10 August 2017

Top RPA Conversations So Far for 2017

10 August 2017

Top RPA Conversations So Far for 2017

Earlier this year, we made several interesting predictions as to what would dominate the conversation throughout 2017 in the automation landscape as part of a preview for the year in RPA. After consulting with industry thought-leaders, analysts, and RPA specialists, we zeroed-in on a handful of critical topics poised to drive important discussions about RPA trends and developments. As we pass the midpoint of the year, we thought it would be interesting to revisit our predictions and determine which conversations have not only been taking place, but have also proved to be critical talking points for those within the automation industry.

 

Why is this look back to the beginning of 2017 in terms of automation so important? A 2016 study from the industry research firm Gartner suggested the demand for RPA tools is growing quickly…”at about 20 percent to 30 percent each quarter.” This growth was projected to continue into 2017 and thus far industry analysts believe it has, at least through Q1 and Q2 of this year.

 

With these statistics and figures in mind, let’s take a moment to check the pulse of the automation industry thus far in 2017 by considering which predictions and projections have evolved to be critical conversations in RPA.

 

RPA deployment will increase across new industries

 

At the outset of 2017, RPA adoption patterns were poised to experience a significant shift as companies in new and emerging industries discovered the power of automation solutions to enhance their business operations. While the adoption of automation technologies has functioned in somewhat of an opportunistic manner by early adopter companies, wider adoption moments have come to the forefront in such industries as healthcare, insurance, banking, manufacturing, and retail. This also dovetails with industries that have already experienced the benefits of RPA increasing their deployments into the front-office and other customer-facing tasks, actions which have yet to be fully realized by many companies.

 

In a 2016 report that surveyed the adoption of eight new technologies — including robotics and automation — by the professional services firm Deloitte suggested that:

 

More companies are increasing investments in these technologies. New technology investments over $1 million have increased…[and some companies are planning to] spend at least $100 million on new technologies over the next two years.

 

Rather than just being a way for companies to streamline their business operations, RPA and other automation platforms are transitioning from a luxury to a necessity. This conversation has not only persisted as the year progressed, but the drumbeat for automation platforms as a key aspect of any given company’s operation strategy has only increased as global economies and industries become more and more connected.  

 

Automation will replace more tasks, not actual jobs

 

The emergence and proliferation of automation has caused a certain degree of panic over the possibility these technologies could replace the need for human employees in the workplace. Especially as automation moves from the back-office to more customer-facing tasks, customer relations-related areas such as call centers and other customer service platforms have suddenly become the subject of how and when automation could render these functions less necessary from a manual intervention standpoint. However, as we’ve moved through 2017, this concern has continually been minimized be the actuality of automation deployment.

 

Automation certainly has the ability to replace certain tasks or remove human personnel from specific department or business moments, especially those that are tedious, repetitive, and time-consuming: in fact, that’s what it is meant to do. However, this doesn’t mean the entire workforce will be replaced by robots. In fact, a 2017 publication by the McKinsey Global Institute suggests that:

 

The right level of detail at which to analyze the potential impact of automation is that of individual activities rather than entire occupations. Given currently demonstrated technologies, very few occupations—less than 5 percent—are candidates for full automation. However, almost every occupation has partial automation potential.

 

This kind of automation paints a hopeful picture for the future, one where humans and automation work side by side, which is the critical point of this conversation: debunking the myth RPA will essentially replace all methods of human intervention. In point of actual fact, RPA and human personnel will work in conjunction with each other which will allow human employees to focus on higher-level tasks that are meaningful and interesting, thus creating a space for automation to work through more repetitive, high volume tasks.

 

AI and machine learning will advance RPA

 

It has long been discussed how intelligent technologies like artificial intelligence, cognitive computing, and machine learning are expected to develop in the coming years and decades. In addition, a critical element of discussion within the automation landscape is how these technological developments will integrate and bolster automation functionality.

 

In a recent discussion with Forbes, Ash Ashutosh, the founder and CEO of Actifio, predicted that:

 

Just as most companies evolved to include cloud capabilities and features, 2017 will bring machine learning to almost every aspect of IT…[these technologies] will usher in a new era of data understanding and analysis.

 

While this is certainly a salient point, what’s less often considered is how RPA solutions will combine with intelligent technologies to deliver even greater automation potential. No longer can these technologies be viewed as disparate from each other when companies consider automation and how RPA can help enhance their business operations.

 

But what’s perhaps most important in this discussion is how intelligent technologies will be able to learn and make decisions beyond their initial programming. This means they are able to learn from previous actions and deal with unforeseen exceptions in a business process. Because RPA is able to quickly generate and gather data, combining RPA with intelligent technologies means that the “learning” process can take place at accelerated rates. While these two technologies are only starting to be used together, the smart automation they can produce means that companies will be able to foster both increased productivity and creativity going forward.

La conversation by Guillaume Andreux is licensed under CC BY-SA 2.0


by Nick Ostdick

TOPICS: Learning RPA, 2017, RPA conversations

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