Global Business Services (GBS) organizations are navigating an era of unprecedented and increasing complexity. With operations spanning regions, languages, and regulatory environments, these organizations require efficient and standardized processes to thrive. What differentiates GBS organizations is how well they understand their existing processes and can further improve them to improve operational efficiency. For this reason, you see process improvement, metric reporting and increasingly process mining as key compontents for successful organizations.

This article explores why GBS organizations are embracing process mining and how it’s transforming their operational landscapes.

Why GBS Organizations Need Process Mining

Complexity and Scale

Global service organizations manage intricate, interdependent workflows across multiple countries. Process mining enables them to untangle these complexities by delivering real-time, data-driven insights. Whether it’s ensuring seamless handoffs between teams or optimizing cross-border workflows, process mining empowers GBS leaders to pinpoint inefficiencies and enhance performance.

Standardization and Consistency

For GBS organizations, consistency is key to customer satisfaction and trust. Process mining helps standardize workflows, ensuring service delivery is uniform across all locations. By identifying and addressing variations, organizations can maintain high service levels and deliver a consistent customer experience globally.

Particiular importantance should be paid to how processes can be standardized across different systems - thus allowing for further simplification and long term consolidation of systems.

Compliance and Risk Management

Navigating regulatory requirements is a significant challenge for global organizations. Process mining provides real-time insights into compliance gaps, helping GBS organizations proactively mitigate risks. This not only reduces potential fines but also ensures adherence to industry standards, strengthening operational resilience. This is an area which will grow as process mining will enable real-time proactive monitoring and insights.

Benefits of Process Mining for GBS

Enhanced Process Transparency

Process mining delivers a bird’s-eye view of end-to-end workflows, making it easier to spot bottlenecks, redundancies, and delays. This visibility accelerates problem-solving and fosters a culture of accountability and improvement.

Data-Driven Decision-Making

Real-time data is a powerful enabler for prioritizing improvements. Process mining provides actionable insights that allow organizations to make proactive, evidence-based decisions. For instance, identifying a recurring delay in procurement can lead to targeted interventions that streamline operations.

Continuous Improvement and Automation

Process mining is a catalyst for continuous improvement. By identifying repetitive tasks suited for automation, it helps GBS organizations streamline processes and free up resources for high-value activities. This iterative approach ensures processes remain efficient and aligned with business goals.

Customer Experience Enhancement

Fast, efficient processes are the backbone of exceptional customer experiences. Process mining reduces processing times, ensures consistent service delivery, and facilitates rapid issue resolution—transforming the customer journey from reactive to proactive.

Real-World Applications of Process Mining

Case Study: Three-Way Matching of Invoices

For a large medical customer, a custom analysis capability comparing multiple data sources to ensure accurate invoicing and reduction in duplicates. This capability previously existed but required a costly subscription and was delayed due sharing of files. Leveraging process mining allows this activity to be near real-time and proactive notifications for prompting action.

Case Study: Standardizing Order to Cash

Leveraging a standard data model, a Fortune 50 supply chain was able to compare multiple different SAP instances. Being able to see how 10+ SAP systems perform in comparision to each other enables simplification, standardization and ultimately consolidation. Futhermore this high degree of insights enabled a cash flow improvement program leveraging GBS resources.

Conclusion

Global Business Services organizations face growing complexity and heightened expectations. Process mining emerges as a critical tool, providing visibility, control, and the agility to adapt. By embracing process mining, GBS leaders can drive operational efficiency, elevate customer experiences, and achieve strategic objectives.

If you’re ready to explore how process mining can transform your organization or want to highlight your successes in this space, please reachout!

Challenges of Remote Work

Remote work introduces several challenges that can impact productivity and efficiency:

Communication Barriers: Virtual teams often face difficulties in communication and collaboration, leading to misunderstandings and delays.

Process Visibility: Managers may struggle to gain visibility into how remote teams execute tasks, making it difficult to identify bottlenecks and inefficiencies.

Performance Monitoring: Tracking employee performance and ensuring accountability can be challenging without the right tools and processes.

Work-Life Balance: Remote work can blur the lines between work and personal life, leading to burnout and reduced productivity.

Leveraging Process Mining for Remote Work

1. Enhancing Communication and Collaboration

Process mining can analyze communication patterns and identify areas where processes occur, and which can be improved. By examining data from tools like Slack, Microsoft Teams, and finance systems, organizations can understand how information flows within the team and address communication gaps.

Use Case

Siemens applied process mining to analyze their order-to-cash process, which involved thousands of remote workers. By identifying inefficient communication channels and restructuring them, Siemens improved collaboration and increased efficiency, reducing variability and costs.

2. Optimizing Workflows and Task Management

Remote work often involves complex workflows that can lead to delays and inefficiencies. Process mining provides a visual representation of these workflows, allowing organizations to identify bottlenecks and areas for improvement.

Use Case

Vodafone used process mining to streamline remote work processes and optimize order processing. This effort led to a 13% reduction in unit process order costs and significantly improved operational efficiency.

3. Performance Monitoring and Accountability

Process mining can track employee performance and productivity, ensuring accountability in a remote work environment. By analyzing task completion times, resource utilization, and adherence to deadlines, organizations can set benchmarks and identify top performers.

Use Case

An international retailer used process mining to uncover inefficiencies in its operations, identifying $200 million to $500 million in potential savings. By improving process visibility, the company was able to focus on key areas for improvement, ultimately enhancing accountability and performance.

4. Supporting Work-Life Balance

This is perhaps the most important benefit and gets to the big benefits of process intelligence, removing manual work and freeing up capacity of people to do more important things! As it stands, remote work can lead to burnout if not managed effectively. Process mining can help identify patterns of overwork or excessive overtime, allowing organizations to address work-life balance issues proactively.

Use Case

A company in the aerospace and defense sector utilized task mining to analyze employee activities, discovering that employees spent excessive time on repetitive tasks. By implementing automation and better process governance, they were able to reduce workload stress and improve work-life balance.

5. Continuous Improvement and Adaptation

The remote work landscape is dynamic, and organizations must continuously adapt to changing circumstances. Process mining enables businesses to monitor processes in real-time, providing the agility needed to respond to challenges and opportunities.

Use Case

AB InBev employed process mining to reduce costs and enhance performance visibility across its teams. This approach helped them streamline supply chain processes and adapt quickly to market changes, ultimately achieving better efficiency and performance insights.

Process mining offers a powerful tool for optimizing remote work processes, providing organizations with the insights needed to enhance productivity and address the unique challenges of virtual environments. By leveraging data-driven analysis, businesses can streamline workflows, improve communication, and support employee well-being. As remote work continues to evolve, process mining will continue to grow in importance as work is done virtually versus a team co-located. We know the benefits of co-located process intelligence, but for those thinking about the next 5 years…now is the time to invest in this capability.

Are you curious about how your organization’s process intelligence stacks up against industrystandards? We’re going to be launching an Industry Assessment and Benchmark study, focusing on the latest trends and best practices in process mining. By subscribing to our newsletter, you can gain exclusive insights, get your organization included in the benchmark, and stay ahead of the curve with actionable data tailored to your industry.

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Process mining is a technique that combines data science, business process management, and artificial intelligence to provide insights and solutions for complex business processes. Much has been written about “how to technically implement”, but the more interesting piece is “how to realize value.”  Process mining can help identify bottlenecks, inefficiencies, deviations, compliance issues, which is why this work to generate insights matters. 

Process mining is a strategic approach that requires a clear vision, a strong governance, and a collaborative culture. In his book, Process Mining in Action, Lars Reinkemeyer, a leading expert and practitioner of process mining, shares his extensive experience and knowledge from working with process mining in various industries and domains, such as manufacturing, logistics, healthcare, finance, and IT. He also presents real-life case studies and best practices from leading organizations, such as Siemens, ABB, Celonis, and others.

Main Insights from the Book

Impacted Stakeholder Buy-In

Process Mining is a novel and emerging technology that can help organizations discover, monitor, and improve their business processes. However, to successfully implement Process Mining, it is not enough to have the right tools and data. It is also crucial to have the support and collaboration of the people who are involved in the processes. 

