Policy paper

OPSS Data Strategy 2022-2025

Published 25 July 2023

Purpose and aim

This is the first full data strategy for OPSS, reflecting the importance of data to our organisation. Whilst it is the first time we have published a strategy, this document builds on work we have been undertaking since 2018.

The purpose of this strategy is to direct our data programme by setting out OPSS’ ambition, approach and priorities, as well as provide transparency about our approach to the partners we work with, to those we regulate and to those on whose behalf we act, consumers and the public.

Our ambition is to embed good use of data into who we are and how we operate, improving our data maturity as an organisation. We are committed to using the power of data to deliver our organisational purpose.

The focus of this strategy is how we will use data to deliver our policy and regulatory functions. As the National Data Strategy acknowledges, data is notoriously difficult to define and means different things to different people. For clarity, this strategy covers the administrative and operational data collected in the course of delivering our policy and regulatory responsibilities, as well as analytical and statistical data that helps us make decisions and measure our impact.

Read the National Data Strategy.

The aim of our data strategy is to:

• value the role of data in enabling us to achieve our strategic outcomes by
• actively using data products to inform our choice of the intervention needed to
• drive behaviour or a change in behaviour, including consumer action and business compliance

The strategy is supported by an internal data programme, a series of clear and measurable actions that we are undertaking over the next period. These actions are summarised in this strategy.

Introduction

The role that data plays in our everyday lives has grown exponentially in the last few decades – how we communicate with friends and family, shop for daily essentials or learn new skills. We create data in enormous quantities and through processing, analysis and deploying data, we can all make more informed decisions, understand our choices and measure the impact of those decisions. This is especially important for regulatory bodies, charged with protecting people, ensuring fairness and creating level playing fields.

In our first product safety strategy, we set out the importance of data in our role as a product safety regulator – captured through the four building blocks of our regulatory approach – Analyse, Inform, Enforce, Build. Since publication of that strategy in 2018, we have been building our data capability in a number of ways, including:

• Establishing a dedicated Analysis functional group within OPSS, bringing together specialist skills and capabilities in data science, statistics, social research and economics.
• Delivering a Strategic Research Programme which has built our knowledge base.
• Signed agreements with partners and third parties to increase our access to external data.
• Built digital infrastructure to improve the capture and exchange of data relating to product safety risk.
• Built internal systems to improve data storage and introduced a Data Library to index relevant data sets.
• Introduced new learning and development opportunities for staff to improve confidence in using data effectively.
• Commissioned a data architecture review to inform future technology choices Introduced new internal structures to improve data governance.

These early steps are providing important foundations but we recognise that there is still much to do if we are to achieve the ambition of our new OPSS Product Regulation Strategy. As a relatively new organisation, we want to seize the opportunities to learn from others’, as well as harness the potential of technological tools, in driving forward our data capability.

Read the OPSS Product Regulation Strategy 2022-2025.

Context: National Data Strategy

In late 2020, Government published the National Data Strategy, setting out how best to unlock the power of data for the UK through five priority areas of action, including to transform government’s use of data to drive efficiency and improve public services. The strategy also identifies a number of opportunities for data to positively transform the UK, including driving better delivery of policy and public services.

Public services are complex to deliver… engaging with millions of people across the UK every year. Likewise, keeping people safe requires access to the right information. These services and capabilities rely heavily on data, but the systems that handle this data have grown iteratively and independently, increasing in complexity over time. Many legacy systems are out of date, costly to operate and incapable of exchanging data with one another, presenting challenges in a world where public services are increasingly interconnected.

For central government, better data also means better decision-making. It means policies that can be tailored and delivered more efficiently and significant savings for the public purse. Better evidence on whether policies are delivering their intended effects in different areas and for different groups means interventions can be far more effectively designed. This aligns with the public’s new expectations in our increasingly digital context.

The OPSS Data Strategy is aligned to these wider cross Government actions and objectives of the National Data Strategy, and the organisational objectives of OPSS.

