This article will explore the notion of scaling and operating robotic process automation (RPA) using an integrated automation platform
How useful can this kind of platform be for companies?
The scaling of any technology is important when it comes to meeting increasing and changing demands. However, this can take up time, as well as being potentially costly for company budgets, making this endeavour risky if not thought out properly. However, could the use of an integrated automation platform for scaling RPA overcome these risks?
“This is already happening,” said Gopal Ramasubramanian, senior director, intelligent automation & technology at Cognizant. “For example, at Cognizant, we have started adding hyper-automation technologies to our existing automation offering. Companies such as Microsoft, Amazon, and Google are also investing heavily in building integrated hyper-automation platforms for scaling automation.
“Gartner has predicted hyper-automation will be one of the top technology trends for 2020, but RPA alone cannot automate end-to-end business processes as required. It is not simply a question of scaling RPA; there is in fact a need for multiple technologies to work together, including RPA along with optical character recognition (OCR), process mining, analytics, machine learning, chatbots, and business process management (BPM), amongst others.
RPA revenue to reach nearly $2 billion in 2021 — Gartner
“This in turn will drive the need for an integrated automation platform to bring these technologies together in one place.”
Handling unstructured data
One challenge that companies have encountered when it comes to leveraging RPA is handling unstructured data. However, Chris Porter, CEO of NexBotix, says that an integrated automation platform, alongside other technologies, can come to the rescue in this instance.
“Traditional RPA has a problem with scaling – there are lots of reasons for that, but one of the biggest problems is that RPA can only handle structured, rule-based digital processes,” explained Porter. “Most modern businesses are full of unstructured data and judgement-based work. Humans work in a certain way, which is why a lot of the business processes we see in enterprises are built the way they are – they are designed around the human and the gaps in IT systems that exist today.
“Many customers have already invested in traditional RPA and they are now hitting this wall of complexity around unstructured data. As a result, RPA is failing to deliver on its promised benefits, and vendors are looking to add capabilities to their platforms through acquisitions or partnerships.
“The alternative – and something that NexBotix focuses on – is an integrated RPA platform, where all of those capabilities are already built in. We don’t really talk about individual technologies – we look at solving an end-to-end business process.
“The focus is not just on RPA, but also machine learning, analytics and workflow that help our customers achieve value regardless of whether or not they have an existing RPA capability already. An integrated, but flexible, approach is the highest value for customers to unlock their end-to-end automation needs.”
Why problem solving using analytics needs new thinking
Sharing and reuse (Peter Walker)
The use of an integrated automation platform for RPA has also been found to be useful when it comes to the sharing and reuse of automation assets.
“Our intelligent automation technology is designed to scale activities and compound the resulting gains right across the business,” said Walker. “This is achieved by the unique collaborative capabilities of our platform that enables people to not only centrally design, draw and ‘publish’ processes that digital workers automate, but to share, improve and re-use these ‘published’ automated assets – anytime, anywhere – with zero coding required. Crucially, everything is done most securely, compliantly and transparently, as there’s a centralised irrefutable audit trail of all process automations, including all digital worker actions and training history too.
“A great example of intelligent automation sharing and reuse is in the NHS, where healthcare organisations sharing their tried and tested automations using a newly created private online marketplace, called the NHS Digital Exchange. This allows NHS teams to further accelerate the deployment of new automations that better support their work activities. These pre-built automation assets cover more than 40 processes enabling key support for recruitment, HR on-boarding, finance processing, and tackling enhanced access to services, patient communication from admissions and outpatient support.
How the NHS can best manage its data amidst coronavirus and beyond
“Ultimately, to really scale and sustain intelligent automation initiatives across the business, the complete journey must be defined upfront. Once senior support is gained and a vision of desired results created, starting small is recommended, then start delivering – while learning fast. Another common scaling challenge is identifying process automation opportunities – so be crystal clear about what makes a truly good process and always select ones that will generate the fastest benefits.”
Uses beyond the back office
“As organisations start to look at a more holistic hyperautomation approach, the convergence of technologies is important when enabling them to expand the scope of opportunities inside their company,” said Rayner. “No longer are customers just automating repetitive back office tasks, they now look to the following additional use cases:
• Creating efficiencies in the front-office through attended automation and agent-console.
• Interpreting unstructured and semi-structured data through document understanding, sentiment analysis and classification using machine learning.
• Enabling power users/citizen developers inside their organisation to leverage low code/drag and drop tools to automate simple and repetitive tasks. Reducing the investment and cost of ownership by the existing automation centre of excellence.
• Mining data inside their enterprise applications to identify inefficiencies in large processes, with an ‘automation first’ mindset.
Mining the metadata and more: Tips for good AI data storage practices
“At UiPath, we have aligned our product suite and roadmap enabling the full end-to-end journey in which we are able to manage the lifecycle of an automation from discovery through to measure. The integration of these technologies under one platform is critical to having full traceability.”
Initiating digital transformation (Sathya Srinivasan)
While there are plenty of ways in which this kind of product can be successful, a final point to consider when it comes to leveraging an integrated automation platform for RPA is to ensure that they are involved throughout the digital transformation process.
“Integrated automation platforms should span the breadth of a company’s digital transformation vision,” said Sathya Srinivasan, vice-president, solutions consulting (Partners) at Appian. “This makes it easier to see end-to-end activities and find opportunities for workflow automation as well as robotic automation.
“This visibility is essential for both the success and scaling of RPA. Having that bird’s eye view makes it easier to identify areas where robotic automation adds value, plugging in bots to assist in that digital leg of the overall journey.”