UiPath 2020.4: Why Business Process Understanding may be the difference between RPA success and failure

Continuing to deliver on the 2020 vision

UiPath launched the fast-track support release 20.4 in May 2020 and continues to deliver on its 2020 vision. Following UiPath’s 2019.10 release in November 2019, we shared our thoughts about “five exciting new capabilities in UiPath release”. At this time, we’d like to double down with one of these capabilities. We believe that business processes understanding drives RPA success. In fact, research shows that this capability is a key success factor to achieve successful business outcomes. Conversely, not having this capability can lead to RPA failure. In addition, our own experience with customers supports the research.


Hyperautomation combines RPA with complementary technologies

First, let’s start with how UiPath’s 2020 vision aligns with Gartner’s Hyperautomation trend. Gartner identified hyperautomation as the #1 trend in its Gartner Top 10 Strategic Technology Trends for 2020 that drive disruption and opportunity for the next 5-10 years. Gartner didn’t just include it, Gartner called it the #1 trend. Hyperautomation combines several complementary technologies, including RPA, business process management (BPM), machine learning (ML), and artificial intelligence (AI). Successful intelligent automations “allow organizations to visualize how functions, processes and key performance indicators interact to drive value” (Gartner).


Business process understanding drives RPA success

Now, let’s examine the importance of understanding and improving business processes to the successful outcomes of RPA. ABBYY, a leading software company, published the study “State of Process Mining and Robotic Process Automation 2020” in March 2020. The survey included 400 senior executives from organizations in the US, UK, France and Germany representing 6 industry verticals.

ABBYY’s research shows that one of the major requirements for RPA is often not met. Specifically, 60% of organizations frequently do not follow their company’s business process. The “why” behind this finding informs us about some automation challenges. For example, deviations are made because of customer needs (51%), complex processes (37%), and process standards not well understood (27%).

What to do? Do we understand our business processes? Can we simplify, standardize and improve our business processes? Do we have clear business process documentation? Should we automate something that may be changing frequently, overly complex, and maybe not even well understood?


Leverage technology and data for business process understanding

The research further finds that we rely on humans (internal teams or external consultants) to review and assess business processes. Among organizations that review process efficiencies, those that do so frequently rely on internal teams (60%) and leverage technology (53%). However, when including organizations that do so frequently or sometimes, a significant third option is to hire consultants (72%). The use of internal teams and consultants implies there is a gap in scientific, data-driven approach to understanding business processes and identifying opportunities for improvement and automation. Tada! Process mining and business process understanding fills that gap and helps solve the business problem. The benefits of leveraging technology and data for business process understanding will be better RPA adoption and success.

“Companies realize they need better insight into business critical and customer facing processes. Those who are passive in understanding their processes risk operational inefficiencies and poor customer experiences” (ABBYY).


Understand and improve before automation

Not surprisingly, 65% of companies are using or in early stages of process mining. That’s the good news. At the same time, 64% of companies are using (33%) or intend to use (31%) RPA within the next 12 months. It should be noted that unless these companies embrace process mining to understand and improve their business processes BEFORE automation, there may be a high risk of sub-optimal outcomes (likely case) or even failure (worst case).

Various other Digital Transformation initiatives have a risk of failure that will waste resources, miss strategic objectives, and impact a company’s performance. In a post Covid-19 world, these risks and their potential impact may be magnified – there is less room for error.


UiPath enables process understanding and business outcomes

The single largest driver for successful RPA projects is strong understanding of the business processes being automated. Conversely, the key factors for failed RPA projects include project complexity (38%) and not fully understanding the intended automated processes (31%). The first and second factor are often related, as project complexity can be the result of wanting to automate processes that are too complex and/or not well defined and understood.

Business process understanding drives RPA success. For this reason, we emphasize the importance of one of UiPath’s key capabilities just released with its 2020.4 fast track release. You’ll thank us later!


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