RPA – Where Next?


The RPA software market grew 63.1% in 2018 and 62.9% in 2019, according to Gartner. That’s more than five times the growth rate of the enterprise software sector overall. What’s more, expectations of outsize growth persist, despite the pandemic.

Can RPA continue its stunning growth and remain the #1 fastest growing software segment? Based on the experience and plans of our own customers, and on the perspectives of expert industry analysts, here is Lithe’s current view of what to expect.

Is the RPA Wave Subsiding?

The fastest growing of the leading vendors, UiPath, had grown over 120% in 2019 and its trajectory seems unchanged. At end of April 2020 UiPath took in a $568m investment, valuing the company at $7b. In mid-July the Company took another $225m investment, at a valuation of $10.2b. Amid the worst global economic crisis in a century, RPA and UiPath appear to roar on.

It’s not only the current RPA market leaders who are confident of RPA’s continued growth. Established tech giants have jumped from the side-line into the RPA game. Shrugging off the pandemic’s impact, Microsoft accelerated its entry as an RPA provider by acquiring Softomotive in May 2020.

Furthermore, young tech firms are surfing the tide of investment money flowing to anything RPA. In June 2020 New York start-up Hyperscience took $60m from respected VC Bessemer to “do something RPA hasn’t easily achieved”.

So where does the surging RPA wave go next?

New Waves Rising

RPA was initially seen as the tail end of a wave of process automation technologies that had washed over the corporate world for almost 20 years but was ebbing away. According to this narrative, RPA would do the small amount of process automation that remained to be done.

A new digital workforce of RPA software robots would automate the residual and previously manual/human work of transcribing data between different enterprise systems via UI interactions. Small tasks, quick and easy to automate.

It turns out there was a lot of task automation to do, and the population of software robots quickly became vast. Rather than the tail end of a wave, this was the start of something.

The start of what? I’ll highlight three of the rising RPA waves that Lithe customers are experiencing.

Machine Learning (ML) for Smarter Robots

The initial population of RPA robots did a great job, efficiently and reliably emulating the movement of human hands on a keyboard to automate repetitive data entry and extraction tasks. But they didn’t have cognitive power. For example, they couldn’t look at a document and understand its content.

Today’s new generation of robots, however, is equipped with cognitive ability via Machine Learning (ML) technology, and can recognize, read and understand documents – call it “Intelligent Document Processing (IDP)”.

With IDP skills, the digital workforce is being applied to an immensely expanded scope of tasks that previously required human intervention in core business processes – loan origination, finance reconciliations, new account opening, insurance claim processing, citizen benefit administration, etc. This is the most popular new extension of RPA amongst Lithe customers today, whether they’re using UiPath, KofaxABBYY or other of the many who provide IDP capability.

Two other applications of ML and RPA are much talked of but, as of today, in less widespread use. First, “predictive analytics” allows software robots to acquire that elusive human skill, good judgment – so, they can make good “next best action” decisions automatically. Second, robots combine with “conversational AI” so the dialogue you have with an insurer, bank, service center, etc. seems more natural, less robotic.

It is early in their maturity cycle, but smarter robots are coming.

Mining for Automation Gold

RPA robots have proven so tireless and beneficial that the job of finding them work has become a job in itself. The tool for the job is “process mining”. An already mature technology, process mining is a hammer that has found its proverbial nail in the wake of RPA.

Process discovery is today often done by a team of consultants or process analysts, manually, using white boards, Post-Its and graphical flowcharting tools. Process mining automates this process of process discovery.

Like a metal detector, process mining sees below the surface to find the actual process that is executing in a business. This technology is not a pipedream, it’s available now. Customers are starting to apply it with the aim of quickly identifying new work their digital workforce can automate.

Work is also underway to automate the creation of RPA robots based on task and process mining – some RPA software vendors already offer some of this capability. When ready, this combination of processing mining and RPA will not only automate the discovery of work but will also automatically create a robot to do that work.

Again, this is early in its maturity cycle, but “automation of the automation” is coming.

Scaling RPA

Soon after their early RPA successes, customers often stumble to replicate and multiply those successes. RPA is easy to get started with, but the need to manage, maintain and scale the new (and invisible) workforce of software robots soon becomes a new and urgent priority. For most customers this entails use of complementary technologies and application of program management disciplines, often via Centers of Excellence.

Which complementary technologies? Think of the digital workforce as an army of robots wearing blinkers – they see only the task they’re built to execute and need to be told when to start and stop. This “orchestration” of the robots is a necessary part of managing the workforce and many Lithe customers are now augmenting their RPA with orchestration technology (most commonly a BPM, business process management, tool). As we’ve seen, process mining too is increasingly a popular complement that addresses RPA’s scalability challenge.

Governance of the digital workforce, in ways analogous to what a management and HR function does for the human workforce, is a growth area in many customers. Most are maturing beyond early project management to new Centers of Excellence, creating cross-functional committees, program management discipline, ROI and project prioritization, etc.

Centers of Excellence are much less about technology than about management of human organizations as they adopt technology.  While CoE’s are not a new phenomenon, RPA’s ease of use and speed of implementation have added a sense of urgency. So, CoE’s are rightly getting more attention – everyone wants to maintain the momentum of RPA’s success and CoE’s help do exactly that.

Where Next for your RPA Initiative?

Business stakeholders have been impressed with the ease and speed of RPA implementation, at least in its early days. They welcome RPA’s evolution so long as those same advantages are not lost in the transition. I’ve highlighted some of the wave dynamics our customers are experiencing as RPA flows through their organizations. If you want help to navigate your own RPA success, whether you’re just starting on your first projects or moving to next phases of an existing RPA initiative, contact us and we’ll do all we can to assist.

Selected Sources:

Gartner. Market Share Analysis: Robotic Process Automation, Worldwide, 2019, 26 May 2020

Gartner. Magic Quadrant for Robotic Process Automation, 27 July 2020

Forrester. RPA Inquiry Spotlight, 2020. Forrester Inquiries Highlight Scale, Security, Governance, And AI Integration Issues May 11, 2020

IDC. The New Business Automation Toolkit. YouTube, 2 August 2020

Everest Group. Intelligent Document Processing (IDP) – Technology Vendor landscape with Product PEAK Matrix Assessment, 27

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