Process Mining is a technology that can be used to analyze and optimize a wide variety of processes. All digitized processes provide data that a process mining software extracts from the IT systems and merges.

With its functions, Process Mining supports the analysis of data and the optimization of processes, because inefficiencies and measures to increase productivity are identified.

However, the extent to which a Process Mining tool provides support and how holistically it analyzes the data depends on its technology. There is a big difference between Object-Centric Process Mining (OCPM) and classic Process Mining.

Classic Process Mining: Limitation to end-to-end processes

An essential requirement for Process Mining is the clear identification and delimitation of processes. To this end, each activity in a process is assigned a unique identifier and a time stamp. The activity is also clearly named. Systematic tables - called event logs - are created on the basis of this information on the individual activities of a process.

Clearly identifying and delimiting processes has the advantage that no incorrect data is collected. This increases the quality of the data analysis and ensures the analytical findings are process-related. However, in classic Process Mining, processes are viewed in isolation, which makes holistic analysis more difficult. In this way, for example, the connections and interfaces between the processes are not taken into account.

Since you are restricted to end-to-end processes, an incomplete or even unrealistic picture of the operational processes is drawn. Process Mining can already be used to achieve considerable optimizations in companies.  Object-Centric Process Mining, however, significantly expands the scope of classic Process Mining and is therefore generally considered to be the better method.

Object-Centric Process Mining (OCPM): No longer process-centric, but object-centric

In classic Process Mining, data on individual events (i.e. actions or activities) is compiled in event logs. The data generated from the company's IT systems  is summarized in several event logs. This results in numerous tables in which the processes are mapped individually.

These are the special features of Object-Centric Process Mining:

  • The event log is not process-centered (e.g. invoicing), but object-centered (e.g. order of product XY including all associated processes).
  • Object-centricity makes it possible to view several processes in the context of one object. For example, the ordering process, shipping and invoicing for a product can be evaluated simultaneously.
  • Some processes are interdependent. This is taken into account in the OCPM, which provides a holistic picture of company processes and enables more comprehensive process optimization.

As a result of the holistic analysis of company processes in OCPM, process-related dependencies can be recognized more easily. The extraction and storage of data is more complete thanks to object-centricity. This means that more detailed analyses can be carried out and improvements to business processes can be better implemented.

In-depth overview of the differences between OCPM and classic Process Mining

So now the main differences between OCPM and classic Process Mining technologies should be clear. The differences are explained in more detail below. If you were to summarize all the advantages of OCPM in one sentence, you could say that Object-Centric Process Mining forms a digital twin of the entire company in all its interrelated complexity.

Object-Centric Process Mining reflects reality on a large scale

Good Process Mining software should be able to view objects or activities in the company independently of the data source. This is exactly the case with Object-Centric Process Mining. This is because data is obtained from a wide variety of programs and linked to the object to be analyzed. All business processes that are related to the object and, where applicable, other objects can be viewed in their entirety. This includes the following aspects:

  • Recognizing dependencies between different objects, processes and departments
  • Analyzing interfaces between the individual business processes and departments
  • Combining data from several sources in one place (i.e. in the Process Mining software) and viewing it in a coherent manner

The properties of OCPM are also referred to as three-dimensional process modeling. In contrast to classic Process Mining, the software no longer only maps not only the isolated business processes end-to-end, but also the complex network of processes with all the associated influences.

If you were to visualize the processes, which is what you do in Process Mapping, for example, you could say that classic Process Mining is a timeline, while Object-Centric Process Mining is a three-dimensional mesh. This visual image makes the biggest difference between the two Process Mining methods clear.

Easier configuration of data as a further advantage of the object-centric approach

As a digital twin of the company and all business processes, Object-Centric Process Mining contributes to the analysis and optimization of business processes to a much greater extent. It also offers further advantages. One very important advantage is that data configurations only need to be carried out once.

With classic Process Mining, there is the far-reaching problem that users receive various tables with a large amount of data due to the event-based approach. The crux of the matter is that the data is isolated in relation to individual processes. If you now want to look at a specific process from a different perspective, you have to re-sort and prepare the event data once again. This involves considerable effort.

The situation is different in the OCPM, where all objects and process flows that you want to view are selected. After the one-off data configuration, all relevant information can be viewed in various ways and with all correlations. It is not necessary to repeatedly carry out new data configurations for different analytical questions or perspectives.

Example of the added value of OCPM

In an interview with BigData-Insider, Wil van der Aalst, godfather of Process Mining, describes the added value of process mining tools with an object-centered approach. As an example, van der Aalst cites the following order process:

  1. A customer orders four gifts. One of them is in stock, the other three still have to be produced.
  2. The gift that is ready for dispatch is sent to the customer immediately.
  3. An order is also created for the production of the missing three gifts.
  4. The ordering process involves several process steps and objects. These include the sales order, the sales order items, the production orders, the dispatch of a gift in stock and, after production, the three additional gifts and finally invoicing.
  5. In addition, several departments of the company are involved in the entire process flow.

Now van der Aalst identifies the problem that a classic Process Mining tool cannot capture all objects and processes and their interrelationships without the object-centered approach. Instead, classic process mining technology requires each process and each object to be captured separately. Van der Aalst cites Object-Centric Process Mining as a solution to this problem.

In object-centric Process Mining software, all processes and objects related to the order would be recognized. This enables holistic process analysis and process optimization. Those responsible in the company would not wonder why there was a delay in invoicing or shipping products to the customer, but would know that this was because three of the four gifts had not yet been produced.

FAQ: Questions and Answers about the difference between OCPM and classic Process Mining

What is the difference between OCPM and classic Process Mining?

OCPM enables the cross-process modeling of business processes. For example, the potential for optimization at the interfaces of several processes is also uncovered. Classic Process Mining, on the other hand, is only used to analyze and optimize individual processes with a clearly defined beginning and end.

Can I use OCPM if I am already using Process Mining?

Yes, we are happy to support you in upgrading from conventional Process Mining to a system with OCPM. By using a suitable tool, it is possible to switch from conventional Process Mining to the more advanced and comprehensive OCPM.

What is the difference between Data Mining and Process Mining?

Data mining is used to analyze large amounts of data. This is also the case with Process Mining, but it is dynamic. In Process Mining, data is not only analyzed statically. It also examines how this data came about. While data mining only evaluates the data that is currently available, process mining is dedicated to analyzing processes.

What are Process Mining and Task Mining?

Task mining is used to evaluate data and analyze individual interactions within processes. This is where the “task” comes from in the name. Process Mining looks at and analyzes processes that consist of several steps or tasks.

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In our Focus webinar, our experts will discuss the unique benefits and opportunities arising from Object-Centric Process Mining.