Overview

The Volunteer Lifetime Report provides a single, exportable dataset covering the full volunteer lifecycle, from initial Email Invite through to deletion.

The report is designed to support:

• operational oversight of volunteer recruitment and progression,
• data protection and retention compliance,
• internal audit and assurance activity,
• and organisation-wide analytics on volunteer pipelines and attrition.

The report is available as a downloadable CSV or Excel file.

It captures both automatic and manual deletions and preserves a permanent, pseudonymised audit trail after a volunteer record is removed from the system.

From what date is data available?

The report includes all deletion records from 1 January 2026 onwards.

From the date the Volunteer Lifetime Report was released, all qualifying deletions (and live records too) are captured automatically and are included in the report on an ongoing basis.

What data is included in the export?

For each volunteer record that has been deleted, the export includes the following fields.

• Volunteer
• ID number
• Status
  • Live on the system, or
  • Deleted from the system
• First Name, Last Name (if live; blank if deleted)
• Mobile & Email (if live; blank if deleted)
• Date the person invited to apply (the Creation Date)
• Volunteer Category
• Location (if set)
• County
• Region, derived from the county
• Country
• Date of deletion
• The stage at which the deletion happened, for example Pending Invite, ID validation, etc.

What deletions are captured?

The report captures:

• all automatic deletions generated by system rules, and
• all manual deletions performed by administrators.

Both deletion types are included in the same export.

How to download the Volunteer Lifetime Report

Go to Settings > Reports > Volunteer > Volunteer Lifetime Report > Open the Excel file

What business outcomes does this report support?

This report has been designed to directly support the following outcomes.

Outcome 1: Improved operational visibility

Administrators and managers can:

• see how volunteers are entering the system,
• understand where volunteers are progressing or stalling,
• and identify at which stage volunteers most commonly exit or are removed.

This enables more informed operational decisions around:

• recruitment processes,
• onboarding flows,
• identity validation and safeguarding steps,
• and follow-up activity.

Outcome 2: Better analytics and performance reporting

The dataset enables organisations to:

• analyse recruitment volume and trends,
  measure drop-off points across onboarding stages,
  track the impact of process changes over time,
  and report consistently on volunteer pipeline health.

This improves general analytics across:

• volunteer recruitment,
  progression,
  and retention performance.

Outcome 3: Stronger data protection and data retention governance

The report provides a clear and auditable record of:

• when a volunteer record was deleted, and
• the lifecycle stage at which the deletion occurred.

This directly supports compliance with the GDPR, in particular:

• Article 5(1)(e), storage limitation,
• Article 5(2), accountability, and
• Article 30, records of processing activities,

and enables organisations to demonstrate that personal data is retained and deleted in line with defined retention schedules.

It also supports:

• internal retention and deletion policies,
• audit and regulatory inspections, and
• internal assurance reporting to senior management and boards.

Outcome 4: Pseudonymised post-deletion reporting

Once a volunteer record is deleted:

• the volunteer’s name is removed from the dataset,
• and the unique VolunteerID is retained instead.

This allows organisations to:

• continue to analyse lifecycle and deletion trends,
• without retaining identifiable personal data beyond the deletion point.

This approach supports privacy-by-design and data minimisation principles.

How volunteer identity is handled after deletion

While a volunteer remains active in the system, their name is visible when exported in the Volunteer Lifetime Report.

Once a volunteer record is deleted:

• the name is no longer shown in the export,
• and the record is represented by the volunteer’s unique VolunteerID only.

The VolunteerID:

• remains stable for audit and reporting purposes,
• and allows lifecycle and deletion analysis to continue without retaining personal identifiers.

How this supports operational teams

Operational teams can use the report to:

• monitor volumes of expressions of interest over time,
• identify high-volume counties, regions and areas of interest,
• understand where volunteers are not progressing beyond certain stages,
• and detect bottlenecks or delays in onboarding and validation processes.

This allows teams to target:

• additional communications,
• changes to onboarding workflows,
• or resourcing decisions.

How this supports compliance and governance teams

Compliance and governance teams can use the report to:

• demonstrate that deletions are occurring in line with organisational policy,
• verify that automatic deletion rules are operating correctly,
• confirm that manual deletions are being applied appropriately,
• and evidence retention and deletion activity during audits.

The report also supports internal review of:

• deletion volumes,
• deletion timing,
• and deletion reasons at lifecycle stage level.

How this supports analytics and reporting

Common analytics use cases include:

• monthly and quarterly deletion volumes,
• lifecycle stage drop-off analysis,
• regional and county-based pipeline reporting,
• and comparison of deletion trends against Volunteer Category, Regions, or Locations.

