Scheme member data quality

Overview

A core accountability of trustees and scheme managers (governing bodies) is to make sure data quality is well managed. This enables you to make informed decisions, ensure your scheme is well-run, deliver good outcomes for members, and meet legal obligations, including those set out in data protection legislation.

This updated guidance (previously named as Record-keeping) sets out the practical steps and good practice that trustees and scheme managers can take to meet the expectations that are set out in the data monitoring and improvement module of our code of practice.

Roles and responsibilities

Governing bodies

You are accountable for the quality of the member data you hold. You have a legal duty to ensure that schemes have governance and internal controls in place to monitor and improve data, even if you delegate some of these duties to your administrators or sub-committees. You should challenge your administrators or sub-committees where your expectations are not being satisfactorily met. You must be able to demonstrate that you are maintaining and monitoring scheme member data in line with legislative requirements and TPR’s expectations.

Member data is a strategic data asset, vital for achieving your long-term goals and a good member experience. You should think of your member data strategically and holistically, and not just as an operational afterthought. Having good quality member data means that:

• scheme members can receive the right information and the right benefit at the right time
• you can minimise errors and mistakes, which can have serious negative impacts on members and be costly for you to resolve
• defined benefit schemes have accurate funding plans in place
• defined contribution schemes can process core financial transactions promptly and accurately
• all schemes can meet regulatory data requirements, including those introduced by pensions dashboards
• schemes can deploy advancements in technology and member communications to drive efficiencies and improve members’ accessibility and inclusivity
• members can engage with their pensions easily and effectively
• schemes can achieve their desired strategic ambitions such as buy-out or scheme consolidation

You should take an active role in the management of your member data. This means you should:

• ensure your administrators have adequate controls and processes in place to maintain good quality data
• obtain regular data reports from your administrator/s and tell us your latest data scores in your scheme return
• consider data quality regularly at board meetings
• reflect data quality on your risk register as appropriate
• make relevant decisions required by your administrator promptly and effectively
• ensure that sufficient resource and budget is allocated appropriately to resolve any data issues as they arise
• ensure that data is processed in accordance with data protection legislation and Information Commissioner’s Office guidance, a guide to the data protection principles.

Your governing body, as a team, should have sufficient understanding and experience in administration and data management, and keep up to date with relevant developments and best practice. This will assist you in having effective discussions with your administrators to ensure your scheme data is of good quality, secure, and compliant with regulatory requirements. For larger schemes, you may consider putting in place a dedicated data quality team or sub-committee to assist you in meeting your duties.

Administrators

Administrators play a key role in maintaining data quality, as they process and manage scheme member data on a daily basis, along with other parties such as employers, actuaries and software providers.

Administrators are responsible for implementing the agreed data control policies and processes, which include, but are not limited to:

• conducting regular data reconciliation exercises
• conducting regular data tracing and mortality screening exercises
• measuring the quality of member data on a regular basis
• embedding quality assurance processes
• participating in benefit audits
• working with employers to improve the data they provide
• identifying and investigating any data gaps and errors
• developing and implementing robust data improvement plans to address any identified data gaps or errors

Administrators should provide regular reports on data quality. These should promptly escalate any data issues and risks to relevant governing bodies highlighting any common member queries, errors or complaints that provide evidence of data quality issues.

These reports should include an assessment of the impact of any identified issues on the scheme and its members. This will support the governing body in deciding whether any actions are needed to improve member data quality. 

The Pensions Administration Standards Association’s (PASA) standards include a specific standard on member data quality and provide further detail about the role of the administrator in ensuring the quality of scheme member data.

Defining scheme member data

Scheme member data comprises:

• common data: information that is needed to uniquely identify and engage with a member
• scheme-specific data: information about the member’s participation in the scheme which is key for its effective operation

Both sets of data are equally important. You must work with your administrator to decide what data items are relevant for your scheme under each category, regularly reviewing them to ensure they meet your scheme’s needs.  

Common data

Common data is information needed to uniquely identify and engage with a member.

Good common data is essential to effectively communicate with the right members when needed and, in conjunction with scheme-specific data, to accurately calculate and pay members’ benefits. All schemes should hold this data for all members.

Common data consists of the following data items.

