Financial translation

Operational drift, in CFO language.

Execution degradation converts to capital exposure on two dimensions — delivery delay and attrition. The range reflects scenario sensitivity, not measurement uncertainty. The window is named explicitly.

Estimated exposure · pilot scenario · 90-day horizon
~$3.0M
range · $2.7M – $3.3M
Delivery delay
~$2.1M
Attrition
~$0.9M
Window
4–6 weeks

From signal to dollars.

Each at-risk roadmap item is ARR-weighted by its probability of slip under sustained drift. Critical-personnel attrition is modeled with elevated-risk multipliers against fully-loaded replacement cost.

Capital preserved · per $ deployed early
7.7×
The translation process

Four steps, signal to exposure.

1

Signal detection

Input
Latency +18% · concentration +85% · cycle +27%
Output
Drift score 71 / 100
2

Scope quantification

Input
Drift score, affected teams, organization size
Output
14 of 31 roadmap items · 11 critical ICs
3

Financial mapping

Delivery delay
Days delayed × daily revenue at stake · rework waste — ~$2.1M
Attrition
P(leave) × replacement cost per person · ramp — ~$0.9M
4

Window & cost analysis

Input
Days since drift onset · window remaining
Output
4–6 week window · 2–3× cost after close
The reversibility curve

Cost to correct rises 2–3× once the window closes.

Weeks 0–6 · early
~$390K
Drift still in operational patterns. Reversible without organizational change.
Weeks 6–12 · late
~$1.4M
Drift now visible in KPIs. Catch-up cost plus partial replacement.
Weeks 12+ · reactive
~$3.0M+
Attrition fired, quarter missed. Hiring, replan, customer concessions.
Example scenario

340-person engineering org. Real numbers.

Drift detected
Day 28
Total exposure
~$3.0M
Act now
~$390K
ROI of acting now
7.7×
NOT ESTIMATES · CALCULATED EXPOSURE
ARR-weighted slip, replacement-cost multipliers, org-wide impact modeling. The methodology is auditable and repeatable — reproducible by your finance and data-governance teams.