A common mistake is to launch an RPA project by selecting a tool without having clarified the objectives. Before looking at the technology, you need to answer the following questions: What are the strategic objectives?<\/strong> Reduce costs, improve customer experience, ensure compliance? Which processes contribute most to these objectives?<\/strong> Processes need to be mapped, and their automatibility (volume, variability, stability) assessed. <\/p>\n The BFSI sector is an instructive example: it accounts for almost 29% of the RPA market. However, automation is advancing faster in branches where management has defined a clear roadmap and articulated precise objectives (reducing loan processing time, reducing the risk of error, improving customer service). <\/p>\n Effective RPA governance is based on :<\/p>\n An executive sponsor<\/strong>: a member of the management committee who sets the vision, arbitrates investments and facilitates communication between business and IT.<\/p>\n<\/li>\n A Center of Excellence (CoE)<\/strong>: a unit dedicated to automation, comprising RPA developers, data analysts, business experts and IT architects. The CoE defines standards (process modeling, robot nomenclature, security), provides training and supports local teams. <\/p>\n<\/li>\n Business referents<\/strong>: for each area (finance, HR, production, etc.), a referent identifies automation opportunities, validates needs and evaluates gains. They work with the CoE to design and test the robots. <\/p>\n<\/li>\n A change management framework<\/strong>: communication, training and support for teams to encourage acceptance. Automation should not be perceived as a threat, but as a means of enriching missions. <\/p>\n<\/li>\n<\/ul>\n An impact\/feasibility matrix<\/strong> can be used to prioritize processes. Criteria include : <\/p>\n Business impact<\/strong>: number of hours saved, effect on customers, risk reduction.<\/p>\n<\/li>\n Process complexity<\/strong>: number of systems involved, variability of cases, exceptions.<\/p>\n<\/li>\n Dependencies<\/strong>: planned IS evolution, data availability, current projects.<\/p>\n<\/li>\n<\/ul>\n In the start-up phase, we recommend choosing quick wins<\/strong>: processes that are simple to automate, with a visible impact. For example, automating invoice reconciliation in an accounting department, or generating compliance reports. <\/p>\n A robot generally follows the following steps:<\/p>\n Process capture<\/strong>: document analysis, interviews, task mining. This phase models the flow, variants and exceptions. <\/p>\n<\/li>\n Design<\/strong>: writing the functional and technical specification. It describes inputs, outputs, business rules and interactions. It’s important to take exceptions into account right from the start. <\/p>\n<\/li>\n Development<\/strong>: implementation of the workflow in the RPA tool, creation of scripts, integration of API or AI calls, variable configuration.<\/p>\n<\/li>\n Unit and integration testing<\/strong>: checking the robot’s operation on a test environment, handling simple cases and exceptions.<\/p>\n<\/li>\n User test (UAT)<\/strong>: validation with the businesses and any adjustments required.<\/p>\n<\/li>\n Production launch<\/strong>: planning and deployment via the orchestrator, configuration of accesses and parameters.<\/p>\n<\/li>\n Supervision and maintenance<\/strong>: monitoring logs, resolving incidents, optimizing the robot, adapting to changes (new functions, interface upgrades).<\/p>\n<\/li>\n<\/ol>\n To measure the effectiveness of the RPP program, we generally follow :<\/p>\n Automated hours<\/strong>: time saved per year thanks to robots.<\/p>\n<\/li>\n Error rate<\/strong>: comparison between manual and automated errors.<\/p>\n<\/li>\n Processing times<\/strong>: before\/after automation.<\/p>\n<\/li>\n Robot availability rate<\/strong>: proportion of time robots are operational.<\/p>\n<\/li>\n Return on investment (ROI<\/strong> ): financial gains generated by robots compared with development and maintenance costs.<\/p>\n<\/li>\n<\/ul>\n5.2 Setting up governance<\/h3>\n
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5.3 Prioritizing use cases<\/h3>\n
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5.4 Robot life cycle<\/h3>\n
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5.5 Monitoring KPIs<\/h3>\n
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5.6 Lessons learned and pitfalls to avoid<\/h3>\n