Common data item	Why this data item is needed
Name: Surname Forename or initials	Identification
Date of birth	Identification Calculation of benefits
National Insurance number	Identification
Member’s scheme identification number Only if there is one	Identification
Sex Only if the scheme requires this information as per scheme rules or legal requirements	Calculation of benefit, in line with any sex-related scheme-specific rules or legal obligations, for example, earlier retirement dates, guaranteed minimum pension equalisation (GMP), Equality Act 2010 etc.
Date pensionable service started; membership/policy start date or first contribution date	Calculation of defined benefits Assisting validation with other data, for example, when members make claims related to their benefits or where a data issue which applies to specific members is identified Must be provided in line with the pensions dashboards requirements
Expected retirement/maturity date (target retirement age) For pensioners, this is their actual pension commenced date (crystallisation date)	Calculation of benefits Facilitate targeted member communications  Must be provided in line with the pensions dashboards
Membership status Active, deferred or pensioner	Helps identify scheme-specific data items for different member categories Enables targeted member communications  Determines members in scope for pensions dashboards
Last status event – the date at which the membership status last changed Where appropriate, you should also capture the reason for the change in status (for example, retired or left employment)	Calculation of benefits Assisting identification Supporting validation with other data
Member contact details At least one set of the following contact details should be kept on record: Personal address including postcode Personal telephone number (landline/mobile) Personal email address	Communication with members Identification – including matching for pensions dashboards

For public service pensions schemes (PSPS), there are certain data items that scheme managers are legally required to keep. These are set out in the section called legal requirements PSPS. 

Scheme-specific data

Scheme-specific data is information about members’ participation in a scheme which is key for its effective operation and ensures members have good outcomes and experience. The data you need will depend on the:

• nature of the benefits provided
• member status
• applicable legislation to your scheme
• strategic goals

For example, you may need more data if you are preparing for consolidation or if your scheme has complex benefit structures.

You should work with your administrator to assess and decide which data items are essential to the operation of the scheme and why these are critical. You should also be clear as to why other data is not considered essential.

Some of the scheme-specific data items you need to include will not be relevant for all members. Where this is the case, you may want to group your members by type and define your scheme-specific data accordingly. Taking this action may also assist you in identifying and resolving data issues that apply to specific groups of your membership.

As a minimum, the scheme-specific data items need to cover the following scheme functions.

Calculating pension values

Your scheme-specific data should include the data items you need to accurately calculate the pension values for your members. The data required to calculate values will vary depending on the type of scheme, the complexity of the benefits, and members’ statuses.

More complex benefit scenarios may require additional scheme-specific data items to ensure accurate calculation, such as:

• discretionary benefits, whether and to what extent any discretionary benefits are included within the benefits to be valued
• special cases, for example, non-standard pension age, salary differences, divorces, bridging pensions, underpins
• cash transfer sum (early leavers only)
• whether members have any special benefit under the scheme, such as injury benefit, death benefit or other compensation benefits

Processing member queries and events

The scheme-specific data items, that are combined with common data, to enable you to respond to member queries effectively, include, but are not limited to:

• decumulation requests, such as flexible benefit access, queries around relevant tax allowances (for example, annual allowance, lump sum allowance), queries on contingent/dependent benefits
• members’ choices on retirement options
• member events, such as injury, divorce, changes to part-time hours, retirement, death

Other scheme-specific events or features

Your scheme may have been subject to events or have specific features which require you to include additional data items within your scheme-specific data, such as:

• contracting out
• changes to scheme rules
• providing the option to build up an additional pension or a pot through additional voluntary contributions
• remediation exercises, for example, McCloud, GMP equalisation
• scheme within a buy-in or buy-out process

The data items that are legally required for PSPS to keep can help you identify your scheme-specific data. You can find the details of these data items in the table called Legal requirements for PSPS.

The PASA Data Scoring Guidance can also help you identify your scheme-specific data and provides further practical considerations around scheme-specific data.

Legal requirements for public service pension schemes

There are legal requirements for PSPS. The data items and what needs to be included for each item are as follows.

