Data Processing vs. Process Management?


In today’s data-driven business landscape, managing data effectively is crucial for achieving organizational goals. While data processing systems play a vital role in collecting and organizing data, it is often overlooked that data should not be managed solely for its own sake. True value lies in understanding how data can be leveraged to achieve business objectives, which is where the concept of process management comes into play.

Today we live in a world where data is everywhere and every enterprise knows about the value of data. But how do we handle data? How do we create, collect analyze it? This is the area of data processing software. And we all use databases, spread sheets and data management systems to manage all kind of data. Many software systems are build around specific data domains and we use this software to create and maintain the data.

But in this context, however, it is often overlooked that data should not be managed for its own sake. The reason why we need data in companies is that we want to achieve certain business goals. And in this context, we come to the question of how corporate goals can be achieved at all? This is the area of process management.

So what’s the difference between data processing and processes management?

The Problem of Data Processing

In data processing, we collect data according to a predetermined schema. This can be a database table, a spread sheet or a complex data structure. It is usually disadvantageous to change the data schema in such software systems afterwards. As a result data processing systems often increase in complexity over time as more and more disparate data has to fit into a general schema. This can lead to software systems becoming unmanageable or development costs rising to astronomical heights over time. Microservice architecture is a common approach to stop this development and consistently create independent smaller data silos from the start.

The Idea of Process Management

On the other hand we have the concept of process management. In this area we are focusing on the question how to process data and not how to put data in a rigid schema. The idea of process management software is to process data in a highly flexible way. The main question is: who needs what kind of information in a business process? And these processes are highly versatile because our business requirements are changing much faster in our today’s rapidly evolving business landscape. Thus, process management focuses on the question of how data can be processed quickly and flexibly.

BPMN 2.0

The business process management notation (BPMN) is the industry standard to describe and execute business processes. It enables enterprises to describe how data should be processed, who is responsible and how certain situations should be handled.

BPMN 2.0 example diagram

One advantage of BPMN 2.0 is that those process models can be executed by software systems automatically. Process Management Suites like Imixs-Office-Workflow can handle this kind of workflow models. A change in the process flow can be modeled with tools like Open-BPMN easily within minutes and this gives an enterprise the flexibility to manged their own processes.

Process Management and AI

In general Process Management solutions handle data in a more flexible document-centric way. This simplifies the data management on a higher level. Typically, you don’t ask what kind of data was processed, but look for answers to questions like:

  • Why did we need to process this kind of data?
  • Who knows about specify data in our company?
  • When did certain data events occur?

Artificial intelligence (AI) plays an increasingly important role here. Large language models (LLMs) are optimized to handle this type of unstructured data and can quickly find answers to these types of questions. Imixs-Business-AI is one approach to combine the flexibility of BPMN with the power of AI. It allows a process-modeller to create prompts in the context of a specific business process. This empowers companies to combine new questions with the processing of their data.

Conclusion

Process management offers a flexible and adaptable approach to data handling, focusing on how data can be processed to support evolving business requirements. By combining the industry-standard BPMN 2.0 with the power of artificial intelligence (AI), enterprises can gain a deeper understanding of their data and make informed decisions that drive business success. Solutions like Imixs-Business-AI exemplify this integration, empowering organizations to create prompts within specific business processes and leverage AI capabilities to uncover valuable insights from unstructured data. As the business landscape continues to evolve rapidly, process management’s ability to adapt and harness the potential of AI will be instrumental in maintaining a competitive edge.

As an open source company, we at Imixs believe that process management is the new way to process data. We are therefore focusing on the further development of these combination of technologies.