convergence ago is now a reality thanks to

convergence
of data, process and technology has unlocked a plethora of opportunities for
businesses to create value, save costs and produce real competitive advantages.
What seemed impossible ten years ago is now a reality thanks to data, most
recently termed the world’s most valuable resource, and rightly so. Data fueled
technologies such as Robotic Process Automation (RPA), Intelligent Automation,
Cognitive Automation, Artificial Intelligence (AI) and Machine Learning are the
latest buzzwords in the global marketplace. Many of these terms are used
interchangeably. Are they the same, but different?

 

Some
view RPA and AI as a continuum, a journey from one to the other. A contrasting
view projects RPA and AI to be two different technologies with different
purposes nudging organizations to make a choice between them. Nevertheless,
it’s clear that intelligent automation is here to stay. RPA is poised for
explosive growth given that every data reliant firm has a significant potential
for adopting automation. A recent report on disruptive technologies suggests
that automation technologies will have a potential economic impact of $ 6.7
trillion by 2025. This would evidently pave the way for large scale
implementations set to take place all over the world.

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Every
coin has two sides, and so does RPA. EY’s research indicates that while RPA can
transform the economics and service level of current manual operations, 30 to
50% of initial RPA projects fail. A pragmatic view of RPA implementations
suggests that RPA projects might not necessarily be delivering expected
benefits. RPA could expose the organization to unforeseen risks that are given
little thought at the time of implementation. For instance, a multi-billion
dollar American airline suffered losses of more than $150 Million when systems
suffered from misconfigurations. Misconfigurations were pushed out quickly
through automated systems, bringing the systems down and delaying flights
impacting customer goodwill on a massive scale. This is a clear cut example of
how customer experience can be impacted when automation goes wrong. Further, in
the arena of customer service, unmanned bots are not always adept at handling
intricate customer interactions, leading to poor consumer experiences.

 

Cyber
risks arising from interconnected automation technologies are a reality that
ought to be dealt with head-on, especially in manufacturing and engineering
industries. Often, multiple vendors are needed to create an automated warehouse
or controlled distribution centres, each vendor bringing with it the risk of
access to information. This exposes the organization to new avenues of system
breaches since RPA requires access to company databases, effectively leaving
data open to vendors. Ransomware attacks on industrial automation systems are
increasingly becoming a menace leading to loss of control over these systems. For
example, a municipal transportation agency
in the United States was infected with ransomware resulting in its
turnstiles being blocked. The attackers demanded a ransom of almost $100,000 to
unlock the infected systems.

 

Due attention should also be paid to
regulatory and compliance related risks. RPA solutions could be bought from
country A, the process might be based in country B and the customer serviced
could be based in country C. Complexity of combinations make it even more
imperative that implementations take into account applicable legislation and
ensure compliance. Determining who is liable for what in case the
implementation fails, is of paramount importance.

What can companies do to ensure the sustained
success of RPA programs? A three point framework could potentially steer
organizations in the right direction. Firstly, incorporate the right kind of
governance mechanisms to ensure smooth change management, vendor management and
benefit tracking. Secondly, it is crucial that the algorithms built at the very
outset are well designed and trustworthy. Errors in this could potentially be
the root-cause for multiple issues causing a down-stream domino effect. Lastly,
a continuous testing and monitoring process can ensure that the RPA environment
is audited remotely in real time.

Professor Shoshana Zuboff of Harvard Business
School asserts, “Everything that can be automated will be automated”. Successfully
maneuvering the maze of intelligent automation will depend on the ability of
organizations to govern, operate, monitor and improve upon the technology. A
pro-active approach to intelligent automation will take companies a long way in
minimizing the risks that come with both, large and small scale
implementations.