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Howard Rabinowitz
Howard Rabinowitz
3 min read

Start your automation journey – but watch your step

A conversation with Lila Benhammou, CEO of Humans4Help.
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Robotic process automation (RPA), a suite of digital technologies that automate manual workflows, delivers value. By eliminating repetitive tasks, it frees talent to focus on more high-value work, reduces costs, and improves quality. In the first year, a company’s return on investment in RPA can be 30% to 200%, according to McKinsey.

No wonder the RPA market is exploding. In 2021, enterprise spending on RPA was $1.89 billion; it’s projected to hit $13.74 billion by 2028, according to Grand View Research. Today the lion’s share of that spending (46%) is by financial services companies, but RPA is poised to transform every industry, from healthcare and IT to retail and manufacturing.

For organizations just beginning their RPA journey, the road has pitfalls. They’ll have to figure out how to structure their unstructured data (such as video, voice, social media, PDFs, and IoT data), which can comprise as much as 80% to 90% of a company’s data. They’ll need to find ways to integrate new technologies into legacy systems. Perhaps most important, they’ll need to decide where and how to begin.

To help navigate these challenges and look at how RPA is evolving, we sat down with Lila Benhammou, founder and managing director of Humans4Help, a digital technology consulting firm that helps its clients leverage RPA for maximum business value.

How should companies approach RPA to get the most out of their investment?

The first step is to understand your business processes well. The selection of which processes to automate is critical to the success of an RPA journey. The bottom line is the simpler, the better. Maybe 80% of the time, companies choose very complex processes to start with, which is absolutely wrong.

What’s an example of a process that might be too complex?

It can be a matter of input-output, like trying to automate processes that rely on a lot of unstructured data, or trying to use data that is difficult to access because it’s on a legacy system. Those factors add a lot of complexity, but it can be a tricky thing to explain that to a company. Often they will say, “Complex or not, this is what I need.” If they forge ahead with it, it can be a pity, because their first experience with RPA will be a bad one. They might say, “We tried it, it failed, and we’re done with RPA.”

When you work with a company, how do you help them decide which processes might be best suited to automation?

We recommend three steps. To begin with: Think big. Often when we work with clients, we generate a heat map of their business processes – for example, finance, legal, HR, and IT processes – to chart which ones are repetitive and labor-intensive, which require the most resources in terms of employee time and expense, which are connected to one another, and so on. That helps us visualize operations, begin to explore where RPA makes the most sense, and discuss specific goals.

The next step is: Start small. We should select one or two killer use cases where we know that we’re going to get the best reduction of repetition along with the best buy-in internally, because leadership needs to be convinced that the effort is worthwhile, and so do managers and workers and so forth.

The third step is: Scale fast. When we’ve chosen our use case or cases, we should establish a concept of excellence around measurable outcomes that reflect value internally as well as externally for customers. If our pilot on the use case delivers on that concept of excellence, then we go big.

RPA is evolving fast, integrating with AI tools like natural language processing, speech recognition, and computer vision. How can we expect its capabilities to change in 2022?

We’re going to see more and more cognitive RPA. Last year, RPA was task-centric, like a human doing a repetitive task but faster and without mistakes. Tomorrow, with AI, bots are going to be thinking like humans. They will increasingly be able to make intelligent decisions. A chatbot, for example, will interact with more intelligence, deal more with an unstructured world and make sense of it more like a human. I like to say, “To act like a human, think like a human.”

Low-code tools have put RPA within the grasp of people who are not necessarily technologists. Has that enhanced companies’ ability to leverage RPA?

Yes, definitely. Making the complex simple is basically what low code/no code is about. It’s a very user-friendly interface, so you can very easily onboard the lines of business, the owners of these business processes, who may have no clue about the nuts and bolts of IT. Explaining how RPA will work and benefit them can be complex. With low code/no code, you can create your business rules and your workflows in the morning, and they’ll see results by the end of the day. That’s going to lead to high adoption of those kinds of tools.

Interested in more from Lila?

Check out her episode on how hyperautomation is making smarter work possible on Pega’s Bold stories. Future focused. podcast.

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