It goes without saying that RPA isn’t a set it and forget it technology. RPA is essentially software built on top of other software. Each bot has a multitude of interactions with different systems and is impacted by any change to those systems.
Each stage of the RPA lifecycle will impact the bot’s uptime and ability to continually deliver the value RPA promises.
Many of the pain points RPA programs are experiencing today can be traced back to sub-optimal practices during every stage of the RPA lifecycle. For example, bots must be explicitly connected and mapped to their dependencies to enable proactive change management when an impending change to a legacy system or regulation impacts a bot in the future, which it will. This ensures the bot doesn’t just break and sit idle while its break is investigated, corrected, tested, and redeployed.
The good news is that it doesn’t have to be that way. Improved RPA uptime and greater returns are easily attainable with the right solutions and the addition of some best practices in your RPA lifecycle management.