“While innovative IT tools can be a great enabler, it is a key success factor to get the right people on board. All smart data, insights, and transparency will be useless if the process experts or process owners do not appreciate and support the approach. Similar to applying MRT technology (MRI), the affected people must be determined to pursue a therapy and strive for improvement. The process owner must be seeking digital transformation or process improvements and actively support the usage of Process Mining.”

Opportunities of Technological Change

Technological change is often seen as a disruptive force that threatens to replace human workers with machines. However, this perspective overlooks the potential benefits and opportunities that technology can bring for enhancing skills and creating new roles. 

“While technological change is often perceived as a threat, it can also be an opportunity for new skills and roles. Many of the roles described … led to new types of experts, both in business and IT. Harvard Business Review has, e.g., coined the role of "analytics translators" who bridge the gap from technical realms of data engineers and scientists to the people from the business realm—procurement, supply chain, manufacturing, sales, finance, etc. This kind of competency is of increasing value and offers new opportunities. As a general trend, the automation of work is continuously progressing and part of the economic evolution. At the same time, it goes against human nature to work on monotonous tasks, and robots take over repetitive or mundane work, while leaving opportunities for new tasks and skilled workers.”

A Transatlantic Divide

Process Mining and Robotic Process Automation (RPA) are two technologies that aim to improve business processes by analyzing and automating them. However, their perception and adoption vary significantly across the Atlantic in terms of business adoption, management styles and cultural beliefs. European companies tend to value both technologies equally, while American companies favor RPA over Process Mining. 

This discrepancy might be due to the different levels of maturity and awareness of Process Mining in these two markets. A survey conducted by the Process Mining Group in 2020 found that 58% of the European respondents had a high or very high level of Process Mining maturity, compared to only 39% of the American respondents. Similarly, 52% of the European respondents reported a high or very high level of Process Mining awareness in their organizations, compared to only 35% of the American respondents. These results indicate that Process Mining has a stronger foothold and recognition in Europe than in the US. 

Remaining Humble, Process Improvement Takes Time

This might be my favorite take away!  Satisfaction = Results – Expectations is a framework for how we should look at things from a broader perspective. Acknowledge the factors that contributed to the success of the project, such as having a strategy, learning from trial and error, and having some luck. However, not everything will work, and people should stay humble and not overestimate the role of strategy or underestimate the role of hard work. Satisfaction should be based on the results achieved and expectations, which were realistic and flexible as more was learned throughout a project.

Conclusion and Key Takeaways

Process Mining in Action is a valuable and insightful resource for anyone who wants to learn more about process mining and those who have practical experience.  It can be a bit of a technical read, but that is to be somewhat expected as this covers both technical and business application of key concepts. 

As Reinkemeyer writes in his book, "Process Mining is not a silver bullet, but a powerful enabler to achieve process excellence and digital transformation."  As such, I hope this article gave you further ideas on how to improve your implementations and value realization work. 

While every process and improvement project is different, below are 3 examples of leveraging these pre-existing frameworks to get the most value out of these tools. 

Failure Mode and Effects Analysis (FMEA)

Failure Mode and Effects Analysis (FMEA) is a systematic approach used to identify potential failure modes within a process, assess their impact, and prioritize corrective actions. By integrating process mining outputs into FMEA, organizations can gain deeper insights into process behavior and performance, thereby enhancing the accuracy of risk assessment and mitigation strategies. While some of this could be calculated and derived via technical means, the process of doing this with key stakeholders brings non-system and insights into the conversation.

Example:

A manufacturing company is experiencing a high defect rate in a specific production line. By analyzing process mining data, the team identifies instances of prolonged activity duration as a significant contributor to defects. Integrating this insight into FMEA, the team then prioritizes communication of completion at each step and prioritization of aging orders.  Combining these technical insights with experts would allow for further conversations around communication challenges, planned production schedule and prioritization of work which would not be included in the technical analysis. 

Y = f(X) Methodology

The Y = f(X) methodology, central to Six Sigma principles, emphasizes the relationship between process inputs (X) and outputs (Y). Process mining provides a wealth of data on process inputs, outputs, and their inter-dependencies, enabling organizations to apply Y = f(X) analysis more comprehensively to identify critical factors impacting process performance.

Example:

In a service-oriented function, customer satisfaction (Y) is a key output metric influenced by various process inputs such as response time, accuracy, and communication quality. Process mining analysis reveals that delays in responding to customer inquiries or inaccurate responses are correlated with lower satisfaction scores. Applying Y = f(X), the organization identifies response time as a critical input factor and then works with the impacted team to implement process changes to streamline customer communication channels, resulting in improved satisfaction levels.

Pareto Analysis

Pareto Analysis, based on the Pareto Principle (80/20 rule), focuses on identifying the most significant factors contributing to a problem. By integrating process mining data into Pareto Analysis, organizations can prioritize root causes more effectively, directing resources towards addressing the most impactful issues first.

Example:

A financial institution experiences an increase in transaction errors leading to customer complaints. Process mining analysis highlights discrepancies in data entry processes as a prevalent issue. Conducting Pareto Analysis based on process mining data reveals that 80% of errors stem from 20% of data entry fields. By focusing efforts on improving the accuracy of these high-impact fields, the institution can achieve a significant reduction in transaction errors.

This is probably the best example as you NEED to do this to process the amount of data provided by process mining.  When looking at a process mining visualization, it is imperative to filter out the noise and focus on the most common error types. Combining this technique with others to ensure you are correctly selecting cases will set you up to address the issue’s root cause. 

Integrating Lean Six Sigma techniques and tools with process mining outputs enhances the depth and effectiveness of root cause analysis efforts. The whole point of process efficient efforts is to lean out processes, improve outputs and generate a positive ROI.  Leveraging technology to rapidly provide process insights and then follow up by bringing the process stakeholders through six sigma workshops results in the most favorable way to generate a positive outcome.  Embracing this synergistic approach empowers organizations to achieve higher levels of operational excellence and combine the best of both old or new techniques. 

There are a few things that I want to unpack from this prior to sharing my thoughts:

• Audit, Quality & Compliance are areas that have been modernized over the years, but in general lags as no one wants to be the first to make revolutionary changes as this carries additional inherent risk.  AKA Limited rewards for being first vs. massive downslide for any failures.

• Typically audits are done based upon what is documented, not what has actually happened.  Hence why process mining uncovering how processes perform can lead to more audit findings and headaches. 

• Big-4 audit firms make most of their revenue from billable hours, automation or anything that threatens those hours is treated with skepticism.

• Most of the Big-4 audit firms also have separate consulting divisions who do technology and process work.  As such, there are situations where recommendations in a technology or process might decrease the need (and the associated spend) with an audit. Therefore, most clients will leverage different firms to ensure they are receiving unbiased advice.  

While there is much to be made of the “ignorance is bliss” observation, what really jumped out to me is how reactive most are when it comes to leveraging this technology and how there is an argument to be made to stay that way. 

When starting process improvement work, most businesses leverage their existing providers as process excellence is a service that has been added to numerous audit/consulting firms.  To an extent, this makes sense for any improvement or system to be successful, you need to understand what happens today and how it can be redesigned in the future. To their credit, large audit/consulting firms are great because they have:

• A proven track record of delivering successful projects across various domains and industries.

• A large pool of qualified and experienced consultants, who can provide a wide range of skills and expertise.

• Access to advanced tools and technologies, such as proprietary software, databases, and frameworks, that can enhance the process mining capabilities and outcomes.

• Global presence and network, which can facilitate the coordination and communication of the process mining project across different locations and regions.

• A strong reputation and credibility, which can increase the trust and confidence of the stakeholders and regulators.

I have worked with some great teams at these big firms and whole-heartedly recommend their services. However, in the same breath, I have worked with others who under-delivered or given me cause for concern.  Things you should keep in mind or have previously happened to me:

• They can be very expensive, as they charge high fees and rates for their services and resources.

