Housing Data Strategy 2026-2029

Introduction

A data strategy is a structured framework which sets out how an organisation captures, manages, and uses data to achieve its strategic aims and objectives. It ensures a consistent approach to data handling across the organisation.

In order for us to succeed in providing an excellent service, Bassetlaw District Council’s Housing Services must foster a strong culture which recognises the value of data, treats it responsibly, and uses it to drive learning and improvement. Central to this is ensuring that customers are empowered to share their experiences and insights, enabling them to influence services at all levels and remain at the heart of decision-making.

This strategy sets out how Bassetlaw District Council’s Housing Services collects and utilises household data to continuously improve services and protect customers. It focuses on improving customer satisfaction, supporting operational improvement, and ensuring adherence to relevant legislation and regulatory requirements.

Housing Ombudsman

In May 2023, The Housing Ombudsman Service published a spotlight report on knowledge and information management which highlighted poor data quality and inadequate record-keeping as key contributors to service failures and maladministration. The report reinforces the importance of ensuring that data relating to tenants, their households and vulnerabilities, their homes, and service interactions is accurate and effectively maintained.

It is equally important that all data we hold is well organised and readily accessible, enabling the Council to respond quickly to requests from the Housing Ombudsman during complaint investigations, or when providing the evidence required by the Regulator of Social Housing (RSH) during routine inspections.

Scope

This strategy covers the collection and processing of household data associated with tenants of Bassetlaw District Council (‘the Council’) and the properties in which they live.

Development and maintenance of the IT systems the Council uses is covered in the ‘Information & Communications Technology (ICT) Strategy 2024-28’.

Definitions

Data

Data can be defined as raw facts, statistics and figures that have not yet been processed or interpreted. Once the data has been analysed, it becomes useful information that can be used to inform decisions and actions.

Data is usually classified as qualitative (non-numerical and descriptive data) and quantitative (numerical data, such as statistics and percentages). These classifications can be further broken down into four key types of data:

Data Type	Description	Examples
Nominal	Qualitative data that is used to label or name things and doesn’t have any order. It tells you what something is, and not how much or in what order.	Gender, ethnicity, marital status, types of housing, tenure type.
Ordinal	Qualitative data that can be put in order or ranked. In other words, ordinal data shows which comes first, next, and last, but can’t measure the exact difference between them.	Tenant satisfaction levels (e.g. very satisfied, satisfied, neutral, dissatisfied, very dissatisfied), priority bands for housing.
Discrete	Quantitative data which can be counted as whole numbers (1, 2, 3…) and cannot be split into smaller parts such as decimals (e.g. 3.5, 2.6)	The number of tenants in a property, the amounts of complaints received in a week, how many homes in an area.
Continuous	Quantitative data which can be measured rather than counted and is more precise than discrete data.	The amount of rent paid (e.g. £432.54), length of tenancy (e.g. 2.5 years), noise levels (e.g. 34.6 decibels).

‘Customer’ is used to describe named tenants (and their households) of the Council.

‘We’ refers to Bassetlaw District Council.

Current State

How we collect data

Housing online - The customer Housing Online Portal allows customers to report non-urgent repairs and view or amend information relating to their tenancy. The portal is under continuous development to enhance accessibility and user experience, such as identity linkage with third-party authentication platforms (e.g. Google) to allow for easier access, and additional self-service modules so customers can update their details quickly, easily, and at a time that is convenient for them.

Customer engagement - Information is gathered through direct customer engagement across a variety of channels. This includes telephone conversations, during tenancy sign-ups and other face-to-face interactions with tenants, as well as digital forms and online surveys that capture information and feedback.

Partner data sharing - Household data is also collected and enriched through structured data sharing with a range of partner organisations. This includes secure data-sharing arrangements with social care services, health partners, domestic abuse services, supported housing providers, and voluntary sector agencies. All such arrangements are governed by formal Data Sharing Agreements (DSAs) and supported by Data Protection Impact Assessments (DPIAs), ensuring that data is shared lawfully, securely, and in compliance with the UK General Data Protection Regulation (UK GDPR) and the Data Protection Act 2018.

