Here are 7 types of failures enterprises run into when launching RPA programs and tips on how best to avoid them.
Usually, when an organization points to an inability to deliver sufficient ROI, it’s because it did not invest in appropriate management and oversight for the program.
2. Choice of automation candidate
RPA projects sometimes fail to produce ROI because enterprises choose the wrong automation candidate.
3. Management challenges
RPA failure often results from the management of the digital workers once deployed to production. Much like a new employee, the automation will encounter scenarios in its early days in production that it did not see in the training.
4. Scaling challenges
Bots are a great stopgap measure for many scenarios that involve copying data from one application or system to another, but they can face scaling challenges compared to direct API integrations.
5. Unrealistic expectations
“Most of the failures I’ve encountered center on unrealistic expectations,” said Lauren Lang, associate director for the business performance improvement practice at Protiviti, a global consultancy. Many projects begin with hopes of instant gratification.
6. Siloed RPA deployment
Most digital transformation projects fail because those who rely on it don’t understand how it operates or felt that they were left out of the planning process, said Prince Kohli, CTO at Automation Anywhere, an RPA tools provider. To avoid these mistakes, capitalize on the skill of nontechnical employees who appreciate being involved in bot development and can offer insight into how automation technology can advance business goals.
7. Improperly defining success criteria
IT leaders also inadvertently doom their automation initiatives from the start by failing to define success, Kohli said. Understanding the desired outcomes at the beginning sets up the entire journey for success, yet oftentimes, organizations embark on RPA with a sole focus on cost savings.