The challenge
Manchester City Council’s Revenues & Benefits service receives more than 3,000 emails each month from residents, businesses, landlords, agents and other stakeholders. These cover a wide range of topics, including account queries, requests for information, changes in circumstances and general service enquiries.
As emails are often unstructured, every message had to be manually reviewed to determine the appropriate action, before being indexed and uploaded to the council’s document management system (DMS) for processing. This took up valuable officer time and created a significant administrative burden.
Email remains an important customer contact channel – it can’t simply be switched off. While the council had encouraged customers to use online forms, many enquiries still arrived via email. Closing the inboxes would inhibit customer choice – impacting efficiency and increasing pressure on higher-cost channels, such as the contact centre.
Manchester City Council needed to manage growing email volumes without asking officers to spend their time manually reading, classifying and routing every message.
“Inbox Assistant has initially been implemented in just one inbox, but its success clearly demonstrates the wider potential. We’re now looking to expand this across additional high-volume Revenues and Benefits correspondence channels to drive greater efficiency and enhance service delivery.”
John Bailey
Business Analyst – Systems and Subsidy Team, Manchester City Council
The solution
Manchester City Council partnered with Govtech to implement Inbox Assistant, combining webCAPTURE digital process automation with Liberty IDP (intelligent document processing).
The council’s previous solution relied heavily on customers providing a valid account reference number (ARN). When information was missing or incorrect, emails required manual intervention, limiting automation and creating delays.
Manchester wanted an intelligent solution to understand the content of emails and attachments. It would identify the information required for processing and determine the appropriate next action – regardless of whether an ARN had been supplied. The objectives were to:
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Increase automatic indexing rates
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Reduce reliance on ARNs
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Identify customers using alternative information, such as addresses and personal details
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Analyse email content to determine the nature of the enquiry
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Automatically categorise correspondence into the correct document and work types
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Improve workload prioritisation
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Support greater end-to-end email automation across existing workflows.
Inbox Assistant reads and understands incoming correspondence, extracts relevant information and automatically guides each email towards the right outcome. A tenancy change can be processed automatically. A general enquiry can be categorised and routed to the right team. Emails requiring action can be prepared for intelligent document processing with less manual intervention.
“Inbox Assistant has transformed the way we manage incoming emails, significantly reducing admin effort and delivering measurable efficiencies. As a result, our teams focus on providing exceptional customer service and supporting higher-value customer activities.”
Samantha Sauco
Senior Systems & Subsidy Manager, Manchester City Council
The results
Immediate results
measurable from the first month of the deployment
3,218 Emails triaged
100% automated handling
62% Prioritised
1,997 emails automatically categorised and prioritised
1.3 FTE
equivalent saved from inbox administration and Revenues processing
20% Instant responses
653 emails were provided instant, automated responses
18% Fully automated
568 landlord tenancy change cases were automated end-to-end
Future potential
to automate more of the work traditionally associated with incoming email
Business impact
By understanding enquiry content rather than relying solely on reference numbers, Inbox Assistant delivers higher levels of email automation, reduces manual intervention, and saves the equivalent of 1.3 FTE in inbox administration and Revenues processing.
Automated email and document processing significantly reduces manual administration, allowing officers to focus on supporting customers rather than co-ordinating correspondence.
AI analyses email content and sentiment to improve routing decisions and workload management. This enables teams to identify and fast-track urgent enquiries for a quicker, more consistent response.
Irrelevant enquiries or those with missing information are automatically identified and responded to, preventing avoidable workloads.
Residents can continue using email as a contact channel without increasing pressure on contact centre resources.
Supporting Manchester’s intelligent document processing
The initial deployment focused on a single high-volume Revenues & Benefits inbox, but the results point to great potential for expansion. This shows what is possible when AI is applied to a practical, high-volume service challenge – releasing people from repetitive work that gets in their way of more important work.