Treat Data as a Product, Not a Project

Too often analytics work is an afterthought, a report requested at the tail end of a feature release. Data capabilities must be first-class portfolio items: data products with owners, SLAs, and measurable consumers.

Begin by defining the product, what the data delivers, who consumes it, the refresh cadence, and the quality SLAs, then fund accordingly. A data product that serves multiple teams should be governed like any other capability, with a roadmap, agreed SLAs, and a minimal onboarding path for consumers. This reframing changes prioritization; building a one-off report becomes less attractive when a reusable data product unlocks multiple downstream outcomes.

Operational discipline reduces duplication and eliminates multiple single-use pipelines, increases trust in analytics outputs, and shortens time to decision. Investments in a minimal, well-owned data product drive higher adoption and clearer ROI, not because analytics are magical, but because the product has defined consumers, SLAs, and a straightforward billing or chargeback model.

Treat data product success as adoption rather than dashboard count. Measure consumers onboarded, time to answer for key questions, and the business outcomes enabled by the product, and fund iterations based on those real signals.

If the portfolio is to get smarter, stop organizing analytics as isolated projects and start funding data as products you would buy once and reuse over time.