Intelligent Automation: Why does it Matter?

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intelligent automation

Hyped up in the headlines, robotics has driven both fear and anticipation through shared services organizations over the past two years. Why now is the moment to pay attention.

 

Why does intelligent automation matter?

That’s the question on everyone's lips at the moment. Robotic process automation, or RPA, has spread like a fever across business and support services over the past few years, driven by headlines promising an end to relying on human FTEs, 24/7 performance, and near zero defects. And while there is certainly a lot of truth to the promise of robotics, a lot of experts are warning: Not so fast.

For while the possibilities around robotic processing are, truly, significant, it's not quite as easy as just implementing a new technology solution. (Although, some would say, it’s even easier!)

But we are getting ahead of ourselves. The truth is that most organizations are currently finding themselves in an Uber moment of sorts, experiencing enormous disruptions in their industries. And while not every enterprise is under threat, the danger of standing still has never been greater.

The World Economic Forum predicts that 5.1 million jobs will be displaced across 15 major economies by 2020, as a result of automation – mostly low skilled offset by some increase in mid-level skilled. At the same time, scientific pioneers like Elon Musk, Bill Gates or Stephen Hawking are warning about the risks resulting from the rapid adoption of AI and its implications for humanity. Others like Tim Cook and Eric Schmidt downplay the risks.  The reality is likely somewhere in between.

One thing all experts agree on: Change is coming and will impact how business is conducted in ways we are not yet fully able to comprehend today.

In this new world, digital automation is key and the possibilities are endless. Consider, for example, the impact on compliance and corporate audits, where the effect of IA makes possible a sea-change in sample size: Corporate compliance departments, audit firms and others already are working to make sample sizes of 100% of transactions a reality. This changes the conversation from “a finding” to “acceptable risk” – a brand new conversation for corporate audit committees.

Forward-looking enterprises have read the writing on the wall and are now actively grasping "digital" and integrating it into every aspect of their business. The extension of this digital thinking: intelligent automation.

IA is the fastest-growing technology with the greatest power for disruption. On the one side it eliminates mundane and transactional activities; on the other hand, it has the potential to replace high level cognitive activities, stretching far beyond what humans are capable of today. And all that, reliably, quickly, and constantly.

Today's opportunities originate in Alan Turing’s research, as well as the shift from humans consuming data, to machines consuming data. What that immediately did was make operations smarter and autonomous. Opportunities now emerging build on the awareness of digital, the automation of robotics; and new age processing based on machine learning and augmented or cognitive intelligence.

This next generation of transformation will leverage analytics-based, intelligence-driven automation in order to better meet corporate objectives – which are still about providing excellent customer service/experience and delivering value to shareholders.

IA makes all this possible, by sustaining constant change to achieve enterprise goals.

Is it hype?

Where there are opportunities there is inevitably hype, much of it propagated by the sell side anxious to get ahead of its competition. From a shared services or business services perspective, IA is simply another tool that improves performance, but it does not stop at "performance". IA is not about cost so much as it is about quality. By leveraging enterprise data [and here is where many organizations will need to do a lot of prep work], robotic automation, machine learning, and, eventually a variety of cognitive or artificial intelligence driven capabilities, the differentiating point is that intelligent automation can drive a new organizational model that operates a step-change away from traditional models.

In the not too distant future we can assume that the same recommendation engines that guide our personal, online engagements, will guide corporate decision-making. The impact will be felt across the enterprise, but nowhere is the potential more promising than in support services, in other words HR, marketing, risk management, finance, regulatory processing, etc.

While many of the transactional activities have already been automated through various solutions including robotic automation [offshore operations still leveraging low-cost FTEs days are surely numbered, unless they change their model] the broader and evolving continuum of intelligent automation will drive smarter decision-making and processing across support services by accessing relevant data pools or lakes and "learning" how to make the most effective decisions based on a given status quo.

However, where IA is frequently misunderstood is that it is less of a tactic than a strategy. And with most practitioners jumping straight to the technology question, the need for strategic minded individuals to take the lead is being overlooked.

Where is the opportunity right now, in Intelligent Automation?

Intelligent automation reflects the enormous range of automated opportunities starting with scripting all the way through to artificial intelligence. But while the headlines and conversations are obsessed with artificial intelligence (AI), right now, the biggest wins are still to be gained from robotic desktop or robotic process automations.

In terms of deployment, there are two main approaches: 

Desktop-based IA solutions
  • Software is designed to help user interface on desktop, replaces the individual workstation, and is run on individual desktops.
  • Software can be run on a PC/desktop while also using the PC/desktop to perform other regular tasks simultaneously.
  • Software is often referred to as 'Attended RPA’ where it requires human interaction in order to initiate a task, as well continue the process.
  • Software is often used to automate multiple small micro-tasks within a larger end-to-end process.
Server-based IA solutions
  • Software is written and designed in a data center to execute the task autonomously without human interaction i.e. the software, the process, and the robot is run only on server.
  • Human interaction is not required, as this is 'Unattended RPA'.
  • Often there are trigger-based rules, which initiate the RPA.
  • When the software is being run on a desktop, it consumes the entire PC thus the PC cannot be used to perform other regular tasks simultaneously.
  • Software is often used to automate long end-to-end tasks entirely without human interaction.

Where will IA take us?

While robotic automation emerged as a stopgap to integrate new solutions with legacy systems, and while this opportunity remains, self learning and the ability to solve challenges that humans might not be able to are real game changers. And yet, there is a long way to go and plenty of data that needs to be trawled and learnings that need to be incorporated before any enterprise finds itself at that level. In the meantime, robotic desktop automation and robotic process automation, combined with early machine learning and cognitive capabilities, will provide enterprises that understand how, with near unimaginable opportunities in the future.

Already, operators like Procter & Gamble’s GBS are experimenting with "exponential technologies" through a Next Generation Services division to learn how digital disruption can be deployed to P&G’s advantage. And where the Shared Services model is concerned, P&G has always led.

It would behoove SSO executives worldwide to pay attention.

Find out more about IA via hand-picked case studies at the free online IA World Series.

 

Note: SSON Analytics’ Intelligent Automation Universe offers a comprehensive knowledge database of software vendors that provide technology within the Robotic Process Automation to Artificial Intelligence spectrum to business support services. It also showcases the types of organizations that have implemented this technology, including their locations, industries, company size, functions and processes automated. This tool is being continuously updated as more vendor and customer data is contributed.

 


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