Updated January 2026 to reflect pensions dashboards progress and operational readiness.
When pensions dashboards go live to the public, members will not only be finding their pensions. They will be seeing values, often for the first time in years. That moment matters. The accuracy and clarity of what is shown will shape trust, confidence and follow-up behaviour.
This moment also carries emotional weight. First impressions of pensions dashboards will influence how members feel about their savings and the organisations behind them, a theme explored further in our article on building an emotional connection with pensions dashboards, written with Richard Smith.
The first step in connecting members to their pension information is accurate Find Data. These personal identifiers allow dashboards to locate pension records in the first place. Once that link is made, attention quickly shifts to something just as important. Value Data.
Value Data is the information that allows pensions dashboards to show members meaningful outputs. This includes current pension values and projected retirement income. It is the information members rely on to understand what they have and what it may be worth in future.
Without accurate Value Data, dashboards cannot deliver on their core purpose. Members may see incomplete or misleading information, which undermines confidence and drives follow-up queries to schemes and administrators.
Dashboards rely on trust. Members need confidence that the information presented reflects their true position. Even where matching works as intended, poor Value Data leads to confusion and dissatisfaction.
Inaccurate or missing values create more than a poor experience. They increase administrative effort, generate inbound contact and place additional pressure on teams already managing dashboards activity.
Defined benefit (DB) schemes face a distinct challenge. Deferred members often have complex benefit histories, historic data gaps and calculations that depend on actuarial input. For many schemes, Value Data is not readily available in a form that can be surfaced through dashboards.
For DB schemes with deferred members, this work must be completed by the dashboard’s accessibility point. Without the right tools and preparation, it becomes a time-consuming and labour-intensive exercise. It is not something that can be resolved quickly once dashboards usage begins to increase.
Schemes without complete or accurate Value Data face a practical constraint. In some cases, they will have just 10 days to provide missing information once requested. Combined with an increase in dashboards-driven member queries, this creates significant pressure on administration teams and actuaries.
This is not a theoretical risk. Value Data issues surface at the same time as member engagement increases. That combination is what creates bottlenecks.
There is also a regulatory dimension. The Pensions Regulator has been clear that schemes are expected to meet pensions dashboards requirements, and those that fail to address known data issues may face scrutiny.
Industry attention has focused heavily on Find Data and matching. That focus is necessary, but incomplete. A confirmed match does not guarantee a smooth experience if the value shown is outdated, inconsistent or missing.
This mirrors the challenges schemes face with possible matches, where uncertainty drives follow-up contact and operational strain, as explored in our article on planning for possible matches.
From a member perspective, the outcome is the same. The information does not align with expectations, prompting further contact and investigation. In this sense, Value Data becomes the next operational pressure point once matching is achieved.
Some schemes may be tempted to delay Value Data work until there is certainty around wider public access to dashboards. That approach carries risk. A Value Data audit cannot be completed overnight.
Auditing, correcting or creating Value Data requires planning, access to calculation expertise and time to resolve exceptions. Acting early spreads effort and reduces the likelihood of disruption when dashboards activity accelerates.
Technology plays an important role in making Value Data manageable. Tools such as Heywood’s Calculations Manager support bulk, rules-based calculations aligned to scheme benefits and reduce reliance on manual processes.
Automating complex calculations improves accuracy and consistency. It also supports ongoing maintenance, rather than treating Value Data as a one-off exercise.
Pensions dashboards bring pension information into a live, member-facing environment. Value Data will be seen, questioned and compared in real time.
Schemes that prepare now place themselves in a stronger position to manage that shift. Those that delay risk avoidable operational strain when dashboards usage increases.