Data we collect

The Council collects and processes both property-based and household-based information, ensuring data minimisation and lawful processing. The table below provides examples of the types of data we process:

Data Category	Data items collected
Tenancy & Customer Data	Contact details and communication preferences Household composition and vulnerabilities Tenancy start/end dates and types Payments and arrears Enforcement action Case notes
Repairs and Property Compliance	Responsive and planned repairs records HHSRS inspection data Stock condition data Electrical and gas safety certificates Fire safety, asbestos, water and lifts compliance data Energy Performance Certificates (EPCs) Void status and re-let dates Contractor data
Community Safety & ASB	Incident reports Case workflows and outcomes Multi-agency safeguarding referrals
Customer Feedback & Satisfaction	Complaints and compliments Tenant scrutiny feedback Tenant Satisfaction Measures (TSMs)

How we use the data

Data is used in accordance with statutory duties under the Housing Acts 1985–2004, the Homelessness Reduction Act 2017, and compliance requirements under the Social Housing (Regulation) Act 2023. It is routinely utilised to:

Ensure tenant safety - By monitoring compliance with the Housing Health and Safety Rating System (HHSRS), as well as making reasonable adjustments for customers who require them.
Support tenancy sustainment - By helping us to identify arrears, vulnerability indicators and ASB patterns early, to enable proactive interventions.
Improve repair services - By monitoring response times, contractor performance and repeat repairs.
Promote transparency - By enabling publication of performance results and compliance information.
Provide regulatory assurance - By producing evidence for the RSH under the Consumer Standards framework.
Inform service improvement - By enabling us to act upon customer feedback and address areas of weakness.

As part of this strategy, we will use the household data proactively in service improvement and develop the ways in which we do this. This includes:

Proactively promoting downsizing initiatives to households who are under-occupying their homes
Flexing the aids and adaptations budget to reflect the level of disability among households
Influencing new-build development programmes to address issues around overcrowding and under-occupation.

Data infrastructure - core platforms currently in use

NEC Housing - NEC is a comprehensive, flexible Housing Management platform which the Council uses to provide a 360° view of customers and assets. It is utilised as our main tenancy, rent, repairs, ASB, and case management system, with a new module for complex inspection cases due to be implemented to support with our compliance with Awaab’s Law.

Power BI (Housing Hub) - Power BI is a Microsoft business intelligence and data visualization platform that converts raw data from various sources (such as NEC) into interactive, actionable reports and live dashboards. It enables staff to access operational intelligence without running technical reports.

Microsoft Copilot - Microsoft Copilot helps staff to derive value from available data more efficiently. It can be used to process and analyses anonymised household data, identify patterns, and generate summaries.

Civica (formerly known as Abritas) - Civica is used by the Council to manage housing our Choice-Based Letting scheme including housing registrations, allocations, and homelessness to better understand housing demand and monitor outcomes.

Workforce capability and data culture

Training and awareness

All staff complete mandatory GDPR and information governance training. In addition, targeted training will be provided to customer-facing colleagues responsible for collecting household data, ensuring they have the skills and confidence to gather information accurately and appropriately. Further training can be made available for those who want or require it by requesting it through the Council’s Learning Hub.

AI Policy

The Council has implemented a corporate AI Policy Framework to guide ethical data use and staff engagement with emerging technologies. This:

Ensures compliance with transparency and accountability principles of UK GDPR by preventing inappropriate processing of personal or sensitive data
Promotes safe testing of automation and AI tools within approved boundaries.

AI Apprenticeships

The Council is exploring development opportunities for staff, including AI apprenticeships, to build in-house capability relating to:

Data management
Predictive modelling
Performance insight development

Aims

Understand our data needs

We will identify gaps in our data which may support service improvement by:

Carrying out an internal data audit to identify weaknesses
Speaking with staff of all levels to understand how they use data to inform their decisions
Giving residents opportunities to scrutinise and feedback on how and why we collect data
Defining clear standards for data completeness, accuracy, and timeliness
Connecting data needs to organisational priorities such as reducing void times and increasing tenant satisfaction

Embed a data culture

We will foster a data culture within the Council’s Housing Services by:

Completing a Knowledge and Information Management (KIM) Self-Assessment to identify strengths and areas of improvement
Completing a Training Needs Analysis (TNA) to identify where data skills development is needed
Based on the outcome of the TNA, provide training for staff to fill any gaps in knowledge and improve data literacy
Promoting data confidence by implementing tools and guidance for data collection and entry
Highlighting where good data has led to better outcomes, and share these internally and publicly
Promoting data awareness by sharing insights and statistics which display how data is used to improve services

Hold accurate data

We will ensure that the data we hold on tenants and our properties is accurate and up to date by:

