A struggle to manually process a large volume of inbound cases per day was leading to long lead times, backlogs, and customer dissatisfaction with a public organisation dealing with complaints. The organisation partnered with Baringa to help find a resolution through purpose-led investment in AI. There were four key steps we followed:

1. Build a purpose-led case for change 

Ensure that the deployment of AI is purpose-led and supportive of organisational aims rather than purely opportunistic. 

The Baringa team started by performing a top-down scan of the operation, identifying which tasks were taking most time. They discovered that the team spent 31% of their capacity on reviewing and extracting information from case files. This presented an opportunity to provide staff back with significant capacity. Baringa worked with the organisation to structure the problem statement to clearly articulate the operational impact to the customer and to staff, demonstrating the business case for change. With large incoming volumes of unstructured data requiring manual processing, the opportunity to use AI to support the operations team became clear. A clear purpose enabled the rest of the project to mobilise effectively and provided productivity metrics to monitor success. 

2. Deliver value quickly and build confidence in the technology

Too often promising proof-of-concepts fail to deliver at scale in production. Placing operational value is at the heart of the design, working hand-in-hand with end users, helps not just ensure the benefits will be realised in production but also helps with the change journey, driving improved adoption. 

Baringa built and deployed an AI-powered case categorisation and validation solution, using automation and machine learning to take the unstructured data inputs (such as documents in varying formats) and auto-categorise them without the need for a human being. The solution provides an audit trail about how it made its decision, the sources it used, and the confidence level on the decision, providing full transparency to users on the ground. 

Enablers to delivering value quickly included a collaborative process between Customer Service and IT teams from design to go-live, an empowered product owner who was Head of Operations for the area. Given the speed of technology change, the solution was intentionally built according to Agile principles, to allow future iterations to be added over time as required. 

The solution now handles over 50% of all inbound cases (over 10,000 monthly), saving hundreds of hours of manual effort per week for their customer service teams. This capacity can be reinvested back into the operation, boosting productivity. 

3. Partner with operational teams from Day 1 to ensure sustainable, future-proofed delivery

Co-designing AI solutions with Operations from Day 1 helps to anticipate potential challenges and creates opportunity to increase benefits by re-designing elements of process as well as ways of working in parallel. 

Introducing an AI solution changes the nature of the role of the operations staff in multiple ways. The staff no longer need to spend hours manually sifting through documents, and instead they can spend more time serving customers and handling more complex cases. Staff were trained on how to interpret AI results and how to manage exceptions, and their role became more focused on the more complex cases that required human judgement. The long-lasting impact is an operations team that have more satisfying tasks, reduced frustration, and a culture change in which technology plays a larger role in the workplace.  

4. Build an AI strategy and roadmap for operations

Practical experience from the initial AI deployments can help inform a clearer roadmap to expand the capability and the benefits can help to justify investment in the required capabilities to build at scale. 

Once the first use case was demonstrated, Baringa worked with the organisation leadership right up to board level, laying out the potential of AI and supporting the development of their 3-year digital transformation journey placing AI at the centre. The team built helped to stand up their internal Automation & AI capability across business analysis, development, testing, deployment, data protection and AI governance, providing the capability foundation to continue identifying and deploying new use cases for this technology. 

One example of a future roadmap item is using Generative AI to streamline case decision-making, by readily providing key case information and evidence summaries to the decision maker so cases can be resolved significantly more quickly. 

Improved productivity whilst upskilling people 

The case study of this organisation is commonplace around government and showcases the immense potential for productivity improvements if all departments were aware of the power of automation, AI and digital investment to complement their operations. AI can support operational processes whilst still keeping the ‘human in the loop’, enabling departments to gain significant productivity enhancements whilst upskilling their workforce, often providing a more fulfilling and customer-focused role as a result. 

Get in touch with one of our experts to improve your productivity through purpose-led digital investment. 

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