Robotic Process Automation (RPA) is exceptionally enticing to businesses, promising compelling benefits such as lower costs, greater productivity and eliminating outdated and time-consuming processes. According to Global Analyst House Gartner, by 2020 the RPA market will top $1 billion in sales, with 40 per cent of large enterprises adopting an RPA software tool.
However, despite a multitude of RPA projects, successful implementation requires ownership within an organisation, and the issue at hand is who should take responsibility, business or IT? Although many RPA projects originate from business operations, collaboration between the two departments is key to ensuring profitable delivery.
IT’s invaluable knowledge is essential to successful RPA adoption. IT departments can help businesses implement initial RPA infrastructure and access rights, as well as future application rollouts. IT will also see the project from a different perspective and will build security, reliability and continuity into the process. In turn, this enables business leaders to drive productivity and achieve transformation benefits quickly.
IT can also assess whether there are already existing tools and solutions which can have a significant role in enabling RPA functionality. Technical expertise is critical to anticipate unforeseen issues caused by RPA and its involvement can make the difference between a successful implementation and a project that will likely be short lived.
RPA fails when it does not live up to an enterprise’s expectations, most notably in cutting costs. However, some businesses expectations are too high and many of the business cases are predicated on headcount savings alone. The value case for RPA is generally more nuanced than that. Most RPA bots are designed to automate tasks but do not address the need to optimise or redesign processes, and they cannot deliver meaningful digital transformation on their own.
Problems also arise when a business department mistakes tasks for processes and either vastly underestimates the complexity of the task they are trying to automate or the time it takes to integrate RPA. As a result, this can lead to delayed or abandoned projects.
To avoid project failure businesses must utilise IT knowledge and expertise in process analysis issues. Any IT department has a comprehensive outlook on issues such as compliance, business continuity, technological innovation and other large-scale projects. Within this strategic context, they can understand how RPA may fit into other areas of the business including big data operations, social media, mobile technology and cloud computing and importantly what process changes are required.
IT must be involved, or it is unlikely that RPA implementation will be warmly welcomed. IT operations are already coping with conflicting pressures coming from various directions and without IT’s inclusion RPA is seen as yet another ‘Shadow IT’ project. Most IT departments also have a strategic roadmap that includes an approved architecture and involves significant investment. RPA is rarely included as part of this roadmap as it is mistakenly seen as a business development tactic as opposed to something that meets wider strategic goals.
From the perspective of an IT department, RPA incorrectly represents just one tool in the toolkit. Business process redesign, traditional systems integration and use of Application Programming Interfaces (APIs) are perceived as more robust solutions compared to RPA. These attitudes need to be eliminated through education and collaboration to show IT teams the overall progress that successful RPA implementation can bring to a business.
Most successful RPA programs start in business operations and are advocated and led by a senior operational manager, and this reliable proof of concept goes a long way to influencing IT stakeholders. But the business advocate must be senior in the organisation and have the ability to exert their influence on other areas of the business.
Once the proof of concept is established and supported, IT needs to be invited to participate in the next phase. Within this context, IT can visualise the influential role of RPA as an innovative platform and the first step on a journey that leads to Artificial Intelligence (AI).
RPA and AI technology in their own right are both great tools to streamline business process automation, but together they are a force to be reckoned with. RPA is optimal for industries such as insurance and banking which involve a high number of repetitive tasks. It performs it’s intended functions efficiently and effectively, but it does not have any real intelligence other than the instructed rules.
But when AI is integrated with RPA it allows the automation process to begin much faster, creating an automation continuum. The end result is a completely autonomous process that delivers a more cognitive response, transmitting it directly to the RPA system that can then complete the task. This automation continuum results in even faster, more efficient outcomes and means a whole raft of additional processes and tasks beyond ‘raw; RPA can be concluded giving even greater savings or improvements.
This might seem like quite a leap from working out a proof of concept for an RPA project but it is more than feasible. An article in the Harvard Business Review, Building the AI-Powered Organization, says any organisation can achieve this fusing of RPA and AI, to become an AI-driven outfit, by adopting what it calls The Hub and Spoke model.
A roadmap to AI
The model states that any organisation that is moving along the AI pathway needs to divide key roles between a hub and spokes.A few tasks are always owned by the hub, and the spokes always own execution. Other work falls into a grey area which lies between the hub and spokes.
For instance, the hub consists of a C-level analytics executive who aligns strategy, while the spokes are owned by business units. The grey area could be owned by the hub or spokes but within this area IT plays a central role, tasked with project delivery, data strategy and IT infrastructure.
This model can be used when implementing RPA projects and then used to underpin further RPA initiatives. Once incorporated it provides an established way of operating for further RPA projects which in turn ensures business continuity for further automation. It undercuts an ad hoc approach and replaces it with a foundational template that all stakeholders can agree on. Once an organisation is ready, it delivers a proven way of working when building on RPA automation with AI. IT cannot help but agree and with this understanding will readily fully commit to RPA projects ensuring their success.