Trying to predict what will happen in a coming year is never easy, especially given the, ahem, chaotic nature of recent history.
But at Celonis, we challenge ourselves to constantly consider where organizations are headed, what they’ll need to get there, and how we can improve our process tools to better serve them (and the world).
So, with this in mind: what’s next for process intelligence?
We tapped three of our most future-focused experts at Celonis to help prepare you for how process mining (and, more broadly, process intelligence) will evolve in 2024 (and beyond).
Van der Aalstpredicts that hybrid intelligence — process intelligence work that’s shared between humans and computers — will continue to change as capabilities evolve. “There will be a gradual shift between what algorithms do and what people do … a continuous redistribution of tasks between humans and computers,” he says.
However, he stressed one very human advantage: our ability to respond contextually to new circumstances, which most automations or artificial intelligence with. “W here people add value is where you’re out of the normal specs,” he says. “It will still remain important to understand core process mining principles for situations in which a human needs to take control.”
Van der Aalst maintained that OCPM — which Celonis debuted in 2022— will “continue to keep us busy … we’re still sorting through how it’s impacting process mining.” OCPM — a new type of process mining that captures interactions between systems and between objects, so processes can be followed more holistically across different software, departments, functions, and entire businesses — is a massive change that’s led to new process intelligence capabilities, as well as to reinventions of existing capabilities within a now-more-complex setting.
Shoar agreed, calling OCPM a “sea change.” The coming year, he says, is when OCPM adoption will become even more widespread, in part because “...we’re making it more useful. Within our core fields, we’re unlocking use cases we’ve never seen before.”
Shoar predicts that OCPM will help process intelligence grow in fields where we’ve rarely seen it previously. Beyond typical use cases like finance or supply chain management, we can now “...deploy process mining in more complex, customer-centric situations,” he says, citing healthcare and telecommunications as prime candidates for process optimization.
In healthcare, Shoar says, OCPM could unify patient journeys across facilities and systems, improving patient experience and giving caregivers a more complete view of health history and current conditions. For example, by operating across different electronic health record (EHR) systems, OCPM could make it easier to order, connect, and interpret many lab tests for a single patient, leading to better diagnostic capabilities.
In telecom, OCPM’s “end-to-end, multi-object abilities” could drive collaboration across wildly different departments, systems, and locations, per Shoar; for example, it could give Customer Service teams better insight into how internet equipment moves through logistics processes towards the customer, or better insight into what’s causing outages (and how service could be restored faster).
Van der Aalst predicts an uptick in two more specialized forms of process mining: federated and knowledge-driven process mining. Federated process mining could bring process intelligence to businesses with many organizational units (like banks or car rental companies with multiple branches), developing richer process intelligence through data from all sources, rather than just from one. Knowledge-driven process mining combines process mining and process modeling, using existing process data to let users model new processes while getting real-time feedback on their work.
All three of our experts agreed: IT departments are going to be increasingly involved in process intelligence. “Process intelligence is going to be considered a horizontal capability within IT,” says Attias, citing the increasing necessity for process observability within organizations. He and Shoar both see process mining becoming a standard part of an org’s tech stack. “As a platform that interacts with other layers of the stack, we’ll be able to drive process mining insights more effectively than before,” says Shoar.
Van der Aalst believes IT departments are a natural fit for process mining because “Process mining has this wonderful capability to connect the abstraction that’s part of many IT skills … it connects people who wouldn’t necessarily work together in the business, and IT makes sense as a place for process mining to land because IT is a shared, common business capability.”
Attias sees major potential for process intelligence to make working with systems of record easier. Many organizations use older, often-unwieldy systems of record that are time-consuming or not intuitive to actually work within, but are “too ingrained to rip and replace,” he says. By using Celonis as a platform for overall process intelligence, organizations will be able to “keep their legacy systems going, run Celonis on top, and then transform on top of Celonis — all without touching their legacy systems at all.” Other new applications can plug into Celonis, rather than into the legacy system, opening up a whole new world of capabilities and faster digital transformation.
Many organizations are wary of sharing their data — but as process mining becomes more widespread, “...multiple parties would find value in sharing some information,” says van der Aalst. For example, manufacturers and suppliers who share some data might be able to sharpen processes and gain a market advantage. Van der Aalst thinks resistance to data sharing may be outdated, as organizations are now able to do so while maintaining strict source confidentiality.
Attias also recognizes the potential of a data marketplace for process benchmarking and decision-making. Anonymized, high-quality, and broadly-applicable data could be shared and even offered as a product for reference or comparison purposes. More robust data would help organizations know how their processes are faring and where opportunities may be. “This approach empowers organizations to make more informed decisions, transcending the data boundaries of their own enterprise,” Attias says.
Sustainability is one of Celonis’ core values, and the Celonauts interviewed for this piece agreed that process intelligence will keep supporting business’s efforts to go green.
“Process mining is creating easy fixes that can be added to how you do business,” says van der Aalst. “Efficiency in terms of time and money aligns very well with efficiency in environmental impact. There are many situations where sustainability automatically begins to happen.” As process mining becomes more effective and drives efficiency, the barrier to entry for sustainability in business naturally will become lower, he says, and “...companies just need to be willing to make the initial investment.”
Beyond creating sustainability in business processes, van der Aalst also sees process mining becoming more efficient as a practice. A new development called “approximative process mining” would let users choose the level of specificity needed for certain tasks or queries, potentially saving computing power by purposefully opting for less-specific outputs. “With questions, you need to wonder whether they should be asked. If you think about what it would cost each time, is it worth asking the question? Process mining researchers hope you can decide the level of precision you need for your answers,” van der Aalst says.
