Robotic Process Automation, commonly known as RPA, is pretty hot at the moment. In spite of the attention, RPA is a bit of a misnomer. First, RPA does not involve any robots in the traditional sense. Next, RPA software does not automate large processes. Instead, it automates small, repetitive, rules-based tasks. So in its current form – it would be more accurate to call it robotic task automation. Nevertheless, there’s increasing excitement around RPA as it involves software robots or ‘bots’ to rapidly deliver value. Why? Well, everyone loves ‘bots’ – don’t they?
Some of the excitement around RPA is just plain hype, while a bit of it has some substance. Forrester forecasted that the size of the RPA market will reach $2.9 billion by 2021 – only to quickly point out that this number pales in comparison to the size of the total Artificial Intelligence (AI) spend estimated at $48.5 billion. Further, McKinsey estimated the return on investment (ROI) from RPA around 30% to 200% —in the first year.
There are indeed some very practical aspects of RPA that account for the current level of interest. It typically involves modest project scope, minimal systems integration, has a small IT department footprint and minimal database intrusion. That’s fairly compelling.
RPA has potential – but it does not fix bad processes. Before automating small parts of processes it makes sense to see the big picture. For optimal results leaders need to think about is how an organization’s end to end processes are performing – for both customers and the company – and where RPA may provide the greatest value. That’s how organizations can put process back into RPA.
By viewing the business from the outside-in and in a big picture process-based context, companies can integrate other digital tools such as process mining and artificial intelligence (AI) with RPA. Such integration can help avoid RPA project failures due to planning and implementation issues.
Finding the best opportunities to deploy RPA can be challenging. Relying on small brown paper mapping sessions or interviews to identify where to deploy RPA can be subjective. In contrast, using process mining to develop the end to end “as is” process tracks actual activity in a company’s IT systems. It is comparatively far more objective than analysis based on subjective opinions and an effective way of identifying opportunities to apply RPA.
A further benefit of integrating process mining and RPA is related to data. RPA project failure is often linked to data challenges. Either lack of data or changes in data. Insomuch as process mining examines event logs in a company’s information systems, some of these data challenges can be mitigated. Forward thinking organizations will use process mining to be data driven. In addition, integrating process mining with RPA goes beyond the ‘as is’ analysis as it also has the big advantage of repeating the analysis after improvements are made to see how effective these were.
The integration of RPA and AI holds equal or even greater promise. For example, voice assistants such as Google Assistant and Amazon Alexa are transforming customer relationships in a dramatic way, and businesses are looking for ways for this to be leveraged. The integration of RPA and AI provides the means for ‘bots’ to fetch and deliver the data to the conversational interface ‘Chabots.’ In this way, the RPA robot can query the system of record to retrieve relevant data items, package them and hand it back to the Chabot, enabling the Chabot to restructure these into a natural language response. Forrester has predicted that more than 40% of enterprises will create state-of-the-art digital workers by combining AI with RPA and by the end of 2019; automation will eliminate 20% of all service desk interactions, due to a successful combination of cognitive systems, RPA, and various chatbot technologies.
So what does this all mean? Think about it. Automating bad sub-processes doesn’t make much sense. Consider truly putting ‘process’ back into RPA. Do it by seeing how end to end processes are performing for customers. Integrate process mining and AI with RPA to get maximum benefit.
Originally published in Process Excellence Network.