One of the UK’s leading direct insurers has built its business on friendly and helpful customer service. But with customer numbers soaring towards 3 million, the company’s Head of Operations was increasingly aware that its business processes were not as efficient as they could be. In particular, the insurer was overly reliant on manual intervention to complete many everyday tasks related to quotes, renewals, policy documentation and mid-term changes.
The obvious answer was to find opportunities for automation in its back-office processes, accelerating key steps and freeing up customer service staff. However, with a consistently high workload, the Head of Operations knew his team would struggle to find the time to analyse processes.
The Insight and Analytics team at Davies, who has extensive experience in this space, started work on getting the most out of the available technologies. This focused on the lexicon coding work to build the language packs and root cause analysis reporting structure.
The team developed a 3-tier analytics topics lexicon (including sentiment). Best practice suggests that between 15-20 level 2 topics is about right, as, with a manageable number of topics, you can understand the drivers of good and bad customer experience and drill deeper into the areas of concern. 88 topics were built at level 3 to help determine the root cause.
With the clock ticking, Davies quickly mobilised a small team to support the insurer’s need for speed. Before arriving on-site, Davies liaised with the client to set up meetings and arrange facilities for the project. This is of crucial importance, as fast-paced projects like these have a drum-beat that ensures the most efficient and effective way of operating and delivering.
Once present on-site, Davies organised a discovery workshop on Day 2 of the project to further its understanding of the insurer’s business, capture main pain points and identify the processes that would offer the best opportunities for automation. Although automation was the key focus of this assignment, Davies was also asked to highlight opportunities that they would come across for other forms of optimisation within the business. Then the Davies team undertook a deep dive into these processes, spending time with the insurer’s staff that works daily with the processes, to understand how they worked in detail. All relevant information was documented and specific opportunities for automation were identified.
Importantly too, Davies created an understanding around the volumes behind each process, essential to the next step of assessing the potential benefit of automation.
Davies’ analysts developed models calculating the savings that could be achieved from automating the different processes, as well as capturing the costs and complexity of introducing automation. The latter was checked with the insurer’s current RPA technology partner that they already had in place.
An important incremental benefit Davies was able to provide was their way of working, using Agile processes; daily plan-do-reviews; frequent communication to the various stakeholders who would be needed in the final play-back session. We appreciate that any change starts with effective communications and our client has adopted many of our work practices.
Just three weeks after the project began, Davies returned to the insurer to present back its findings. The opportunities for automation were prioritised based on a combination of quickest ROI and complexity to automate. Davies eventually provided a high-level business case for six automation opportunities which could deliver annual efficiencies worth £300,000, translating to approximately 20% FTE savings within the areas in scope.
Most of these related to streamlining processes around web forms, such as quotes or requests for policy documentation. By automating key steps in these processes, as well as saving money, service staff would be freed up to focus on more valuable tasks while improving customer experience at the same time, given the increased response time for these processes.
In addition to these immediate opportunities, Davies analysis also pinpointed ways to maximise the efficiency of existing bots and identified additional potential savings by enabling agent-assisted automation across other aspects of the operation. Although Davies did not fully business-case these opportunities, the potential saving was estimated at over £1 million a year – something the insurer is naturally keen to investigate further.
of potential savings with immediate opportunities
of potential FTE savings identified