Hub & Spoken: Data | Analytics | Chief Data Officer | CDO | Data Strategy Embedding value into data and AI initiatives from day one
Jun 26, 2025
The discussion dives into the critical importance of embedding real value in data and AI initiatives right from the start. It emphasizes the shift from vague aspirations to concrete outcomes that truly impact stakeholders. The host shares a practical approach focused on collaboration, clear intent, and continuous evaluation to drive meaningful results. Real-world examples illustrate how organizations can move from theoretical concepts to actionable strategies, ensuring their data efforts genuinely make a difference.
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Embed Value From Project Start
- Value must be embedded from the start of data and AI projects, not added later.
- Treating value as an afterthought risks initiatives falling flat or missing real impact.
Value Is Contextual and Specific
- Value is contextual and varies across organizations, teams, and situations.
- Clear upfront definition is crucial to avoid vague interpretations and ensure alignment.
Weight Loss Analogy for Inputs
- Weight loss illustrates the importance of managing inputs rather than obsessively tracking outcomes.
- Changing food, activity, and sleep drives the outcome, similar to influencing business metrics via inputs.
