INTERVIEW OF THE MONTH
Interview With Mr. Steve Halliday,
Steve Halliday Consulting Ltd.
1. What kind of disruption do you believe that RPA will bring about to the business models of enterprises?
Robotic Process Automation or RPA is expected to play an increasingly greater role in our business models cutting across enterprises of varied size and volume. The most critical aspect of the impact is expected to be seen on high-volume, repeat processes that follow a uniform line of execution and built-in exceptions. Some of the examples of such processes would be – invoice processing, service request processing, order processing and others.
2. Do you believe that RPA is likely to lead to a significant shift in the low cost delivery locations and the rise of some new locations?
If RPA is highly successful, the significance of location could slip into irrelevance. This would mean that the traditional low-cost, off-shore locations that exist across the globe, would lose their competitive advantage and become increasingly less attractive, as the advent of RPAs gathers steam.
3. What shift do you see in terms of people skills as a result of RPA? What kind of impact do you see on the job scenario front?
RPA maturity is currently in an early transitionary phase. It is most likely at the beginning of a phase wherein some of the tedious and routine tasks will largely be taken over by RPAs. There will be lesser human intervention and involvement in such tasks, although the requirement for humans continuing to deliver higher value, more complex and less predictable tasks will remain The set asks would be largely judgmental ones such as exceptions monitoring, new rule approvals and ensuring suitability of the input data for structured RPA processing.
Also, human beings would be required for more nuanced judgement and roles that require emotional intelligence, influencing, empathy and negotiation. The RPAs do not yet have the intelligence and certainly the business community does not yet have the confidence to transition these to the RPAs and therefore will be more valued. Full human repllcation remains, of course, in the realms of science fiction, but there is much that RPAs can do at the transactional level.
Roles that deal with sales (and procurement) negotiations will continue to be in the domain of human beings because of the need for human-human relationship that is crucial to sales and is distinct from order processing, for instance.
Similarly, in law, the process wherein a judge and jury understand a case, reach a verdict and pass a sentence would be a poor candidate for RPA – because wider life experience is necessary to do justice to them and such intelligence cannot be in an automated process yet.
In the local government context, many transactional customer engagement processes are being made “digital” already, with little human engagement right now. Paying parking fines is a good example. RPA may add value where further efficiency may be gained from automating slightly more complex service requests and processes, such as benefit claim processing.
But for the most complex processes in public service, RPA will not be the silver bullet. The decision to take someone’s child from them and place them in care is, one would hope, never going to be handed over to an algorithm. These are the sorts of decisions that consume much of local public services’ time and energy; perhaps they might even become more valued as the more robotic processes are delegated to robots.
It’s the “middle tier complexity” processes that are good candidates for RPA driven efficiencies. There is a compelling attractiveness for RPA to deliver cost reducing and customer satisfaction improvements with this tier of processes.
4. What are some of the new technology trends that you are seeing in this space?
The emergence and employment of artificial intelligence is an exciting new trend in this space. For instance, the Enfield Council just announced that it is planning to augment its customer service staff with a robots and, as an extension, RPA. The AI-powered, Amelia, employs cognitive computing and natural language analysis to understand the context of queries, applies logic to questions and over a period of time learns from ongoing experience to resolve customer problems. The robot can sense emotions and adjust its process accordingly, while offering resolution to its customers. This is a great example of AI and RPAs fusing together to build and deploy a more robust, cost efficient and customer-facing solution.