Celonis Chief Evangelist shares customer experiences from his new book

In 2020, Lars Reinkemeyer, Chief Evangelist of Celonis, published a book called Process Mining in Action. The focus, as the title suggests, was to examine how some of the world’s leading companies are using process mining to better understand and improve how their organization works. But technology doesn’t stand still, and since then Celonis has moved beyond the idea of ​​using its platform to understand processes in isolation – and has moved toward what it now calls “process intelligence.”

This was underpinned by the launch of the vendor’s Process Intelligence Graph, which enables companies to develop a knowledge graph that maps all of an organization’s ‘process knowledge’ and creates a ‘digital twin’ of business operations. This is enabled by developments in Object Centric Process Mining, which enables companies to map how different ‘objects’ (e.g. ordering, production, delivery, procurement) interact with each other.

With these developments in mind, Reinkemeyer is publishing a new book called “Process Intelligence in Action” that explains how the Process Intelligence Graph takes process mining to the next level, backed up by examining 12 operational use cases from some of the world’s leading companies – including BMW, Bosch, IKEA, Merck Group, PepsiCo and Siemens.

diginomica got a first look at the book and also spoke with Reinkemeyer to learn more about how process mining technologies are evolving and what can be learned from the customers who support the book’s main arguments. The main principle for Reinkemeyer is that this latest publication helps customers move beyond insights to action:

With process mining, we gained insight and understood processes – we analyzed them, created transparency, identified problems and created an x-ray. Process intelligence is now more about saying, “Insights are great, but it should be more about the value-added action.”

What does an organization do with these insights? How can Celonis help our customers take impactful action with action flows, intelligent operations, automation, and also create value with the Roach approach of an operating model with the value methodology. So for me, the evolution is moving from just data insights to advising customers on what to do with them and how to create impact with them.

On the one hand, there is the methodology and the organizational approach. On the other hand, there is also the technology – we have the Process Intelligence Graph – which forms the data backbone.

Celonis is working on several fronts to extend process automation for its customers (that’s the active part that goes beyond insights from process mining). For example, last week the company announced the launch of its Orchestration Engine with Emporix, which goes beyond simple robotic process automation (RPA) of tasks like pricing or quote creation, and enables buyers to fully automate the entire sales or purchasing process in an organization.

Reinkemeyer believes that among all the clients he has spoken to, the successful companies have one thing in common: they have understood the purpose of their goals:

It’s not about the bits and bytes, it’s not just about the insights or the data, it’s about the purpose. Talk to someone who’s responsible for a process and ask, “What’s your priority?” Do you want to drive automation? On-time delivery? Reduce working capital? What exactly is the highest priority? If I give you the right skills and insights, will you use them and ask your business to work with them to drive action and value?

And the key is to understand the desired outcome:

What do you want to measure in terms of purpose? Is it dollars? Is it productivity? Is it employee satisfaction? Is it carbon emissions? What exactly is on your agenda? Then work to ensure that the person in charge can leverage the ability to drive measurable, tangible impact and improvement.

This changes the discussion from a cost center to a profit generator.

People are the key

Through speaking to clients for the book, Reinkemeyer was also able to identify common pitfalls when introducing process intelligence into the enterprise. First, he said that the lack of a clearly defined purpose, as discussed above, can cause organizations to become distracted – leading to poorer outcomes. But equally important is putting the right people in place:

Not everyone in the organization is interested in change. You have to find the people in the organization who are interested in data, who are interested in change, who want to do things differently. Not many people are serious about change.

You need a good range of skills in terms of this understanding of change management. You need to recognize who in the organization is open to change. How do I build this cascading structure throughout the organization with the right people and the right skills? In every organization there are people who reject change and people who recognize that something can help them.

One approach Celonis has long championed to get the most out of employees and drive change is to establish a Center of Excellence. The vendor has found that establishing an effective Center of Excellence with strong executive support can lead to greater transparency, result in higher impact use cases being prioritized, and result in greater cost savings.

Future ambitions

In addition, Reinkemeyer believes that introducing generative AI into the Celonis Process Intelligence Graph will further drive adoption and change. But the key is recognizing that the Process Intelligence Graph can act as a new level of engagement for the business:

One of our core approaches is the shared user plane, where Celonis acts as a user interface on top of SAP, Oracle, Salesforce, etc. In terms of IT architecture, we take a company like Siemens, which has set up a shared data lake with Snowflake. That’s their only shared data lake where all event logs and process information is stored, regardless of whether an order came in to Oracle, SAP or Salesforce.

Siemens can do end-to-end visualizations through this common platform available in Snowflake. Everyone dreams of AI, but in two or three years, when a regular user asks the Celonis copilot, “Tell me how to make my delivery arrive on time,” the LLM needs to have all the data. That’s why you need a common database where you can link this information to provide a meaningful answer. Here we strongly believe in the Process Intelligence Graph as a single source of data.

However, Reinkemeyer believes that companies that switch to this common data layer will benefit from the use of LLMs within Celonis in the future:

I expect it will be even easier in the next few years with a co-pilot. Having anyone in the organization be able to just type in natural language, “Tell me how my working capital has improved” – that will make it even more attractive and easier.

That’s why we’re so keen to launch this co-pilot – even people who don’t have any special skills can use it. I believe that software should be interactive without having to train people to work with the software.

As for the future development of process intelligence in companies, Reinkemeyer believes that generative AI will enable companies to become more proactive by having a co-pilot predict a user’s needs:

Let’s just imagine there was an intelligent copilot that was actively alerting someone in procurement and saying, “These are your top 10 priorities.” A copilot that could learn which blocks to automatically remove to get cash. A copilot that could understand a user who was interested in inventory and ask, “What can I suggest to this user to repurpose working capital?” I think the direction that things are changing is that we’re going to see these intelligent copilots.

My opinion

What makes Reinkemeyer’s new book so compelling is that it’s based on a dozen case studies from some of the world’s leading companies. While it highlights the successes of these organizations, it doesn’t shy away from providing insights into how to do things better. As companies shift their focus from process mining insights from individual processes to implementing process intelligence across multiple processes, they need to think more broadly about how to motivate their employees to think outside of silos. This culture shift is difficult, but there are many opportunities for those who understand how to truly implement change.