I recently wrote a piece on Forbes about the realities of automation in digital transformation. Namely—I discussed the fact that many companies have recognized that despite its miracle-worker status, automation isn’t as “easy” as we may have originally thought. For instance, automation requires tremendous coordination throughout the enterprise for companies to recognize the fullest and deepest benefits. At an age when many companies are still trying to figure out how to manage data from a central location, that coordination itself has yet to be optimized. Piggy-backing on that issue is another essential issue: identifying tasks to automate. Without digging deep into the identification process, no company will experience the full extend of efficiencies offered by automation. That’s why it’s so important to focus on creating a “101” type of automation strategy before you even put an automation system in place.
When it comes to identifying tasks to automate, there are many ways to do it—but fewer ways to do it well. What many companies do is start piecemeal. They hear of new technology through the grapevine that can automate time sheets, payroll, or scheduling, for instance. So, they begin the process of incorporating that technology into a certain department clamoring for it. That’s well and good for the single department that benefits. But, what about the other departments throughout the enterprise dealing with similar issues—similar tasks that could likely use the same algorithms to make their work faster and easier? This is where taking the time of identifying tasks to automate becomes a more valuable process. It’s also where most companies forget to spend their time.
As you commit to making the most of your automation processes and investments, consider the following guidelines. They can help you identify tasks that are “automation compatible”—tasks that are not just replicable but commonly used throughout the enterprise.
Physical vs. Mental
This one is no surprise. We saw it go gangbusters in the first and second industrial revolutions. Where robots can manage repetitive actions in place of humans, let them do it. This could include carrying, lifting, sorting, assembling, packing, shelving, etc. Nowadays, it can also include dangerous activities, such as performing site checks in construction zones or performing safety checks on behalf of law enforcement. These physical activities don’t require independent thinking but they offer tremendous time and safety savings for your teams.
Repetitive vs. Variable
I’ve talked a lot about the ways technology like machine learning is working to make the processing of qualitative/unstructured data easier to manage. But, let’s say your company isn’t there yet. You’re just looking to find the lowest hanging fruit that your entire company can benefit from when it comes to automation and identifying which tasks to automate. First, you’ll look at those repetitive and non-variable tasks that are routine and predictable. This could be sorting through data to find red flags on a credit report, key words on a resume, or unapproved charges on an expense report. These are things easily performed by robotic process automation. Not only does it take the work out of the hands of your employees, it also performs the work far faster—15 times faster, increasing capacity for your teammates company-wide.
Independent vs. Interactive
In general, tasks that require interaction with other people—brainstorming, fixing a problem, helping someone feel valued—are things that require “human” skills. They require compassion, empathy, and a general caring about the work being done. On the other hand, work being done independently—reading reports, reviewing audits, etc., seem like the could be managed by a robot. After all, they don’t require interpersonal skills, just a cognitive (real or automated) thinking cap. I agree, to a degree. Interestingly, many companies today are working fast and furious to outsource their deeply interpersonal customer service work to robots using more advanced machine learning and emotionally intelligent AI. My point being: these aren’t fast and furious rules about automation or identifying tasks to automate. Depending on the time/value ratio you’re looking to achieve, and the types of work done at your company, you may find that automating interactive or unstructured parts of work may be necessary. In general, however, independent work is a good place to start in identifying tasks to automate.
This is not an end-all, be-all list for identifying tasks to automate. It does, however, offer a new way to frame your automation efforts—and framing you must in digital transformation. You also need to realize that you don’t have to go on this automation journey alone. Companies like Pega, Automation Anywhere, and UiPath work with you to help devise a plan and automate parts of your organization. But without a clear plan, you will never recognize the full benefit of your automation investment. Consider the above across the enterprise before making any new automation decisions.
The original version of this article was first published on Converge.
Futurum Research provides industry research and analysis. These columns are for educational purposes only and should not be considered in any way investment advice.
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
