Shifting From Liner Flows to Networked Business Processes with OCPM

How Object Centric Process Mining adds a much-needed edge to process mining for businesses that resolves to grow amidst complexities

Process mining has earned its place as one of the most consequential analytical disciplines of the past two decades. The powerful ability to reconstruct how business processes actually execute, drawn directly from the event logs of operational systems and not assumptions, has given organisations a quality of self-knowledge that was not available before—

Bottlenecks that had been managed by intuition became quantifiable. Compliance gaps discovered in audits became visible in real time. The gap between how a process was designed and how it actually ran closed in ways manual analysis never could.

Yet at times we encounter scenarios in which the dashboards are green, the KPIs are within range, and the audit reports confirm that the process is performing as designed. And yet, delays persist, exceptions keep surfacing, and inefficiencies that no single metric can capture continue to undercut business profitability. The problem is rarely in the measured process and mostly in the intersection of the processes.

 It is where Object-Centric Process Mining (OCPM) adds to the capabilities of process mining, enabling businesses to analyse the interactions between processes with greater clarity than ever before!

A Shining Heritage

Traditional process mining has built its track record on a precise and productive abstraction: the case notion. By anchoring each event in an event log to a single object like a purchase order, an insurance claim, or a patient record. It created the structured foundation on which dozens of discoveries, conformance, and performance analysis techniques were developed and refined. As a discipline, it delivered measurable value across industries and geographies, and it continues to do so.

However, the question the discipline now faces is not whether that foundation was sufficient for what it was designed to do, but rather what becomes possible when we extend it. The answer is Object-Centric Process Mining, which extends the scope of conventional process mining to capture the full complexity of how growing enterprise processes operate in an uncertain world!

What Conventional Process Mining Made Possible

To understand where OCPM takes us from here, it helps to appreciate the world that traditional process mining opened for businesses.

Changing How Businesses Understood Their Processes

What conventional process mining made possible was straightforward in principle and profound in practice: Business systems like ERP record transactions, approvals, and status changes that leave a digital trace. It formalised the methods for reading those traces as a coherent picture of actual process behaviour.

It is not a picture drawn by consultants or described by employees, but one derived directly from operational reality. The Process Mining Manifesto, published by the IEEE Task Force, codified this as a discipline in the opening of the last decade, and the growth that followed was incredible— more than three dozen commercial products, including mid-market focused platforms like FUTUROOT with applications in healthcare, finance, manufacturing, logistics, and the public sector.

A Track Record Built on Rigorous Methodologies

For any process that can be meaningfully represented throughout the lifecycle of a single object type, conventional or case-centric process mining delivers discovery, conformance checking, and performance analysis in real time. For instance, a company auditing its accounts payable process through the lens of individual invoices gets reliable answers about cycle times, exception rates, and compliance with approval hierarchies. A logistics operator examining shipment-level data understands delivery performance with a clarity unavailable from any other method. Over the years, these capabilities have driven measurable operational improvement at scale.

The discipline’s methodological maturity is equally significant. Led primarily by Wil van der Aalst at RWTH Aachen, it gave rise to techniques such as alpha algorithms, inductive miners, and conformance-checking frameworks — all theoretically grounded, practically tested, and now embedded in commercial platforms used by thousands of organisations worldwide. This infrastructure is the inheritance that OCPM builds upon, not something it sets aside.

Where Process Mining Needs to Move Further

Real enterprise processes, when examined carefully, do not flow linearly through the lifecycle of a single object. Instead, they involve multiple object types, such as orders, items, shipments, invoices, and payments. Each of them, as it progresses through its own lifecycle, is also connected to the others through evolving relationships. It is what Van der Aalst describes as the Rainbow Spaghetti, wherein each strand represents the lifecycle of a different object, all intertwined and shaping outcomes together.

When traditional process mining is applied to these multi-object scenarios using a single-case notion, it forces relational data into a flat, sequential log. It simplifies the relationships it is trying to describe, raising real challenges, and becomes more pronounced as the processes under analysis become more interconnected.

Understandably, to resolve such complexities, businesses need an analytical lens that, when turned on a multi-object process, does not flatten what it sees. Instead, it separates it into its constituent colours, adding clear visibility to each object’s lifecycle and interactions.

It inspired us to name FUTUROOT’s OCPM capability as FR Prism. While the conventional view collapses process complexities into a single view, FR Prims reveals the full spectrum within it.

Real Life Example: The OTIF Problem

The On-Time-In-Full (OTIF) failure in supply chain management is a typical multi-object event. It involves interactions among orders, items, warehouse picks, delivery packages, and dispatch schedules. Each object progresses on its own timeline and potentially contributes to the failure.

