As we all wind down our year-end activities for some much needed time off, most of us enter that wonderful, holiday reflective state. We break down our past year and prepare to build ourselves back up into an improved, wiser version of ourselves for the next year. It is in that spirit of reflection that we offer up some of our key observations in Robotic Process Automation (RPA), RPA software and broader intelligent automation from 2018. We have also put together key predictions that we believe will evolve in 2019 and beyond in a different post being published next week.
As an industry, 2018 saw tremendous growth that over-exceeded even our bullish expectations. The numbers are staggering. When we look at the areas that created, they can be summarized in 3 words: EXPECTATION, SCALE & ORCHESTRATION.
Growth by the Numbers
RPA become a ‘Top 5’ search term on Gartner.com. According to Gartner, RPA software spending is on pace to total USD $2.4 billion in 2022. Global spending on robotic process automation (RPA) software alone is estimated to increase by 57% YoY to reach $680 million in 2018. By the end of 2022, 85 percent of large and very large organizations will have deployed some form of RPA. Forrester actually increased their forecast of RPA spend to $2.9 billion by 2021.
RPA Software Funding Explodes
Close to $1 billion dollars of funding was handed out to RPA software vendors in 2018. More than half of that went to UiPath and Automation Anywhere. Money talks and 2018 has had a rather loud voice. Our belief is that the ‘Big 3’ of RPA (UiPath, Automation Anywhere and Blue Prism) have really distanced themselves in 2018, and this funding will help distance themselves further with funds for scale and innovation.
Business Cases
Regardless of the talk about customer experience and operational efficiency, the #1 metric that we continued to see as the key business case justifier was still cost cutting. Right, wrong, or indifferent, expectations are still misaligned, and inflated FTE reduction #’s have been a recipe for stalled Intelligent Automation programs.
Project Failures
Failure was still relatively high within RPA projects. Deloitte’s survey of 400 global firms found that 63 percent of surveyed organizations did not meet delivery deadlines for RPA projects. These delivery deadlines led to an erosion of initial ROI estimates. And an EY study found 30 to 50 percent of initial RPA projects fail. Part of these failures are due to inflated business cases and learning curves with new technology. But part of the blame is also on the inaccurate marketing by the RPA vendors themselves that states it is so easy to implement, your company should do it yourself. I’ll admit my bias here as a service provider focused on Intelligent Automation, but trying to internalize RPA roll-outs is like giving yourself a root canal- I can identify where the pain is and can read the steps on the procedure, but I am no dentist.
Process Still a Challenge
The lack of pre-existing process foundation is still the #1 barrier to automation programs according to APQC. But the challenge is more around education and expectation rather than capability. Discipline around Process Discovery is key to Automation success. RPA platforms like UiPath, Blue Prism, and Automaton Anywhere do exactly what we script them to do. And these platforms are getting smarter. But in order to unlock even more value out of process automation, we need to start with process standards, and think about ways to discover, automate, extend, and analyze these processes continuously.
Process Orchestration
Our experience is that most organizations are still doing ‘RTA’ (Robotic Task Automation), not RPA. But 2018 saw some indicators that this is changing. Intelligent OCR technologies saw tremendous growth over the last 12 months. ABBYY saw their highest revenue growth in 5 years in 2017, and 2018 is likely to be even higher. Google and Microsoft have dedicated full teams of engineers and co-selling resources to leading RPA platforms to fuel their AI and Cloud consumption ambitions and extend automation and cognitive capabilities. RPA demand is driving this growth and attention. RPA use cases with semi-structured document recognition needs like reading Invoices have been a catalyst. Organizations have started to realize that they must look upstream and downstream (AI) in order to unlock the true potential of intelligent process automation.
Attended vs. Unattended RPA Software
Those that have spent any time in the RPA space knows that there are several different flavors, namely attended and unattended RPA. Where the higher value lies is in leveraging both attended and unattended RPA to extend processes. We call this Hybrid RPA. We did not observe much Hybrid RPA in 2018. The majority of the market has still been adopting RPA as an ‘either, or’ decision when it comes to attended or unattended. To the above point on Orchestration, this will be critical in order to extend and reinvent processes that wow our customers.
Business Model Evolution
Outsourcing in its traditional labor arbitrage model is decreasing in most functions. Automation is increasing. A Next-Generation Operations model has emerged in 2018 that combines technology, process, and people in a smarter, more efficient way.
The Future of Work
In 2018, our observation is that there was a lot conversation on the future of work, but it was at a philosophical level. Concrete actions and the ‘HOW’ and ‘WHAT’ needs to be done to reskill our workforce haven’t advanced as quickly as the technology. We find this so important that we will be keeping this conversation going all of 2019.
Overall, 2018 was an exciting year. The explosive growth would excite the least excitable skeptic. The cracks of scale were also exposed do to the growth and pressure from the C-Suite. Organizations now need to futureproof their foundations before they take it to a broader scale. Our 2019 key predictions released next week will begin to tackle these challenges and open up new opportunities for intelligent automation.
