How can the public sector free up resources while continuing to fulfil its missions? By enabling certain time-consuming and repetitive tasks to be automated, the digital assistants or RPA (Robotic Process Automation) are one possible solution. They enable public servants to spend more of their time on tasks with greater added value. Internationally many public sector organisations have launched projects with the RPA technology, including the French tax administration or “DGFiP”.
An RPA success story at the French tax administration DGFiP...
In 2018, the DGFiP decided to partner up with BearingPoint to launch a study on the use of digital assistants or RPA. Given the use of this technology was not widespread within the French public sector at the time, the goal was first to assess the feasibility of integrating an RPA solution within the DGFiP IT ecosystem and test it on certain simple business processes. The Proof of concept (PoC) proved successful, which led the DGFiP to launch a project with the goal of automating several business processes and to reflect on a future scaling up of the solution: how can we identify and characterize processes with high potential for automation? What is the right long-term governance for the RPA project? What IT architecture is most appropriate? etc.
Having automated several processes, the DGFiP is now developing a long-term RPA framework with the introduction of an RPA center of excellence in September 2020 and of a new technical platform in March 2021. Analysis of other business processes is underway to integrate into this this approach.
With the experience as co-leads for the RPA project, Karen Plissionnier – deputy head of the user experience team within the digital transformation service at DGFiP – and Véronique Jung – IT project manager at DGFiP – have answered our questions and share below some precious feedback for any public actor interested in starting a similar approach.
The DGFiP identified the potential for gains enabled by RPA automation, in terms of performance and public servant experience (accelerating processes, reducing the workload associated with of repetitive tasks, improving security and traceability, etc.). By 2018, the DGFIP was interested in experimenting with the technology. At the time, we wondered if it could fit within the DGFiP IT landscape – which is broad and diverse – and if it could offer significant added value to our business activities.
We quickly identified certain constraints:
Before going any further, we decided to launch a first experimentation in 2018 with a PoC on four business processes.
We chose several processes to cover a large spectrum of business domains and types of operations. The four prioritized processes therefore touch on tax collection, Human Resources, management of relationships with suppliers and on different types of operations (matching information between internal and external sources, consolidating information asynchronously, optical character recognition (OCR), etc.).
The PoC quickly demonstrated the technical feasibility of automating of all the processes in the experimentation, from the least complex to the most through RPA. Beyond proving feasibility, it also showed quantitative and qualitative gains:
These results drove us to start a first live deployment on two pilot processes as part of a wider experimentation.
For the first live deployment, we wanted to move forward fast. Therefore, we put to one side the most complex processes and prioritized those less intrusive for the DGFiP (no inputs to critical DGFiP apps). Analysis of the benefits from the PoC also allowed us to favor processes with the highest return on investment.
Given the very positive results of the live deployment of the two pilot processes in late 2018, a mapping of automation needs within local offices and central teams was undertaken at the beginning of 2019. We analyzed every one of the 130 business requests to assess the adequacy of RPA automation according to different criteria (task repetitiveness, process standardization and documentation, number of systems involved, etc.). RPA automation seemed particularly well suited to four processes that were selected for the new deployment. This first mapping campaign, largely experimental, showed the importance of helping functional areas within the organisation expressing needs to better adapt their proposals to the analysis criteria and potential return on investment. Due to the volume of needs that were identified, a a more structured methodological framework based on a standardized eligibility grid was developed in the summer of 2020 to help scale up and “industralise” the approach.
|Type of automated process|
Role of the RPA robot
|Tax recovery / control||Collecting different data within IT systems and publishing a consolidated result.|
Downloading documents and publishing a consolidated result.Downloading documents and sending them to the user.
|Accounting and recovery||Downloading a bank statement, identifying a list of operations to be treated and then enter corresponding inputs in the adequate IT systems.|
Two major subprojects were central to the scaling up of the RPA solution at DGFiP:
Progressing the technical architecture of the platform: an analysis on the scale and sizing of the infrastructure was undertaken based on the future ambitions for process deployment. We then implemented a highly-scalable technical platform in line with this ambition.
Switching RPA solution editors: the state of our project allowed us to change editor without risk or major business impact.
These subprojects enabled us to have:
During the deployments, we encountered difficulties with the initial RPA technical solution, which was chosen at the PoC phase. With hindsight and in looking to scale up this technology, another solution seemed better suited to our needs and requirements, in particular from a technical and support perspective.
The decision to switch editor also raises the question of the choice of solution: even if an adjustment is still possible down the line, it is preferable to compare the different available solutions and to select the one which seems most adapted to the context from the very start.
This change of trajectory was possible because we were at a turning point in the project cycle. The relatively limited number of RPA robots deployed allowed us to change solution without a major impact on existing processes. This decision was also taken to meet the ambitious objective of deploying RPA robots on a major process involving numerous special cases and impacting a large population.
The switching of solution was key in the scaling up of processes at DGFiP. The implementation of a new technical platform supported this scaling up and the center of excellence, which needed to be reinforced and to develop skills on a new technology.
During the scaling-up phase, it’s necessary to anticipate and write down all the potential blockers that can be encountered.
During the scoping of needs and requirements, we realized it was important to have the following elements in mind:
During development, three main items appeared critical to us to ensure project success:
Several key challenges were also overcome, and must not, be forgotten:
With the success of our RPA approach and the benefits we measured, and the business actors have recognized, we are moving forward with further robot deployment: