Overcoming Real And Imagined Roadblocks To Automation

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Many companies still struggle to move ahead with clear strategies for tech investments and the organizational changes that must accompany intelligent automation. A few of the biggest myths, dispelled.

The surge of technology investment of the past two years is unlike any we’ve seen before. This includes automation, which has rapidly evolved from an industrialized to an intelligent technology, incorporating artificial intelligence and other cognitive features. As a result, today’s advances in automation deliver far more than the bottom-line efficiencies of the past. They now enable innovative customer experiences and improved decision-making that creates new forms of value and growth.  

But many business leaders remain wary of automation technologies and are held back by outdated myths commonly associated with them. This results in incorrect assumptions about barriers that stand in the way of value. Consequently, many companies struggle to move ahead with clear strategies for technology investments and the organizational changes that must accompany intelligent automation. Here are a few big myths to dispel: 

Myth #1: Customers aren’t ready.

There’s a misperception that people only want to interact with other people and so automation will fail. In reality, a key point of automation is that it frees workers from routine tasks and lets them focus on adding new value with and for fellow humans. Companies that unlock the potential of their people to focus on human considerations—like building personal relationships, managing employee concerns, and improving employee engagement and satisfaction—will ultimately deliver a better service for customers. 

Myth #2: It’s all about the technology.

Intelligent automation is not a race to be the first to implement the latest technology. Success depends on understanding people’s needs, introducing new technologies in helpful, minimally disruptive ways, and addressing issues related to new skills, roles, and job content. In other words, focusing on people is just as important as focusing on technology. 

Myth #3: Automation is on the ‘bleeding edge’ and risky.

In fact, the opposite is true, and your competitors may know this already. Sitting on the sidelines while others achieve and learn will only waste time. The Economist Intelligence Unit 2019 survey of 502 executives across eight countries found that 73% of respondents claim to be either “very” or “entirely” satisfied with the automation benefits they are seeing. This indicates that the risks of jumping into the fray now are not as great as some managers might think.  

Myth #4: Automation is ‘one and done.’

It’s tempting to take a “check the box” mindset, taking satisfaction in the processes that are already “done” and focusing on different technologies to take on next. The reality is that automation is iterative and ongoing. After automating a task or process, a company needs to keep making step-change improvements, especially by combining robotic process automation, AI and modern engineering. 

That said, there are still real obstacles that can stand in the way of a successful intelligent automation program. Here are five ways to overcome the most common barriers and unlock the full potential of intelligent automation: 

1. Strategic alignment. When intelligent automation is managed strategically, thinking happens on two levels. First, there is a clear plan for building an intelligent automation capability within the organization, stating its major goals in clear terms and outlining an action plan to achieve them. Second, intelligent automation solutions are aligned with the overall business strategy. Insufficient attention to either of these levels is a barrier to success. Specific goals, clear metrics and a well-thought-out roadmap are essential to avoid falling into a patchwork of poorly coordinated initiatives and failing to update legacy systems and processes. 

2. The right talent. Most often, managers identify automation skills as being scarce, hard to find and costly. Gartner TalentNeuron data shows that the total number of skills required for a single job has been increasing by 10% year over year since 2017, and over half of the total skills needed for the average job are new. Companies must therefore invest in the capabilities of employees, and in the wider skillsets that they will need to develop, use and manage intelligent automation and AI tools.  

3. Culture change. Intelligent automation initiatives can run up against ingrained habits, attitudes, and assumptions that make it hard for change to take hold. The “but we’ve always done it this way” mentality, combined with existing commitments, means that proposed changes can be shot down despite the best intentions. Worker apathy is sometimes the result of skepticism about the value of the change. Fear can also be a factor, particularly around work displacement. It falls to business leaders to set the vision and communicate the benefits, not just for the business, but for its employees and the new career options automation can open up for them.  

4. Updating processes and policies. A common mistake is to automate processes that were inefficient to begin with. This simply helps companies take the wrong steps faster. It’s often best to begin with a clean slate and redesign processes in light of current realities. Where processes are complicated, or cross over multiple functions, it’s important to clearly define, consolidate and simplify them. More challenging are long-standing corporate policies developed without thought to today’s innovations. Project plans must therefore explicitly include a timely review and modification of policies that conflict with the project’s goals and hinder solution design. 

5. Simplify the tech environment. Most companies encounter barriers as they try to make use of cutting-edge automation technologies. These show up in the form of legacy architectures, inadequate data, and off-the-shelf solutions that are not nearly as turnkey as advertised. The conventional IT stack has reached its practical limit. Businesses need to decouple data, infrastructure, and applications before integrating advanced AI and automation tools. This effort needs to be combined with more effective data management processes to set the foundation for intelligent automation.  

The shift from industrialized to intelligent automation provides new opportunities for innovation, smarter decision-making as well as greater returns from investments in cloud and other technologies. The value is clear and spans multiple functional areas—streamlining accounts payable, personalizing customer service, identifying acquisition opportunities, and much else besides. To succeed, leaders must elevate their strategies by transforming the people, processes and systems to create new forms of value. That requires conversations across the C-suite to bust the myths and tackle the barriers that stand in the way of the automation advantage. 

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