Using process mining, they were able to validate that this new approach has in fact improved the lead time by almost 40%.
With process mining they were able to identify the problem quickly. They got a fact-based insight, which prevented them from jumping to conclusions. Process mining is a great addition to the Lean toolbox and a fun way to collaborate with domain experts to find opportunities to improve.
Building Bridges between Data and Business Value
Building Bridges between Data and Business ValueProcess mining Evangelist Gijs Jansen works as a business intelligence specialist at Essent, a large energy supplier in the Netherlands. One day he was asked to calculate the “snake plot” and “ping-pong factor” for the process of becoming and being a customer. He had no clue how to approach this, but he was eager to solve this problem.
The business intelligence department is responsible to report Key Performance Indicators (KPIs) for these processes. However, reporting a “snake plot” was something different compared to the existing reports they delivered. It required a deeper insight into how the customer passed though the different departments and the number of times each department touched each request.
A colleague suggested that he could try process mining. Gijs first started a small process mining project to analyse the credit insurance process. It was a simple process that was expected to be automated for most cases. However, the process mining results showed the contrary: Gijs found that disputes on contracts required a manual intervention for many cases.
This experience gave him the confidence to attack the “snake plot” and “ping-pong factor” problem. It took some effort but Gijs was able to extract the data for the customer process and transform it into the right process mining format. He then analyzed the process maps and saw how each customer request was handled, which departments were involved, and how often each request was touched by which employee. This resulted into a new set of KPIs that were discussed monthly to reduce the lead time and to limit the number of touches.
Process Mining in Internal Audit - CZ use case
Process Mining in Internal Audit - CZ use caseProcess mining Evangelist Wilco Brouwers and Dave Jansen from CZ share their process mining experience as IT auditors. Also auditors see that the digital transformation is slowly impacting their way of working. Dave and Wilco believe that data analysis skills will become increasingly important for future IT auditors – not only to be more efficient, but also to be more effective.
As the frontrunners within their team, Wilco and Dave have developed a new approach for auditing their digital processes of the future. Process mining plays an important role in this new auditing approach. With concrete examples, they showed where they see differences compared to the traditional audit approach in the preparation, fieldwork, reporting, and follow-up steps in their audits.
Process Mining from a Change Manager's Perspective
Process Mining from a Change Manager's PerspectiveProcess mining Evangelist Sebastiaan van Rijsbergen is a project and change manager from Nationale Nederlanden. As one of the largest financial service providers in the Netherlands, Nationale Nederlanden needs to accelerate the digital transformation to remain competitive.
Sebastiaan knows how to start something new and, step by step, impact the whole organization. From his process mining journey we can learn how involving multi-disciplinary teams, an iterative approach, and data governance are critical to scaling up your process mining success.
Introducing process mining in an organization is often a bumpy road and requires you to power trough the “valley of despair” in the change curve. For example, process mining makes things more transparent than some people are comfortable with and Sebastiaan received quite some pushback from certain people in the company. However, one of the magical moments in Sebastiaan’s process mining journey was when these very same people came back to him later on and told him that, in fact, process mining had brought peace into a discussion that was heated by opinions and conflict before.
“Green Data Science” for Process Mining - Wil van der Aalst
“Green Data Science” for Process Mining - Wil van der AalstProcess mining Evangelist Prof. Wil van der Aalst from Eindhoven University of Technology is the founding father of process mining.
As we have seen in the previous talks, data science, and specifically process mining, can create enormous value. But with great power comes great responsibility. Without taking proper care, the results of a data analysis could negatively impact citizens, patients, customers and employees. This often creates resistance towards these kinds of technologies (for example, laws that forbid to use data in a certain way).
As a data science professional, it is our responsibility to be aware of these new challenges. For example, systematic discrimination based on data, invasion of privacy, non-transparent life-changing decisions, and inaccurate conclusions may lead to new forms of “pollution”. “Green Data Science” is a new data science area that enables individuals, organizations, and society to reap the benefits from the widespread availability of data while ensuring fairness, confidentiality, accuracy, and transparency.
Applying Process Mining to a Dispatching Process
Applying Process Mining to a Dispatching ProcessProcess mining Evangelist
Abs Amiri works at SPARQ Solutions, who provide Information and Communications Technology services to government-owned suppliers like Energex and Ergon Energy in Queensland, Australia. Due to price pressure, there has been an increased need to cut costs and become more efficient.