This improves overall visibility of the volunteer lifecycle and enables consistent, repeatable reporting across the organisation.

Using the Volunteer Lifetime Report to support KPI-driven decision making

The Volunteer Lifetime Report enables teams to move beyond basic reporting and towards evidence-based operational, compliance and strategic decision-making.

By applying lifecycle and deletion data to clearly defined KPIs, organisations gain practical insight into volunteer engagement, onboarding performance, regional variation and retention outcomes, while continuing to operate in line with privacy-by-design principles and GDPR-aligned governance.

The examples below illustrate how different teams typically interpret the dataset and use it to support evidence-based operational and strategic decisions.

1. Recruitment and intake teams

Typical KPI: Early engagement and conversion rate

Teams measure:

• the total number of expressions of interest received, and
• the proportion of those records that progress beyond the earliest lifecycle stages before deletion.

How the data is interpreted

By analysing:

• the date of expression of interest, and
• the stage of deletion,

teams can assess how effectively early engagement and follow-up activity converts interest into active onboarding.

This analysis is focused on the quality and timeliness of engagement and operational follow-up.

Decisions supported

Where a higher proportion of deletions occur at:

• Pending invite or other early lifecycle stages,

this typically informs decisions such as:

• adjusting the timing and cadence of invitation and reminder communications,
• setting or revising internal service targets for first contact with prospective volunteers,
• and prioritising follow-up activity by local or regional coordinators.

The objective is to improve operational engagement practices.

2. Onboarding and validation teams

Typical KPI: Drop-off rate by lifecycle stage

Teams group deletions by:

• stage of deletion.

How the data is interpreted

This highlights:

• the specific stages at which volunteers disengage or fail to progress.

Elevated deletion levels at identity validation, vetting or document review stages often indicate operational friction or capacity constraints.

Decisions supported

This data supports decisions such as:

• improving guidance provided to volunteers,
• refining administrator workflows,
• increasing resourcing at specific stages,
• and prioritising training for staff and volunteer coordinators.

3. Service and operational management

Typical KPI: Average time to deletion by lifecycle stage

Teams calculate:

• the time between expression of interest and the deletion date, segmented by lifecycle stage.

How the data is interpreted

This reveals:

• how long records typically remain in early or inactive states,
• and where volunteers are becoming stalled prior to eventual deletion.

Decisions supported

This informs decisions such as:

• introducing escalation or review triggers,
• revising reminder schedules,

and setting clearer operational ownership for stalled records.

4. Regional and local management

Typical KPI: Deletion rate by county and region

Teams group records by:

• county, and
• region.

How the data is interpreted

This highlights:

• geographic variation in progression and disengagement patterns.

Decisions supported

Where certain regions show consistently higher deletion rates, this supports decisions relating to:

• targeted regional support,
• focused training for local administrators,
• and redistribution of operational capacity.

5. Compliance and data protection teams

Typical KPI: Timeliness and consistency of deletion in line with retention rules

Teams analyse:

• deletion date,
• and stage of deletion.

How the data is interpreted

This enables teams to confirm:

• that automatic deletion rules are operating as configured,
• and that manual deletions are being applied consistently and within expected timeframes.

Decisions supported

Where inconsistencies or delays are identified, this supports decisions to:

• refine retention procedures,
• update internal guidance,
• and adjust automated deletion schedules.

6. Digital and process improvement teams

Typical KPI: Impact of operational changes on lifecycle outcomes

Teams compare:

• deletion volumes,
• and deletion stage distributions,

before and after defined operational changes.

How the data is interpreted

Examples of changes assessed include:

• updates to onboarding communications,
• revised administrator workflows,
• or improvements to guidance and support materials.

Decisions supported

Where the data shows:

• reduced early-stage deletions,
• or improved progression into later lifecycle stages,

this provides objective evidence to support continued rollout of the operational change.

7. Senior management and board reporting

Typical KPI: Volunteer pipeline health indicators

Senior reporting typically uses:

• volumes of expressions of interest,
• overall deletion volumes,
• deletion rates by lifecycle stage,
• and deletion trends over time.

How the data is interpreted

This provides a high-level view of:

• the health of the volunteer pipeline,
• onboarding effectiveness,
• and emerging risks in volunteer engagement or capacity.

Decisions supported

This supports strategic decisions relating to:

• resourcing of volunteer services,
• prioritisation of operational improvements,
• and investment in digital and process capability.