Context: OPSS Strategic Framework

Our primary purpose is to protect people and places from product-related harm, ensuring consumers and businesses can buy and sell products with confidence. We use science, evidence, and data to shape our interventions. We act proportionately, guided by the risk of harm, and seek to minimise complexity and cost for businesses and consumers.

We deliver our responsibilities in line with our guiding principles, many of which emphasise the importance of data to deliver our focus on real world outcomes, evidence-based policy development, joined up regulation and fair, competitive and innovative markets that enable choice for consumers.

• We put protection first – being driven by real world outcomes for consumers, citizens, and the environment.
• We hold business to their responsibilities – being clear that the legal obligation to provide safe and compliant products sits with them.
• We support responsible business – in their compliance, in their success, in their growth, and in product innovation.
• We join up product regulation – to deliver coherent and efficient enforcement for the benefit of consumers and businesses.
• We focus on risk and the management of risk – recognising that not all risks can be eliminated and establishing our risk-based approach to prioritise resources.
• We make decisions based on science and evidence – ensuring that in-depth knowledge and understanding shapes product regulations and their enforcement.
• We establish the right systems and relationships – to support regulatory outcomes through effective engagement between the state, businesses and citizens.
• We follow the principles of good regulation – being proportionate, accountable, consistent, transparent, and targeted in our actions.
• We act promptly and target the right points for intervention – taking robust action, identifying where the greatest impact can be achieved, and seeking to head off problems before they occur.
• We recognise the different needs of different groups – making sure that product regulation, product design, enforcement, and advice takes account of the needs of different citizens and different types of citizens
• We measure our impact – so that we know what works and demonstrate value for money.

Strategic data challenges: the pillars

The National Data Strategy identified a number of interconnected challenges which currently prevent the best use of data in the UK:

1. Data foundations: The true value of data can only be fully realised when it is fit for purpose, recorded in standardised formats on modern, future-proof systems and held in a condition that means it is findable, accessible, interoperable and reusable. By improving the quality of the data, we can use it more effectively, and drive better insights and outcomes from its use.
2. Data skills: To make the best use of data, we must have a wealth of data skills to draw on. That means delivering the right skills through our education system, but also ensuring that people can continue to develop the data skills they need throughout their lives.
3. Data availability: For data to have the most effective impact, it needs to be appropriately accessible, mobile and re-usable. That means encouraging better coordination, access to and sharing of data of appropriate quality between organisations in the public, private and third sectors, and ensuring appropriate protections for the flow of data internationally.
4. Responsible data: As we drive increased use of data, we must ensure that it is used responsibly, in a way that is lawful, secure, fair, ethical, sustainable and accountable, while also supporting innovation and research.

Read the National Data Strategy.

Strategic data challenges: application to product regulation

In applying the four pillars of challenge from the National Data Strategy to OPSS, we have identified the following issues. We note many of these challenges are widely applicable to regulators and we will work closely with other regulatory agencies both to learn from, and to share our own experiences.

• Systematic legal, cultural and technological data sharing challenges, including the lack of common data standards and poor data quality. (Foundations)
• The complexity of regulated sectors in terms of the number of actors, differing operating models, legal responsibilities and incentives. (Foundations)
• Information asymmetry often occurs due to complexity of product design manufacture which needs correction through regulatory intervention. (Foundations)
• The regulatory regime has few touch points between the regulator and regulated entities (such as registration or licensing) which limits data collection. (Availability)
• The limited availability of regulatory data can lead to an overreliance on partner or third party data. (Availability)
• There can be issues of trust and a lack of incentive for industry to voluntarily report information that can assist in building better pictures of emerging issues. (Responsible)
• The changing nature of consumer behaviour and the diversity of need. (Responsible)

Strategic objectives

Overall through this strategy, we wish to develop our data maturity as an organisation – identifying data gaps, improving data exchange and embedding data into our decision making processes across our policy and regulatory functions to enable us to better deliver our organisational outcomes. To provide focus to this strategy, we have four specific objectives:

1. To sharpen our understanding of the regulatory landscape and key actors, through the acquisition and development of data sources and reviewing legal obligations for information notifications under relevant legislation.
2. To ensure the effective governance and deployment of data we own and share with others, through improved consistency and use of common data standards, as well as upskilling staff in key data skills.
3. To use data analytics and data products to inform policy development and delivery, and drive behavioural change in consumers, businesses and the public, through greater evidence of what works in practice.
4. To use trend and predictive data to target our regulatory activity according to risk, as well as improve opportunities for early intervention.