As a senior analyst, programmer and data science lead, Abs developed new and innovative ways to help Energex and Ergon Energy improve their operations. His approach started with involving leadership to formulate the right questions. Then, he used his data expertise to wrangle the data into a format that was ready for process mining. He continued to validate the data and involved people with domain knowledge.
He then used process mining to understand how the processes actually worked and identified the factors that were causing variation and bottlenecks. By analysing the end-to-end processes with process mining, he was able to create significant benefits for the call dispatching processes.
Increasing the Audit Process Efficiency at DHL
Increasing the Audit Process Efficiency at DHLProcess mining Evangelist Deutsche Post DHL Group is the world’s leading logistics and mail communications company. The mail division delivers approximately 70 million letters in Germany, six days a week, and provides services across the entire mail value chain.
Marc Gittler and Patrick Greifzu are a Senior Audit Manager and Audit Manager in the Corporate Internal Audit team of DHL Group, Germany. Their view is that due to the increasing amount of data and process complexity a sample-based testing approach is no longer adequate.
Marc and Patrick did not only analyze the efficiency of the parcel delivery process based on hundreds of millions of events, but they also used process mining to analyze the quality of their own audit process.
Improving the Incident and Work Order Processes
Improving the Incident and Work Order ProcessesProcess mining Evangelist Carmen Lasa Gómez works at the Spanish telecommunications company Telefónica. Carmen’s team defines the analytics strategy of the “Delivery Operations & Deployment” area. They also provide analytic capabilities to execute the defined strategy and advice to other units in the Company.
She analyzed incidents and work orders (planned disruptions to install new software releases, bug fixes or new equipment) from different service areas. One of the problems they found is that a high percentage of work orders was performed outside the scheduled window. Due to their analysis, the percentage of work orders that are out of window could be decreased from 62% on April 2015 to 5% on April 2016.
Service managers from different areas are now asking Carmen’s group to analyse their services as well. One service manager, Sara Gómez Iglesias, concluded Carmen’s talk by sharing her experience with a recent process mining project in her area.
2024-Media-Literacy-Index-Of-Ukrainians-ENG-SHORT.pdf
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Adopting Process Mining at the Rabobank - use case
Adopting Process Mining at the Rabobank - use caseProcess mining Evangelist Frank van Geffen is a Process Innovator at the Rabobank. He realized that it took a lot of different disciplines and skills working together to achieve what they have achieved. It's not only about knowing what process mining is and how to operate the process mining tool. Instead, a lot of emphasis needs to be placed on the management of stakeholders and on presenting insights in a meaningful way for them.
The results speak for themselves: In their IT service desk improvement project, they could already save 50,000 steps by reducing rework and preventing incidents from being raised. In another project, business expense claim turnaround time has been reduced from 11 days to 1.2 days. They could also analyze their cross-channel mortgage customer journey process.
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Building Operational Profiles for Philips MRI Machines
Building Operational Profiles for Philips MRI MachinesProcess mining Evangelist Philips Healthcare is a global maker of many healthcare products, among which are imaging systems such as X-Ray, CT, Fluoroscopy and Magnetic Resonance Imaging (MRI) machines. ESI is an independent research organisation for high-tech embedded systems design and engineering.
Carmen Bratosin is a research fellow at ESI and Mark Pijnenburg is a Clinical Verification Lead at Philips Healthcare. Mark and Carmen showed how process mining can be used to analyze the system usage of an MRI machine. Understanding the actual usage patterns in the field is especially interesting to improve the system requirements and to increase the test coverage based on real-life behavior for these machines.
Preparing the data for process mining is not easy, because the logging produced by the MRI machines is only available on a technical log level used for debugging. Furthermore, each physician has their own preferences regarding the machine setup for certain exams, which adds to the complexity. They started by selecting the key activities in the technical log and then aligned them with the user interface elements. Finally, they matched the logged events with the steps described by the American College of Radiology to get them on the abstraction level that a radiology expert would understand. In this way, they were able to compare the actual usage of the MRI system with the expected (and designed) behavior.
How to make impact with process mining? - PGGM
How to make impact with process mining? - PGGMProcess mining Evangelist PGGM is a non-profit cooperative pension administration organization. They are founded by social partners in the care and welfare sector and serve four million participants.
Bas van Beek is a process consultant and Frank Nobel is a process and data analyst at PGGM. Instead of establishing process mining either in the data science corner or in the Lean Six Sigma corner, they approach every process improvement initiative as a multi-disciplinary team with people from both groups.
