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Case Study

Harnessing Data to Support Growth and Strategic Goals in Community Housing

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Table of Contents

  • Summary

This case study explores how a leading community housing provider addressed challenges related to data integration, accessibility, and governance following acquisitions and organisational changes. The organisation faced complexities in consolidating data from acquired entities and managing data associated with divested business units. By developing a comprehensive data strategy, Transform LogiQ ensured that the organisation’s digital landscape was safeguarded while advancing its strategic and customer-centric goals. Key outcomes included improved data availability, accessibility, confidentiality, and integrity, enabling better decision-making and operational efficiency.

The Client

A prominent not-for-profit organisation in the community housing sector, committed to providing affordable housing and support services across Australia. With a growing portfolio of properties and services, the organisation encountered challenges in managing disparate data sources following the acquisition of new entities and the divestment of business units. These challenges highlighted the critical need for a robust data strategy to integrate legacy systems, standardise access controls, and ensure effective governance.

The Challenge

The organisation faced significant challenges in managing its data effectively, particularly following acquisitions and divestments. These issues are not unique to the community housing sector but are reflective of broader trends in industries grappling with rapid organisational change and increasing data complexity. Key challenges included:

  • Unorganised, Siloed Data from Acquired Entities: Newly acquired entities brought fragmented and siloed data that required integration into the primary organisational systems. This lack of cohesion led to inefficiencies and made it difficult to utilise the data for strategic purposes.
  • Divestment Data Gaps: Business units were sold without clear processes to manage the data associated with these transactions. This created risks around data loss, mismanagement, and privacy breaches, exacerbating compliance challenges.
  • Delayed Integration of Acquired Data: An entity acquired many years ago had only recently been consolidated from an IT perspective, leaving financial and data systems misaligned. This delay hindered operational effectiveness and strategic decision-making.
  • Misunderstandings Around Data Integration: Integration efforts focused heavily on people and processes but often neglected critical technical aspects, such as legacy systems, access controls, and data governance frameworks. This gap amplified risks and reduced the effectiveness of integration efforts.
  • Data Privacy and Security Risks: Sensitive client data, particularly related to individuals with complex needs and medical or personal circumstances, required a higher level of protection. Ensuring privacy across external departments and multiple physical locations posed significant challenges.

These issues reflect broader industry trends, where organisations struggle with fragmented data systems, limited connectivity, and inadequate governance frameworks. Without addressing these challenges, the organisation risked inefficiencies, non-compliance, and an inability to fully leverage data to achieve its strategic goals.

The Approach

Transform LogiQ’s methodology focused on developing a tailored data strategy aligned with the client’s organisational objectives, leveraging the Data Value Chain framework to demonstrate how data-driven actions directly impact business value. This framework helped the client understand the importance of treating data and information as valuable assets and provided a foundation for actionable steps to increase the utility and value of their data.

Strategic Framework and Methodology
  • Data Value Chain: The client was introduced to the concept that business value is derived from actions driven by reliable data. This strategy emphasised initiatives that enhance the quality and accessibility of data, ensuring that the organisation’s decisions are rooted in accurate and actionable insights.
  • Future State Vision: A dual approach was designed:
    • Bottom-Up Methodology: Focused on sourcing and storing data securely to ensure its accuracy and reliability at the ground level.
    • Top-Down Alignment: Ensured data initiatives were closely tied to the organisation’s overarching strategic objectives, transforming data into a driver of operational efficiency, customer satisfaction, and regulatory compliance.
Initiatives for Transformation

High-level activities were designed and categorised under key data management initiatives to guide the client’s transformation efforts:

  1. Data Quality Management: Establish processes to maintain accuracy, consistency, and reliability of data.
  2. Data Catalogue and Metadata Management: Implement a system to track and manage data assets and metadata, enabling better data discovery and utilisation.
  3. Data Storage & Lifecycle Management: Develop policies for secure data storage and lifecycle management to optimise costs and enhance efficiency.
  4. Data Integration & Interoperability: Address the challenges of fragmented systems by enabling seamless data integration across platforms.
  5. Data Analytics & Business Intelligence: Build capabilities to derive actionable insights from data to improve decision-making.
  6. Data Security & Privacy: Implement robust frameworks to safeguard sensitive client data and ensure compliance with privacy regulations.
  7. Master Data Management (Single View of Customer): Create a unified, consistent view of customer data to enhance service delivery and strategic planning.
Performance Measurement

To ensure the effectiveness of the strategy, Transform LogiQ worked with the client on developing provided sample KPIs with clear explanations, enabling the client to systematically measure progress across their data initiatives. This focus on quantifiable metrics supports accountability, drives continuous improvement, and ensures alignment with information governance standards.