These objectives span across the various stages of the data lifecycle, as set out in the Government Data Quality Framework.

Our approach – working across the data lifecycle

Our approach: assessing our data needs

The OPSS regulatory approach is underpinned by the Regulatory Delivery Model, a model that describes the prerequisites and practices that need to be in place to enable good regulatory delivery. We have structured our data needs assessment around the three regulatory practices of the model – outcome measurement, risk assessment and intervention choice.

Regulatory delivery model practices

Regulatory questions we are seeking to answer:

Outcome measurement	Risk assessment	Intervention choice
What has changed as a result of our intervention?	What risks are caused by specific products? What impacts the likelihood of compliance in scenarios? Which products carry unacceptable risk?	What regulatory and non regulatory tools do we have to tackle issues of non-compliance? Which tools are the most effective in scenarios?

Example data types or datasets required to answer regulatory questions:

Outcome measurement	Risk assessment	Intervention choice
OPSS administrative and operational data	Hazard data – by product type, by harm type (e.g. choking, electrocution)	Legislative powers and tools available to the SoS/ regulator
Evaluation studies measuring compliance levels pre and post specific interventions	Production data (scale)– volumes of products, manufacturing/ distribution/ supply by sector, product origin, business type	Behavioural insight studies and control trials to measure responses
Surveys of regulated entities and beneficiaries e.g. impact on confidence levels	Population data (scale) – by business type, product type, consumer population, diversity, vulnerability	Systems mapping – understanding system actors and influence
	Compliance data – e.g. product testing failure rates, product seizures at points of entry

Objective 1: Sharpening our Understanding

This objective is focused on sharpening our understanding of the complexities of the regulatory landscape, including addressing priority data gaps and investing in behavioural science to better understand key actors and beneficiaries.

In summary, we will:

• Identify priority data gaps and agree data sharing arrangements, building on our early work with partners such as London Fire Brigade.
• Explore policy and legislative opportunities to improve data flows, including through the consultation on the Product Safety Framework and the development of the Building Safety Bill (construction products).
• Review and refine innovative approaches to sourcing data through partners, including initial work undertaken on hospital data with the NHS.
• Use our Strategic Research Programme, industry and consumer surveys and other relevant data sets to further strengthen our knowledge of product sectors, as well as improve our understanding and identification of consumer vulnerability and business segmentation.
• Develop our data approach to open policy making and widen our stakeholder networks to continually sharpen the impact of our policy setting, including working with relevant international organisations.
• Embed the importance of data in our project and activity planning, so data needs are considered at project inception.

Objective 2: Effective Governance and Deployment of Data

This objective focuses on improving data governance and data quality to ensure effective use and control of data we own and share with others.

In summary, we will:

• Engage with the Government Data Quality Hub to evaluate our baseline data maturity as an organisation, identifying priorities for improvement.
• Establish clear roles and accountabilities within OPSS for data quality and provide a central source of advice and support for staff in use of data.
• In line with Government Open Standards, adopt common data standards to assist in building a shared data model across the organisation.
• Strengthen networks with other regulators and government departments to facilitate data exchange and the development of data processes.
• Roll out the OPSS Data Library across OPSS to provide an index of all data sets held and data owners, with improvements to functionality iterated over time.
• Embed Microsoft Dynamics as OPSS’ case management system, leading to improved operational data capture and removal of legacy systems. This will include consideration of appropriate migration and archiving of legacy data.
• Explore greater automation of data exports from key OPSS IT systems.
• Embed training and guidance for OPSS staff on use of data, using the results of a skills audit to prioritise needs.

