What does connected RPA look like?
Robotic process automation, a software category that Blue Prism pioneered and created, has been driving seismic change across the international workplace and is widely believed to be a key catalyst for the fourth Industrial Revolution. This category is now entering its next evolutionary phase, connected RPA, which promises an exciting era of collaborative technology innovation, led by digitally savvy business users — the makers — and enabled by ever greater intelligent business automation.
With connected RPA, organizations will increasingly unleash the combined creativity of the makers, the people that really understand their business, by giving them the ability to access and exploit leading-edge cloud, AI, cognitive and other capabilities — so they can invent, innovate and swiftly develop new, disruptive offerings.
Why is connected RPA required?
Today, IT departments often spend most of their budget on maintaining and updating processes and systems, rather than focusing on new initiatives — creating a digital entrepreneur gap. This gap leaves organizations vulnerable to more agile competitors who can innovate faster.
Connected RPA closes this gap by giving organizations a compelling way of staying competitive by leapfrogging generations of technology advancements, eliminating multiyear waits on the IT work queue and bypassing the challenges of enterprise-wide, IT-led implementation. With connected RPA, business users are equipped with an easy drag-and-drop route to orchestrate any past, present or new technology, with links also provided to a widening community of collaborators. This unique, business-led capability will enable the creation of more innovative new services and products — at pace — to keep up with ever changing market demands.
The evolution of connected RPA
To understand why connected RPA can be achieved, it’s important to understand why RPA was created. The origins of RPA date back to 2001 when we started solving the “human middleware” issue in banking environments, where human workers act as human-robots performing repetitive tasks, to bridge system processes that aren’t integrated or that have no system-based interoperability.
The breakthrough came with the invention of RPA software that carries out tasks in the same way humans do — via an easy-to-control, automated digital worker, or advanced software robot. Digital workers work by mimicking the way human workers operate, accessing and reading the user interface to interoperate and orchestrate any third-party application and repurposing the human interface as a machine-usable API.
Digital workers have evolved to not only “read” applications like a human, but to also conduct work like a human. They are interconnected, communicate with one another to collaborate, share workloads and operate as a digital team. Digital workers make adjustments according to obstacles — different screens, layouts or fonts, application versions, system settings, permissions and even language — and with connected RPA, they’ll become even smarter.
It’s the unique, universal enterprise connectivity capabilities of digital workers, coupled with the increasingly intelligent way that they operate, that’s now being harnessed by business users to integrate with and orchestrate any new or existing technology application. Business users simply create automated processes by drawing and designing process flowcharts, which are intuitive for business users and are used by the digital worker to automate a task.
With both human and digital workers working in tandem — and seamlessly interacting with existing and new applications — a powerful, intelligent, collaborative, digital ecosystem is created, which is the essence of connected RPA. This is also set to provide the foundation for ongoing digital transformation — and leading industry academics expect connected RPA to emerge as the execution platform of choice for swiftly utilizing best-of-breed AI and cognitive technologies across the digital enterprise.
What to expect from connected RPA
The following 10 use cases are typical examples of what can be achieved with connected RPA:
- Collaborating with artificial intelligence and machine learning tools for multilingual, automated email processing for inbound customer inquiries and email triage.
- Anti-money laundering prevention in conjunction with blockchain technologies and business process management tools.
- Automated case handling and resolution for insurance claims.
- Automating the extraction of unstructured data.
- Using AI tools to gauge sentiment analysis, intensity and mood for customer support, and then automatically elevating requests to a customer representative.
- Working in conjunction with process mining tools to automatically extract historical records, data research and business intelligence analytics.
- Dynamically and automatically verify legal compliance on complex contracts.
- Collaborating with OCR and computer vision technologies to automatically verify identity for loan processing or transform secured faxes into searchable, text-embedded formats.
- Automatic, real-time translation in virtual meetings.
- Automatically connecting chatbots and humans for financial transactions, human resources or customer service requests.
Keeping connected RPA sustainable
What’s important to understand is that although connected RPA is business-led so the makers can keep pace with market demands, it still operates in an IT-endorsed and controlled environment too. This is because for connected RPA to maintain long-term success, it must successfully operate and scale in large, enterprise-wide deployments where security, resilience and governance are equally, if not more important than speed, automation and simplicity.
Digital workers are therefore designed to be scalable, robust, secure, controllable and intelligent, so they’re trusted to operate within the most demanding enterprise environments, such as banking, finance and healthcare. Business users train digital workers without coding, so the system infrastructure remains intact. If code is used to build automations outside the technology department, “grey IT” is introduced, along with unaudited process models that represent backdoors, security flaws and audit failures.
For connected RPA to deliver value, longevity and resilience at scale, automations should also be carefully planned, modelled and designed, so all automated processes achieve design standards, and are completely transparent and centrally pooled to offer the potential for reuse. This collaborative facet is also an important part of connected RPA, as it introduces the widest pool of nontechnical business users who contribute their automations so they can be managed and reused by the whole business — turbo-charging productivity gains.
It’s also important to protect the business from rogue employees, rogue robots and grey IT so the process models run by a digital worker are made explicit in a process flow chart for each process automated. The process flow chart is subject to audit and change control and security with dual key authentication.
A vision for moving forward
Connected RPA will continue to evolve this year and widen the number of collaborators within an ecosystem to include developers, academics and contributors — creating a growing community and brains trust that can share best practices and help achieve optimum business value. This community will increasingly generate ever easier access to emerging tech via connected RPA’ s integration capabilities, so those participating create new offerings faster and ensure that their organizations stay ahead of the competition.
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