The nature of each initiative can be quite different. For example, some projects are more focused on the redesign or implementation of an IT solution. Others require extensive involvement from the business to change the way of working. In a third example, they showed how they used process mining for compliance purposes: Because they were able to demonstrate that certain individual funds actually follow the same process, they could group these funds and simplify the audit by using generic controls.
Process Mining as Enabler for Digital Transformations
Process Mining as Enabler for Digital TransformationsProcess mining Evangelist Raiffeisen Bank International (RBI) is a leading Retail and Corporate bank with 50 thousand employees serving more than 14 million customers in 14 countries in Central and Eastern Europe.
Jozef Gruzman is a digital and innovation enthusiast working in RBI, focusing on retail business, operations & change management. Claus Mitterlehner is a Senior Expert in RBI’s International Efficiency Management team and has a strong focus on Smart Automation supporting digital and business transformations.
Together, they have applied process mining on various processes such as: corporate lending, credit card and mortgage applications, incident management and service desk, procure to pay, and many more. They have developed a standard approach for black-box process discoveries and illustrate their approach and the deliverables they create for the business units based on the customer lending process.
Process Mining Machine Recoveries to Reduce Downtime
Process Mining Machine Recoveries to Reduce DowntimeProcess mining Evangelist
ASML provides chip makers with everything they need to mass-produce patterns on silicon, helping to increase the value and lower the cost of a chip. The key technology is the lithography system, which brings together high-tech hardware and advanced software to control the chip manufacturing process down to the nanometer. All of the world’s top chipmakers like Samsung, Intel and TSMC use ASML’s technology, enabling the waves of innovation that help tackle the world’s toughest challenges.
The machines are developed and assembled in Veldhoven in the Netherlands and shipped to customers all over the world. Freerk Jilderda is a project manager running structural improvement projects in the Development & Engineering sector. Availability of the machines is crucial and, therefore, Freerk started a project to reduce the recovery time.
A recovery is a procedure of tests and calibrations to get the machine back up and running after repairs or maintenance. The ideal recovery is described by a procedure containing a sequence of 140 steps. After Freerk’s team identified the recoveries from the machine logging, they used process mining to compare the recoveries with the procedure to identify the key deviations. In this way they were able to find steps that are not part of the expected recovery procedure and improve the process.
Skills for Successful Process Scientists
Skills for Successful Process ScientistsProcess mining Evangelist The final speaker at Process Mining Camp 2018 was Wil van der Aalst, the founding father of process mining. In his closing keynote, Wil talked about the updated skill set that process and data scientists need today. Since process mining research was starting up in Eindhoven in the late 90s, the availability of suitable data has increased tremendously, which makes it even more important that this data can and will be used in an appropriate and responsible manner.
This requires dedicated capabilities from the process miner in each stage of the analysis pipeline: Processing and analyzing data, being responsible about the effects on people, and on business models. When you look for people who are skilled in all of these technical areas, as well as in soft skills like communication and ethics, you start looking for (as they would say in the Netherlands) a “sheep with 5 legs”, or something that is very rare. Becoming a data scientist requires a lot of effort to learn all the skills that are needed to live up to these high expectations.
As ambassadors of process mining, we also have the responsibility to use the right terms. Wil sees a clear a distinction between Artificial Intelligence (AI), machine learning, and data mining. At the same time, one could argue that process mining is data mining, but the underlying techniques are very different. So, saying that process mining is part of data mining, or AI, doesn’t make any sense.
There are incredible expectations around AI and Big Data, which is very dangerous as we have seen in past “AI winters”. We should be careful not to overpromise and try to be realistic. The incredible successes of machine learning techniques like deep learning are, for example, still limited to very specific fields.
Some in the media and big technology companies use terms like Artificial Intelligence, Machine Learning, and Deep Learning interchangeably. They might argue that you don’t need process mining as you can just put an event log into a deep neural network and a process model will come out. There is, however, not one deep learning algorithm that can discover a process model. Instead, when we look at process mining it combines the fields and methods of ‘process science’ and ‘data science’. This makes it even more challenging for us to cover all required skills.
But do you, as a professional, need to know how a car works internally in order to drive it? It depends on what you want to accomplish. For example, if you need to drive fast around the Nurburg Ring, it can be very useful. Also, if you need to select a car then it would certainly be useful to know about its internals. Process mining is a relatively young technology. Therefore, it is useful to know how it works in order to select the right tool, and to use it to maximum effect.
