The context
The Finance function within a UK Defence Industry prime supports a complex and fast-moving portfolio of programmes. From monthly financial close to portfolio-level performance reviews, the team must provide accurate, timely insight while operating in an environment shaped by organisational change, legacy systems and increasing scrutiny.
By the time the modernisation programme began, Finance teams were dealing with growing volumes of data, evolving organisational structures and pressure to modernise reporting — all while maintaining business-as-usual delivery. The challenge wasn’t access to data, but turning it into something reliable, consistent and genuinely useful for decision-making.
The challenge
Over time, financial reporting had evolved in a reactive way. Processes were highly manual, Excel-heavy, and difficult to scale. Definitions varied between teams. Reports were time-consuming to produce and required significant effort to validate.
Key challenges included:
- Fragmented data sources and inconsistent data standards
- Highly manual month-end and reporting processes requiring extensive checking and reconciliation
- Limited ability to analyse trends or compare performance over time
- Significant effort spent reconciling numbers rather than challenging them
- Ongoing organisational change, adding further complexity
Finance reporting was well-controlled but heavily manual, with outputs typically shared in static formats, meaning significant time and effort was required to interpret, validate, and consolidate information at month end.
While modern analytics tools existed within the organisation, they were not yet embedded into day-to-day financial reporting. Insight was slow to generate and expensive in terms of time and effort.
The finance team initially asked for better dashboards. What they needed was a more efficient, repeatable way to process and present financial data to reduce manual overhead, while preserving the rigour and assurance required at month end.
The problem beneath the problem
The real constraint wasn’t the absence of a data model. It was how heavily manual the end-to-end process had become.
Data was already being mapped and reconciled, but this work relied on significant human effort at each step. As reporting needs evolved, maintaining consistency and timeliness became increasingly difficult, even with strong controls in place.
Rather than knowing what the numbers meant, the challenge was the amount of effort it took to produce, validate and reuse them.
Our approach
We worked as a fully embedded extension of the finance team, operating as one team rather than a traditional supplier.
Instead of locking requirements upfront, we took an iterative, collaborative approach. This allowed finance stakeholders to explore what was possible, refine their needs as insight improved, and arrive at better outcomes faster.
Our focus was on fundamentals:
- Strengthening data mappings and processing discipline to support consistent, repeatable reporting
- Automating data pipelines to reduce manual effort and risk
- Designing reporting around how the team operates, not just how data is stored
- Upskilling the finance team, enabling them to own and evolve the capability
This approach supported delivery across multiple finance reporting workstreams, including:
- Month-end file processing
- Work In Progress (WIP) and Debtors reporting
- Summary Status Report (SSR) portfolio reporting
- Financial Data Integration (FDI) for improved cost attribution
The outcome
The programme delivered more than improved reporting outputs. It reshaped how finance teams access, review and use data across the organisation.
Over 500 hours saved per year (equivalent to more than 60 working days) through reduced manual processing and more efficient month-end and reporting activity.
The team now has a clear understanding of the value of robust data pipelines and governed dashboards. The tooling is transparent, repeatable and easier to extend, providing a practical foundation for future improvement and reducing reliance on manual spreadsheet processes.
We ended up with a very different set of requirements by the end of the project compared to the start. Ultimately, the output we ended up with is much better than the original idea we had.
Looking ahead
The capability remains embedded within the organisations finance operations. Its success has sparked interest in wider replication and continues to provide a strong foundation for future digital and data-led improvement.
This work is a clear example of how Techmodal helps large, complex organisations move from data overload to decision advantage — by building capability that lasts.
Turn finance data into trusted insight.
We design robust data pipelines, automate reporting processes and embed governed dashboards that give finance teams clarity, control and confidence.
If improving financial visibility and reducing reporting overhead matters to your organisation — we can help.
