In a recent report entitled “Disruptive technologies: Advances that will transform life, business, and the global economy” by the management consulting firm McKinsey & Company, analysts predict automation technologies will have an economic impact of between $5.2 and $6.7 trillion by 2025. Some of the technologies accompanying this trend include machine learning and big-data technologies. And the connection between these platforms and automation is robotic process automation (RPA) which draws from each of these systems to position itself as one of the leading automation technologies.
RPA’s already progressive developments beg one of the biggest questions in the field of automation: What can be expected of upcoming developments in RPA technologies? What are the future prospects of RPA? How will companies deploy RPA in the coming years and what will this mean for the future of a variety of industries? With all this in mind, let’s explore what the future of RPA looks like as a result of the emergence and growth of Internet of Things (IoT), improved cloud services, and enhanced machine learning.
The IoT consists of various devices — smartphones, TVs, cars, wearable devices, industrial equipment — with internet connectivity and capacity for communication between people and systems. As part of the IoT, internet-connected devices allow for increased generation of unstructured data, also called Big Data. The IT research and advisory company Gartner predicts by the end of 2017 there will be 8.4 billion internet-connected devices in use worldwide by businesses and their consumers. These numbers are only expected to increase in the future, with 20.4 billion devices predicted by 2020.
With the assistance of RPA, the IoT and the 24/7 connectivity of devices has transformed a number of industries in streamlining business processes and optimizing operational efficiency. More specifically, RPA can contribute to the analysis of Big Data and uncover valuable business insights. For example, RPA’s software robots record their own actions in automating data entry, claims processing, or optimizing production lines as well as the time it takes to complete such tasks. RPA is also able to monitor the online activities of consumers, taking note of how they use their electronic devices or interact with other users on social media.
Most importantly, though, is RPA has the potential to analyze these data sets. Examining this Big Data more closely, RPA can expose business patterns that were not previously evident. The tool may indicate where there are inefficiencies and bottlenecks in operational processes, helping to inform a company’s operational planning as well as financial budgeting. With the significant growth that is expected of the IoT in the future, RPA’s abilities to drive improved data management, streamlined internal workings, and positive business operations will only be heightened.
As we’ve seen, RPA provides companies with a wealth of information as well as an overall increase in digital processes that generate data through internet-connected devices. Still, RPA platforms, particularly the software robots that calculate process steps, require computational power to analyze this data. Improvements to cloud technology are becoming increasingly valuable in this regard as more and more computational power is made available in decentralized facilities around the world. The cloud supplies on-demand access to unlimited, off-site storage for Big Data. It also provides the computational power to analyze data without organizations having to allocate their own local servers and powerful computers.
By drastically increasing their computing resources through the cloud, businesses are able to automate more and more complex processes. And what’s more, cloud-based technology is only expected to become global. The global media company Forbes, for example, suggests that the cloud computing market is projected to increase from $67 billion in 2015 to $162 billion in 2020 attaining a compound annual growth rate (CAGR) of 19 percent.
As a result of these forecasted developments, RPA technologies are positioned to become even more integrated with cloud services in the future. Many sectors — manufacturing, for example — rely on high systems availability made possible through cloud computing in order to maintain their automation processes. While the automation enabled by RPA can, of course, still be delivered as an onsite software package, moving business processes to remote servers as part of the cloud will allow many businesses to obtain greater operational productivity and efficiency than has ever been possible in the past.
RPA software robots are already able to automate simple, repetitive processes as well as a range of more complex tasks. In the future, RPA robots will be able to improve their own performance and make decisions through the incorporation of intelligent technologies like machine learning. Through machine learning algorithms, computer systems are able to improve their performance by incorporating Big Data and adapting to new rules based on previous experiences without human intervention. This means such technologies are able to make predictions based on detected data patterns, deal with unforeseen errors and exceptions in business processes, and take actions based on scenarios never before seen.
A 2016 report by McKinsey suggests machine learning’s greatest potential includes improving forecasting, predictive analytics, and real-time optimization of business operations. Accompanying this growth of machine learning technologies, industry analysts also suggest the combination of RPA solutions with even more intelligent technologies has great potential for widespread adoption across all industries. With the addition of RPA to provide process automation support, the journey of machine learning and the development of even more intelligent technology will only be rapidly accelerated.
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 enhanced automation they can produce means that companies will be able to foster both increased productivity and creativity going forward. Businesses will become more agile and responsive in processing business transactions, a crucial component of staying ahead in today’s increasingly competitive and global marketplaces.
RPA technologies have significantly developed since the days of basic screen scraping and simple workflow management tools first emerged in the 1990s. Today, RPA has transformed how companies across the globe approach their business activities, especially in terms of enhancing and streamlining operations. We cannot know exactly how automation technologies will unfold in upcoming years, yet we have good indication that the future of RPA is very promising. As the prevalence of RPA increases and automation experiences a larger degree of deployment in more varied industries, the full benefits of automation technology will not only be realized, but they will also be leveraged as a critical competitive advantage in a number of crowded, expanding industries.