The most common RPA mistake is automating a broken process rather than fixing it first. Bots built on inefficient workflows automate inefficiency, amplifying the problem at scale. Teams frequently underestimate the maintenance burden - every system update or workflow change downstream can break an RPA bot, creating fragile dependencies. Overscoping the initial deployment by trying to automate too many processes simultaneously leads to delays and quality problems. Poor change management leaves agents uncertain about what the bots handle and what they should escalate, creating confusion. Failing to measure bot performance against baseline metrics makes it impossible to demonstrate ROI. Successful RPA programs start narrow, prove value quickly, and build governance structures before scaling.
Common Mistakes