---
id: "question-measuring-judgment-roi"
type: "open-question"
source_timestamps: ["§ A New Differentiator"]
tags: ["metrics", "roi"]
related: ["concept-judgment-infrastructure", "claim-codified-judgment-compounds"]
resolutionPath: "Establish specific KPIs for agentic deployments, such as exception-handling accuracy, reduction in human escalation rates, and time-to-deployment for new agents."
sources: ["agentic"]
sourceVaultSlug: "hbr-seg-agentic"
originDay: 6
articleStem: "hbr-new-27-teach-ai-your-decisions"
sourceUrl: "https://hbr.org/2026/06/teach-your-ai-how-you-make-decisions"
sourceTitle: "Teach Your AI How You Make Decisions"
---
# How do organizations quantify the ROI of building judgment infrastructure?

**Open question:** While the authors claim that [[claim-codified-judgment-compounds|codified judgment compounds]] and leads to faster decisions and greater capacity, they provide no specific metrics or KPIs for measuring the success of the [[concept-judgment-infrastructure|judgment infrastructure]] itself, beyond anecdotal time savings (e.g., months to weeks; a team of two doing the work of ten).

**Possible resolution path:** Establish specific KPIs for agentic deployments — exception-handling accuracy, reduction in human escalation rates, and time-to-deployment for new agents. The enrichment corroborates this gap: compounding is supported by case study and expert judgment, not longitudinal performance data.