Understanding it fully means understanding those interactions in their entirety, not just studying the behaviour of a single object in isolation. At the Process Excellence Network’s 2025 event, Wil van der Aalst used this scenario to demonstrate how OCPM unifies orders, items, and packages into a single analytical model that can compute OTIF scores and locate the precise interaction points where failures originate.

The practical scope of OCPM is wider than OTIF alone. Object-centric analysis adds value at places where the problem statement spans object boundaries. It includes scenarios such as a bottleneck at the handoff between procurement and finance, compliance risk arising from the interaction between workflow approvals and inventory events, managing customer experience at the intersection of the timing of order, item, and logistics lifecycles, and much more!

The Three Promises of OCPM

The OCEL standard provides the technical foundation for OCPM. It defines Object-Centric Event Logs, in which each event can reference any number of objects of any number of types, and supports their exchange in SQLite, XML, and JSON formats. OCEL 2.0 added Object-to-Object (O2O) relations alongside Event-to-Object (E2O) relations, capturing not just which events involve which objects but how objects relate to and influence each other across a process. The analytical leap this enables is promising in the following ways:

• Extract Once, Analyse from Any Angle

The first promise concerns the analytical completeness of interconnected processes. Traditional process mining produces one model per case notion, requiring repeated extraction and reanalysis as questions evolve. However, OCPM extracts once and supports analysis from any angle on a single, unchanging data source. It means a genuine shift in the economics of process intelligence work for analytical teams in organisations with complex, multi-object processes, eliminating the need to repeat extraction even when the viewpoint changes.

• Seeing Across Object Boundaries

The second promise is about clear visibility into inter-object interactions — the connections between process lifecycles that traditional analysis treats separately. When a goods receipt and a purchase order are analysed together as interacting objects rather than as independent cases, patterns that were previously invisible become analytically accessible. It covers the sequences of cross-object events that consistently precede exceptions, the object-type combinations whose interaction timing predicts compliance risk, and the structural relationships between order complexity and delivery performance. These are the interactions where inefficiencies, compliance problems, and bottlenecks most commonly reside.

• The Data Foundation for Enterprise AI

The third promise of OCPM is to build a strong foundation for enterprise AI. This paper argues that OCPM provides the structured ‘process lenses’ through which machine learning models can be trained on data that faithfully represents the causal structure of business processes.  Intelligent capabilities such as predictive process monitoring, next-activity prediction, and anomaly detection achieve higher accuracy when trained on object-centric event data rather than flattened single-case logs. It is because the training data more accurately reflects the relational reality that drives outcomes. For organisations serious about enterprise AI, OCPM is not a separate track; it is pivotal to the reliable operation of AI.

Where OCPM is Heading

Solid Foundations, Active Frontiers

OCPM currently stands on robust foundations. Multiple software libraries and datasets currently support the OCEL 2.0 standard. OCPM techniques for process discovery, conformance checking, and performance analysis have been demonstrated to be applicable across industries such as healthcare, logistics, manufacturing, and financial services. To facilitate further adoption and ensure that tools are built on shared, reliable foundations, the OCED Working Group, a collaboration spanning TU Eindhoven, RWTH Aachen, and multiple industry partners, published its standardisation framework in 2024.

What This Means for Technology Roadmaps

At FUTUROOT, our own roadmap reflects this trajectory. Our FR Prism capability is being extended with full OCEL 2.0-native extraction and analysis. It will enable our customers to examine multi-object process interactions directly, without forcing a case notion choice on every question, and without re-extracting data every time the analytical angle changes.

However, this is not a departure from the process mining on which we have built our platform, but the natural next capability that the complexity of real enterprise operations has always been asking for.

The Discussion Worth Having

The shift from linear flows to networked processes powered by OCPM represents something more measured and durable than yet another hype. It indicates the continued evolution of process intelligence, grounded in the same commitment to evidence-based process understanding that has driven the discipline since its earliest days.

For CXOs reading this, it is time to introspect:

Where are the processes in your organisation where the challenges live at the intersection of object types rather than within any single one? How does it affect your analytics strategy when extraction can be done once and supports any viewpoint? How does the availability of reliable multi-object process data change your approach to enterprise AI?

For business leaders and decision-makers, these questions dwell at the productive edge of a discipline in healthy motion—unlocking new opportunities. How they embrace it will determine whether organisations lead or merely follow.

As a growth-minded leader, the former is the group you envisage your organisation belonging to in the coming days. You can start by identifying the multi-object processes in your organisation today. How their interactions impact your business outcomes—that is where the next layer of operational clarity lies.