Powering Self-Service Analytics: How a Single Data Universe Drove Efficiency and Growth

Our client is a major energy provider in New Zealand focused on delivering sustainable energy solutions.

As the organisation expanded, it needed a Single Data Universe to streamline operations, enhance decision-making, and enable self-service analytics at scale. By consolidating data sources and improving reporting capabilities, the organisation aimed to unlock greater efficiency, empower business users, and deliver long-term business value.

The Challenge

Managing their data effectively became increasingly difficult as the organisation relied on multiple tools and fragmented systems. The lack of a unified platform made collaboration inefficient, delayed insights, and resulted in inconsistent data usage. Without a structured governance framework, users struggled to trust and leverage data for decision-making.

Some of the key challenges they faced were:

Complex Toolset: Multiple platforms (SAS, Tableau) increased inefficiencies and operational costs.
Data Fragmentation: Siloed data across platforms made collaboration difficult and slowed value creation.
Slow Time to Insight: Delayed data processing impacted decision-making speed.
Lack of Governance: No formal governance process led to inconsistent data usage.
User Confidence & Training Gaps: Business users lacked confidence in the data and required training to self-serve insights.

‍

Our Approach

The Data Insight team implemented a Single Data Universe, consolidating all data sources into a centralised platform to improve accessibility, decision-making, and efficiency, while creating a strong foundation for scalable self-service analytics.

The project began with a discovery and scoping phase to identify key use cases and align business needs with a structured transformation roadmap.

A modern data architecture was developed in collaboration with a co-op partner, allowing seamless enterprise-wide access to trusted data. Over 15 Power BI dashboards were created following Data Insight’s visualisation best practices, making insights easier to access, understand, and action through self-service.

To support consistency and trust, a data governance framework was introduced. This ensured integrity across the data ecosystem and enabled safe, repeatable use of data products for self-service analytics.

To drive adoption, a capability uplift programme trained more than 75 users through analyst training sessions and drop-in clinics. These initiatives empowered staff to explore data with confidence and reduced the organisation’s reliance on technical teams. The project was delivered using an agile approach, allowing for rapid iteration and prioritisation of high-value outcomes.

‍

The Outcome

By unifying its data ecosystem, the organisation achieved a streamlined reporting process, stronger governance, and a self-service culture. Business users now have greater confidence in their insights, and decisions are faster, more accurate, and less dependent on technical resources.

The capability uplift ensured the internal team can sustain and expand data initiatives independently, while operational efficiencies and cost savings continue to generate long-term value.
‍