Data Capability by Design | Mosaic Auckland, NZ

Our Approach

Organisations need to manage, govern, and utilise data to enable data-driven business decisions and actions.

At Mosaic, we take a design-led approach to solving complex data-centred organisational challenges by uplifting data capability.

Data capability is more than technology; it’s an alignment process that sits within a wider nexus of moving variables.

At Mosaic, data capability means intentionally aligning:

data strategy and operating models
data architecture and platforms
governance and data quality
analytics and business use cases
selection and procurement of data platforms

Data capability isn’t a separate function; it needs to be embedded by design into how an organisation operates.

Why a mature Data Capability is important

It’s natural to assume that investing in data platforms and analytics tools is enough. In practice, it’s the fragmented processes, unclear ownership, and siloed data that typically prevent organisations from realising value from their data.

Building data capability from the start allows organisations to have:

Early identification of data issues: knowing how, when, and by whom data is used and owned helps resolve issues before they affect reporting and decision-making.
Improved data consistency and trust: clear definitions, governance, and quality controls ensure data is fit for purpose.
Better decision-making: access to trusted and timely data supports more informed and actionable business decisions.
Regulatory alignment: a structured approach to data supports compliance with regulatory expectations and reporting requirements.
Enablement of analytics and AI: sound data practices underpin the successful expansion of analytics and AI initiatives.

A mature data capability closes the gap, giving you trusted data, clear ownership, and the confidence to act on it.

Mosaic Data by Design

We recognise that each organisation is unique, and many are still developing their data capability.

Our Data by Design approach provides a pragmatic, business-relevant framework. We focus on building your data capability across four key areas:

Data Advisory — defining strategy, operating model, and roadmap
Data Foundations — enabling scalable data platforms and architecture
Data Trust — ensuring data quality, governance, and compliance
Data Value — unlocking insights, analytics, and AI opportunities

We apply these principles in a way that supplements business objectives. Data by Design is intended to enable better outcomes, not introduce unnecessary complexity.

How We Work

We work in a consultative and tailored manner, starting by understanding:

your business objectives and priorities
your current use of data across the organisation and beyond
your data architecture and operating environment
your regulatory and reporting obligations

We then design a practical approach to uplift your data capability across your organisation, aligned to your current maturity and future goals.

This ensures that improvements are:

achievable and scalable
aligned with your business needs

Client Work Examples

We’ve partnered with banks, funds managers, and other regulated organisations to solve real data challenges; from regulatory response and remediation through to platform selection and privacy uplift. A selection of our work includes:

Data lineage and classification (major bank) — led a programme responding to Australian regulatory requirements (CPS 234), scaling to a team of 15 at peak.
Regulatory remediation (major bank) — remediation across both customer disclosures and underlying calculations.
Fee review and remediation (major bank) — CCCFA-aligned fee review and remediation.
Pricing remediation (funds management) — ongoing pricing remediation programme.
Data privacy, consent and deletion (financial services) — assessed gaps in existing privacy processes across consent capture, management, and data deletion and retention, and produced an 18-month uplift programme to align with Privacy Act 2020 requirements.
End-to-end data platform uplift (leading NZ automotive brand) — played a key role, as part of a wider delivery team, in data platform tooling selection and procurement, maturity assessment, capability uplift, and platform decommissioning and migration.