Action Plan and Timeline

An action plan was developed, outlining data initiatives organised by strategic pillars and prioritised based on dependencies and impact. The timeline provided a clear sequence of activities, ensuring that foundational initiatives were completed before advancing to subsequent phases, maximising the efficiency of implementation. By adopting this structured and comprehensive approach, the client was equipped with the tools, frameworks, and guidance to transform their data management practices, ultimately enhancing operational efficiency and aligning data initiatives with their organisational goals.

The Results

Although quantifiable results are not yet available, the client has experienced several qualitative benefits from implementing the data strategy. These include:
  • Improved Capabilities in People, Processes, and Technology: The organisation has enhanced its ability to deliver customised, privacy-conscious services by developing the skills of its workforce, optimising processes, and leveraging modern technologies. This has positioned the client to meet regulatory requirements and better serve customers with complex needs.
  • Cultivation of a Data-Driven Culture: Continuous training initiatives and the introduction of a unified data ecosystem have fostered a culture of collaboration and data-driven decision-making. This cultural shift has improved task performance, reduced inefficiencies, and streamlined processes across departments.
  • Clear Roadmap for Data Governance Improvements: The prioritised action plan has provided the client with a structured and strategic approach to addressing data challenges. By organising initiatives by strategic pillars, the client is able to systematically improve data accessibility, enhance data security and compliance, and achieve a single view of customer data.
  • Enhanced Decision-Making Capabilities: With a focus on data quality and governance, the client now has a more reliable and accurate foundation of data to support critical decision-making processes. This has boosted operational efficiency and the ability to make informed, timely business decisions.
  • Increased Organisational Alignment: The top-down and bottom-up alignment of data initiatives with business objectives has helped integrate data management practices into the organisation’s strategic goals, ensuring that data initiatives are relevant and impactful.
These outcomes reflect a significant step forward in the organisation’s journey toward leveraging data as a strategic asset, improving their ability to deliver outcomes aligned with customer and organisational priorities.

Lessons Learned/Best Practices

Although quantifiable results are not yet available, the client has experienced several qualitative benefits from implementing the data strategy. These include:
  • Improved Capabilities in People, Processes, and Technology: The organisation has enhanced its ability to deliver customised, privacy-conscious services by developing the skills of its workforce, optimising processes, and leveraging modern technologies. This has positioned the client to meet regulatory requirements and better serve customers with complex needs.
  • Cultivation of a Data-Driven Culture: Continuous training initiatives and the introduction of a unified data ecosystem have fostered a culture of collaboration and data-driven decision-making. This cultural shift has improved task performance, reduced inefficiencies, and streamlined processes across departments.
  • Clear Roadmap for Data Governance Improvements: The prioritised action plan has provided the client with a structured and strategic approach to addressing data challenges. By organising initiatives by strategic pillars, the client is able to systematically improve data accessibility, enhance data security and compliance, and achieve a single view of customer data.
  • Enhanced Decision-Making Capabilities: With a focus on data quality and governance, the client now has a more reliable and accurate foundation of data to support critical decision-making processes. This has boosted operational efficiency and the ability to make informed, timely business decisions.
  • Increased Organisational Alignment: The top-down and bottom-up alignment of data initiatives with business objectives has helped integrate data management practices into the organisation’s strategic goals, ensuring that data initiatives are relevant and impactful.
These outcomes reflect a significant step forward in the organisation’s journey toward leveraging data as a strategic asset, improving their ability to deliver outcomes aligned with customer and organisational priorities.

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