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Intelligent automation has been attracting a lot of attention lately. Many people want to know what the future holds, and many do not want to feel left out.
However, intelligent automation (aka “hyper-automation”) is an ever-changing collection of technologies. New tools come out every year. It’s difficult to keep up.
In addition, others worry whether the hype corresponds to reality. For example, in July 2021, IBM executives scaled back expectations for Watson. IBM first pitched Watson as revolutionary, promising advanced AI capabilities like automating cancer detection and treatment recommendations. Now IBM has positioned Watson as a tactical natural language processing tool. Even the best can get caught up in the hype.
Instead, it pays to automate intelligently. But how can digital leaders think about intelligent automation to make smart investment decisions?
Also see: Why intelligent automation is the only answer to wage inflation
We can divide intelligent automation into three categories. Here we want to cover 80% of the skills. The remaining 20% are niche functions that will be covered in a more detailed study.
The three skills are:
- automate tasks
- Orchestrate workflows
- automate decisions
The first skill is task automation. This is often referred to as Robotic Process Automation (RPA), where a bot repeats a series of tasks in the same way a human would. This frees people up to focus on more valuable work.
Well, task automation isn’t new. Excel macros have been around since the 1990s. However, modern RPA has an interesting history.
Daniel Dines founded UiPath, a leader among RPA companies, as DeskOver in 2005. They initially created tools to help developers build software. Dines tried to sell them to companies like Amazon, Google and Microsoft but didn’t get much interest.
Dines fought. He thought about closing the company. However, in a fortunate moment, a business process outsourcing company in India was looking for an automation tool. Today, outsourcing firms perform repetitive tasks with thousands of employees from low-wage countries. The price pressure is great.
Back then, UiPath didn’t know anything about outsourcing. However, they managed to turn away and impress the outsourcing company. The rest is history.
Thus began the modern era of intelligent automation when a company that made productivity tools met an outsourcing company looking for help increasing productivity. Today, thousands of companies operate millions of bots, all performing the same tasks repeatedly. They free up millions of hours so everyone can focus on more important tasks.
See also: Automation Becomes a Business Imperative: Don’t Wait Until It’s Too Late
Sometimes it is not enough to automate individual tasks. Instead, we need to redesign the business process. This brings us to our second skill: orchestrating workflows.
The groundbreaking book by Michael Hammer and James Champy, Restructuring of the group, contains a classic story. There was one division at IBM that was very profitable. However, they had a major challenge: on average, it took six days to create a contract for a customer. This was unacceptable to sellers. During this time, a customer could select another provider. Therefore, they wanted to improve operations by automating tasks.
However, this was not the right approach. Two senior executives had a brilliant idea. They walked an application through the business process and asked each person to focus on just that one task. They found that the department could complete an application in 90 minutes.
Now suppose the executives had a magic wand that would allow everyone to work twice as fast. You would only save 45 minutes. Most of the time was spent waiting in line. The solution wasn’t to get things done faster.
Therefore, the business process was redesigned so that one person could mostly fill out an application in one step. They reduced the average wait time from big days to four hours, resulting in a 100x increase in productivity.
So the second set of tools is about orchestrating workflows. Low-code workflow engines enable business users to orchestrate enterprise-wide business processes. You can increase productivity beyond just automating a single task. In addition, the automation of tasks and the orchestration of workflows go hand in hand. We can orchestrate the workflow first and then automate individual tasks for even more efficiency.
See also: 4 reasons workers should embrace artificial intelligence in the workplace
The third group of technologies focuses on the automation of decisions. There are easy problems and difficult problems. This leads to Moravec’s paradox.
In 1988, Hans Moravec wrote: “It is comparatively easy to get computers to perform at adult levels on intelligence tests or at drafts, and it is difficult or impossible to teach them the abilities of a one-year-old when it comes to perception and mobility.” For example, we’ve taught computers to play checkers, but we struggle to teach computers a toddler’s cognition and mobility skills.
In 1966, the famous computer scientist Marvin Minsky wanted to teach a computer to recognize everyday household objects. Thinking it would take a summer, he hired a student to do the project. It turned out to be extremely difficult. Fifty years later, computer vision systems are emerging.
Well, if computer vision is a difficult task to automate, what could be easier? Researchers have made advances on specific problems. For example, IBM Watson’s computer vision capabilities can rival that of a radiologist for certain types of cancer. As another example, credit bureaus use decision engines to predict the risk of credit fraud or default using huge data sets.
See also: Robots are stealing our jobs
Unlock the power of intelligent automation
The true power of intelligent automation lies in the combination of the three capabilities – automating tasks, orchestrating workflows, and automating decisions. For example, we can first orchestrate the workflow by redesigning the business process. Second, we can automate individual tasks to free people from mundane tasks. Third, we can automate decisions about which machines have an advantage.
Now, delivering on the promise of intelligent automation can be difficult. Some struggle to separate the hype from reality. Others fall in love with the tools and lose sight of solving business problems. Therefore, to unleash the power of intelligent automation, a company must start with a strategic view of the business challenges. These business problems make the field of intelligent automation exciting today.