No organization is immune to change resistance. Even the most progressive, digitally-attuned employees will resist new technologies unless they understand how to use them and why (i.e. what is in it for them, their teams and the organization at large). 

In fact, according to a large-scale survey of close to 80,000 business professionals found that:

• Only 15% of employees always understand the rationale behind their leaders' strategy
• 24% of employees say understanding the rationale behind change drives their willingness to embrace it
• 23% of employees say that confidence in their personal ability to succeed in the new, “changed” environment drives their willingness to embrace change
• Only 15% of employees believe that their organization always openly shares the challenges facing it
• Only 22% of frontline employees like to leave their comfort zone

When it comes to embracing cognitive technologies such as RPA and intelligent automation (IA) these factors are especially true. For many, the adoption of these tools spark fear of job loss and skill obsolescence. In addition, about half all AI projects fail to make it into production often due to human error somewhere along the data to AI pipeline. Furthermore, according to a report by Mckinsey, AI high performers invest significantly more time and resources on the human-side of innovation such as training, engagement and establishing governance. 

With that in mind, here’s a look at how 4 pearls of wisdom for transforming their IA dreams into reality.

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Tie Automation to Employee Experience

The goal of IA and similar AI-powered tools such as RPA bots and virtual assistants isn’t to replace workers but enhance the employee experience. By automating time consuming and boring administrative tasks, workers can focus on what really matters: strategic decision making, relationship building and other high-value activities. 

For example, Morgan Stanley recently rolled out the AskResearch bot, a new virtual assistant designed to help analysts mine the 50,000+ financial reports they review each year for useful insights. Powered by machine learning (ML) and natural language processing (NPL), these tools dramatically reduce the time it takes for junior analysts to locate, synthesize and share meaningful research with clients.

As Jennifer Casas, Executive Director of Research Technology Management at the bank, explained to American Banker, “Every day, with the amount of information available and the pressures of the market, there are more and more asks of our analysts, junior to senior. So if you free up the time a junior analyst will have to spend sending a model or looking for a report, then that junior analyst can dedicate that time to something else, something new, something that can enhance their platform.”

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Evangelize Success

There are few things, if any, that are more persuasive than proven business results. IA applications can start delivering results immediately, however these successes must be celebrated and shared on an enterprise-level scale in order for them to drive change.

Many organizations even build full-blown marketing and messaging campaigns around early automation successes. Jaguar Land Rover (JLR), for example, showcased its early success with BluePrism through habitual in-person meetings, internal newsletters and offsite hype sessions. Many organizations, such as WarnerMedia, have also embraced data visualizations and dashboards as a way to communicate its RPA/IA successes in real time and in a visual language that resonates with the business. 

Scalable RPA & Intelligent Automation Live

The key for global corporate enterprise is to benefit from the collective intelligence presented by RPA and cognitive technologies along with human workers. Only by having technology combine with human talent can global corporate enterprise achieve scalable intelligent automation. And only with scalable intelligent automation enterprise resiliency be realized.

 

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Create Space for Error 

Always remember, true lasting change doesn’t happen overnight. It happens in fits and starts, especially when you’re dealing with new, emerging tools such as cognitive automation. Afterall, even successful IA implementations rarely go as planned. 

Cultivating a tolerant, open dialogue around the ups and downs of implementation can help mitigate these issues. For example, automation leaders at Fresenius Medical Care realized their IA change management plan had fallen short when business units struggled to properly identify and submit processes that were ideal for automation. 

Though the automation thought they had adequate educated business units on the nature of RPA/IA and what these tools could and could not accomplish, as far as the internal customer was concerned, they had not which led to frustration and despondency on both sides. Seeing this as an opportunity to re-engage with business users and boost collaborative efforts, ultimately boosting long-term business results and resilience. 

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Employees are your greatest asset. Invest in them.

Last but not least, studies have shown that if employees view the introduction of IA and advanced automation tools as an opportunity to develop new skills and advance professionally, they are much more likely to embrace them. 

Upskilling talent to properly leverage these tools not only increased the likelihood of achieving ROI, it also boosts long-term business resilience. 

Amazon, for example, plans to invest over $700 million to provide upskilling training programs to ensure its workforce is prepared to thrive in the digital economy of the future. As they explained in their original announcement, “For us, creating these opportunities is just the beginning. While many of our employees want to build their careers here, for others it might be a stepping stone to different aspirations. We think it’s important to invest in our employees to help them gain new skills and create more professional options for themselves.”