• They follow standardized and predefined methodologies and approaches, which might not suit the specific needs and context of the organization.  This can be great when you need this type of support, but other times you need consultants who can plug into a pre-existing team.

• I’ve had Big-4 consultants who are redesigning enterprise systems tell me “They don’t need to know how the current process works.” Beyond concern around how they are documenting the system– this shows that they don’t understand the value of clear processes.

• I’ve had Big-4 consultants who didn’t know what process mining was... after their leadership presenting them as experts and having been trained.

• I’ve had Big-4 consultants who view process mining as a point-in-time tool, meaning they didn’t see long term potential for continuous improvement. If their clients are listening to their recommendations, I feel like they are doing a disservice as they are missing out on longer-term improvements.

There is no definitive answer or a single approach – each process mining project and company is different and ultimately which requires leaders to figure out the best fit for their organization, situation, and needs. Done right, they will vet and evaluate potential partners, and select the most suitable consulting partner, ensure projects are properly managed and that a long-term successful program view is taken into consideration for future business improvement.  

I also have had numerous conversations and am actively working on building niche products within process mining space which would help to further uncover processes and their audit compliance which is so terrifying to Big-4 firms. So their reason for worry is valid, just give it a few years. 

This is a somewhat controversial post, so I invite you to reach out and start a conversation with me if you are:

• Work at a Big-4 firm and disagree with me! What am I missing? How are you automating the audit and process discovery processes?

• Looking at automating or monitoring your processes for audit purposes? What can we learn from each other?

• Have a process improvement success or failure story which I should feature on The Process Mine.  This could be associated with Big-4 firms or completely independently.

• Interested in learning more about my first hand success stories in process mining.

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Data Visualization Problem

“For a long time, there was this self-service belief that we needed applications where business users get a toolbox, they get data and then they do their analytics themselves. This is not the case - working with data is a profession in itself”.

When founding MagnaView in 2004, there was an initial focus on data visualization with an R&D effort in the process mining space from 2007 onwards. It wasn’t until the end of 2015 when this turned into a combined business under the ProcessGold name which brought together the technology vendor with implementation consultants under the same banner.

As the business grew, different verticals grew out that would be dedicated to a particular functional area or business to bring to potential clients. While there are many insights to any startup, this comes back to solving a key business problem.

Do Talk About

"Focus on how you can help solve a key business problem, and how you have leveraged the data of the user to get to key insights, and what that implies for the business."

Erik-Jan shared an example of how in one of their client meetings a key potential business stakeholder after showing a wide variety of process mining functionality without reference to the business remarked “well, I'm still confused, but at a much higher level.” Erik-Jan: "This is why we must always focus on our value first and why to focus on substance of insights rather than fancy technology."

Do Not Talk About

So, stay away from technology and solutions. Erik-Jan: "Do not lead the conversation with explanations of process mining, tools or that latest dazzling functionality which was just implemented. They are not useful when explaining the value of process mining to a first-time user."

Acquisition Process

Prior to the UiPath acquisition, Erik-Jan who was serving as CEO for ProcessGold predicted the external interest in an acquisition and prepared accordingly. What I think is most interesting in the acquisition process is the decision Erik-Jan made at the end of 2018 to have young talents Roel Vliegen and Chris Esmeijer promoted into the CEO role and take a sabbatical mid 2019. I think this speaks to a selfless leader who realizes when it makes sense to lean on their team and allow others to take the lead. This ensured continuity of leadership in the pre- and post-acquisition process.

Growth of AI in Process Mining

Like most areas, AI will continue to grow in usage for the process mining space. It will take time, but eventually there will be a real artificial process analyst which will help you improve your processes and provide external insights. Erik-Jan: "We do need some kind of symbolic AI, though, on top of the generative, statistical methods that are currently in fashion, to get there."

Post ProcessGold

Being successful in the software space, has translated to Erik-Jan to write a book on Successful Process Improvement which is focused on how to best embed process mining into enterprise clients and get the best adoption / value realization. I am currently working my way through this book, and you can anticipate a review in the next few weeks.

Additionally, Erik-Jan is currently seed investor and serving as Entrepreneur-in-Residence at the University of Technology Eindhoven, in the Netherlands supporting young startups. Interestingly enough, two of those, Mindzie and WavesPI, happen to be in the process mining space - so past learnings are now helping to shape the next generation of technology.

For those wondering why I am so interested in Founders Stories, it is because it allows further context of where we have been. If we know where we have been collectively, then it is easier to understand where we will be going and identify long-term trends. If you know someone we should interview as part of this series, then get in touch!

How has marketing shifted from a singular product to a suite of tools?

Historically, we have had several standalone process mining customers due to the Process Gold acquisition into UiPath. However, as the process mining journey goes for most customers, you have an amazing first impression from process mining and then you want to know what is next from the technology. 

They might implement it in one team, or region and that takes a bit of time at first. But eventually they get to this point, where they are able to understand the power, how to deploy it, how can we get even more value, and leverage the tool’s complete offerings.

That’s where UiPath is suited to customers that are going through this as you have an ecosystem that not only gives you the insight, but it helps you take the action to achieve those business outcomes that you're targeting. It is one of those things where customers can pick and choose and say, I wanna start with process mining today and then in a month from now or six months from now I wanna to expand to task mining or take action with RPA, so it’s a value platform approach and differs by each customer’s needs and business goals.

In terms of education, and in particular for new customers, it is all about how to frame the problem and associated value.  The most challenging aspect is understanding the specific use cases that potential customers want to go for. So it is all about qualifying the use case, qualifying the specific value that they're trying to achieve and what is the most suitable technology for that. This could be process or task mining, RPA or Machine Learning (ML), all of which have something slightly different to offer in problem solving. 

Most of the time in qualifying the use case, the value, the specific business outcomes which are being targeted will reveal how process mining, automation, task mining, all these different technologies can play in the mix to arrive at the desired business goal. 

Our goal should be to produce the outcome that is being targeted, this is why process mining is a very important pillar and enabler for multiple different technologies and platforms. If we are able to produce the desired outcomes, then we are able to go higher and higher into the organization driving C-Level conversations around processes and then enabling technologies. 

In terms of future growth, the most exciting near-term item will be how Generative

and Specialized AI will change the way users interact with their process insights and take the necessary action. This could be something similar to Google where you are able to ask text based questions and have specific insights generated by your company and industry standard data. The real game changer here is that users will not need to sift through their data as much, as insights will be generated, monitored and improvements all potentially tracked within a single toolset. 

As users mature, and processes are being monitored from a more end-to-end perspective, additional capabilities such as task and communication mining will continue to rise in popularity. This enables teams the ability to further extrapolate or extract a set or a part of your process. 

Having said that, Yiannis believes more companies will look to focus on “pockets of value” in conjunction with mapping of entire end-to-end processes and systems. This is because there are so many different stakeholders and systems which must be managed in an end to end flow.  As a result, he is focused on enabling people to go deeper than going wider in finding value. This is very different from how others are looking at this space, but it makes sense when looking at how organizations are structured and where UiPath can add value in more powerful use cases leveraging AI, integrations and multiple technologies to enable value. 

This ties into a prediction of where the broader Process Intelligence space is going, which is more consolidation. A good example of this is in the task mining space where there are many small to medium vendors whose customers will eventually want and need more functionality.  As companies look to integrate their offerings, they will focus on outcomes first and how these tools can drive changes. 

Lastly, these consolidations will be focused on making it easier to understand insights from a process, perform cost/benefit analysis and reliably predict what is needed to enable automation. We are already seeing this with the enablement of “citizen development” being pushed by automation companies, but combining that with process insights will vastly change the organization’s processes. 

The key takeaways from this conversation is how much further investment is going into transforming processes. At The Process Mine, we harp on how process needs should be equal to business and IT needs, and you are able to see that in action. Today’s tools inform and enable users to solve their specific problems today. Tomorrow’s tools will be even more intuitive and able to provide context for what is occurring in your processes and why you should take action. Powerful Stuff! 

