The first step isn't building — it's mapping the full solution space so you know what you're choosing between. Business objectives are achieved through tangible work products, and each one carries its own cost/benefit profile.
Accuracy, interpretability, speed to production, regulatory burden — every business decision is a multi-dimensional tradeoff. "Most accurate" or "highest ROI" is rarely the best answer. Twenty years across analytics, strategy, and operations have revealed which tradeoffs in which contexts actually matter.
The Complexity Tax →Whether it's a model build, a platform migration, or a product rollout — the skill is the same: decompose, sequence, find the bottleneck, solve it. The right sequencing means early deliverables generate value while the rest are still being built.
Analytics is only as valuable as the decision it changes. Board and C-suite audiences don't need to understand the methodology — they need to understand the implications, the tradeoffs, and recommendations.
At Nomis, we routinely build sophisticated neural networks we know will never hit production — specifically so we can have the right conversation with the C-suite about why the logistic regression is the right answer.
Rapid prototyping of a voice-enabled mortgage application system and lessons learned about compound AI systems.
Moving beyond binary recommendations to AI systems that provide arguments, alternatives, and contextual insights.