Member and beneficiary information:

• name
• date of birth
• sex
• member's last known postal address
• member’s scheme identification number
• member’s National Insurance number (if they have one)
• dates that active, deferred and pensioner members join and leave the scheme
• details of active, deferred and pensioner members’ employment with any employer participating in the scheme, including the period of pensionable service and the amount of pensionable earnings each year

Contributions details (member, employer or other payee):

• employer or member contributions paid in relation to each active member
• any information relevant to calculating each member’s rights under the scheme which is directly or indirectly attributable to a pension credit or debit

Payment to members:

• member’s name
• date of payment
• if a member leaves the scheme:
  • Date of leaving
  • Member’s entitlement at that date
  • Method used for calculating any entitlement under the scheme
• how that entitlement was discharged

Payments or transfers made by or on behalf of the scheme manager to any person other than the member:

• name and address of the person that the payment or transfer was made to
• reason for the payment or transaction

Transfer records:

• member’s name
• transfer terms
• name of the scheme into or out of which the member has been transferred
• transfer date
• date of receipt or payment of money or assets

For money purchase benefits:

• any investment decisions taken by or relating to a member
• any investments held on behalf of a member
• any anticipated date of retirement notified by a member

For other benefits that aren’t money purchase benefits, injury benefits or compensation benefits under the scheme:

• any formula used to calculate a member’s or beneficiary’s pension or benefit
• the percentage to be applied for revaluation each year to a member’s accrued rights to benefits under the scheme
• any increase to be applied to a pensioner member’s or beneficiary’s pension or benefit in payment in each year

Online learning

• Trustee toolkit: the 'Running a scheme' module contains a tutorial on 'Scheme administration and member data'.
• Public service toolkit: learn more about keeping and maintaining records in the 'Maintaining accurate member data' course.

Assessing member data quality

Once you have identified the data items that are essential to efficiently run your scheme, you need to measure the quality of this data. This will help you identify any actions that are needed to improve its quality.

Frequency of data quality assessment

Our general code requires you to assess the need for a data review exercise at least annually. How often you measure the quality of your member data in practice will depend on the size, nature, scale, and complexity of your scheme.

Member data degrades and is subject to change. Therefore, most schemes will need to carry out a review at least once a year to make sure their data stays high quality. Larger schemes and those with a complex benefit structure may need to review the quality of member data more frequently.

Unless your scheme has triggered a wind up, you will need to report scores for your common and scheme-specific data to us in every scheme return. In the sections called calculate common data and calculate scheme-specific data, you can find out how to do these calculations.

Certain events may trigger the need for additional data reviews, for example:

• where a decision has been made to buy-in or wind up a scheme (transferring to another scheme or buying out)
• where there has been a change of administrator or administration system/platform
• where the scheme is affected by bulk activities, such as a merger, an acquisition, section disposal, or de-risking exercises
• where the scheme needs to comply with new legislative requirements or carry out a remediation exercise that involves significant data, for example pensions dashboards, guaranteed minimum pension equalisation
• where data improvement work has been completed

Scope of data quality assessment

The scope of a data quality assessment will depend on your scheme’s circumstances. For example, a small scheme that is closed to contributions or future accrual and processes a relatively small number of transactions will have fewer changes to its records over a year. Therefore, the data assessment may be scaled accordingly. A scheme that has a high turnover of members or one that processes a large number of transactions is likely to require a more comprehensive data assessment.

Understanding your scheme’s needs is important when assessing the quality of your member data. Perfect data quality may not always be achievable. Therefore, focus should be given to ensure the data is as fit for purpose as it can be. Once you’ve decided what actions to take to assess and improve your data, you will need to work with your administrator, and any other identified service providers, to ensure these actions are taken in a timely manner. To find out how to improve your data, read the section called data improvement.

There will be instances when you may have exhausted all reasonable measures to improve the quality of specific data items, for example due to historic issues or data loss. In this situation, you need to challenge your administrator on whether all measures are truly exhausted, and if so, to agree, record and implement a consistent and fair policy for these situations.

Data quality assessment dimensions

Data quality dimensions are the characteristics against which you measure quality. Just checking that each field has data is not sufficient. You, or your administrator on your behalf, should assess your member data from different dimensions to ensure that it is of sufficient quality and determine if improvements are needed. You should know what tests your administrator runs when assessing the quality of your member data.

In the government’s news story, meet the data quality dimensions, it recommends looking at six core data quality dimensions as defined by the Data Management Association UK. It is good practice to ensure that your scheme member data has been assessed against these data dimensions.