Christiaan started his career supporting process mining as a BPM consultant, believing in the technology, knowing the pros and cons of using it and how this can revolutionize company’s operations. This put him and ProcessGold in a position where they were initially focused on consulting and implementation of other toolsets, but eventually there was a gap in the market due to competing priorities, shifting strategies and external acquisitions.

One of the tools Christaan OEMd in this previous job was a BI software built by a company called MagnaView and during a coffee chat one day, they discussed how bringing in some simple components/code could reimage the toolset into a process mining tool. This led to the current CTO (Roel Vliegen) implementing this functionality over Christmas of 2015 with supporting research provided by Wil van der Aalst from the University of Eindhoven. 

Now ProcessGold is focused on consulting and sales as they are the exclusive distributors of the new tool and MagnaView focusing on software development.  Seeing as this was a close and exclusive relationship, the two companies merged a year later to bring the entire team under the same roof. The name of ProcessGold was kept as this had a better market presence with Christiaan becoming the CEO and Roel Vliegen becoming the CTO and Co-CEO.

In terms of selling this new company’s software, it was pitched as “an X-ray for your processes” with the only thing needed is data out of your system to visualize end to end processes. There was a lot of disbelief and evangelizing back then because process mining was really new and unknown. The first customers were pulled in through the website and previous contacts, customers and by leveraging their extended network.

So thinking back, what was one of your key learnings in this phase of the company?

“I'm a technologist, so I love technology, so we were talking a lot about features and functionality and not about the value that it will bring. So that was a very steep learning curve for us in that time to really switch between talking about the product and the features and how great it is, instead of talking about what it will deliver for you and the return on investment.“

Ultimately what made ProcessGold successful?

“I think we did everything for our customers that was humanly possible. If customers had questions or they wanted to have a feature in the product, we did everything we could in the weekends, in the evenings and the nights to fix that expanding the products with functionalities customers really wanted.  And back then we were just a company of I think 60 people before we sold it. So we were a very small dedicated team and the only purpose we had was making our customers happy and that's what our customers felt as well.”

Expanding in terms of capabilities and team size is a testament to how well this strategy worked, however in 2019, ProcessGold was looking for further investment to expand the sales and marketing teams, when they were approached about being acquired by UiPath.  Initially, the goal was not to be acquired, but it was a good fit with culture, technology and made sense as the team was thinking about taking the next step with the product. Beyond culture, the two main drivers were:

Product Synergies - From a product perspective, process mining by itself does not really solve problems. It creates a visualization, showing where process improvement can be made, but ultimately you still need to act upon them. This merger would help to drive further user and system action in driving improvements by leveraging UiPath’s existing RPA capabilities.

Selling Capability - UiPath also had a large portfolio of robots, out-of-the-box connectors, and integrations for off Prem and on Prem cloud providers. This combined with their huge sales and marketing force made it attractive to bring ProcessGold into their environment so that they could further leverage this broader network in cross selling to a broader audience.

After this merger, it took some time to fully enable the existing salesforce and position process mining within the broader UiPath framework of tools. Additionally, the core code needed to be updated to better fit into the pre-existing UiPath cloud native SaaS product.  This was no easy feat, taking over two years and involving the original development team as well as additional developers pulled from other UiPath development teams.

Now that there is a unified platform, leveraging security, authentication and multiple different capabilities UiPath is now able to better leverage these different individual capabilities to offer more value and ultimately more ROI for their customers.

In terms of what’s next for UiPath process mining, Christiaan indicates this is an area of continued investment as there are numerous new technologies and customer expectations impacting the market such as:

Changing Customer Expectations - Customers are now expecting near-immediate insights into their data, as there are many more pre-existing connectors and analysis.  Process mining is becoming more commoditized as there are more toolsets with the focus now on driving broader value.

Suite of Tools - Stand-alone tools are expected to be able to integrate and have additional capabilities to drive additional insights and execute immediately on these insights with actions.

GenerativeAI - Customers want to be able to interact with their data in new ways and in an upcoming release users will be able to ask how the process is performing and be given recommendations based on specific customer data as well as areas of traditional improvement.

It is easy to look at toolsets for what they are today - but I think the history and insights provided by Christiaan are indicative of a broader trend we will continue to see. Companies and solution providers need to continue to innovate both internally and through external acquisitions to ensure they are staying relevant and delivering maximal value to their customers.

Your company has started to dabble in process mining, whether engaging in a Proof of Value project or extending the capabilities you already have. You want to set up best practices in a consistent manner and align to your organization’s priorities. It sounds like you want to build a Center of Excellence.  But how to get started? How do you ensure you are working on the right projects that will provide the ROI you are seeking?

Programs inherently drive benefits important to the organization’s strategic objectives.  Process Mining is used by organizations to drive benefits. Establishing a Process Mining Center of Excellence as a program will allow you to follow a systematic approach for success.

According to PMI’s The Standard for Program Management, the domains of Program Management are Strategy Alignment, Stakeholder Engagement, Governance, Benefits Management, and Life Cycle Management.  Each of these domains relate to building and sustaining a process mining CoE.

Strategy Alignment is the CoE strategy.  A strategy needs a purpose.  It is WHAT you are trying to do and HOW you are going to get there.  A Process Mining CoE needs to have a clear objective and a way to measure success.  For example, the organization’s goal may be to streamline processes and automate manual work by 30% or save a portion of the bottom line. The program manager will work with executives to understand their objectives and decide what the strategy is for the CoE. By knowing WHAT the strategic objective is, the program can build a plan on HOW to get there.

Stakeholder Management is about the people that are part of the program.  The CoE needs to identify and analyze WHO will make the program successful. Who are the sponsors of the program?  Who is responsible for the end-to-end processes you are looking at and who will make the actionable decisions for each use case? Who else should be included? Process Mining stakeholders include the technical teams that will be the data engineers and analysts who bring in the right data to build process maps and dashboards. Source System Owners may be needed to identify what tables/fields are required for the use case.  Process Subject Matter Experts (SMEs) will confirm and explore the process.  Process Owners review the findings, evaluate potential opportunities, and commit to actions to produce benefit. Continuous stakeholder analysis allows the CoE to identify who you need to manage closely, keep satisfied, monitor, or inform. A CoE is to produce best practices and consistency. It is the stakeholders that the CoE needs to make sure are aware, aligned and know where to go for the best practice.

A program uses Governance to provide oversight and control.  The CoE creates a methodology of tools and processes for its stakeholders in order to deliver the intended benefits. This typically includes what tools that will be used, documentation requirements, detailed roles & responsibilities, training, and communication. Governance also includes logs, such as issue and risk logs, decisions logs, and a benefits register. The CoE may develop Guiding Principles, the framework that guides teams on their process mining journey. It is important to develop a consistent user experience, standards for bringing in data, global templates for dashboards development, and a data dictionary. The CoE brings best practices to life as part of the Governance domain.

Benefits Management is the reason to do process mining because it brings benefits to the organization. The CoE will prioritize use cases based on potential impact so it focuses on use cases that yield the highest benefit. It will also track the value of each use case using a value framework. The CoE partners with process owners and their teams to review potential value, confirm actions that are needed, and establish a commitment to a quantifiable benefit for monitoring.  By following-up on the benefits derived from process mining, the CoE is able to communicate the status and total ROI being achieved. This not only provides kudos to the teams involved but raises interest from other teams. The CoE can work with these teams to evaluate their ideas and build a roadmap of opportunities to continue to obtain value generated from process mining.

Life Cycle Management pulls all of the domains together and is the management of the program.  Once benefits are achieved, it is necessary to ensure the organization is prepared to operationalize the process changes to ensure the improvements continue as expected. If automation is involved, the operational support team may be IT or the process mining technical team. Regardless, the CoE needs to identify the tools used, responsible teams, deliver training and escalation paths, and provide guidance on how to continuously monitor the new process. Change management may also be needed to deliver the right communication.  Organizations don’t want to lose benefits because the improvements from process mining don’t stick. The CoE supports the organization with the capabilities and keeps a check on the operations.