So what kind of skills do you need as a process miner? You need to be able to extract and clean the data, spend time on the analysis, and interpret the results. This is not easy.
Process Mining and Jira - Air France KLM
Process Mining and Jira - Air France KLMProcess mining Evangelist
The sixth speaker at Process Mining Camp 2018 was Marc Tollens, a digital product owner at Air France KLM. In order to compete in the aviation market, KLM focuses on providing an excellent customer experience. They adopted the agile methodology to be able to reduce the time to introduce new touch points in the traveler’s journey. The performance of the agile teams is crucial to get the most out of each sprint.
As a Sunday afternoon project, Marc collected data from Jira, a project management software for (agile) software development, to see how process mining could be applied to help the teams learn from each other. Surprisingly, the flow of each team was quite different.
Marc started comparing the flows of the three teams to identify key differences in behavior and the resulting effects. In this way he could see if a team was able to deliver what they promised and whether they started testing too early or too late. He shared his observations with the teams during the retrospective and returned for the next sprint to see how the improvement worked out.
Understanding Complex Development Processes
Understanding Complex Development ProcessesProcess mining Evangelist The fifth talk at Process Mining Camp was given by Olga Gazina and Daniel Cathala from Euroclear. As a data analyst at the internal audit department Olga helped Daniel, IT Manager, to make his life at the end of the year a bit easier by using process mining to identify key risks.
She applied process mining to the process from development to release at the Component and Data Management IT division. It looks like a simple process at first, but Daniel explains that it becomes increasingly complex when considering that multiple configurations and versions are developed, tested and released. It becomes even more complex as the projects affecting these releases are running in parallel. And on top of that, each project often impacts multiple versions and releases.
After Olga obtained the data for this process, she quickly realized that she had many candidates for the caseID, timestamp and activity. She had to find a perspective of the process that was on the right level, so that it could be recognized by the process owners. In her talk she takes us through her journey step by step and shows the challenges she encountered in each iteration. In the end, she was able to find the visualization that was hidden in the minds of the business experts.
Controlling Financial Processes at a Municipality
Controlling Financial Processes at a MunicipalityProcess mining Evangelist
The fourth speaker at Process Mining Camp 2018 was Wim Kouwenhoven from the City of Amsterdam. Amsterdam is well-known as the capital of the Netherlands and the City of Amsterdam is the municipality defining and governing local policies. Wim is a program manager responsible for improving and controlling the financial function.
A new way of doing things requires a different approach. While introducing process mining they used a five-step approach:
Step 1: Awareness
Introducing process mining is a little bit different in every organization. You need to fit something new to the context, or even create the context. At the City of Amsterdam, the key stakeholders in the financial and process improvement department were invited to join a workshop to learn what process mining is and to discuss what it could do for Amsterdam.
Step 2: Learn
As Wim put it, at the City of Amsterdam they are very good at thinking about something and creating plans, thinking about it a bit more, and then redesigning the plan and talking about it a bit more. So, they deliberately created a very small plan to quickly start experimenting with process mining in small pilot. The scope of the initial project was to analyze the Purchase-to-Pay process for one department covering four teams. As a result, they were able show that they were able to answer five key questions and got appetite for more.
Step 3: Plan
During the learning phase they only planned for the goals and approach of the pilot, without carving the objectives for the whole organization in stone. As the appetite was growing, more stakeholders were involved to plan for a broader adoption of process mining. While there was interest in process mining in the broader organization, they decided to keep focusing on making process mining a success in their financial department.
Step 4: Act
After the planning they started to strengthen the commitment. The director for the financial department took ownership and created time and support for the employees, team leaders, managers and directors. They started to develop the process mining capability by organizing training sessions for the teams and internal audit. After the training, they applied process mining in practice by deepening their analysis of the pilot by looking at e-invoicing, deleted invoices, analyzing the process by supplier, looking at new opportunities for audit, etc. As a result, the lead time for invoices was decreased by 8 days by preventing rework and by making the approval process more efficient. Even more important, they could further strengthen the commitment by convincing the stakeholders of the value.
Step 5: Act again
After convincing the stakeholders of the value you need to consolidate the success by acting again. Therefore, a team of process mining analysts was created to be able to meet the demand and sustain the success. Furthermore, new experiments were started to see how process mining could be used in three audits in 2018.
