Adopting the programme and project data standard (HTML)

1 About

The ’Programme and project data standard’ sets expectations for how programme and project data is defined, formatted and updated. It supports consistent, high-quality data across government.

This handbook explains how to adopt the standard. It covers

writing an implementation plan
using the standard on a day-to-day basis

The programme and project data standard is currently in trial. It is not yet mandatory. Feedback from this trial will help improve the standard before it becomes mandatory.

This handbook is for anyone involved in the creation and management of data in government programmes and projects.

2 Writing an implementation plan

The first step in getting ready to implement the programme and project data standard is to write an implementation plan.

1.4.2 of the programme and project data standard says:

Implementation plans describe the changes and activities needed in the organisation to enable programmes and projects to create and manage data in line with the standard.

For in-scope organisations, senior officers accountable for project delivery are responsible for developing these plans.

Government Project Delivery Policy Note 02/25 says:

In scope organisations should review the new subject-specific standard and begin developing implementation plans to meet its requirements.

Senior officers accountable for project delivery may want to delegate responsibility for preparing implementation plans to departmental portfolio teams and centres of excellence.

Implementation plans should describe the activities needed to close the gap between the current ‘as is’ state of an organisation’s programme and project data environment and the requirements of the standard.

1.4.1 of the programme and project data standard says:

The path to full compliance will vary depending on each organisation’s unique programme and project data environment, which is made up of IT systems, data management practices and data maturity.

To understand gap and what activities might be needed to bridge it, it’s helpful to:

assess your organisation’s ‘as is’ state, which may include:
- which data entities are used to monitor and control programmes and projects (section 2.1.1)
- any programme and project management solutions (section 2.1.2)
- relevant data management guidance and template (section 2.1.3)
- roles and responsibilities (section 2.1.4)
analyse the gap between the “as is state” and the requirements of the standard (section 2.2)
plan the activities that will close the gap and enable your organisation to comply with the standard (section 2.3)

2.1 Assessing your organisation's 'as is' state

The ‘as is’ state of an organisation’s programme and project data environment describes how programme and project data is currently managed across the organisation.

Remember, there may be differences between portfolios and between programmes and projects with different levels of overall maturity, scale and complexity.

To help understand how programme and project data is managed across the organisation, senior officers accountable for project delivery, or portfolio teams and centres of excellence, may want to commission programme and project teams across the department for information.

Below are the types of information that should be included in the ‘as-is’ assessment.

2.1.1 Data entities used to monitor and control programmes and projects

The standard sets expectations for data entities and attributes fundamental to project delivery in government. It’s important to establish which data entities and data attributes are currently used to support programme and project delivery in your organisation.

1.2.1 of the programme and project data standard says:

A data entity a main category of information about the work of a programme or project.

Each data entity has several data attributes that help identify, describe or measure it in detail.

This version of the standard covers the data entities most used by project delivery professionals across government.

The in-scope data entities are:

project features

risk

issue

milestone

benefit

cost

people

Comparing data entities and attributes currently captured to the expectations set by the standard will help identify any changes that might be required to data attribute definitions or formats and to project delivery platforms or data management guidance or templates.

2.1.2 Project delivery platforms

Your organisation might use one or more project delivery platforms to manage programme and project data.

A project delivery platform, sometimes called a Programme and Project Management (PPM) solution, is a software tool or IT platform that helps organisations manage portfolios, programmes or projects. PPM solutions often enable users to input, manage and analyse data about portfolios, programmes and projects. Typical capabilities of PPM solutions include risk and issue management, cost tracking, report and dashboard generation.

When this is the case, it is important to assess how your organisation’s project delivery platform can support the expectations set by the standard.

To do this, you might consider:

which platform(s) are used?
what data entities and attributes do they capture?
who provides them? Are they in-house or procured from an external supplier?
to what extent does the current configuration support the expectations set by the standard?
can it be reconfigured to support compliance with the standard?
if so, when can this happen and are there any costs associated with reconfiguration?
who are the product owners within your organisation?

2.1.3 Data management guidance and templates

Your organisation might have collections of guidance on how to manage programme and project data and templates that give users a common starting point to create data.

Guidance and templates may include instructions for creating data and standard formats for risk registers, issue logs, plans, benefits profiles and reports.

Guidance and templates might be owned centrally by portfolio teams and centres of excellence or managed locally by programme and project teams.

Where guidance and templates exist, they should be reviewed to check whether updates are needed to help users create and manage data in line with the standard and consistently across the organisation. Any required revisions should be captured as actions in the implementation plan.

2.1.4 Roles and responsibilities

You should confirm whether the accountabilities and responsibilities of data owners and data stewards are assigned and understood across the organisation.

The governance section of the programme and project data standard says:

For each portfolio, the portfolio director, and for each programme or project, the senior responsible owner ensures that programme and project delivery data is created and managed according to this standard.

In programmes and projects, the senior responsible owner acts as the data owner, with ultimate accountability for the data created by their programme or project team.

Data stewards manage the quality of specific data entities within their programme or project. Anyone in a programme or project team can act as a data steward.

Programme and project team members may already be carrying out the responsibilities of data stewards by assessing and managing data quality.

You should capture existing roles and responsibilities and any that need clarifying in your implementation plan.

2.2 Analysing the gap

The next step is to produce a consolidated view of the areas where your organisation’s current programme and project data environment does not support teams to create and manage data in line with the standard.

Describing these gaps in one place makes it easier to understand what needs to change and helps you decide the actions to include in your implementation plan.

Example: Gap analysis

An organisation uses all the in-scope data entities to monitor and control programmes and projects. However, the current PPM solution use definitions for risk data attributes that are different from those set by the standard. The guidance that helps project delivery professionals to use the PPM solution also provides definitions for risk data attributes that are different to the standard.

