---
id: "question-new-performance-metrics"
type: "open-question"
source_timestamps: ["§ Breakdown 2: Incentives reward the wrong behaviors."]
tags: ["metrics", "performance-management"]
related: ["action-adjust-incentives", "concept-triple-burden"]
resolution_path: "Case studies of consulting firms that have successfully transitioned away from utilization-based compensation toward value-based or knowledge-sharing metrics."
sources: ["reskilling"]
sourceVaultSlug: "hbr-seg-reskilling"
originDay: 10
articleStem: "hbr-sig-50-adoption-overloading-managers"
sourceUrl: "https://hbr.org/2026/06/ai-adoption-is-overloading-your-middle-managers"
sourceTitle: "AI Adoption Is Overloading Your Middle Managers"
---
# What specific metrics should replace billable hours in an AI-leveraged firm?

**Open question.** The authors clearly state that traditional metrics rewarding billable hours and individual output are counterproductive for AI adoption (see [[prereq-consulting-business-model]] and the second of the [[framework-three-breakdowns]]). Yet they do **not** prescribe the exact quantitative metrics that should replace them — only that reviews should be tied to documenting/sharing use cases and to coaching (the direction set by [[action-adjust-incentives]]).

**Why it's open.** Rebalancing the [[concept-triple-burden]] requires a measurement system that can value coaching and knowledge transfer, which are notoriously hard to quantify — and no firm-tested standard is offered.

**Resolution path.** Case studies of consulting firms that have successfully transitioned away from utilization-based compensation toward value-based or knowledge-sharing metrics. Adjacent practitioner tooling (accountability matrices, capability-development scorecards from the AI-resistance literature) may supply candidate metrics.