As you can see, establishing a process mining Center of Excellence as a program will help set up best practices, build a community to support process mining capabilities, and ensure the use cases align to your organization’s priorities.  The intended benefits will result with positive ROI outcomes and be monitored for long lasting results. What are you waiting for?

Leslie Goldstone, PgMP, PMP

LinkedIn

What is your role with Celonis?

My role at Celonis is Sustainability Go-To-Market Lead, with a particular focus on Europe. We help companies plan and launch sustainability programs using process mining. In addition, we build and maintain standardized sustainability apps which can be quickly deployed for standard data models such as Order-to-Cash (OTC) and Procure-to-Pay (P2P). 

Why use Process Mining?

When it comes to most technology problems, there are many tools which could be leveraged to solve a given problem - so for sustainability, why use process mining? 

With Celonis, you are able to capture performance metrics such as cost or emissions and have them automatically measured and tracked. If you are already leveraging process mining to improve your performance, this is a new use case where you can use a pre-existing data model.  However, supply chain leaders cannot improve their processes without key insights on how the process is performing today. Or as Michael stated:

“Everything you do at scale comes down to the process, it’s the lifeblood of an organization.” - Michael Hogenboom

When you compare process mining to other analytics tools you run into limitations. For example, with most reporting tools, you are limited by the data and data models available. You lose the ability to span across various toolsets, groups and processes in some cases. Also, when building reports you depend on the analyst to decide what's valuable and what is relevant – and the value based on their capabilities and insights. Whereas with process mining you start with a 100% process view. At Celonis we provide unparalleled visibility into how a company’s processes run – think of it like an MRI over your business. That means finding your status quo and unearthing ‘unknowns’ and downstream impacts is rapid and effective.  

How do Companies Get Started?

I think for many companies, it is pretty daunting to start with sustainability in process mining because it is like a double innovation with both digital twin and sustainability work happening at the same time.  The IT discipline has a lot to contribute with the agile methodologies breaking complex big things into small steps. Therefore we have a “think big, start small” approach where we boil it down into one small chunk of the process and start tracking/improving the process. For example we might start with outbound shipping emissions at one site, and once we understand how to track, improve and control that process we scale up to a regional analysis. 

Successful companies typically pull together a cross functional team of experts representing the following three key process areas. 

IT Teams - Who know the data, the technology, how to automate processes

Business Teams - Who are interested in how to improve performance and what could be done on a cost of emissions basis

Sustainability / Strategy Teams - Understanding the broader picture and how to best align to the company's strategic goals 

What are the Impacts Being Realized?

There are a lot of efficiency gains that can be realized with process mining that have win-win impacts such as reducing error freight or half-empty trucks. This would lead to a cost and emissions reduction, but also a business improvement in the broader sense. When talking about sustainability, it is not something that we separate from a broader business ROI perspective. When speaking with customers, we typically focus on top line value and bottom line value. In the context of sustainability, we introduced a concept of green line value, which is the necessary emissions reductions required to meet corporate goals and be in alignment with the Paris Agreement. 

Efficiency gains are how we started moving into the sustainability space, but as our ambition has grown we want to help companies make sustainability a focus for operational improvements. The first step for that is measuring in an automated way continuously as part of your process performance and then being able to plan, prioritize and realize improvements in that performance. This information is scattered across systems and there for most companies there is not a single source of truth. 

This is especially important for talking about a company’s Scope 3 Emissions which are all the emissions that occur upstream and downstream in a supply chain, not directly by the company but caused by suppliers and customers. In essence this means that if you contract a company to do your freight or transportation, their emissions are included in your Scope 3 emissions. What is interesting about Scope 3 is that it's the area that companies do the least amount of tracking at the moment, but often account for around 70-80% of a company’s total emissions! Depends on the industry of course but if you look across many industries they are the massive bulk of emissions and they are essential to tackle if you would want to be net zero or have sustainable business practices. 

Tracking these emissions is critical, therefore process mining is critical in validating metrics and improvements. With process mining we are embedding granular measurements and logic in the data models, which can then be audited by external parties and updated as necessary, which ultimately provides flexibility and traceability to a sustainability program. 

How do I Learn More? 

Sustainability is one of those overarching topics which should be a goal of every company regardless of your vendors. Celonis offers some key advantages, but there are lessons here which could be applied to any company or technology leveraged.  I recommend the following sources to learn more:

Celonis Sustainability Solutions - Dedicated to the services, goals and objectives of this unique group

Celonis Sustainability Report - Covering Celonis own sustainability performance and initiatives

Hackathon - Pre-existing customers can leverage their existing data and compete in building new analysis dedicated to sustainability 

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Martin started doing manual consulting work at different companies over 15 years ago and kept thinking that there must be a better and more efficient way to do this work. Ultimately, this led to him implementing automation and lean process improvement as he wanted to increase the value of his actions. Today, he takes a hyper-automation approach to consulting for companies, which includes intelligent automation process mining, BPM, BPMS, and associated toolsets.

Is there a standard approach for Process Mining?

When Globant engages with a new client, they have a standard approach, but at the same time, every client is different and there is no “silver bullet” for how to do these kinds of actions in the “best” way however, in general, the following steps are used:

● Educate: First, we demonstrate the potential and explain what process mining can do. Sometimes people may not understand why this technology is relevant and what we can do with this information. We don’t want to implement just to introduce new technology; instead, we want to ensure process mining is adding value by doing it the right way.

● Identify Use Case: Next, we need to find a great candidate where we have the information, people to support the project, and a gut feeling that there might be valuable outputs which can drive business transformation.

● Find Data: After that, we really need to get more tactical as we look to outline what we are going to map and what data sources we are going to go after.

● Industry Considerations: Depending on the industry, there are some differences in where there is the majority of value. Most companies see value in “Order to Cash” and “Procure to Pay,” but then you get into use cases specific to the industry. A good example of this would be Meter to Cash processes in the energy industry where there might be less pre-made analysis and more custom-driven insights.

What is One Example of a Unique Use Case?

At Globant, they have done a lot of “standard” process mapping use cases, such as SAP, JDE or WMS systems, but beyond that, there are a lot of different custom use cases that can be applied.

Globant has used process mapping on a custom software which combines SAP, Excel, and IoT devices to provide a full end-to-end process view. This was a very unique data model, as they first needed to build a common database with all these disparate data sources. What is cool about this use case is it is tracking a person’s journey when visiting a sports stadium. It allows them to understand when a customer bought the tickets, when they checked in, and then combine that data with technology like face detection to understand their experience at the stadium and improve their experience in real time.

Where Do You See Technology Evolving?

Process mining is part of a broader suite of tools supported, which includes RPA, Machine Learning, and BPM. All of these technologies have different use cases and sweet spots to add value. Over the past few years, we have started to see these technologies converge as platforms are starting to support all these different capabilities. The problem today is the use cases typically do not easily leverage the best of these different pieces. There might be technical hurdles to bring in these different capabilities, cross-team conflict for these broader use cases, or data limitations. As a result, today Globant is leveraging separate models in different tools, but in the next five years I think we will see more automatically triggered modules crossing between process mining, RPA, and AI/ML. In essence, we will have a single autonomous model able to leverage the best of these different technologies, which will enable real-time actions and improvements.

What Are The Main Process Mining Use Cases You See?

There are four main use cases that clients normally use when it comes to process mining:

System Migration - Leveraging process mining to prepare the current state process maps and then using this information to build the new system and prepare for migration.

Operational Efficiency - Most popular use case in understanding how stand-alone processes are performing and how those processes are interacting with other processes and systems.

RPA Identifications - Determining where we can best automate our existing processes, track improvement gains, and ensure our automations are performing as expected in the context of the end-to-end process.

Audit & Compliance - This is one of the fastest-growing use cases as we work to understand where compliance is failing, the specific path of those orders, and uncover potential fraud. Using AI with process mining to do more proactive and reactive analytics on the processes to help enable efficient audits.