Completeness

The member data you need should be in your administration records and ready to be used. This doesn’t mean that every data item must be populated for every member, but rather that it is there if it should be. For example, you would need to hold the expected retirement date for active and deferred members, but not pensioner members - for them, you should hold their actual pension commencement date.

Accuracy

Member data should reflect reality, from the moment it is collected and stay accurate over time. For example, by confirming date of birth against identity documents. While some information (for example, date of birth) is static, other data changes over time. You should have processes in place to capture this updated data. This may be provided by the employer or the member, or you may identify issues when using the data (for example, getting gone-away responses to mailings shows inaccurate address information).

Uniqueness

Duplicate data items may indicate issues. For example, unless your scheme operates with more than one record per member, two records with the same National Insurance number may indicate an error. This is particularly relevant when data sets have been combined.

Consistency

Your data items should not conflict within your records or with other data sets. For example, the date a member joined the scheme should be later than their date of birth and before the date they expect to retire.

Timeliness

Your data should be available when expected and needed. This is particularly important for processing retirements and transfers, meeting disclosure requirements, or providing information to members through dashboards. For example, you need members’ up to date pensionable salary information to be available so you can issue annual benefit statements.

Validity

Your data should be configured to the expected format, type and range. For example, all email addresses must have an @ symbol, UK postcodes must appear in the Royal Mail postcode list, and National Insurance numbers must follow HMRC rules on length and permitted letters. There are also specific requirements on how data must be formatted when it is sent to pensions dashboards.

Examples of assessing the quality of your member data

Your administrator will assess the quality of scheme-specific data for a member in a number of ways. An example of how the assessment could be done is as follows:

• Completeness: checking there is a record present in all relevant fields for this member. If any records are missing, the administrator should look into why.
• Uniqueness: checking there is no duplicate member record for this individual. If this member has multiple benefit records or employment records, these should be linked together under that member.
• Timelines: checking when the data was last collected, updated or reviewed for this member. Active and pensioner records will typically be updated monthly, while an administrator may only review and update deferred member data once a year.
• Validity: checking all relevant data items are in the correct range and format. For example, the sum of the transactions made, equals the total amount of contribution received in any given month.
• Consistency: checking the records held in other data sets (for example, data provided by other providers, or data held by your actuary or investment manager) is the same as the records held on your administration system. If different data sets conflict, look into why and decide which one is more reliable and should be used. Update agreed data in all data sets and check that the new data will not be unintentionally overwritten through automated data feed.
• Accuracy: checking that data held against this member reflects reality at a reasonable level. For example, that the value of their pension accurately reflects what they are entitled to under the scheme rules, taking into account salary and contribution information, investment returns and other relevant factors.

Data report

You should obtain a report on the results of the data quality assessment from your administrator. You should review this report and raise any queries with them. You must make sure you are satisfied that the report provides a true assessment of your scheme’s data quality. It must also provide sufficient information to understand the impact it has on your strategic goals and to make relevant decisions.

The data report can be a stand-alone report, an automated report from the system, or included as part of your administrator's report. Your administrator may provide multiple data reports for different purposes. For example, they may provide an automated report which allows you to monitor the data quality as you need, a regular report that relates to day-to-day data cleansing work, or a specific data review report for certain scheme events.

As a minimum, you should receive a data quality report from your administrator once a year, which includes the data score for your common and scheme-specific data and sufficient contextual information to enable you to understand:

• which data items are being tested, for which members
• how they are being tested
• whether there are any systemic issues which need to be addressed, for example, if issues are associated with one particular employer or membership type
• the impact of any identified data issues on the scheme
• any actions that could be taken to rectify the identified data issues

Submit data scores to us

You must send us the scheme’s data scores in each scheme return. You need to submit separate scores for common and scheme-specific data.

You should ensure that the score you submit is a true reflection of the quality of your member data. Your data score is the percentage of members in the scheme that you hold complete and accurate data for.

As you may need different data items for your members depending on the benefit type (defined benefit or defined contribution) or member status (active, deferred or pensioner), you may wish to segregate your members to test the different groups against the relevant data items. This will help prevent false negatives from being included in your scores. You will then need to combine these scores to provide a single overall score for the scheme.

Example calculation – common data

A data review of a scheme with 100 members shows that 40 addresses are missing but the rest of the data is present and accurate. The common data score is 60% as 60 members have full and accurate common data.

