Case Study

Big 4 Bank: Federated Data Operating Model

Building a modern data mesh through a Federated Data Operating Model for driving demand of a new data platform. ​

At a Glance

DigiRen helped a major Australian bank drive demand for its new data platform by designing a user-led Federated Data Operating Model. Through stakeholder engagement and backwards design from real use cases, DigiRen defined roles, responsibilities, and collaboration mechanisms—enabling clarity, federated ways of working, and stronger alignment across data teams. The result: increased platform adoption and a united data community ready to deliver value at scale.

Yes
Defined federated ways of working​
Yes
Clarity and direction for the data community​
Yes
Increased collaboration between core data functions​

Challenge

Our client is one of the largest financial institutions in Australia, serving over 17 million customers with many decades of data. As the bank is looking to ‘build tomorrow’s bank today’ for their customers, the focus has shifted towards data and AI. The bank is undergoing a journey towards a federated data operating model centred around a data marketplace, establishing clearly defined business domains and data ownership.​

As the Bank is pre-occupied with the design and build of data platforms and the marketplace, a state-of-the-art platform loses its value if there is little demand. The Bank needed a federated data operating model that will convince the businesses that the new platform is the easier and best way to transact data between domains/lines of business.

The Challenge for DigiRen

To support driving demand of the new data platform, by understanding potential users and working backwards to design a Target Operating Model.

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Approach

DigiRen leveraged its user-oriented design to define a federated operating model that will foster collaboration between data consumers and producers.​

  1. An understanding of the Consumers/Producers: DigiRen interviewed a few key data consumers/producers and platform owners to understand the sentiment and clarity required to adopt the new platform. ​
  2. Delivering recommendations for federated ways of working: Working backwards from selected tenant use cases, desired user journey and service model, DigiRen recommended the key capabilities and collaboration forums across both platform provider and users of the platform that are essential towards self-sufficiency and federated ways of working.

Outcomes

A user-driven target state: DigiRen collaborated with customer stakeholders across the bank and its partner ecosystem, and defined the target state, roles and responsibilities, service model and incentivisation mechanisms for the producers to create meaningful data products. ​

Engagement of potential user communities: DigiRen’s outputs provided target state clarity that formed the foundation for collaboration between the bank's core data functions (e.g. data platform, data governance & mgmt, customer enablement) and federated data delivery capabilities. The outputs served as inputs to the roadshows that engaged the wider data community and sparked demand for the new, Cloud data delivery platforms.​

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