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Why and how to shift your focus to object-centric process mining.

Marshall Peter
Nov 12, 2024

Discover the benefits of this next-generation approach to process mining.

Keeping pace with the rapidly advancing digitalisation of processes can prove to be an enormous task. As the never-ending quest to become more efficient leads many businesses to a more digital and data-driven approach, the sheer volume of data output from various systems brings a string of new challenges along with it. 

Object-centric process mining (OCPM) is the next-generation novel approach to case-centric process mining (CCPM), designed to explore relationships between various organisational functions, such as accounting, payments, and third-party vendor-dependent processes. In comparison to CCPM, it operates by recognising events as being related to multiple objects (e.g., sales orders, production orders etc.) instead of linked to a single case (each process instance), and therefore, overcomes the limitation of process convergence and divergence to deliver a holistic view of end-to-end business processes.

By capturing multiple objects in process analysis, OCPM helps visualise how interdependencies between functions like sales orders, invoices, and payments create bottlenecks or delays. This allows businesses to identify not just isolated inefficiencies but broader systemic issues that span multiple departments.

Building on the CCPM technique of extracting event log data from transactional systems, like Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM), OCPM enables users to better understand the complex overlaps of business operations. Extracting data from different systems allows a company to knit together a digital twin of their processes to identify and visually track process journeys in real-time, all in a single platform.

In process mining, a digital twin is a virtual representation of the company’s processes in real-time, based on event log data from various systems. It allows for tracking and visualising business processes as they occur, which is crucial for identifying inefficiencies.

How do the functions of CCPM and OCPM compare?

How does OCPM work?

To demonstrate the true power of OCPM and its benefits, let’s use a hypothetical scenario within the financial sector.

Suppose a team of senior managers at a large financial institute want to better understand their Order-to-cash process (O2C) and its impact on the overall business. Their back-office consists of typical operations like accounting, legal, payment processing etc., which come under the umbrella of O2C, spanning internal, third-party vendors and client-facing functions. Tracking all the activities encompassing various systems and functions would prove cumbersome using traditional analytical methods.

The team would first utilise the CCPM approach, with the goal of bringing clear visibility to their O2C process by extracting the event data from the systems involved to construct the as-is process. The construction of a digital twin would allow users to discover the disparity between how processes are functioning versus how they perceived those processes to function, as not all activities within processes follow the designated sequences. Process mining platforms extract every sequence that occurs within a process, revealing sequences that occur less frequently and, crucially, those that deviate from the standard process. The visual output is a complex web of conforming and non-conforming processes, highlighting key pain points within the O2C journey. Whilst this approach will highlight the potential opportunities for improvement within O2C, it will fail to capture the complex relationship between functions such as accounting and payment processing, each with its sub-processes attached to other IT systems. For example, payment processing might rely on an external vendor to provide identity verification before the issuance of a product by the company to its customers.

The case-centric process mining would allow the team to realise that their O2C process is being impacted by processes that sit outside the standard O2C process making it inefficient. To help them dive deeper into the problem of inefficient O2C the team would next deploy OCPM. This will enable the senior managers to construct data models that reflect reality, allowing them to view the complex relationship between functions such as invoices and sales orders. In the example above, payment processing is not an isolated function. Instead, it has an intricate relationship with other functions, such as O2C, invoice generation and accounting. Where case-centric process mining answered how the O2C process can be improved, OCPM will provide answers to more complex and impactful questions like ‘What will be the effects of delayed payment processing on the revenue forecast?’

For instance, if the delayed payment process in O2C is tied to external vendor identity verification, OCPM can reveal the broader financial impact, such as how delays in this stage impact days sales outstanding (DSO) and cash flow forecasting. This granular insight helps businesses predict revenue fluctuations more accurately and take corrective actions pre-emptively.

In conclusion…

Case-centric process mining operates as a foundational enabler to identify process-specific improvement opportunities. OCPM on the other hand, represents an opportunity for organisations to magnify the benefits that process mining can bring. It highlights the relationship between different functions instead of isolating processes like O2C to understand an issue intricately linked to other functions. Better understanding of cross-function relationships will help uncover opportunities to drive operational efficiency, increase employee productivity, improve enterprise profit margins, and shift the needle on key performance metrics. Combined with the existing process mining capabilities like conformance checking and predictive analytics, OCPM will transform how users view their operational performance and allow them to capitalise on opportunities previously eclipsed by their traditional analysis.

How can Capgemini help?

Our value-driven holistic approach to process mining is built on our extensive data and analytics expertise, and our deep technology and engineering knowledge, combined with proven strategy and domain acumen. We partner with some of the world’s leading process mining technology vendors to deliver best-in-class tailored solutions for our clients. We provide tool-agnostic process mining services, which include tool comparison and selection to match business objectives. Strategic partners include CelonisMehrwerk, and SAP Signavio. Capgemini is proud to be a Celonis Platinum Partner, strengthening our capability to accelerate outcome-driven transformation at scale across the value chain.

Our work spans a wide range of industries where we have helped clients worldwide leverage the real business potential of advanced process data and modern analytics in the supply chain, shop floor, procurement, engineering, and more. We keep clients engaged and invested throughout, ensuring a journey to efficient operations and tangible business outcomes.

To discover more about our process mining expertise and solution offering, head over to our dedicated solution page which contains further thought leadership articles, blogs, client stories and a snapshot of some use cases. https://www.capgemini.com/solutions/process-performance/

Reach out to our process mining team here to start the conversation today.

Meet our experts

Marshall Peter

Marshall Peter

Data Analytics & AI Consultant
Marshall is an Analytics & AI consultant aligned to the Process Analytics and Automation discipline. He brings 4+ years of experience in working on data projects within the Public and Private sectors. His expertise lies in data modelling, machine learning and building visualisations using tools like R, Tableau and Power Bi to help drive operational optimisation. He is also Prince2 certified and has experience in managing projects using Agile methodologies.

Neil Ferber

Managing Consultant
Neil is an experienced consultant focusing on process insight and transformation, agile product delivery, business modelling, and data analysis and visualisation. He deploys process analysis approaches including process mining to identify improvements, and has strong capabilities in requirements gathering, SME roles, and supporting software design, testing, rollout, and training. Neil is skilled in stream and delivery management, with strong consulting, people, and project management abilities.

Dr. Nick Blackbourn

Head of Process Intelligence, UK
Nick is the Process Intelligence Lead at Capgemini, where he heads a specialist team in delivering high-impact process mining projects that accelerate operational excellence and business transformation. Drawing on extensive implementation experience, Nick has a proven ability to equip clients with actionable insights from their business processes, empowering data-driven decisions and driving sustained improvements. His expertise lies in establishing and scaling strategic process mining functions for complex organisations, making him a valued advisor in the process intelligence field.

Dougie Mackenzie

Director, Analytics & AI
Dougie heads up the Process Analytics and Automation discipline within the Analytics & AI team at Capgemini. Over the years, Dougie has led a number of complex transformation projects using Data and Analytics across a variety of sectors, including utilities, financial services, consumer products & retail and the public sector.