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Data Strategy: What It Is & Why You Need One

In today’s digital age, data is more than just a buzzword; it’s a valuable asset that organisations across all sectors, including social housing, rely on for decision-making, improving services, and achieving their goals. However, without a clear data strategy in place, organisations risk missing out on the full potential of their data. In this quick guide, we’ll explore what a data strategy is, why it’s crucial for organisations in the social housing sector, and the initial steps to design and implement one effectively.

If you’d like to find out more about data strategy then keep an eye on the Guides section of our website as we’ll be publishing a comprehensive whitepaper on this subject in the coming weeks.

Understanding Data Strategy

What is a Data Strategy?

A data strategy is a comprehensive plan that outlines how an organisation will collect, manage, analyse, and leverage data to achieve its objectives. It involves defining goals, establishing processes and procedures, and allocating resources to ensure that data is used effectively throughout the organisation.

Function of a Data Strategy

A data strategy’s primary function is to enable an organisation to achieve its goals and objectives by effectively leveraging data. It provides a roadmap for how data will be used to drive decision-making, improve operational efficiency, and enhance services. Additionally, a data strategy helps organisations mitigate risks associated with data management, such as data breaches or compliance issues.

Mobysoft head of data, Jon Gill says:” Developing an effective data strategy begins, like all business planning, with a clear understanding of your desired outcomes. This context is essential for accurately appraising the current data situation, which  includes coverage, quality, accessibility, usability, as well as governance and security, before defining a targeted roadmap to achieve these objectives.

“Encourage active stakeholder engagement across your organisation when developing your data strategy. Remember, businesses are dynamic entities; as goals, teams, regulations, skills and technology evolve, your data strategy must also adapt. It should be a living artefact, regularly reviewed and updated, to ensure continued outcome alignment and delivery.”

The Importance a Data Strategy for Social Housing Organisations

Why Social Housing Providers Need a Data Strategy

In the social housing sector, data plays a crucial role in delivering quality services to residents, optimising resource allocation, and ensuring compliance with regulatory requirements. A data strategy can help organisations in this sector address the various challenges they face, including:

Resource Optimisation: By analysing data on occupancy rates, maintenance requests, and tenancy information, social housing organisations can optimise resource allocation and better meet the needs of their residents.

Improved Service Delivery: A data strategy enables organisations to gather feedback, track service performance, and identify areas for improvement, ultimately leading to better outcomes for residents.

Compliance and Risk Management: With increasing regulatory requirements around data privacy and security, a data strategy helps social housing organisations ensure compliance and mitigate risks associated with data breaches or unauthorised access.

“Through our client engagements, we see firsthand the critical role data plays in the social housing sector.” says Jon Gill.  “For example, it supports income teams by helping to optimise case presentation, enables the streamlining of repairs for improved customer satisfaction and strengthens the audit trails necessary for regulatory compliance. An effective data strategy supports all of these complex challenges.”

“To ensure data delivers for your organisation, I recommend integrating key business performance indicators (KPIs) such as customer satisfaction measures, directly into your data strategy. By connecting data driven initiatives with KPIs, you will have objective efficacy measures to demonstrate clear business impact and to course correct as required”.

Designing and Implementing a Robust Data Strategy

Initial Steps for Developing a Data Strategy

Define Objectives: Start by identifying the specific goals and objectives your organisation aims to achieve through data-driven initiatives. These could include improving tenant satisfaction, optimising maintenance processes, or enhancing financial performance.

Assess Current State: Evaluate your organisation’s current data infrastructure, capabilities, and processes. Identify any gaps or areas for improvement that need to be addressed in the data strategy.

Engage Stakeholders: Involve key stakeholders from across the organisation, including management, IT, operations, and frontline staff, in the development of the data strategy. Their input and buy-in are essential for successful implementation.

Data Governance Framework: Establish a data governance framework to define roles, responsibilities, and processes for managing and ensuring the quality, privacy, and security of data.

Data Collection and Integration: Determine what data sources are needed to support your objectives and develop processes for collecting, storing, and integrating data from various internal and external sources.

Data Analysis and Insights: Implement tools and techniques for analysing data and extracting actionable insights that can inform decision-making and drive organisational performance.

Continuous Improvement: A data strategy is not a one-time effort; it requires ongoing monitoring, evaluation, and refinement to adapt to changing business needs and technological advancements.

Mobysoft head of data, Jon Gill, suggests that whilst the most compelling aspect of data is arguably its potential to create value, the importance of data quality cannot be overlooked. “High quality data is essential for achieving sustainable, predictable and compliant solutions. For instance, a data-driven strategy aimed at improving customer satisfaction will fail if the data quality is poor, with tenants being provided inaccurate information or recommendations that do not meet their needs.” says Gill.

“To develop an effective data strategy it is therefore crucial to thoroughly assess your current data quality position, to understand possible improvements and limitations, and to establish a continuous monitoring plan. Strategies that assume sufficient data quality are likely to fail, setting unachievable expectations that the available data cannot fulfil.”

“As part of your data quality program, ensure you have consistent data definitions. We recommend implementing a semantic layer to enhance data understanding within your organisation. Doing so will not only help eliminate data misunderstandings but also empower the wider business – including income officers, repairs operatives, and finance teams – to play their part in maintaining and improving data quality.”

By following these initial steps and incorporating feedback from stakeholders, social housing organisations can develop and implement a robust data strategy that enables them to leverage data effectively to achieve their goals and better serve their communities.

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