Mining a Global Trade Process with Data Science - Microsoft
Mining a Global Trade Process with Data Science - MicrosoftProcess mining Evangelist
The third speaker at Process Mining Camp 2018 was Dinesh Das from Microsoft. Dinesh Das is the Data Science manager in Microsoft’s Core Services Engineering and Operations organization.
Machine learning and cognitive solutions give opportunities to reimagine digital processes every day. This goes beyond translating the process mining insights into improvements and into controlling the processes in real-time and being able to act on this with advanced analytics on future scenarios.
Dinesh sees process mining as a silver bullet to achieve this and he shared his learnings and experiences based on the proof of concept on the global trade process. This process from order to delivery is a collaboration between Microsoft and the distribution partners in the supply chain. Data of each transaction was captured and process mining was applied to understand the process and capture the business rules (for example setting the benchmark for the service level agreement). These business rules can then be operationalized as continuous measure fulfillment and create triggers to act using machine learning and AI.
Using the process mining insight, the main variants are translated into Visio process maps for monitoring. The tracking of the performance of this process happens in real-time to see when cases become too late. The next step is to predict in what situations cases are too late and to find alternative routes.
As an example, Dinesh showed how machine learning could be used in this scenario. A TradeChatBot was developed based on machine learning to answer questions about the process. Dinesh showed a demo of the bot that was able to answer questions about the process by chat interactions. For example: “Which cases need to be handled today or require special care as they are expected to be too late?”. In addition to the insights from the monitoring business rules, the bot was also able to answer questions about the expected sequences of particular cases. In order for the bot to answer these questions, the result of the process mining analysis was used as a basis for machine learning.
Process Mining at Deutsche Bank - Journey
Process Mining at Deutsche Bank - JourneyProcess mining Evangelist Niyi started with process mining on a cold winter morning in January 2017, when he received an email from a colleague telling him about process mining. In his talk, he shared his process mining journey and the five lessons they have learned so far.
Deciding Surgery Room Allocations in a Hospital
Deciding Surgery Room Allocations in a HospitalProcess mining Evangelist The first speaker at Process Mining Camp 2018 was Fran Batchelor from UW Health in the United States. Fran is a Nursing Informatics Specialist who supports the surgical services at three of UW Health’s hospitals. She used process mining to analyze the flow of urgent and emergent surgical cases added to the schedule. What did she find?
The operations for most cases are scheduled and planned well in advance. For these patients the room is being prepared and the patient is transported to the room and after the operation the patient is transported to the recovery room. At the hospital they have 27 operation rooms available.
There are other patients that require urgent care, for which additional ‘hold’ rooms are reserved. However, sometimes there are more emergent cases than available operating rooms, such that schedules need to be adjusted. The smooth flow is critical for emergent cases and the challenge is to allocate the operating space for these patients.
At the hospital, two additional operation rooms were to be opened for the emergent cases and a project was started to determine how these rooms could be best allocated. Neurosurgery had made a case for all available new space and was in line to receive it. However, Peripheral Vascular also voiced a need. A team was assembled to provide information regarding the decision making. How many add-on cases are there without a dedicated hold room being available? How are they moving through the process and are they still meeting the internal performance metrics?
From the database the team extracted the data for each step in the process and developed the logic to identify the add-on cases. By visualizing the process using process mining they were able to see how add-on cases behave. They were able to see that 70% of the cases were scheduled and of the 30% unscheduled cases 12% didn’t have dedicated hold rooms.
When looking at the flow of the add-on cases, they realized that not all cases have the same urgency. By giving the cases a priority, they were able to distinguish between the different levels of urgency. Especially when focusing on the emergent cases of Neurosurgery and Peripheral Vascular they found that 43% of the cases that took longer than 1 hour to get to the operating room belonged to the Peripheral Vascular surgery (a higher volume compared to Neurosurgery). So, it was most logical to allocate the additional rooms for both of these procedures.
Process mining reduced the political and emotional components when taking these decisions. By looking at the data and the visualization it was possible to tell the story more easily. Without process mining it would not have been possible to make such a clear-cut case and the decision would have been made differently.
However, it was not easy and took two years to get to this point. First of all, it was a challenge to set up the project and get access to the right data.
Mining the Customer Journey, accelerating New Product Introduction
Mining the Customer Journey, accelerating New Product IntroductionProcess mining Evangelist Mick is a supply chain manager at Veco, a precision metal manufacturer. With process mining, Mick found a technique to radically accelerate the New Product Development cycle and convert this to an opportunity for faster growth.