Example calculation – scheme-specific data

Scenario 1

If a data review of a scheme with 100 members shows that 40 members have at least one scheme-specific data item missing, the scheme-specific data score is also 60%.

Scenario 2

A scheme has 100 members, of which 60 members are active members and 40 members are pensioners. Different data items are included in the scheme’s specific data for active and pensioner members. To ensure that the data score provides an accurate reflection of data quality for the whole membership, the administrator calculates the scores separately for active and pensioner members, and then combines the individual scores. The data score for active members is 50% and the data score for pensioner members is 75%. 50%*[60/(40+60)] + 75%*[40/(40+60)] = 60%. The overall scheme score would therefore be 60%.

Scenario 3

A hybrid scheme has 100 members, of which 60 members have defined benefits and 40 members have money purchase benefits. The data score for members with defined benefits is 50% and the data score for members with money purchase benefits is 75%. 50%*[60/(40+60)] + 75%*[40/(40+60)] = 60%. The overall scheme score would therefore be 60%.

Scenario 4

A hybrid scheme has 100 members, of which 60 members have defined benefits and 80 members have money purchase benefits. The data score for members with defined benefits is 50% and the data score for members with money purchase benefits is 75%. 50%*[60/(80+60)] + 75%*[80/(80+60)] = 64%. The overall scheme score would therefore be 64%.

Data quality improvement plan

You might find data issues through your data review, audit, valuation or other activity. If these require improvement work, you should put an improvement plan in place to address them. Your administrator should be able to help you design an effective improvement plan.

You should keep a clear record of the plan so you can refer to it easily. Typically, the improvement plan is a standalone document. This means you do not have to locate multiple documents or items of correspondence to monitor its progress.

The improvement plan should clearly set out the steps you’re taking to improve your scheme data.

Your plan should be unique to your scheme’s circumstances. The amount of detail should depend on the complexity of the issues you’re trying to address.

Set objectives and scope

The data improvement plan should clearly set out both its scope and the objectives you’re trying to achieve by having better data. If you have more than one objective, you should list them in order of priority.

Objectives can include:

• addressing data issues that impair your ability to run your scheme effectively, paying benefits correctly at the right time, processing core transactions accurately and promptly, ensuring a high standard of service for members, keeping costs manageable or meeting legal obligations
• improving members’ experiences, such as providing them with online access to their records
• improving operational resilience, administration efficiency and scalability, such as implementing automation to reduce service times as information is more readily at hand
• preparing to move to a new administration system or a new administrator
• improving employer confidence in the valuation of liabilities and the appropriateness of their contributions and recovery plans
• improving data ahead of a risk-reduction or a liability-management exercise
• reducing the risk of fraud, such as identifying late notification of death to stop overpayment of benefits

Clearly set out the scope of your improvement work, particularly:

• which data is included
• which membership groups are included
• how far back your improvement work will cover

You may need to take a phased approach or prioritise certain objectives if there is a lot of work required. You should prioritise data that will have the greatest effect on member benefits and the most impact on your core scheme activities. Other factors you could consider for prioritisation include:

• data type: for example, focusing on personal information that will improve your ability to communicate with members
• member type or profile: for example, looking at pensions in payment or members that are closer to retirement first
• data source: for example, looking at the largest employer first
• scheme events: for example, focusing on the data you need for certain scheme events such as issuing benefit statements or valuations
• return on investment: for example, working on issues that have the greatest impact on running costs
• technical solution: for example, starting with data issues that can be resolved using bulk automated solutions
• quick wins: for example, working through known data issues that are relatively easy to fix

Define roles and responsibilities

For the governing body

You need to have appropriate oversight of progress and check the quality of the work being done. You also need to be available to answer any queries the administrator has as the work progresses and make any required decisions.

You should agree roles and responsibilities from the start. Your plan should set out who will make decisions, such as sign-off for the outcome being met, or changes to work on the improvement plan. Clearly document any areas where the administrator has flexibility, and the limits they need to work within.

You should agree and document how and when the administrator will report their progress. This should include reporting to you and other relevant parties, such as for pension boards or employers.

You may need a range of other formal controls in place depending on the complexity of the work. These can include a decisions/action log, a change control log, or cost reporting.

