1. 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 treatment
14/09/2015 Share: 0Share Tweet 0 0 0Like
Artificial intelligence and cognitive learning technologies will shape the future of complaint handling says
Andrew 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 topic
with utility providers and consumers.
With Ofgem stating in its last formal report at the end of
2014 that over half of those that complained to their
utility were not satisfied with the way in which they were
handled, it is more important than ever to explore the
ways in which failing systems can be improved to meet
expectations. The industry is ready for change. British
Gas has committed to invest £50 million in improving its
customer services, and similar announcement will no
doubt follow across the sector.
Throwing money at the challenge of better complaint
handling is not necessarily the answer however.
At the heart of the problem lies our innate human
tendency to express dissatisfaction emotively. Whether over the phone or, increasingly, via email, we
want to use descriptive words to communicate our unique circumstances and how a particular issue has
made us feel.
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Complaint handling needs AI treatment
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2. 14/09/2015 Utility Week – Complaint handling needs AI treatment
http://utilityweek.co.uk/news/complaint­handling­needs­ai­treatment/1169182#.Vfar8xFViko 2/3
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 binary
language of computers.
It is the responsibility of companies to handle and respond to these “unstructured” correspondences
correctly and in a timely manner, primarily to resolve the customer queries or complaints, but also
because 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 handling
unstructured data.
Established options, such as Customer Relationship Management (CRMs) systems and Robotic Process
Automation (RPA) systems, often fall short of the mark. The former, while useful for recording and
storing structured information across internal business operations, have little ability to understand
unstructured data, and so cannot prompt or deliver actions which respond to these customer
communications. Furthermore, call centre information isn’t always readily accessible on central CRM
systems and therefore customers find themselves having to fill in the gaps in data when they
communicate via different complaint channels.
RPA systems meanwhile, offer the opportunity to automate the handling of structured data between
systems. It is sometimes possible to convert unstructured data into relevant structured formats, however
doing 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 need
to 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 and
financial services industries are experimenting with artificial intelligence and cognitive learning
technologies in order to improve their complaint handling performance.
Automation and specifically cognitive learning technologies enable organisations to consume and
understand what their customers are saying regardless of the fact that the content is unstructured and
unpredictable. More importantly, the technology is able to learn, so the work force doesn’t need to scale
to cope with growth or even unexpected surges in demand. For example the cognitive learning technology
and 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 to
revert to the outsourcing of manual labour.
AI will enable organisation to understand large volumes of unstructured customer interactions in real­
time, and to respond appropriately. A growing proportion of this correspondence will be dealt with
without any human intervention, delivering swift, consistent, yet personal service at a lower operational
cost. Using AI will also increase the productivity and effectiveness on issues which do still require human
intervention is required.
With the plethora of solutions available it is not always easy to find the right solution for customer service
data handling. But what is clear is that utilities companies need to respond much quicker and more
attentively to their customer needs and expectations.
Kneejerk reactions will not be sufficient and do not address the root cause of an epidemic of poor
customer service within the industry.
Author: Andrew Anderson, CEO, Celaton,
Channel: Operations & Assets
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3. 14/09/2015 Utility Week – Complaint handling needs AI treatment
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