Veco had started using process mining three years ago as an addition to their Lean Six Sigma methodology, which helped them to reduce the lead time of production orders significantly. However, you often see that when you solve one problem, you uncover another.
As part of their growth strategy, Veco wanted to expand to new and existing customers outside of their existing part portfolio. When customers request a new product that they have not ordered before (so, it does not yet exist in the product catalogue), additional steps take place in the sales process: A sample first needs to be engineered, produced, and shipped to the customers before larger quantities are ordered.
To be able to close new deals quickly, Veco has the ambition to produce and deliver these samples within 15 days. However, by extracting data from the CRM and ERP system and analyzing it with process mining, they saw that it in fact took on average 52 days to deliver the samples to the customers. The longer the sample production process takes, the higher the risk that they may be losing these orders to the competition.
To understand the root cause of the delays, Mick and his team identified a new process ‘From Engineering to Order’ that was not managed before. In contrast to the production process of their regular catalogue parts, these sample parts required the involvement of the engineering department before they could be produced.
By involving members from both engineering and production, a “fast lane” was created for the engineering and production of these samples to speed up the ‘Engineering to Order’ process. By experimenting with this new process for a few weeks they were able to get “jaw-dropping” results. Within weeks, the director gave them the green light to implement this new way of working as the standard process, paving the way for future growth.
Lean & Process Mining - have fun and add value at the same time
Lean & Process Mining - have fun and add value at the same timeProcess mining Evangelist Roel Blankers and Wesley Wiertz work at VGZ. The health insurance cooperation VGZ is using operational visual management to track process performance every day. Lean has been adopted as the problem-solving methodology.
However, it took Roel a lot of time to map the existing processes during brown paper sessions before they were able to understand the real problem. When they analyzed the non-routine dental care claims process they decided to try a different approach: Process mining.
After extracting and preparing the data, they discovered that this process took 28 days to complete. In the discovered process maps they could see that a lot of the requests were being forwarded from the administrative teams to the medical advisors. Just by sharing the discovered process and asking why these claims needed to be forwarded to advisors, they found that a lot of these cases could actually be handled by the administrative teams. Therefore, it was proposed to set up an experiment to transfer the knowledge between the medical advisors and the administrative teams. Using process mining, they were able to validate that this new approach has in fact improved the lead time by almost 40%.
With process mining they were able to identify the problem quickly. They got a fact-based insight, which prevented them from jumping to conclusions. Process mining is a great addition to the Lean toolbox and a fun way to collaborate with domain experts to find opportunities to improve.
Building Bridges between Data and Business Value
Building Bridges between Data and Business ValueProcess mining Evangelist Gijs Jansen works as a business intelligence specialist at Essent, a large energy supplier in the Netherlands. One day he was asked to calculate the “snake plot” and “ping-pong factor” for the process of becoming and being a customer. He had no clue how to approach this, but he was eager to solve this problem.
The business intelligence department is responsible to report Key Performance Indicators (KPIs) for these processes. However, reporting a “snake plot” was something different compared to the existing reports they delivered. It required a deeper insight into how the customer passed though the different departments and the number of times each department touched each request.
A colleague suggested that he could try process mining. Gijs first started a small process mining project to analyse the credit insurance process. It was a simple process that was expected to be automated for most cases. However, the process mining results showed the contrary: Gijs found that disputes on contracts required a manual intervention for many cases.
This experience gave him the confidence to attack the “snake plot” and “ping-pong factor” problem. It took some effort but Gijs was able to extract the data for the customer process and transform it into the right process mining format. He then analyzed the process maps and saw how each customer request was handled, which departments were involved, and how often each request was touched by which employee. This resulted into a new set of KPIs that were discussed monthly to reduce the lead time and to limit the number of touches.
Process Mining in Internal Audit - CZ use case
Process Mining in Internal Audit - CZ use caseProcess mining Evangelist Wilco Brouwers and Dave Jansen from CZ share their process mining experience as IT auditors. Also auditors see that the digital transformation is slowly impacting their way of working. Dave and Wilco believe that data analysis skills will become increasingly important for future IT auditors – not only to be more efficient, but also to be more effective.
As the frontrunners within their team, Wilco and Dave have developed a new approach for auditing their digital processes of the future. Process mining plays an important role in this new auditing approach. With concrete examples, they showed where they see differences compared to the traditional audit approach in the preparation, fieldwork, reporting, and follow-up steps in their audits.
