Ember Analytics

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Streamlined Operations Proves Valuable for Merton Council Customers

Driven by a need to make significant savings, the London Borough of Merton was looking at new ways to reduce cost without compromising services to residents. One area of attention was its council tax service. With plans in place to introduce a customer relationship management (CRM) system for the Borough’s 200,000 residents, Merton Council wanted to examine how workflow and processes could be developed more efficiently ahead of its deployment.

The Council wanted a clear understanding of the reasons why residents contacted it about council tax and how effective its 40-seat contact centre was in dealing with those enquiries. With an IVR already in place, and a dedicated team to handle Council Tax enquiries, it wanted to examine the productivity of each component of the contact centre. To help provide the necessary insight Merton Council invited Ember Services, to analyse its contact centre operations.

Using Speech Analytics to Spot Patterns

Ember began by visiting the Council Tax Team in order to make its own observations about how calls were being handled, to talk to agents and gain a precise understanding of the processes, policies and systems that supported how the calls were dealt with. Ember applied speech analytics to 1,383 calls made to Merton’s Council Tax Team in 2012. It started with a sample of 2,451, approximately one week’s worth of calls. Shorter calls were examined to check if there were technical issues, before being stripped out.

“Avaya’s ability to place speech analytics into context and identify key words and phrases helps us to interpret the findings intelligently and turn them into robust, actionable recommendations.”

David Naylor, Head of Analytics, Ember

Ember Analytics

“Avaya’s Speech Analytics enabled us to replace guesswork with certainty,” Naylor recalls. “Coupled with our understanding of a client’s business and our experience as customer operations practitioners and consultants, we can turn that information into action.”

The difference, says Naylor, with Avaya Speech Analytics is its search capabilities. It uses a phonetics-based rather than transcript-based approach. “We’re looking for phrases in context, not simply words. For us, Avaya is the best technology out there. It’s faster and more effective.”

Evidence for Change

“We were looking for the answers to three key questions,” says David Keppler, Head of Revenue & Benefits, Merton Council. “Why do residents call, how well do our people respond and what action can we take to either remove the need for the call or decrease the time they need to spend talking to us – making life easier for them and saving time and effort for us; which ultimately helps us to also reduce costs.”

Ember’s first level of analysis gave Merton Council clarity about why residents were calling. More meaningfully, it measured the amount of time and effort taken to resolve each query type – the ‘workload’. For the first time, the Council was able to replace guesswork with certainty and understand exactly the type of queries that were both most common and absorbed the most resource and effort. In simple terms it showed 57 per cent of calls needed further action, and transfers occurred in 28 per cent of calls.

“This allowed us to clearly see where we should be focusing our effort,” says Keppler. For example, it was clear that although calls about moving house and changes to benefits didn’t account for the largest percentage of calls, they contributed disproportionately to the team’s workload.

“We subjected these call types to a detailed review to see what could be done both to simplify the process and, where possible, to encourage residents to resolve their query online.”

David Keppler, Head of Revenue & Benefits, Merton Council

Ember Analytics

Actionable Insights

This first sweep generated 20-plus actions, overseen by Merton Council’s process improvements manager. As a result, online and call processes are being improved and agents are actively educating callers on how to use the Council’s self-service options.

This is making an immediate contribution to the Councils efforts to improve efficiency and reduce the need for residents to call the Council Tax Team.

“Ember, utilizing Avaya technology, allowed us to see that, in fact, we were contributing to the volume of calls received.”

David Keppler, Head of Revenue & Benefits, Merton Council

“Around 30 per cent of calls were driven by our actions – either because we failed to resolve the query first time, or because we sent them a communication that was unclear, didn’t meet their needs or – at the very least – drove them to call us with a question,” Keppler recalls.

The Council is now taking action to improve the processes that give rise to these calls and plans to use its new CRM system to automate inter-department workflow and ensure better communication. “Our aim is to resolve residents’ enquiries at first contact. We want to send out clear, correct, helpful information every time so that residents don’t need to call us in the first place,” affirms Keppler.

Ember was also able to show Merton Council which types of call generated the best and worst first call resolution rates and to pinpoint the causes. “Ember showed us that, on a particular call type, staff frequently told residents to call back and check that their request had been completed,” says Keppler. “It turned out that this was because they simply didn’t trust the system that supported the process and so were ‘going the extra mile’ to ensure a positive outcome for residents.”

“We are now able to focus on the root cause, improve systems and give our staff the confidence they need.”

David Keppler, Head of Revenue & Benefits, Merton Council

Calls to pay council tax obviously represent both a high volume of calls to the Council and create a considerable workload. Ember was able to identify inconsistencies in call handling that were compromising the caller experience and causing extra work for the team. Whilst some staff were taking and processing payments, others were passing callers to another finance team and were not encouraging callers to use the Council’s automated payment line. As a result, staff have benefited from additional training to help them manage calls more efficiently and, where possible, to encourage use of self service. First time resolution rates are improving and more detailed work is now planned to measure the degree of shift to self-service and its impact on operating cost. The evidence from the speech analytics has shown that a target of eliminating 21 per cent of contacts identified ‘unnecessary or preventable’ is realistic, along with moving 12 per cent of voice contacts to lower-cost self-service channels.

Prioritising Action

Using Avaya Speech Analytics Ember’s Managed Analytics service provided a wealth of feedback and insight; its ‘Value-Irritant Model’ has helped the Council to plan its process improvement activity.

“Very simply, call types can be allocated to four different groups based on the value they add or the irritant they cause to the resident and to the Council. For example, a call to discuss the inability to pay a bill is valuable to both parties, but a call about a billing error is an irritant for both and action needs to be taken to eliminate those calls by preventing billing errors. A call to report a change of address is valuable for the Council, but a pain for the resident, so needs to be simplified as far as possible,” explains Naylor. Ember was able to categorise Merton Council’s call types into four groups and, on that basis, advise the best improvement approach to take.

Ember Analytics
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  • United Kingdom

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  • 50

Ember was founded on the principle that the best business decisions are based on hard data. So, in every consulting project they will identify not only how to make your business better, but how much you stand to gain by doing so. They are unashamedly financially focused in their support of customer strategy and operational delivery.

What our Customers are saying
“Avaya’s ability to place speech analytics into context and identify key words and phrases helps us to interpret the findings intelligently and turn them into robust, actionable recommendations.”

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