All large programmes and projects, including those on the Government Major Project Portfolio (GMPP), have responsibilities assigned to individuals that are similar or equal to the responsibilities expected of data owners and data stewards. However, some medium and small projects in the organisation do not recognise these roles and responsibilities or do not have them assigned.

You can use the questions below as a final check to make sure that your gap analysis has considered all the expectations set by the standard.

Does the organisation’s current programme and project data environment:

apply consistent definitions for data attributes in line with the standard?
allow consistent data formatting for attributes in line with the standard?
ensure minimum update frequencies in line with the standard?
have data owners and data stewards in place across the organisation and in programmes and projects?

If the answer to any of these questions is no, make sure you’ve understood why and captured any changes needed in your gap analysis.

2.3 Planning the activities required to close the gap

Once you have a consolidated understanding of the gap, you are ready to plan the activities to close the gap and create your implementation plan.

Implementation plans can be written in any format that makes it easy to describe and monitor the completion of the activities. Once you’ve completed the activities, your organisation should be compliant with the standard. You should aim to achieve compliance as soon as possible. See Government Project Delivery Policy Note 02/25 for implementation timeline.

Below are 2 examples of how content in an implementation plan might look.

2.3.1 Example: Actions grouped by standard requirement

Use this format when you want to connect actions to expectations in standard (standard definitions, formats, update frequencies, roles).

Requirement	Gap	Action(s)	Responsible team(s)	Due date
Use standard definitions and formats	PPM solution uses risk attribute definitions that differ from the standard	Map current risk attributes to the definitions used in the standard definitions	Centre of excellence	DD/MM/YYYY
Use standard definitions and formats	PPM solution uses risk attribute definitions that differ from the standard	Reconfigure PPM fields	PPM product owner	DD/MM/YYYY
Data owners data stewards in every programme and project	Small and medium projects do not have roles assigned	Mandate role assignment; publish role guide; run briefings	Portfolio office, Human resources/Learning and development	DD/MM/YYYY

2.3.2 Example: Actions grouped by people, process or technology

People

Objective	Action	Responsible team(s)	Due date
Help raise awareness of new data owner and data steward roles and responsibilities	Prepare communications that outline the roles of data owners and data stewards and who is fulfilling these roles (referencing the standard)	Centre of excellence	DD/MM/YYYY

Process

Objective	Action	Responsible team(s)	Due date
Ensure programmes and projects have documented data owners and data stewards	Support programme and project teams to record who their data owners and data stewards are in programme and project management plans	Portfolio teams	DD/MM/YYYY

Technology

Objective	Action	Responsible team(s)	Due date
Align PPM fields/validation to the standard	Configure fields; enable validation check at the point of entry	PPM solution owner	DD/MM/YYYY

It may be helpful for programme and project teams to develop their own implementation plans to ensure any programme or project-specific data management practices or templates also align with the standard.

Where programme or project teams prepare their own implementation plans, they should engage with implementation planning leads at an organisational level to ensure alignment.

3 Using the standard as part of day-to-day work

This section provides suggestions for how data owners, data stewards and reporting managers can use the standard and check compliance on a daily basis.

3.1 Data owners

Data owners should:

assign data stewards to all in-scope data entities
raise awareness of data stewards and their roles throughout programme and project teams
plan for assurance activities to check the quality of programme and project data against the standard

3.2 Data stewards

Data stewards should confirm that data created by the programme or project meets the expectations set by the standard.

To check this, consider:

do all programme and project team members understand the definitions of the data attributes in the standard relevant to their work and are they prepared to create data in line with those definitions?
do guidance and templates used by the programme or project allow users to create data in the expected formats?
are attributes that have Text formats set up to receive only text data?
are attributes that have Date formats set up to receive only dates that meet the validation rules set by the standard?
are attributes that have Numeric formats set up to receive only numeric data?
is data updated in all systems and programme management artefacts according to the minimum update frequency set by the standard?
are metadata attributes captured about programme and project data?
are validation rules enforced at the moment the data is created?
is the data needed for reports updated at least as recently as the minimum update frequency expected by the standard?

Where any of these checks return a negative response, you should take remedial action as necessary.

3.2.1 Remedial actions

Clarifying definitions

If teams do not understand attribute definitions, arrange a briefing or share a summary guide.

Point them to the relevant section of the standard with examples

Updating locally manged templates and guidance

If templates do not allow correct formats, work with template owners to:

add correct field formats (e.g. date pickers for dates, numeric-only fields).
include validation rules where possible.

Notify teams and data owners when updates are made.

Correct invalid data

Reformat incorrect entries (for example, convert” 1st Apr ‘26” to YYYY-MM-DD).

Replace invalid category values with approved list options.

Apply validation rules

Run checks for:

date logic (start date precedes end date)
numeric values (positive, correct scale)
category validity

Correct any errors found before submission or reporting.

Fill gaps in datasets

Identify gaps using the attribute list in the standard.

Request missing values from responsible team members or data owners.

Ensure data is updated appropriately

If data has not been updated in line with the update frequency expectations set by the standard, schedule updates according to the minimum frequency set in the standard.

Automate reminders where possible.

Escalate issues

If systemic problems exist (for example, PPM solution constraints, escalate to your data owner).

3.3 Reporting managers

Prepare reports on programme and project work using data that aligns with the expectations set by the standard. To do this, confirm:

the data entities that you will draw upon to create your report
that the data needed for the report has been updated according to the minimum update frequency set by the standard
that the meaning or format of data points hasn’t been changed by the way in the creation of the report

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