Process Mining from a Change Manager's Perspective
Process Mining from a Change Manager's PerspectiveProcess mining Evangelist Sebastiaan van Rijsbergen is a project and change manager from Nationale Nederlanden. As one of the largest financial service providers in the Netherlands, Nationale Nederlanden needs to accelerate the digital transformation to remain competitive.
Sebastiaan knows how to start something new and, step by step, impact the whole organization. From his process mining journey we can learn how involving multi-disciplinary teams, an iterative approach, and data governance are critical to scaling up your process mining success.
Introducing process mining in an organization is often a bumpy road and requires you to power trough the “valley of despair” in the change curve. For example, process mining makes things more transparent than some people are comfortable with and Sebastiaan received quite some pushback from certain people in the company. However, one of the magical moments in Sebastiaan’s process mining journey was when these very same people came back to him later on and told him that, in fact, process mining had brought peace into a discussion that was heated by opinions and conflict before.
“Green Data Science” for Process Mining - Wil van der Aalst
“Green Data Science” for Process Mining - Wil van der AalstProcess mining Evangelist Prof. Wil van der Aalst from Eindhoven University of Technology is the founding father of process mining.
As we have seen in the previous talks, data science, and specifically process mining, can create enormous value. But with great power comes great responsibility. Without taking proper care, the results of a data analysis could negatively impact citizens, patients, customers and employees. This often creates resistance towards these kinds of technologies (for example, laws that forbid to use data in a certain way).
As a data science professional, it is our responsibility to be aware of these new challenges. For example, systematic discrimination based on data, invasion of privacy, non-transparent life-changing decisions, and inaccurate conclusions may lead to new forms of “pollution”. “Green Data Science” is a new data science area that enables individuals, organizations, and society to reap the benefits from the widespread availability of data while ensuring fairness, confidentiality, accuracy, and transparency.
Applying Process Mining to a Dispatching Process
Applying Process Mining to a Dispatching ProcessProcess mining Evangelist
Abs Amiri works at SPARQ Solutions, who provide Information and Communications Technology services to government-owned suppliers like Energex and Ergon Energy in Queensland, Australia. Due to price pressure, there has been an increased need to cut costs and become more efficient.
As a senior analyst, programmer and data science lead, Abs developed new and innovative ways to help Energex and Ergon Energy improve their operations. His approach started with involving leadership to formulate the right questions. Then, he used his data expertise to wrangle the data into a format that was ready for process mining. He continued to validate the data and involved people with domain knowledge.
He then used process mining to understand how the processes actually worked and identified the factors that were causing variation and bottlenecks. By analysing the end-to-end processes with process mining, he was able to create significant benefits for the call dispatching processes.
Increasing the Audit Process Efficiency at DHL
Increasing the Audit Process Efficiency at DHLProcess mining Evangelist Deutsche Post DHL Group is the world’s leading logistics and mail communications company. The mail division delivers approximately 70 million letters in Germany, six days a week, and provides services across the entire mail value chain.
Marc Gittler and Patrick Greifzu are a Senior Audit Manager and Audit Manager in the Corporate Internal Audit team of DHL Group, Germany. Their view is that due to the increasing amount of data and process complexity a sample-based testing approach is no longer adequate.
Marc and Patrick did not only analyze the efficiency of the parcel delivery process based on hundreds of millions of events, but they also used process mining to analyze the quality of their own audit process.
Improving the Incident and Work Order Processes
Improving the Incident and Work Order ProcessesProcess mining Evangelist Carmen Lasa Gómez works at the Spanish telecommunications company Telefónica. Carmen’s team defines the analytics strategy of the “Delivery Operations & Deployment” area. They also provide analytic capabilities to execute the defined strategy and advice to other units in the Company.
She analyzed incidents and work orders (planned disruptions to install new software releases, bug fixes or new equipment) from different service areas. One of the problems they found is that a high percentage of work orders was performed outside the scheduled window. Due to their analysis, the percentage of work orders that are out of window could be decreased from 62% on April 2015 to 5% on April 2016.
Service managers from different areas are now asking Carmen’s group to analyse their services as well. One service manager, Sara Gómez Iglesias, concluded Carmen’s talk by sharing her experience with a recent process mining project in her area.