For the administrator

The plan should break down the activities your administrator will perform, and for each activity it should be clear what the administrator will do. It should include:

• the issue to be addressed, including which members (member groups) are covered
• the method to be used, for example, member address tracing or researching company employment records
• who is doing the work and how long it will take
• any assumptions made, for example, the number of records likely to need work
• how you will know the task has been completed

You may also use a specialist service provider to deliver some or all of these planned activities. If so, you will also need to be clear on the respective roles and responsibilities. You will also need to confirm the data sharing and implementation processes between your administrator and the selected specialist service provider.

Identify dependencies with other work

You should identify any other work that might affect or depend on your improvement work, especially where data is being changed or the same resources need to be used.

This will help you identify potential sources of conflict or opportunities to minimise burden and maximise efficiency. For example, reducing how often you ask employers for data, or only contacting members once to request information.

Other work you may need to consider includes:

• valuations
• member communication exercises
• guaranteed minimum pension reconciliation and equalisation
• year-end reconciliation
• negotiating an administration contract or changing an administrative platform
• risk-reduction exercises
• proposed scheme structure changes
• preparing to comply with new legislation

Set a timeline for the plan

You should work with your administrator and agree a timeline for the data improvement plan.

The plan must have a defined end date within a reasonable period. More complex work can take several months, so you could consider breaking it down into phases.

Your timeline should clearly set out key milestones, when reporting and decisions need to happen, and any risks or barriers to meet this timescale. It should also include the dependencies you have identified.

You may need to take a phased approach if there is a lot of work required, or this is a particularly complex project. These should also be reflected in your timeline.

Assign resources

Plans should take account of available staff and financial resources, as well as other pressures such as emerging regulatory changes. The administrator and employer will need to help you, so you should agree resources with them.

You should agree at the start whether the work will be delivered as part of ongoing business as usual administration, or as a separately managed project with additional budget and resources, or a combination of the two. If you’re diverting resources from other work, you should set out how this will affect the scheme.

As well as the administrator’s resources, you should consider which other parties you may need to source data from. Likely sources and examples of data they can supply include:

• employers – providing member information, employment and contribution history
• members – name changes, dates of birth, email addresses
• next of kin – death details, beneficiaries of the estate, spouse or dependent information
• tracing companies – address checks, existence checks, email addresses, phone numbers, likely spousal information, address history
• other parties, such as actuaries or additional voluntary contribution providers

Set measurable outcomes

You should set out the outcomes you are aiming to achieve, based on your objectives. Include how you will measure them and how long they will take to achieve.  

For example, if one of your objectives is to improve member communications by ensuring you can send the right communications to members at the right time, your desired outcomes could be set as follows:

• Desired outcome: you hold accurate contact details (postal, or personal email addresses, or personal phone number) for all members.
• Timeframe: before you issue your next annual benefit statement.
• Measurement: how many members receive their annual benefit statement. You could also consider using a survey to ask members for feedback. This can help you measure your success.

Embedding improved data into your scheme

Improvement work doesn’t end when the data is clean. Make sure the data is fed back into systems. Work with the administrator and employer on follow-up activities such as:

• ensuring that any changes to member records are also made across all administrative systems that hold the same data
• ensuring there are no unintentional overwrites through automated data feeds, this may include employer HR systems and pensioner payroll
• correction work, such as sorting out payment errors
• capturing and documenting changes to data and processes so future administration teams know what has been done
• updating and documenting procedures to reduce the risk of errors recurring and to make sure improvements are maintained

Maintaining data quality

Good data management is not a one-off task; it is something you need to keep doing. You must monitor the effectiveness of your internal controls for your data.

There are many ways to enable your scheme to maintain good quality member data on an ongoing basis.

Data management strategy

It is good practice to formally capture your strategic approach to member data in a data management strategy (sometimes known as a data management plan). This sets out key data considerations for your scheme. It clarifies who is responsible for data quality and data security and documents your policies and processes for organising, receiving, storing, sharing and improving data.

You should regularly review your data management strategy, especially when there are changes to your scheme. For example, changes to your scheme’s long-term strategy. You need to consider how these changes would impact your data management strategy, and whether new or amended processes are required.

Data quality should be one of the key components of your scheme’s data management strategy. You should document the measures that you and your administrators are taking to maintain, monitor and improve data quality. This provides clarity, accountability and consistency for your administrators and all other providers to manage data in the way your scheme needs.

