S5 | Ep 43 | Measuring for Success with Sarah Hardison, Product Director, Analytics Enablement at GSK.

In Episode 43, of Season 5 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Sarah Hardison. Product Director, Analytics Enablement at GSK where they discuss the results from a research project on the investment and value in Data and AI that was conducted to support an MBA Thesis in partnership with University of Cambridge, which includes;

• Why aligning data and AI initiatives with overarching business strategy is the most critical factor for success, with 80% of respondents citing it as essential to delivering value.
• How failing to measure value directly correlates with an inability to demonstrate impact. All organisations that had not shown value also reported not tracking any metrics.
• Why only 50% of surveyed organisations reported actively measuring the value of their data and AI initiatives, despite it being foundational to demonstrating return.
• How 65% of participants believed they had successfully demonstrated value. The remaining 35% had not, and all of those lacked measurement frameworks.
• Why cost reduction and revenue generation were reported as the primary ways value is defined, yet only a few sectors could clearly demonstrate revenue impact.
• Why metrics such as customer satisfaction and innovation are harder to quantify but still considered essential soft indicators of value.
• How the perceived value of data as an asset varies depending on business context and use case, making standard valuation challenging.
• Why telling success stories and communicating achievements across the business was identified as a critical enabler for cultural adoption and stakeholder engagement.
• How incremental delivery through proofs of concept helps secure long-term value and supports agile execution.
• Why business cases are more compelling when they include both financial metrics and alignment with strategic objectives.
• How the cultural orientation of a company, whether strategy-driven or metrics-driven, should guide how data leaders approach value articulation.
• How networking internally and understanding business pain points leads to more relevant and supported data solutions.
• Why data’s value is similar to that of brand equity, being intangible, influential, and entirely context specific.

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