Manchester University NHS Foundation Trust — one of the UK's largest NHS trusts, managing a £2B+ annual budget across multiple hospital sites — transformed its financial planning function using Anaplan's connected planning platform. The result: monthly forecasting cycles cut from 3-4 days to approximately 1 day, and over 100 staff days saved every month.
Manchester's case study is particularly instructive for public sector finance teams who are often told that their governance and compliance requirements make modern planning platforms impractical. The NHS Trust's successful implementation — which had to meet NHSFT reporting standards, data security requirements, and multi-site governance rules — demonstrates that these constraints are challenges to be engineered around, not blockers.
The Healthcare Forecasting Challenge
NHS trusts face an unusually complex forecasting environment: budget pressures from central government, highly variable demand driven by seasonal illness patterns, rigid workforce cost structures, and increasing pressure to demonstrate value for public money. Manchester's finance team was spending the majority of its time maintaining spreadsheet models rather than analysing the financial picture they were struggling to produce.
- £2B+ annual budget across multiple hospital sites
- Monthly forecasting cycle: 3-4 days of intensive manual work
- Data sourced from 15+ separate systems with no automated integration
- Finance team capacity consumed by data gathering, leaving little time for analysis
The Anaplan Implementation
Manchester's implementation focused on the core financial forecasting and reporting processes first — building Anaplan models that automatically pulled data from their patient management and payroll systems, applied their forecasting logic, and produced consolidated trust-wide reports. The team deliberately started with a narrow scope to achieve rapid time-to-value, then expanded.
The 100+ Staff Days Figure: What It Means in Practice
100 staff days per month sounds abstract. In concrete terms, it means that the finance team has reclaimed the equivalent of 5 full-time employees' monthly working time from manual data processing. That capacity has been redeployed into variance analysis, departmental finance partnering, and strategic scenario modelling — activities that directly support better patient care decisions.
Lessons for Public Sector Finance Teams
Manchester's implementation offers several lessons specific to NHS and broader public sector finance contexts.
- Start with the highest-pain, most manual processes — build early credibility
- Public sector data governance requirements are achievable within modern planning platforms
- Stakeholder engagement is critical: department heads must trust the numbers or they won't use them
- ROI in public sector is measured in staff capacity and decision quality, not cost reduction
100 staff days per month sounds like an efficiency metric. In practice, it means we have the equivalent of five full-time staff doing variance analysis and strategic planning instead of spreadsheet maintenance. That's the real transformation.— Finance Director, Manchester University NHS Foundation Trust (Anaplan Case Study, Mar 2024)
Practical Implementation Checklist
- For public sector teams: start by documenting your data governance and compliance requirements before approaching vendors — this allows vendors to demonstrate specific compliance capabilities rather than making generic promises
- Begin with the highest-pain, most manual process in your finance function — for Manchester, this was the monthly forecasting consolidation; for your organisation, audit where finance time is most painfully consumed
- Secure departmental stakeholder buy-in before go-live, not after — in NHS and public sector environments, department heads who don't trust the numbers won't use them to make decisions, negating the ROI
- Measure ROI in capacity redeployment, not headcount: public sector organisations can't always reduce headcount, but they can and should redeploy capacity from data maintenance to analysis and patient care support
- Use the parallel run period to build trust: run old and new processes simultaneously for 2–3 full cycles and let department heads verify that the outputs match before decommissioning the old system
- Document the data lineage from source system to planning model for every data feed — this is particularly important in NHS environments where data auditability is a regulatory requirement
Manchester University NHS Trust's transformation demonstrates that 100+ staff days of monthly savings from planning automation is achievable even in the governance-intensive NHS environment. The key is starting narrow, proving value rigorously, and letting demonstrated results build the credibility needed to expand scope.
Key Takeaways
100+ staff days saved monthly by automating data gathering and consolidation
Forecasting cycle cut from 3–4 days to approximately 1 day
Public sector implementation is viable: data governance requirements are achievable
ROI is measured in redeployed capacity to analysis and business partnering, not headcount reduction
Start narrow: the highest-pain processes first, then expand scope
Document data lineage from source to model — essential for NHS and regulated-sector auditability requirements
Stakeholder trust must be built before decommissioning old processes — parallel run periods are the trust-building mechanism
