Start with low risk-high benefits initiatives
Prioritise projects that demand low investments but deliver high benefits to demonstrate the value data and analytics can bring to the organisation. By showcasing cost-effective use cases, data leaders can garner support from champions and sponsors and communicate the achievements and benefits of data initiatives across the organisation.
Start small and take incremental steps
Begin by identifying small problems related to cost, compliance, and decision-making speed across the organisation. Gradually build a compelling data story displaying the achievements and value added, incrementally increasing funding with each successful step.
Prioritise functions with spreadsheet overload
Identify functions that waste time working with inefficient tools and demonstrate how data & analytics can help streamline processes. By combining bottom-up and top-down strategies, data leaders can gather support for D&A and request funding from executive leaders.
Provide data for essential business metrics
Align data with critical business metrics to guide funding decisions toward profitable revenue streams and customers. This approach highlights how the right data can drive significant business outcomes.
Leverage AI to drive interest in data
The growing interest in AI technologies presents an opportunity to demonstrate the value of data and drive investment in D&A capabilities, as good AI relies on good data.
Use stakeholders’ language
Effectively advocate for D&A initiatives by addressing stakeholders’ pain points and focusing on the aspects of data most relevant to their roles and interests. Partnering with external experts can help explain how data can drive better business outcomes.
Measuring Data Value and Metrics for ROI
Measuring the value of data remains a controversial subject, but data leaders agree on two approaches for determining ROI:
Identify and quantify business problems and translate them into monetary value, showcasing how data can solve these issues and reduce operational costs.
Negotiate with business leaders to agree on the importance of data for specific projects. Measure the value of data based on the project’s overall value or metrics.