Data Leaders members can access the full summary of this discussion via the Data Leaders Hub.

Data platform adoption in large organisations presents significant challenges. Many organisations struggle to integrate data platforms effectively, facing resistance from stakeholders, technical hurdles, and funding limitations.

To unfold effective strategies for driving platform adoption, Data Leaders convened experienced data practitioners to advise a client that had implemented a unified approach to break away from siloed data management practices. This approach led to the creation of a robust data platform built on data mesh principles. With the platform now operational, the Data Leaders client sought guidance on promoting widespread adoption across the organisation.

A framework emerged from the discussion, offering practical strategies to guide organisations through the complexities of data platform adoption.

Peer Insights

Data Leaders’ accelerator discussions are vendor-free, giving CDOs a confidential space to share their experiences openly.

The following framework was created from the combination of strategies and approaches shared by a selected group of experienced data leaders, focusing on building strong foundations, fostering a data-centric culture, empowering users, securing funding, and motivating stakeholders to embrace and utilise the platform effectively.

1. Foundations

Align the data strategy with business goals, build a robust technical infrastructure, and clarify roles and responsibilities, placing data owners and stewards in the different business domains. This creates a foundation for seamless data platform integration and business alignment.

2. Data-Centric Culture

Foster data literacy, integrate a business glossary for consistency and involve business stakeholders in requirements gathering. Encouraging platform advocacy by creating intermediate roles or a dedicated team to engage with different departments and appointing ambassadors helps build a culture that values data.

3. User Empowerment

Empower users by providing a semantic layer to democratise data access and reduce dependency on engineering resources, allowing analysts (or data-fluent users) more control over the semantic layer through the decentralisation of parts of the governance model, and adopting flexible governance based on specific needs and maturity levels of all different organisational functions to support the distinct data personas and domains.

Streamlining resource access to expedite decision-making processes due to easy data access via the platform is also key to this pillar.

Finally, data leaders must target users with decision-making power and ensure that the data delivered aligns with the user’s role.

4. Financial Alignment

Two contrasting data platform funding models were highlighted in this discussion: decentralised (departmental budget autonomy) and centralised (director-controlled budget allocation). The strategies shared for each funding model involve aligning with organisational financial structures to secure consistent funding for data platform initiatives.

For instance, to align with a decentralised budget model, data leaders can adopt a cost recharge mechanism: for every data-related use case or demand, the associated cost is recharged back to the respective department’s budget. On the other hand, to align with a centralised budget model, data leaders must adopt a proactive approach by engaging with other function heads to secure potential backup budgets in case the original allocation is diverted.

5. Key Levers to Drive Motivation

Drive platform adoption by highlighting the benefits and value of platform adoption, demonstrating the risks of non-adoption, and tracking success with clear metrics. Engaging stakeholders with use cases, incentives, and compliance considerations motivates and sustains platform use.

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