RPA and artificial intelligence, or process performance management

May 14 BSSI

RPA has quickly become the fashionable tool for optimizing organizational processes, but there is no miracle tool (yet!), And process management is a broad theme that brings together several technologies from some not very heterogeneous.

When we talk about process, the first word that comes to mind of Business Departments or CIOs is very often 'modeling'. Here we enter the world of BPM (Business Process Management), which appeared in the last century with its historic tools, its international standard born of several years of reflection, BPMN (Business Process Model & Notation), and its recent developments. -cents. The arrival in force of the RPA should not make us forget that the BPM is still relevant. Process automation in no way prevents the modeling effort. Recent BPM tools also bring collaborative functionality, 'real-time' process monitoring, management of alerts, documentation, profiles or resources concerned, and even optimization solutions.

Then there is only one step to take to enter the world of BPA (Business Process Automation). As the name suggests, the processes are automated here. However, at this stage, the tool will allow you to launch predefined jobs (or scheduled for the needs of the cause) without being able to easily take care of all the actions present in a complex process, or integrate a user interface able to model actions charged to employees; which will justify the introduction of the RPA. However, we are integrating with this major evolution, a fundamental architecture concept, which allows BPA to integrate into the IS and to connect, through the APIs (application interfaces) necessary, with any other solution of the system. We will of course find this aspect in RPA solutions.

We are finally at the heart of the subject: What does the RPA bring? Robotization reproduces the tasks of the process as they are daily implemented by an employee. Obviously, the BPA can do this too, but it is necessary to program the associated job. The RPA presents an interface which makes it possible to do it much more simply, either by capturing the user gesture, or by chaining preprogrammed 'robots' supplied in a library of the solution. These two technologies have their advantages and disadvantages, but both provide the possibility of robotizing any process. It is in this user interface that the originality and added value of RPA are. It allows a relatively quick handling and remains accessible to less technical profiles (with a certain rigor in the reproduction of processes, and a limited complexity of the rules of chaining of tasks). Here we come to the point where human actions are potentially replaced by RPA. But who says human replacement says 'Artificial Intelligence' (AI). Above all, it should be specified that all human actions will not be replaced.

The interpretation of data in a complex context, the transformation of a process caused by an external event, the decision-making related to the commitments and responsibilities of a manager ... are all examples that are a matter of human reflection , and which will not be replaced in the short term by the robot. However, advances in AI today allow for a number of advances, ranging from simple text recognition (OCR) to Deep Learning. The purpose here is not to define the terms and scope of AI, but to understand its value, in the context of process performance management, and in association with RPA. OCR or NLP (Natural Language Processing) are analysis tools that allow performance improvement. Chatbots bring a first 'intelligent' response because they can communicate with humans. But it is in Machine Learning (ML) and in Deep Learning (DL) - which are also also associated today with recent Chatbots - that AI brings to process management all its power: help with the decision. It is not a question here of replacing the human, but of advising him a behavior vis-à-vis a situation for which he has a decision to make. These latter solutions are based on Machine Learning to improve over time and on Deep Learning to understand situations by correlating information that they already master. We then reach the final stage of the performance of the organization's processes, in any case as long as we have decided that human beings always have a role to play in the functioning of our society! How do you get started with optimized process management? The multiple tasks of a company are more or less well treated, depending on the maturity of the organizations The objective is not to multiply the tools, on the contrary, but to equip itself with the solution appropriate to its immediate need, and to its evolution over two to five years. We must take into account the impacts on the organization of the company, but also the ability of systems to provide the right information at the right time. Here we tackle the no less important subject of data governance, intimately linked to the governance of processes, and to the monitoring of Quality. We are therefore implementing good practices and governance that does not mean starting from scratch the entire Quality approach. The implementation of the RPA is very often an opportunity to optimize the internal functioning, little by little, process by process.

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