Besides these four use cases, there are a lot of specific use cases that are customer- specific, such as tracking waste or CO2 emissions. Over time, we expect these company or industry-specific use cases to become more standard and popular as more companies look to track different parts of their operations.

How Do You Find Value?

Process mining is a great tool to monitor processes as you are able to find an opportunity, implement a change, and then measure the improvement afterwards. The challenge, however, is that principle process mining by itself doesn't execute anything. You are only finding the opportunity, so operating alone will not have an ROI. However, sometimes you could not find that opportunity without process mining, and even if you could, how would you track the impact without process mining?

This is very different from something like RPA, which is very straightforward because you reduce the time, you reduce the cost, and all of a sudden you’ve got a clear ROI which you can communicate back to leadership on the project’s success. However, with process mining you get that initial insight, then you can layer on RPA improvements and ultimately then bring in AI to start improving the process proactively. This is a much more complex program potentially involving multiple technologies and teams, but has a much higher reward than a simple automation.

A good example of this would be looking at shipping. You could start applying process mining to a warehouse system to understand inefficiencies in the process and identify potential areas of automation. You could apply RPA to some of the simpler administrative tasks to further enable the shipping process. Then you could think about how to embed AI/ML into the business process and do things like trigger automatic RPA workflow when an order could be potentially late.

I typically do not talk about a specific ROI that process mining can achieve, because this gets back to the individual use cases and, as mentioned previously, process mining is at least initially uncovering how work is being done. In general, we can get some insights in 4 to 6 weeks, but then it might take longer for the RPA and AI/ML work to be completed.

While there are no perfectly safe harbors, as spending priorities will vary based on the company, industry and their specific financial situation, I would argue that long-term successful companies will look at the current economic situation with a long-term lens. This isn’t just an opinion, during the 2008 depression, Toyota recognized the importance of their workforce and the opportunity presented during the decline in demand. 

"During the worst economic downturn since the Great Depression, we kept every one of our regular U.S. manufacturing team members employed, even as global auto sales plummeted," James said. "Instead of layoffs, we protected employees by adjusting production."And during production lulls, Toyota kept employees busy by offering additional training, devoting time to continuous-improvement projects and providing them paid time off to volunteer in the community” Staying True to the Toyota Way During the Recession by Josh Cabel

This approach ensures that as the economy recovers, there is both a ready workforce in place but also a more efficient workforce. Toyota was able to improve their internal manufacturing processes and assist in leaning out volunteer organizations.  Furthermore as seen during the Covid-19 pandemic, there will be issues in scaling back up operations once the market improves. 

So what are companies to do with this uncertainty? Toyota was in a fortunate position in the situation above, and we all have seen the effects of a slow rebound when Covid-19 demand spiked. My recommendation would be the following: double down on ensuring you have efficient operations, clear processes and automatons where it makes sense.

Improve Current Processes

In any market, there are ongoing changes to customer demand, but they occur over a long enough time horizon where businesses can be slow in responding. However, with any major market change (recession, panic, pandemic) that the market demand can drastically change. Therefore it is imperative to invest in understanding your current processes, documenting how work is currently being done, base-lining metrics and overall leaning out where possible. 
Once your operational processes are efficient, then you can start looking at how you can apply digital tools to bring this data into your planning processes better. A good example of this is leveraging order-to-cash (OTC) and procure-to-pay (P2P) process models into your demand signals for earlier detection of a demand change and alternative products which could satisfy customer demand. 

Automate Where Possible

The most unfortunate part of any recession is the human impact and in this case, those who will lose their positions due to reduced demand or changing business priorities. This is an unfortunate part of any enterprise, but in a recession there are typically fewer workers doing the same amount of work with ultimately lower performance and morale. 

“A key reason for this underperformance is that remaining employees are often forced to take on more work. This tends to leave them feeling burnt out, undervalued, and unmotivated.Automation does the opposite—employees are enabled to do more with less, and spend a smaller part of their workday on tedious tasks. Since they enjoy their jobs more and are gaining new skills, they’re more likely to stick around for the long haul and grow with the company.”

Here’s Why Experts Consider Automation “Recession Proof” by Bobby Patrick
Even in great economic times, automation should be a priority for every business as there are numerous tasks which need to be completed, but are more transactional in nature and not requiring human intervention. In a recession, this becomes much more important as there are fewer workers, more work and limitations on what the bottom line can support. Automation benefits are hard to quantify, but Forrester and Automation Anywhere report found a 6 month payback period and a 3-year ROI of 186%. Great statistics in the best of times, but could be company saving in the worst of times. 

Prepare for Demand Changes

There will be changes in priorities from customers and companies as their business needs change. I think back to the quote by Greek philosopher Heraclitus  “The Only Constant in Life Is Change.”  Judging by past major market changes, we can anticipate that the needs will change rapidly and in ways we would not have been foreseen.  Who would have imagined the hot items early in the Covid-19 pandemic would be N95 Masks and toilet paper?

Therefore, it is important now that companies prepare for this uncertainty. How quickly can you spot changes in your customer behavior and demand? Where are your critical materials and bottlenecks within your processes?  We tend to let processes slowly evolve and change over time as there is no major impetus for making radical changes.  I do not think companies should make major changes to their processes, but they should know what their processes are and understand how they will change their processes if needed. 

Hopefully there is no need to make drastic business changes and companies will not have to implement this safety plan.  If that is the case, the organization is better documented, prepared for further process improvement and in a position to be proactive rather than reactive to a market change. 

Thinking about recessions and the many adverse ways it can affect businesses and us personally is not a fun topic.  While we all hope that we manage to avoid a recession and enter a period of further economic growth, it is inevitable that there will be unseen items in our future.  We know there will someday be a recession or global event that must be handled as it could threaten our business operations. Instead of being reactive waiting for this to occur, I would advise it is better to document our processes now, streamline where possible and be prepared.  

Read More
Lean On Your Supply Chain To Weather The Potential Recession by Guy Courtin

World Wide vs US Comparison

Based on the analysis, in the world there is more interest in Process Mining compared to Process Intelligence.  Process Intelligence tends to be more of a catch all term, encompassing any technology where you are automatically collecting and processing data about a process –  which would include Process Mining, Task Mining as well as some potential RPA and AI tools. 

I think it is interesting that from a world perspective, a more granular search term is in greater use compared to the United States where they are being used interchangeably.  It is unclear if there is any long-term trend or insight, but an interesting observation to track throughout the year.

Tool Comparison in Germany

When it comes to process mining and preferred toolsets, Germany looks like a country divided and I would argue a country with broader implications in terms of existing capabilities, adoption and new capability development. 

• Celonis was born out of a German University and has very strong ties within the country

• Signavio was purchased in 2022 by SAP an ERP company based in Germany and with a highly vested interest in improving their processes

• UIPath has offices within Germany and was founded within Europe

• Germany has been a leading country in terms of adoption and usage

I think monitoring interest and seeing how these preferences change would be valuable to track into 2023.  I would anticipate greater competition between all these firms, new capabilities to differentiate themselves and more fluidity in preferences over the next year.  

RPA & Six Sigma Inflection Point

There seems to be the idea that we should automate everything without little thought into driving to the ideal process. This makes some sense as if it is a truly automated process, who cares if it is inefficient. I think you can see this playing out somewhat in the chart below showing relative interest in RPA vs Six Sigma. 

As a Six Sigma person, we know that we need more data points to confirm this hypothesis, but it still is an interesting anecdote and something worthy of discussion.  Are you automating and making your processes efficient or just automating?

• Strategic business objectives linked projects

• Internal political considerations for a proposed project

• Maximizing organizational/project ROI

• Project/Organizational Risk

• Project Cost

• Security/Upgrade Requirements

• Total Project Budget

After weighing all of these factors, typically projects get classified as a “must do”, “nice to have” or lastly “won’t do” where there are more pressing projects in the backlog.  Seeing as these planning sessions directly impact business operations, it is critical to maximize the value in these workshops and leverage data where-ever possible. 