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2024-Media-Literacy-Index-Of-Ukrainians-ENG-SHORT.pdf
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Adopting Process Mining at the Rabobank - use case
Adopting Process Mining at the Rabobank - use caseProcess mining Evangelist Frank van Geffen is a Process Innovator at the Rabobank. He realized that it took a lot of different disciplines and skills working together to achieve what they have achieved. It's not only about knowing what process mining is and how to operate the process mining tool. Instead, a lot of emphasis needs to be placed on the management of stakeholders and on presenting insights in a meaningful way for them.
The results speak for themselves: In their IT service desk improvement project, they could already save 50,000 steps by reducing rework and preventing incidents from being raised. In another project, business expense claim turnaround time has been reduced from 11 days to 1.2 days. They could also analyze their cross-channel mortgage customer journey process.
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Automation Platforms and Process Mining - success story
Automation Platforms and Process Mining - success storyProcess mining Evangelist
Zig Websoftware creates process management software for housing associations. Their workflow solution is used by the housing associations to, for instance, manage the process of finding and on-boarding a new tenant once the old tenant has moved out of an apartment.
Paul Kooij shows how they could help their customer WoonFriesland to improve the housing allocation process by analyzing the data from Zig's platform. Every day that a rental property is vacant costs the housing association money.
But why does it take so long to find new tenants? For WoonFriesland this was a black box. Paul explains how he used process mining to uncover hidden opportunities to reduce the vacancy time by 4,000 days within just the first six months.
Deloitte - A Framework for Process Mining Projects
Deloitte - A Framework for Process Mining ProjectsProcess mining Evangelist Tijn van der Heijden is a business analyst with Deloitte. He learned about process mining during his studies in a BPM course at Eindhoven University of Technology and became fascinated with the fact that it was possible to get a process model and so much performance information out of automatically logged events of an information system.
Tijn successfully introduced process mining as a new standard to achieve continuous improvement for the Rabobank during his Master project. At his work at Deloitte, Tijn has now successfully been using this framework in client projects.
定制学历(美国Purdue毕业证)普渡大学电子版毕业证
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4. Multivariable statistics_Using Stata_2025.pdf
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hersh's midterm project.pdf music retail and distribution
hersh's midterm project.pdf music retail and distributionhershtara1 midterm project for music retail and distribution
indonesia-gen-z-report-2024 Gen Z (born between 1997 and 2012) is currently t...
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Volkswagen - Analyzing the World's Biggest Purchasing Process
Volkswagen - Analyzing the World's Biggest Purchasing ProcessProcess mining Evangelist Philipp Horn has worked in the Business Intelligence area of the Purchasing department of Volkswagen for more than 5 years. He is a front runner in adopting new techniques to understand and improve processes and learned about process mining from a friend, who in turn heard about it at a meet-up where Fluxicon had participated with other startups.
Philipp warns that you need to be careful not to jump to conclusions. For example, in a discovered process model it is easy to say that this process should be simpler here and there, but often there are good reasons for these exceptions today. To distinguish what is necessary and what could be actually improved requires both process knowledge and domain expertise on a detailed level.
Process Mining at Rabobank - Organizational challenges
Process Mining at Rabobank - Organizational challengesProcess mining Evangelist Frank van Geffen is a Business Analyst at the Rabobank in the Netherlands. The first time Frank encountered Process Mining was in 2002, when he graduated on a method called communication diagnosis. He stumbled upon the topic again in 2008 and was amazed by the possibilities.
Frank shares his experiences after applying process mining in various projects at the bank. He thinks that process mining is most interesting for the Process manager / Process owner (accountable for all aspects of the complete end to end process), the Process Analyst (responsible for performing the process mining analysis), the Process Auditor (responsible for auditing processes), and the IT department (responsible for development/aquisition, delivery and maintanance of the process mining software).
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Process Mining and Official Statistics - CBS
- 1. Johan Lammers Process mining and of2icial statistics
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- 6. Statistical process 6 Design Execution Rules Objects Methodology Process Data collection Analysis Publication Plan Do Check Act Process mining
- 8. Focus on 2irst poll, telephone 8
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- 12. 12 Time needed to handle appointments total &me appointments appointment-‐ handling hours % Morning 1339 456 34,1% A=ernoon 1039 331 31,9% Evening 3158 1092 34,6% Total 5537 1879 33,9%
- 13. Summary Process mining helps J Fast analysis J Iden&fy causes J Testability of causes J No scrip&ng L More filters needed L Postprocessing 13