4 steps to overcoming resistance to robotic process automation
Many organizations can relate to this situation: every time a customer makes a written request to Company ABC, it triggers a series of connected events.
First an offshore team reads the email to decide what the customer is requesting, and whether there is enough data in the message to complete the request. The team then enacts standard processes to retrieve data requested by the customer to update the customer’s account. Team members identify and pass on complex queries to an onshore team. Finally, the offshore team must choose from more than 100 templated responses depending on the action needed.
Robotic process automation (RPA) promises a host of benefits to organizations like Company ABC. RPA can automatically retrieve data from systems, give exceptions for complex scenarios, update templated responses with customer information and respond to inquiries.
As more organizations discover the potential benefits of RPA – lower costs, higher-quality outcomes and improved end-user experience – many are moving quickly to implement it. In fact, an ISG survey finds that the number of mission-critical processes supported by automation and artificial intelligence (AI) will grow by more than three times over the next two years.
In the race to automate, it’s important that both RPA service providers and their corporate clients keep in mind the one major roadblock to successful automation is employee resistance. To ensure they roll out a technology that employees will actually use, organizations should use a measured approach that respects the human dynamic of automation.
Here’s a four-step process to do just that.
First, think through what you’re trying to achieve.
Organizations should approach RPA systematically, using a Center of Excellence model that deploys focused resources for implementation, training, communication, and change and implementation management. This helps companies figure out how to prioritize the technologies they need, identify who oversees and executes process automation and measure the results.
It’s best to run before walking, but 78 percent of automation deployments do not do this. They begin before they have a strong operating model or governance structure, resulting in silos of automation and less-than-optimized rollouts.
Most workers would be happy to have a better solution to their computer problems than having to tell an IT staffer that, yes, they tried turning their computer off and back on. Yet a stunning 76 percent of automation end users, per ISG’s survey, have a substandard understanding of how automation impacts processes.
Employees need to understand why a new technology is being rolled out and, more importantly, why they’ll benefit from using it. Is it faster? More intuitive? Higher quality? Let employees know the end game and how they are involved in making the business run better.
Third, train, test and adapt.
Most organizations wouldn’t roll out a chatbot to customers without testing. Likewise, companies shouldn’t roll it out to employees without testing. Small-group testing is essential. So is a training plan in which employees are exposed to repetition of the new process so they can build “muscle memory.” Employees also need to feel their opinion is valued, so be sure to create a closed-loop mechanism for workers to implement feedback into process automation.
Fourth, motivate and reward.
Automation success is most often about the “will” and not the “skill.” Building motivation is an often-overlooked but nonetheless critical part of successful change. Enterprises should find pockets of success and celebrate that success – whether with verbal recognition, free pizza or a more formal type of reward.
Getting people to change their habits is hard work. It’s tempting to skip the change management and focus just on the new technology. But without adopting a measured approach that includes these steps, a company’s investment could fall short of expectations. Employees may fail to grow and attain new skills. In the age of continuous technological disruption, failures like these can put companies at risk of falling behind – or worse.