Continuing to verify and update customer details and vulnerability information during each contact with the Customer Service team
Implementing regular Occupation Visits (3-yearly visits for general needs, annual visits for those assessed as requiring them such as tenants connected to the Lifeline service) with the purpose of collecting up-to-date and robust data about household composition and condition of properties, to enable us to better understand the needs of our tenants and adapt services as required
Increasing participation in the annual tenant census by adding a QR code to the rent statement
Issuing devices to frontline staff to allow system access while undertaking estate visits and tenant support work. This will strengthen data accuracy and timeliness as it allows staff to update records, log repairs, enter case notes, and update vulnerability flags while on site
Promoting the Housing Online portal and encouraging customers to check and update their information regularly
Matching data with trusted external sources where appropriate, to validate key information and ensure services are suitably tailored
Holding staff briefings and management supervision sessions which reinforce data quality expectations

Improve data infrastructure

We will improve our data infrastructure by:

Reducing duplication of work and improving data sharing within the service by linking systems where possible
Upgrade current systems by introducing more integrated, specialised modules to consolidate data into a single platform, making it easier to locate and access information across departments
Reviewing forms and templates to remove unnecessary fields and focus on capturing high-value data
Integrate NEC Housing into Power BI to support more efficient reporting and dashboards
Implement full adoption of SharePoint across the service to support improved accessibility, collaboration, and secure data sharing between teams

Strengthen compliance with regulatory requirements

We will ensure greater compliance with regulatory and legislative requirements by:

Expanding the scope and frequency of reporting to tenants and Members, ensuring a broader range of service areas and performance indicators are transparently monitored
Reviewing and refining our data collection and storage methods to allow for more efficient regulatory reporting
Implementing a rolling stock condition survey programme on a three-year cycle to maintain up-to-date information on the condition of our housing stock
Enhancing audit and scrutiny processes to regularly review compliance and identify areas for improvement
Improving record-keeping practices to ensure clear audit trails and evidence for regulatory submissions and inspections
Making performance data more accessible to the public to support greater transparency and accountability

Improve overall service

We will improve the overall service that the Council’s Housing Service provides by:

Using EPC and fuel poverty data to prioritise retrofits
Embedding predictive analytics within our systems to support early identification of households at greatest risk of homelessness or tenancy failure, allowing for prevention activities
Using repairs data to identify recurring issues and reduce repeat repairs, shorten response times, and increase satisfaction
Analysing void turnaround times by property type, contractor, and location to identify bottlenecks
Ensuring properties are maintained to a consistent and lettable standard
Monitoring data on application and offer processing times to reduce delays
Utilising heatmaps and root-cause analysis to identify trends in ASB, damp & mould, and areas requiring stock investment, allowing for early intervention and effective resource targeting

Compliance

The Council has implemented appropriate technical and organisational security measures, in line with Article 32 of the UK General Data Protection Regulation (GDPR).

Within our approach to compliance, we will ensure that data is accessible to the appropriate individuals, supported by robust security controls to protect sensitive information and maintain confidentiality. At the same time, we will promote a culture of openness where it is appropriate to do so, enabling data to be shared effectively across the Council to support collaboration and informed decision-making.

As part of our commitment to transparency and compliance with data protection legislation, we will ensure that customers are aware of their rights and how to exercise them; this includes providing clear and accessible routes for submitting Freedom of Information (FOI) requests and Subject Access Requests (SARs). Information on how to request access to personal data or other information held by the Council can be found on our website here:

Equality and diversity

Understanding and valuing the diversity of our customers is central to delivering inclusive and equitable housing services. By collecting and effectively using data on household characteristics and individual needs, we can ensure that services are accessible and fair to all tenants. We are committed to removing barriers to access by providing information and services in a range of formats, languages, and channels to suit different needs.

An Equality Impact Assessment (EIA) has been completed for this strategy and has identified no adverse impacts on customers with protected characteristics. It is expected that the strategy will have an overall positive impact by making greater use of data to improve delivery of services.

Review

An annual review of this strategy will be carried out by the Strategy and Engagement Team, to assess progress against its aims.

Related Council Policies and Strategies

Key Legislation and Regulation Frameworks

UK GDPR & Data Protection Act 2018
Social Housing (Regulation) Act 2023
Awaab’s Law
Equality Act 2010
Housing Acts 1985 & 1996

Version Control

Version 1.1 - 14/07/2026.

Last Updated on Friday, July 24, 2026