I recently had one of my business stakeholders put this entire process in the correct perspective.  They came to me and asked the simple question “where should my team focus for the next year?” In the prioritization process, there was a set amount of resources dedicated to process optimization and they wanted to leverage process mining to direct their improvement efforts. They did not bias our review or give us pet-project areas they wanted to improve.  As a result, we were able to look enterprise wide for where we saw the most value for these business/technology improvements. 

We started by pulling a number of key enterprise wide metrics that we knew all teams should be working to maximize.  We then ranked all of these opportunities in a chart similar to what is below, so that we got the necessary context and could pick out true outliers.

After a metric was selected, we were able to do a deep dive into the process area leveraging Process Mining and determine insights / root causes.  For instance, we would look at Process Area 5’s cycle time and work to understand if this is being driven by a product, sales org., or maybe a single user.  Additionally, we can quantify this potential improvement in cycle times, cash flow improvement or customer happiness to ensure we are maximizing our ROI. 

As much as process mining is a tool for process improvement, it is equally a tool to manage and drive insights into how processes are performing. Using process data to identify areas of improvement, automation or process redesign is the natural way to leverage Six Sigma Methodologies with a Digital Tool-set. 

I am interested in how others have leveraged process mining in their prioritization matrix.  Feel free to send me a note or reach-out to me if you’d like to share your tips!

Over the last year or so, we have seen more consolidation and interest in the digital process and automation tools. Ultimately, this interest foreshadows what will be occurring in the next one to two years, as it is no longer enough to identify or automate a task – it is now expected you can do both. Taking that a step further, you are now seeing tools that are not related to process improvement realize that an efficient process is imperative for continued use and growth of their tool-set. If you are a vendor not focusing on improving your customer’s experience, you will be a vendor missing huge opportunities.

While not all-inclusive, you can see in the chart below that there are several traditional vendors making key strategic moves to round out their portfolios. Each of these tools has a core strength that needs to be further augmented to keep its market-leading position.

As with any change, this will have both positive and negative consequences for their user. With an increased focus on process and user experience, these tools will ultimately become more efficient – increasing automation, decreasing rework, and improving customer satisfaction. This reinforces my position that companies with exceptional processes will ultimately be more successful than their peers.

Looking Ahead

For uses of these platforms, it will become imperative that you either select a strategic partner or structure your process improvement/automation activities agnostic of a single tool/vendor. Which choice you make will deal with the maturity of your organization and your preexisting vendor relationships. I would caution that this is an evolving space, and it is ultimately hard to predict where technology will be in a few years. 

As such, I would recommend that organizations keep a somewhat flexible approach. Process improvement and automation will continue to go hand in hand – but you cannot wait for all these products to be fully baked. A balance must be reached where you have a short-term roadmap delivering business value but are also looking at longer-term industry trends. I would equate this to the software consolidation we’ve seen in the past where different products are slowly absorbed into a full suite of capabilities. 

1. Lack of Stakeholder Buy-In

In general, process improvement is not typically associated with back-office activities, but rather something is done on a manufacturing line. Therefore, when trying to persuade teams on the value of process improvement and more specifically process mining, it can be very difficult for people to grasp the opportunities and insights available.  This can lead to stakeholders who do not adequately understand potential benefits and therefore view process mining as a useful activity but not critical for success.

In practice, this can mean not receiving adequate resourcing, low SME involvement, and worst of all a timeline that is not achievable to perform analysis and find value. All this can doom an individual project and more importantly can damage the reputation of the overall improvement programs a company is looking to undertake.

Tip: Develop a project charter with key timelines, goals, hypotheses, and SMEs before kicking off any project. It is better to have a smaller well-defined project than a large project which might not be successful to build enterprise capability and buy-in.

2. Limited Data

Process mining requires data to be successful, and in most cases a lot of data. In enterprise environments, there is always the challenge of finding a readily accessible data source and then interpreting tables and customizations in a timely manner. If a direct source connection is required, there are times when this data is just not easily attainable which means ingestion and analysis must be put on hold. When determining project plans, it’s often an overlooked hurdle in unlocking this data and as a result, a process mining project can quickly fall behind before any process mining work is started.

While these “data delays” are easy enough to overcome, the real risk is with disappointed stakeholders and missed opportunities for readouts. As this is a somewhat newer technology, it’s critical to focus on the value and insights, not why projects are behind schedule.

Tip: Include this connection as part of a charter pre-requisite. Once data is populated, build some simple analysis and present it to SMEs as a “first-look” to validate the process and quickly identify areas of customization or further required data.

3. Goldilocks Scope

When launching a new process mining engagement, it’s important to ensure that there is an adequate scope. I like to start all our projects with a few hypotheses or questions where SMEs are looking for insights and opportunities. Then it’s critical to ensure that you have a scope that gives enough flexibility to investigate and find other opportunities. Too small and you risk not finding any major insights and too large and you risk finding insights that are too large to become easily actionable. The key is to find a system and process that spans multiple sub-processes, sites, or product lines but is not too large where a few SMEs can provide insight.  One of my key principles is that process mining is a program, not a project. There should be enough scope to find some quick wins and get insights, but also enough opportunities left that can be actioned in subsequent projects once the team finds some initial success.

Tip: Once data is loaded into a process mining tool, the process mining team should be able to return some initial insights and start on-boarding team members within 4-8 weeks. Any longer and you risk moving into a situation where you’re building analysis that cannot be quickly actioned. Remember, you can always add more systems/sites/insights later, but project success typically hinges on how quickly and enthusiastically the SMEs can drive change.

Every process mining project is different, and I’m sure many of you will have more items to add to this list in terms of watch-outs and failure reasons.  Drop me a note or submit a comment with your key learnings.

What is challenging and somewhat new; is how we prepare our business end-users to consume this data. We’re asking people, who have previously been very siloed to look at their processes but also, the process which comes before and after. We’ve seen numerous instances where business SMEs are very knowledgeable of “their piece” of the process with a limited understanding of how it “fits” within the full end-to-end flow. This is challenging if we want to completely reimage our processes and ensure our operations are both effective and efficient in how work is being completed

Bringing people into process mining is a change management activity and if done properly can have immense organizational benefits. However to bring people on board, you need to educate them on the current process, what different KPIs and metrics mean, and ultimately what broader business goals are being impacted by their individual performance. This problem is not unique to process mining, but something being seen with any new major technology (AI, RPA, ML, NLP). I would recommend reading HBR’s work on analytics translators where a dedicated group is focused on added context and explaining metrics to those less technically inclined.

For process mining specifically, I do believe there is a need for analytics translators - but it goes beyond that. Most organizations are geared around separate businesses and IT teams focused on their piece of the process. This inevitably leads to somewhat adversarial relationships with each party focused on their organizational goals at the expense of process excellence as a holistic company. IT hitting targets to hit their metrics instead of adapting to help sales meet/achieve/surpass theirs. Most of our customers don’t care how the work is done, only that it is and meets expectations.

Instead of treating this problem as a single choice where one side takes action, instead, I propose we elevate the process back into the overall equation. Focusing on the process creates options and allows for increased flexibility in meeting organizational objectives.

Oftentimes, new regulations and requirements are identified which will turn into a system request to build this new capability. Instead of moving directly to a system change request, we should let process and organizational goals be our guide.

1. Process mine the existing process to understand how business and IT systems are currently working.

2. Compare existing processes and future state processes to understand where those updates need to occur.

3. Evaluate those required updates and identify the best solution forward.

   • Changing a business process with no system change

   • Implement RPA or other advanced capabilities to enhance the process

   • Put in a change request to update the system

There is no right answer, each request will be slightly different however, if we follow our process and key objectives we, will be making decisions on what’s best for a holistic enterprise. With every system change, there is a much larger cost to build, maintain and support this change request. Likewise, there is an equally impactful opportunity to reduce non-value activities in most business processes. We cannot improve both of these constraints without a dedicated focus on process excellence.

Why #1: Why write a process & task mining blog?

Answer: There has been a lack of coverage and resources on how to best implement these tools.

Why #2: Why has there not been sufficient coverage on the process and task mining tools?

