Ever wondered what makes an RPA solution fall short of its potential? Implementation complexity may just be the answer!
Robotic Process Automation (RPA) is the buzzword that has caught business attention and is the new buzzword, that enterprises have embraced. To make automation successful, enterprises need to make changes in their vision and strategy. RPA is more than just automation and replacing people with technology rather it involves process design which must be the core of the business strategy.
RPA mitigates rule-based processes to automate it resulting in tremendous process improvement that reduces process costs by nearly 80 percent but only when the right capabilities and teams are put in place. RPA leaders tend to overestimate the speed of RPA implementation, which may lead to difficulties handling resources, managing expectations, and capturing targeted ROIs.
The need of the hour is prudent leaders who have a clear vision of the future that comes with realistic expectations based on a deep understanding of technology. RPA leaders must distinguish wins from full-scale RPA implementations. This helps in keeping teams motivated by allocating resources based on need.
Businesses have typically turned on to third-party service providers that develop bots, but may fall back in training internal employees who are charged with crucial maintenance and solution upgrades. This makes employees who are not familiar with code, process design, or assumptions for effective functioning. Besides, there needs to be a deliberate and clear knowledge transfer between maintenance teams and bot developers. Costs of neglecting may run high since teams spend more time on bot maintenance which means realising fewer-than-anticipated benefits from the deployed bots.
Many enterprises select members of their RPA team based on domain knowledge and their technical prowess. They underestimate the need for the RPA team to work with other domains of the organization. Making sure the project is in full alignment with IT requires team members who meet IT expectations on a regular basis. This responsibility might be best delegated to someone who has deep existing relationships within the enterprise coupled with management skills than to someone whose expertise is technology.
Similarly, on the business side, an RPA team must go beyond just producing bots for the business to effectively address business concerns around change-management efforts and service level agreements (SLAs). These translators track bot performance against business goals to communicate additional requirements to the RPA teams for a smooth transition across enterprises.