utility week – complaint handling needs ai treatment
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14/09/2015 Utility Week – Complaint handling needs AI treatment
http://utilityweek.co.uk/news/complainthandlingneedsaitreatment/1169182#.Vfar8xFViko 1/3
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Complaint handling needs AI treatment14/09/2015 Share: 0Share Tweet 0 0 0Like
Artificial intelligence and cognitive learning technologies will shape the future of complaint handling saysAndrew Anderson, overcoming the problems existing systems have in interpreting unstructured data.
"As the cost of outsourcing the interpretation of unstructured data mounts in the utilities sector,the need to find better technology solutions becomes more pressing."
Customer service and complaint handling is a hot topicwith utility providers and consumers.
With Ofgem stating in its last formal report at the end of2014 that over half of those that complained to theirutility were not satisfied with the way in which they werehandled, it is more important than ever to explore theways in which failing systems can be improved to meetexpectations. The industry is ready for change. BritishGas has committed to invest £50 million in improving itscustomer services, and similar announcement will nodoubt follow across the sector.
Throwing money at the challenge of better complainthandling is not necessarily the answer however.
At the heart of the problem lies our innate humantendency to express dissatisfaction emotively. Whether over the phone or, increasingly, via email, wewant to use descriptive words to communicate our unique circumstances and how a particular issue hasmade us feel.
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14/09/2015 Utility Week – Complaint handling needs AI treatment
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These sorts of correspondences are often referred to as “unstructured” – as opposed to “structured”language, based on set fields or multiple choice options which are easily interpreted in the binarylanguage of computers.
It is the responsibility of companies to handle and respond to these “unstructured” correspondencescorrectly and in a timely manner, primarily to resolve the customer queries or complaints, but alsobecause doing so will bring reputational and bottomline value.
The trouble is that, to date, it has been difficult to find technologies which are effective in handlingunstructured data.
Established options, such as Customer Relationship Management (CRMs) systems and Robotic ProcessAutomation (RPA) systems, often fall short of the mark. The former, while useful for recording andstoring structured information across internal business operations, have little ability to understandunstructured data, and so cannot prompt or deliver actions which respond to these customercommunications. Furthermore, call centre information isn’t always readily accessible on central CRMsystems and therefore customers find themselves having to fill in the gaps in data when theycommunicate via different complaint channels.
RPA systems meanwhile, offer the opportunity to automate the handling of structured data betweensystems. It is sometimes possible to convert unstructured data into relevant structured formats, howeverdoing so requires time and cost intensive manual labour which is intrinsically prone to human error.
As the cost of outsourcing the interpretation of unstructured data mounts in the utilities sector, the needto find better technology solutions becomes more pressing.
Looking to other sectors, utilities could learn a lot from the way in which the retail, rail, logistics andfinancial services industries are experimenting with artificial intelligence and cognitive learningtechnologies in order to improve their complaint handling performance.
Automation and specifically cognitive learning technologies enable organisations to consume andunderstand what their customers are saying regardless of the fact that the content is unstructured andunpredictable. More importantly, the technology is able to learn, so the work force doesn’t need to scaleto cope with growth or even unexpected surges in demand. For example the cognitive learning technologyand automation would be useful when a company receives a surge of complaints due to a rail strike,delays or even a faulty product. The system implemented could upscale accordingly without the need torevert to the outsourcing of manual labour.
AI will enable organisation to understand large volumes of unstructured customer interactions in realtime, and to respond appropriately. A growing proportion of this correspondence will be dealt withwithout any human intervention, delivering swift, consistent, yet personal service at a lower operationalcost. Using AI will also increase the productivity and effectiveness on issues which do still require humanintervention is required.
With the plethora of solutions available it is not always easy to find the right solution for customer servicedata handling. But what is clear is that utilities companies need to respond much quicker and moreattentively to their customer needs and expectations.
Kneejerk reactions will not be sufficient and do not address the root cause of an epidemic of poorcustomer service within the industry.
Author: Andrew Anderson, CEO, Celaton, Channel: Operations & Assets
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