Abstract

Improving the quality of official statistics starts with understanding the end-to-end processes underpinning their production. The Office for National Statistics (ONS) have recently launched a major programme to strengthen quality by holistically building up the production ecosystem. By mapping processes end-to-end, visualising workflows, and embedding continuous improvement at every stage, our goal is to create a transparent, consistent system that exposes risks, eliminates inefficiencies, and unlocks opportunities for smarter ways of working.

The programme tackles three priorities: process visibility, quality assurance integration, and establishing a culture where improvement is proactive, not reactive. By turning tacit knowledge into explicit process maps, teams gain clarity on how activities connect and where vulnerabilities lie: providing a strong evidence base for decision-making and aligning with broader quality frameworks. Our approach combines expert-led workflow capture, risk-based assessments, and bespoke visualisation tools that transform complexity into actionable insight. These insights drive targeted interventions, from redesigning workflows to clarifying roles and introducing performance monitoring.

Early results are promising: visualisation has improved accountability, early risk detection has reduced errors, and streamlined processes have delivered efficiency without compromising accuracy. More importantly, this work is shifting mindsets, by embedding continuous improvement as a shared responsibility.

In our session, we will share practical lessons and a replicable model for national statistical institutes seeking to institutionalise process-driven quality improvement, to build resilience and adaptability for the future.