The productivity crisis hiding inside your data operation

Manual rekeying and spreadsheet-driven workflows don't just slow operations down. They block the digital transformation your firm needs to stay competitive. The answer isn't working harder. It's building the right foundation.

The hidden tax on your data team

Across the asset management industry, data teams are spending a disproportionate share of their time on work that adds no analytical value: rekeying information from one system into another, reformatting outputs for different channels, reconciling conflicting files before a deadline. According to FE fundinfo's whitepaper, A guide to modernising fund data infrastructure in 2026, manual rekeying and formatting can consume up to half of a data team's time. It is a figure that will resonate with anyone who has managed a fund data operation.

This is not a skills problem. These are talented people working hard inside a system that is structurally designed to produce inefficiency. The underlying cause is well established: according to the Quay Survey cited in the same report, Excel remains the primary data tool for 44% of firms. While familiar and flexible, spreadsheet-driven workflows lack auditability, do not scale and introduce errors that compound across every downstream process they feed.

Efficiency lost is competitive advantage surrendered

The operational cost of manual data management is real and measurable. Slowed product launches, delayed reporting cycles, reactive client communications: these are all symptoms of the same underlying problem. But the strategic cost is less visible and arguably more serious. Every hour spent reconciling spreadsheets is an hour not spent on the work that moves the business forward: sharper distribution analytics, faster product development, more responsive client service.

There is also a forward-looking dimension that cannot be ignored. AI, automation and advanced analytics all depend on reliable, well-structured data. Without investing in that foundation now, firms will struggle to realise the benefits of the next generation of digital tools, and competitors who have modernised will be able to deploy them at pace.

"The businesses that get the most from AI and automation are the ones invested in data quality. It's not the glamorous work, but a clean, governed and trusted data foundation is the difference between enabling technology to genuinely transform your operation and applying technology that simply replicates your existing problems at speed."

—Matt Winder, Market Specialist, Data Management, FE fundinfo

What reclaiming that time actually looks like

Product Mastering eliminates manual effort at its source. Data is captured once, validated automatically against client-specific business rules, and then flows to every downstream system and channel without manual intervention. There is no reformatting. There is no rekeying. There are no conflicting versions. The time previously consumed by these tasks is simply returned to the team.

The financial impact is substantial. A mid-sized asset manager can save several millions of pounds over five years by automating data activities, reducing external vendor reliance and eliminating spreadsheet-driven processes. These are outcomes already being realised by firms that have made this transition, not projections.

Modernisation does not have to be disruptive

The most effective modernisation programmes start with a clear view of the current data landscape: identifying where manual work is most concentrated and where the greatest risk sits. Implementation is then phased, beginning with the highest-priority data attributes and layering in validation, automation and distribution capabilities as confidence builds. The result is a foundation that is scalable, resilient and ready for whatever comes next.

Automated validation eliminates manual rekeying at source

Trusted data flows automatically to all downstream channels

Cloud-native, API-first platform scales as your business grows

Phased implementation delivers quick wins without operational disruption

Purpose-built for asset managers, not a generic data platform adapted for funds

Sources: Statistics in this article are drawn from A guide to modernising fund data infrastructure in 2026, published by FE fundinfo (2026). The 44% Excel figure references the Quay Survey as cited within the same report. fefundinfo.com

Give your data team their time back

See how Product Mastering automates the manual effort out of fund data management and what your team could achieve with the hours it frees up.

Book a demo