One of the major challenges for organizations, particularly in sectors such as insurance, telecommunications or energy, is to focus on high value-added missions. This is one of the reasons why they rely on automation, mainly through the implementation of robots, as it allows them to save time and reduce the risk of human error. Just like our customer who decided to increase his performance by reducing his operational cost through the combined implementation of RPA (Robotic Process Automation) and BPM (Business Process Management). 

Our project was a huge success and brought huge benefits for our customer: 

He saved time: The files, for which our customer had legal constraints of 9 days processing time, are now processed within about 1 hour. 

He gained money: The ROI was achieved in less than 18 months, even before the project was completed. The project was self-financed: the costs incurred were lower than the gains made. 

He created value: The value created by the implementation of automation was measured by satisfaction surveys carried out with all stakeholders. Satisfaction rate was around 85%! 

The strong involvement of the management team in this project has helped to gain the trust of employees and facilitate their involvement.  

So how did it work? 

The first goal was to obtain gains in productivity and reduce operational risk! 

Dematerialization and automation are the main vectors of digitalization. After implementing dematerialization, our client turned to the automation of processes and repetitive tasks. Employees spent a lot of time navigating from one application to another, copying and pasting to manage the follow-up of files and to completing information present in various applications. 

The stakes were therefore high and multiple: 

• to focus on high value-added missions (outgoing calls that could not be carried out by the automaton, files with high industrial risk, those for which regulatory constraints apply…) to gain in productivity and reduce costs. After feasibility studies, it emerged that about 80% of the tasks could be totally or partially automated knowing that the data used were similar from one application to another (such as file numbers, recurring CERFA document numbers, addresses, phone numbers, …), 
• to automate processes with the awareness that some of them can lead to an industrial risk in case of wrong analysis. It was therefore necessary to identify the levels of risk associated with the processes in order to implement a disengagement system that allows human intervention when necessary, 
• to support the GPEC (forward-looking employment and skills management) in the development of team skills and change management, 
• to ensure business expertise and quality deliverables. 

Why would you combine RPA and Business Process Management (BPM)? 

RPA alone is not sufficient to carry out this type of project. This is why we have combined it with BPM (Business Process Management), which allows us to optimize and streamline processes. Indeed, some tasks were purely and simply automation. Others required the integration of strategic thinking (comparisons, calculations, analysis of key words…) and business knowledge through management rules. The latter allowed to ensure both the desired gain in productivity and also the fine business analysis necessary to guarantee industrial security. 

The project was divided into four interlinked steps: 

• The implementation of rules linked to business processes enabling the automatic system to be disengaged in the event of an identified operational risk. 

• The provisioning of the interfaced tool to control the automation process 
• The automated production of deliverables. 
• The increase in team skills and change management. 

What will be the next steps? 

Other topics have been identified to go further, such as intelligent automation. 

To do this, it is planned that in the coming months, the customer will add technical business intelligence bricks to his information system to analyze the data transmitted by the robot and other applications. This data, calculated using the cross-references of the Information system or automatically deduced according to the values present in the databases supplied by the users, will eventually and proactively influence the robot’s processing and operational expectations. 

Based on learning technologies, these evolutions will enable different information systems to communicate with each other in order to automate more complex processes or to improve existing processes automatically. The more information the tool will have at its disposal, the more relevant it will be in its processing. 

The foundations of artificial intelligence have been laid. This will enable the use of cross-data from a set of applications to make predictions in deliverables for employees and the company.  

Writer: Benjamin BLARD
ATLANSE Rhône-Alpes