The Future of Workflow Automation — Good News for a Year That Could Really Use Some

The Future of Workflow Automation —
Good News for a Year That Could Really
Use Some

By Peter Schooff, Editor-in-Chief and Co-Founder of Data Decisioning

It’s no overstatement to say these past two years have presented significant challenges to every
aspect of our lives. And as another wave of Covid appears to be gathering on the horizon, those
challenges don’t seem to be going away anytime soon.
At the same time, artificial intelligence (AI), machine learning (ML), robotic process automation
(RPA), and other new technologies have been advancing at an ever-accelerating rate and
eliminating time-consuming manual processes. So, while much of our lives have been on hold
during the pandemic, robots have been making great leaps forward. You could say, in fact, that
things have been advancing so fast on so many fronts, we need some sort of automated
assistant to keep track of it all. You could even argue that we are past automation, and into the
stage of hyper automation.

Process Automation Trends To Watch In 2022

Advances in AI, ML, and RPA promise to make a massive impact on our lives, most significantly
on our work lives. One of the biggest areas that will be impacted is our daily workflow and the
way that we manage work at scale. Much of it will be impacted by automation. AI, ML, and RPA
(often in combination with each other) open up a whole new world of possibilities. Adding AI to
RPA makes it smarter and improves efficiency, productivity, and that’s to say nothing about
customer satisfaction (I’ll get to that shortly).

But let’s clear something up first. The title of this article mentions good news, and to be
perfectly honest, not everyone associates robots and automation technologies with good news.
Many fear that machines — either digitization via actual robots or a collection of code sitting in
some far-off data center — are coming for our jobs.
That is simply not true. As Didier Bonnet, one of the pioneers of digital transformation said in a
recent podcast I recorded with him: “Machines don’t replace jobs, they replace tasks.”
Business process automation tools are great at executing repeatable tasks that, because of
their utter tedium, have a high margin of error. You know, the jobs most people really don’t
enjoy doing, the very tasks that keep people from doing their best work. And let’s not forget,
with the proliferation of all these machines — someone is still going to have to manage these
robots.
But what if robots get more intelligent, as they undoubtedly will? The Bureau of Labor Statistics
forecasts faster-than-average job growth in many occupations that artificial intelligence is
expected to impact: accountants, forensic scientists, geological technicians, technical writers,
and MRI operators, and the healthcare industry at large just to name a few.

Let’s take a look at the latest and greatest technologies that will be impacting and automating
our workflow in the near future.

RPA

If you’ve been following new technology terms and have heard the term digital transformation
being tossed around lately, then most likely you have heard the term robotic process
automation or RPA. While not exactly a new term or technology, as outlined in the Gartner
Magic Quadrant for Robotic Process Automation, RPA remains the IT industry’s fastest-growing
enterprise service sector for the third straight year. As I already mentioned, RPA is all about
automating manual, repetitive tasks with tireless software bots. This promises to vastly
streamline productivity and send your customer satisfaction scores skyrocketing. In turn, this
frees up team members to focus on more creative, higher-order human-centric work that most
people find more rewarding.

Sounds like a win-win, right? Businesses certainly think so. According to a recent survey
conducted by the Enterprise Technology Research (ETR) of C-suite decision-makers, in the
future most organizations are planning to implement new RPA initiatives to automate IT,
Operations, Finance, and Customer Support.

The simple fact is, with the current labor shortages and the ever-increasing demands for
efficiency, RPA shows no signs of decelerating anytime soon.

AI/ML

While the terms AI and ML are often used interchangeably, most often when folks speak about
AI, they actually mean machine learning. The artificial intelligence of Hollywood movies, which
often boils down to a free-thinking, self-acting, often time-traveling robot (i.e., The Terminator),
and a personified internet of things (IoT), is actually known as artificial general intelligence
(AGI). And AGI is still years, most likely decades, away from an actuality.

But that doesn’t mean AI or ML hasn’t been making a big impact on today’s business needs.
With direct human oversight and the right data, AI has shown to have a significant impact on
the customer experience. Massive volumes of personal data are being generated by customers
on a day-to-day basis. The right algorithms analyze this data and generate richly detailed
customer engagements based on exactly what that customer needs. The battle over customers
is growing more fierce, and customers expect more from their business interactions, making
personalized, detailed interactions the standard in customer engagement.

The availability of mass data is also bringing sharper focus onto customer metrics. More
intelligent machines are allowing companies to understand exactly how their customers make
their buying decisions and at what point they can engage them in the consumer lifecycle.
Besides adding transparency to the buying process, this greatly increases sales forecasts while
increasing insights into new customer channels and product lines.

Also worth mentioning is the use of ML for intelligent document processing. While most
documents in a company are in some sort of digital format — either as a PDF, Word, or Excel
doc — that doesn’t mean the data locked in those documents is readily available. Even in large
companies, making that data accessible usually requires some form of human data entry (is
there anything more tedious than data entry?). But the advent of intelligent document
processing (IDP), which usually combines optical character recognition with AI, allows
companies to extract and process the relevant data from any number of documents in a wide
variety of formats.

Those are just a few examples of what’s ahead in the workflow automation market. But be
aware, automation does not come without risks. As none other than Bill Gates said,
“Automation applied to an inefficient operation will magnify the inefficiency.”

“Automation applied to an inefficient operation will magnify the inefficiency.”
—Bill Gates

Workflow Management At Scale

So how do you make certain all these software bots and automation solutions aren’t actually
making you more inefficient, costing you customers and money? There’s “automation”, and
then there’s “automation.” What do I mean by that? Well, RPA and AI allow for computer and
robotic activities to be pre-programmed and run on “automatic.” However, that doesn’t mean
that complex processes, sophisticated workflows, and human intervention are obsolete or
unnecessary. In fact, it’s never been more important for advanced digital transformation to
consider that other types of platforms need to be deployed alongside RPA and AI to allow for
complexity, adaptability, resiliency, and human decision-making along the way.

That’s where tools like HighGear come into play. This no-code end-to-end work management
platform enables users to automate tasks and processes and to incorporate rules-based
decisioning for even the most complex situations. It can be a conduit for bringing disparate RPA
and other advanced tools together through insights and integration. It provides that “check and
balance” oversight of systems that otherwise may go awry when independently placed on
“auto-pilot.”

“Machines don’t replace jobs, they replace tasks.” —Didier Bonnet

Incorporating user-configurable rules and workflow into human-robot workstreams assures
proper handling of exceptions and timely human escalations. Not only is HighGear extremely
cost-effective, but it is also particularly sophisticated when it comes to transparency of data and
activity. Lastly, audit capability and high-security enablement are critical to consider when
moving through a digital transformation journey.

Whether it’s HighGear or some other type of sophisticated workflow automation software
provider, be sure to develop a deep understanding of your needs and the outcomes you are
looking to drive. The good news is that the digital transformation future is bright and with the
maturing of the building blocks for effective digital transformation and automation strategies,
we finally have an opportunity to get this delicate orchestration right. And that’s very good
news indeed.

Peter is currently Editor-in-Chief and co-founder of Data Decisioning.
He has over 20 years of experience in various executive-level
enterprise IT fields. He first developed a deep interest in enterprise
technology as managing editor for ebizQ, where he created the
industry-leading ebizQ Forum.
Peter was the managing editor at BPM.com for over 5 years, where he
oversaw the BPM Forum as well as other content and media
initiatives. He was also the director of marketing for the email security company Message
Partners. Peter is known worldwide for his views and contributions to data, BPM, decision
management, and Cloud. He was named among the Top 12 Influencers of Case Management
through independent market research.

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