How can a digital twin of a business process help me?

Introduction

In a previous post we have introduced the main concepts of a digital twin, and one of the ones that appeared was that of being linked to a real physical object. Therefore, the first question that arises is, can the concept of digital twin be applied to an ethereal or conceptual element? We have already seen in that post that the limits in the definition of the digital twin are very wide, and that the concept can be applied to objects that do not yet exist (for example, in the design phase of a real product), or that are conceptual, as is the case here. The business process that we may be interested in linking to a digital twin can also be completely conceptual, as in the case of a computerized document management system, or it can maintain links with the real world, as in the case of the last-mile delivery process of a logistics company, where the process as such is conceptual, but is embodied in a fleet of vehicles. In this second case, the ‘real’ part supports the process, but in this article we focus on the process itself, not on modeling or knowing the physical objects involved.

The path

Generally, for the improvement of a business process we will need to go through a three-step path, which will be increasingly complex to achieve, but each step with a greater impact on the final result. The first step is always to know the state of the process. Although it may seem unbelievable, it is incredible how many companies have not even taken this step, operating blindly or reactively. A good alternative is to know when state changes occur. In fact, there is a lot of literature on this subject and many of the major data processing systems are based on this paradigm. If the process is part of a computer application, it will be necessary to collect the logs that it generates, and if the state changes are not registered, modify or extend it so that they are. If, on the other hand, the business process is based on real physical elements, it will be necessary to consider the telematic recording of these changes. Continuing with the example of logistics, it can be clearly seen how modern applications keep an exhaustive record of when the package goes through each stage of the process, mixing smart camera readings, GPS signal and mobile signature applications. In the end, it is imperative to know what and when it is happening, and on this, move on to the second step, detecting deviations. Either because the digital twin is modeled with a set of rules that the process should follow, or because it, applying Artificial Intelligence techniques, is able to discover them by itself, the digital twin can alert us when something that is happening (or in the most advanced systems about to happen) deviates from what is expected. Documents that get stuck in a signature process, vehicles that do not follow the expected route, processes that repeat themselves repeatedly and inefficiently are some examples of this type. Detecting this type of situations can help the company to improve its business processes without even taking the last step, that of using the digital twin as a direct mechanism to change the process itself, either because it incorporates tools that suggest improvement alternatives, or because it allows us to simulate those that we think can improve it.

The result

At the end of the road, by using a digital twin, the company can improve the business process:
  • Detecting anomalous situations.
  • Detecting the least efficient points of the process in order to focus improvement efforts on them.
  • By detecting ‘parallel’ procedures that do not comply with safety or traceability standards.
  • Suggesting improvements automatically, applying predictive techniques
  • Simulating improvements manually, helping managers to anticipate the scope and impact of their decisions.
 

At oga we have experience in the development of digital twins in fields as diverse as health, logistics or the chemical industry. If you want us to help you in your improvement process, contact us.

Acerca del autor

Autor
Jaime Nebrera oga
Jaime Nebrera
Big Data Consultant / Project Manager en oga

Consultant specialized in new technologies and Big Data.

Pioneer in Spain in the use of cutting-edge technologies such as Apache Kafka and Druid, he has extensive experience in the design of innovative technological products.