Objective 3: Inform Policy and Drive Behavioural Change

This objective focuses on using data science and data outputs to inform policy making and drive behavioural change in consumers, the public and businesses, based on greater evidence on what works in practice.

In summary, we will:

• Expand our social research team to provide leadership and capability to embed evaluation approaches across OPSS activities and programmes.
• Embed the use of logic mapping and post event evaluation to track the differential impact of different regulatory interventions.
• Explore using innovative approaches, such as quasi-experiments and randomised controlled trials, to assess the possible impact of different interventions and inform decisions.
• Use public information campaigns to address safety issues, using behavioural science and evidence to design effective messages and mediums, including the ability to target specific groups to address vulnerabilities.
• Use knowledge gained on business segmentation to design innovative approaches to communicate regulatory requirements to different businesses.
• Continue the publication of OPSS data, research and analysis to assist businesses in compliance and consumers in informed choices.
• Introduce metrics which highlight outputs of OPSS and tie to our broader strategic goals.

Objective 4: Target our Regulatory Activity

The focus of this objective is to strengthen our tools and approaches to enable us to target our regulatory activity according to risk and improve the potential for early intervention.

In summary, we will:

• Produce an annual Strategic Intelligence Assessment and Control Strategy for product safety and other areas of product regulation, ensuring these intelligence products are informing decision making in OPSS. Bring Strategic Intelligence Assessment to the attention of local authority trading standards to inform relevant regulatory activity.
• Embed PRISM, a new UK risk assessment methodology for products that replaces the EU based RAPEX methodology, which will provide a more holistic view of the product, including matters relating to its prevalence and capacity to harm non-users.
• Explore use of innovative data science techniques (e.g. machine learning) to become more predictive and make earlier interventions.
• Utilise relevant data from other regulators to assist in targeting our own regulatory activity.
• Continue to iterate our use of tactical tasking and incident structures within OPSS to ensure that intelligence and data is able to inform operational decision making.
• Use of operational performance monitoring data to assess the effectiveness of OPSS regulatory interventions (e.g. changes in compliance rates over time).
• Build an international network of product safety regulator contacts, actively seeking opportunities to facilitate information-sharing with them and joint research.

Governance: OPSS data principles

Our approach is informed by the Government Data Quality Framework and underpinned by the following principles:

• Value – we understand why we collect the data, the purpose and the link to our strategic objectives, as well as the costs of data.
• Quality – we seek to drive up the quality of the data we collect and base our decisions on.
• Integrity – we act with integrity, and in accordance with legal requirements, in our handling, use, application, retention and disposal of data.
• Transparency – we are transparent in why we are requesting data and how it may be used.
• Open – we seek to open our data up to enable reuse by others in support of our outcomes – informed consumers, compliant businesses.
• Accessible – we seek to create an accessible, security compliant infrastructure to ensure all teams in OPSS have access to the data they need.

We recognise the potential burden and cost that data reporting places on industry. In the context of the need to increase data reporting to improve data availability and quality, we aim to ensure data reporting requirements are developed in a manner that is mindful and focused to avoid unnecessary burden.

Measuring our impact

We want to ensure this strategy is delivering against our ambitions. Together with the ONS Data Quality Hub’s data maturity assessment model, we will measure success against a short set of measures:

Leadership and culture

• Are staff engaged with OPSS data processes or systems?
• Are senior leaders across OPSS demonstrating leadership and commitment to data?

Skills and capability

• Has appropriate training been completed? Have we equipped our people with the right skills and development? (including compliance with UKGDPR training requirement)
• Do we have OPSS Information Managers identified and active?

Tools and architecture

• Do we have the information/tools we need?
• Have we addressed our priority data gaps?
• Have we mapped current systems/ processes for data use, sharing, storage towards our aim of simplification and consolidation?

Quality and standards

• Have we adopted common data standards?
• Do we have a system in place for data governance, and processes understood by staff?
• Are we routinely publishing research, in line with Government guidelines?

For further information on the OPSS Data Strategy please contact: opss.enquiries@beis.gov.uk.