Answer: These are new technologies and most of the coverage is still on how to technically enable, not how to gain the most value or fit into corporate culture.

Why #3: Why should people care about your thoughts on getting value?

Answer: I have a Lean Six Sigma background and have been implementing and realizing value from process mining over the past 10+ years.

Why #4: Why should people care about Six Sigma and Process Mining?

Answer: Six Sigma is a methodology mostly applied in manufacturing that can be combined with process mining to ensure we are addressing the correct issues and gaining value.

Why #5 Why should we invest the time in learning methodologies - when there are easy opportunities.

Answer: When implementing any of these tools, there are often immediate quick-win improvements that can deliver substantial value. The key though is turning this into lasting value and an ongoing program, which will require a methodology and more process work.

In time, I see digital process tools improving corporate processes similar to how Lean and Six Sigma massively improved manufacturing and warehousing operations.

Revised Goal Statement:

Through this blog, we will explore how to implement and maximize value for process and task mining by leveraging quick wins and long-term methodologies. The focus will be on combining digital process tools with per-existing standards such as PMP, Lean, and Six Sigma to enable enterprise roll-outs and adoption.

Define, Measure, Analysis, Improve, and Control (DMAIC) is a common framework used to plan a process improvement program. This framework requires improvement projects to first define the problem and then measure the impact in order to draw conclusions and propose improvements. This concept places math and statistics as an integral part of the improvement effort and by measuring key metrics such as cycle times, processes that could be simulated, improved, and ultimately controlled. This is a tried and true approach that has completely reshaped industries. Six Sigma has helped companies such as GE and Toyota reach new heights becoming market leaders in their respective industries.

If Six Sigma can be applied to a wide range of businesses and have a proven track record of success, why would anyone want to change or evolve from this standard approach? Performing Six Sigma projects requires investment from the business to launch data collection plans, process deconstruction, and ultimately implementation of new controls. Most importantly, Six Sigma initiatives require time, resources, and business support which is not necessary for all projects – especially projects outside of manufacturing. This has led to more businesses following the Six Sigma methodology but selectively applying it based on the project. Typically, Six Sigma is applied to manufacturing processes but not to “back office” processes and even then, is not a guarantee of a successful project.

The process improvement mindset must be extended to all processes, whether they are machine or human-driven. The consequences of not adopting this mindset can range from operational efficiencies to a full revolt. Though causation might not be completely proven, major cosmetics company shareholders launched multiple class-action lawsuits against the company claiming poor oversight of the implementation of its ERP system. The lawsuit claimed the stock price was negatively affected because its recent SAP roll-out suffered sub-par controls at the process level, resulting in inaccurate accounting of sales, COGS, inventory, and accounts receivable. The company confirmed that they were unable to fulfill shipments of $60 million worth of product.

An extreme example, undoubtedly, but indicative of what occurs in the business world in regard to process redesign. Technology solutions are meant to support business processes; however, oftentimes documentation or subject matter expert input is not readily available. Automate a poor process and you are only doing failing faster.

Undoubtedly, their manufacturing and warehousing operations are overseen by robust Six Sigma practices in the traditional manufacturing sense. Their service processes could have benefitted from similar oversight in terms of traditional process improvement prior to launching such a massive IT overhaul.

Process improvement methodologies have a key place in business but as we’ve highlighted have some significant challenges that need to be addressed. One of the biggest being, how quickly can we understand our current processes and create process documentation. In traditional projects, this is being done by meeting with subject matter experts (SMEs) in workshops and “walking through the process.” With the growing prevalence of “team-based software”, the complexity of how work gets done becomes even harder. No longer are we seeing one owner, but rather multiple stakeholders with various vested interests being part of a larger end-to-end platform.

An opportunity to improve our six-sigma methodology exists when we apply process mining to the equation. Process mining leverages these system and event logs to create an objective, fact-based process model. These process models include all system-driven tasks such as order entry, processing, and delivery, which in most cases is roughly 80% of the entire end-to-end process. Where we are missing details is the non-system-driven work, so things like “I need to email Carol”, “let’s put this into Excel” are critical for the work to be completed but not as easily understood. This is where we engage with our SMEs as we can fill in the missing manual tasks and ask detailed questions on why certain steps are occurring in the process. In this manner, we are guaranteed to capture 100% of the system processes, reduce the burden on our business SMEs and ultimately complete our current state analysis quicker.

If our goal is to improve our processes, process mining can only go so far, we still must interpret the data through the lens of our business operations. Data gleaned from process mining does not represent the entire end-to-end process nor does it contain the context associated with the business operations. This is where there remains a need for “traditional process improvement” to utilize the outputs of process mining and add further context and clarity. A good example of this is the confusion between causation and correlation.

One pitfall of manual process mapping, depending on a room of experts, is confusing causation with correlation. Correlation is when two or more factors move in proportion to one another and causation is when one of those factors, when moved, causes the other to move. This can be counterintuitive and, at best, confusing and, at worst, dangerous and wasteful. A simple example involves ice cream and murders. It is known that in metropolitan areas when ice cream sales rise so do murder rates. And when sales go down so does the number of murders. So, does eating ice cream cause people to rob others at gunpoint? Obviously not. Statistically, there is a correlation. As temperatures rise in cities, people go outside more thus there are more chances to be a murder victim. Also, as temperatures go up, people buy more ice cream. So, there is causation between temperatures and ice cream sales, and causation between temperatures and murders, but not between ice cream and murder. (Marchand, 2017)

If applying Six Sigma without process mining has its biases and limitations, the converse can be equally problematic. Applying the power of process mining tools without a grounding in the principles of Six Sigma can be akin to a layperson performing surgery on a friend. Six Sigma experience is critical in translating the outputs of process mining into remediation actions with the best ROI. Otherwise, you may find yourself chasing down process variations that are statistically insignificant or updating systems when a business process change would be more efficient. A Six Sigma Black Belt can analyze the outputs of process mining and identify the process owners who need to, for example, use poka-yoke to mistake-proof processes, create dashboards to illuminate those who are not following the process, or simplify the ways a user can enter a process. Without a solid grounding in process improvement and Six Sigma, the power of process mining can take a team on expensive and time-wasting wild goose chases.

Leverage the abilities of process mining to derive actual processes, pain points, and opportunities for improvements based on the system logs. Only then should the SME’s be interviewed as we’ve already captured most of the process details and can ask specific questions to further build out non-system activities and why activities are done in a particular manner. Beyond reducing the burden on SMEs, this approach also ensures that we have a 100% documented process from the system perspective – we are not relying on SMEs to remember everything done in a system.

We then leverage Six Sigma mindsets and tools to then drive the adoption of these changes to the process and systems impacted. The biggest difference is instead of following a DMAIC approach, which is a waterfall-based sequential process, we follow a more agile workflow. Since we have already connected to the source systems and modeled the process, we are able to start in the middle at “Measure” and then cycle through Define, Measure and Analyze phases until we are confident in the updates to the process.

In practice, this is very similar to DMAIC in traditional six sigma, as the Define phase is where we are creating a hypothesis and then working to confirm that hypothesis with data. In process mining first, we already have all the data – so instead of confirming the impacts, we are now working back to confirm the business reasons for these activities to occur. This cyclical approach ensures that we understand the entire process and can drive improvements in the most effective manner.

Once these updates have been made to the processor system, as a closeout we want to ensure we are realizing those benefits and have improved the process as expected. However, in traditional six sigma we would need to do another time study which is a short duration review of the process. With process mining, we can automatically create our control charts and alerts when we deviate from the process and then further refine this future state process. Instead of having an improvement project, we are moving to an improvement program where we continually monitor and improve the process.

All things being equal, a company that is more efficient is going to be more profitable and ultimately long-term successful. In addition to the efficiency gains, companies that follow this approach will have a much better understanding of their current processes and be able to adapt more quickly to changing market conditions. In the past few years, we’ve seen how SARS, Covid-19, China trade disputes all have dramatically reshaped supply lines and those that can transform quickest will have a competitive advantage.