For practical considerations and examples of content for a data management strategy, read the data management plan guidance from the Pensions Administration Standards Association (PASA).

Managing your administrator

You should have a clear agreement with your administrators on the measures for your scheme’s data quality assurance. If you are using a third-party administrator, this should be reflected in contractual documents.

You should review your administrator’s performance against these measures on a regular basis. If the contract or agreement is not effective in ensuring data accuracy and member experience, you need to review and update them.

Further information on appointing and reviewing administration performance can be found in working with advisers, and administration guide.

Quality assurance measures

You should ensure there are sufficient quality assurance processes in place to minimise the risk of data errors caused by poor systems or processes. This includes validating at the entry point when data is received from employers or members, for example conducting bank account verifications or address look-ups. Quality checks should also be built into specific processes, for example checking a sample of annual benefit statements or manually verifying transfer values before these are issued.

Administration and data reports should include insights on errors and be sufficiently detailed to help you identify whether changes to the administration systems or processes may be needed. If you currently do not receive this information in your regular reports, you should explore the addition of this information with your administrators.

It is important that the data process manuals are kept up to date, are relevant to the needs of the scheme and clearly documented. This is to maintain continuity and consistency of service even if there is any change or interruption in administration personnel or service providers.

Further information on quality assurance can be found in our administration guide.

Work with the employer and other data providers

Your administrator needs to accurately transfer members’ data on time to and from third parties, such as employers, additional voluntary contribution provider/s, actuaries or tracing agents. As a governing body, you need to support your administrators to set up and maintain clear data sharing processes with these data providers.

Wherever possible, data should be transferred between these parties electronically and securely. Robust data sharing processes reduce the risk of data errors. Validation checks should be built into the process to identify any inconsistencies.

Employers, including their payroll function, play a vital role in this process. You can support your administrator by educating the employers to understand their role. The employer should provide the required data, monitor it, and notify the scheme whenever there are changes to it. The employer should provide:

• contribution details
• joiners and leavers details
• changes to members’ personal details, including contact details and beneficiaries’ details
• changes to pensionable pay, including changing of working hours

It is good practice for your employer to nominate a point of contact for your administrator. This is so any data queries can be efficiently resolved. You could also invite someone from payroll to board meetings that the administrator attends.

Ongoing monitoring on the effectiveness of the data sharing processes will enable you to identify areas where improvements could be made. For example, if your administrator has to frequently raise queries with certain employers about the quality of data received, there might be validation checks that the employer can put in place to reduce the number of queries and improve data quality.

Engage with your members

Regular and targeted member engagement will also assist you in maintaining good quality data. You should ensure that there are simple and accessible routes for your members to update their information easily, for example via a call centre, email, or online portals. You could also use these to remind your members that it is important to keep you updated with any changes and to educate them about the consequences of not doing so. You should also consider accessibility issues when designing your communication channels.

You should seek opportunities to obtain the latest member information, such as when responding to incoming queries.

Care should be taken to verify the identity of the individual and conduct suitable data validation to ensure the quality of data is sufficiently good at the entry point. You should make any updates in a timely manner.

Where appropriate, you should consider introducing a policy for member tracing. This could be targeted to member types, age, statuses, or specific data items to make it more effective. The introduction of pensions dashboards provides an opportunity for you to trace members. You should ensure that your matching policy is designed to assist you in identifying matches.

You should also have a good understanding of the interaction experience that members have with administrators, including complaints or members’ feedback on the administration service. Member experience is a useful measure of the scheme’s data quality level.

Technology and data standards

Your scheme should have sufficient IT systems to deliver the administration function and maintain data quality. Automating administration tasks and processes, where possible, improves data accuracy, reliability, and compliance with regulatory requirements. You should regularly consider whether any administration or technology innovations could improve data quality, for example automated address verification. It is important that any software used to carry out data-related tasks is tested both at the point of implementation and on a regular basis after that.

To support interoperability, transparency, and futureproofing of pension scheme operations, you and your administrator should consider aligning your data practices with open standards for government data and technology. Open standards are publicly available specifications that define how data should be structured, formatted, and exchanged. They enable interoperability between systems, promote data consistency and reuse, reduce vendor lock-in, and support digital transformation and members’ access to services.