D-NAV Documentation

The language and signals behind faster, clearer decisions

Overview

D-NAV (Decision Navigator) is a framework for making faster, clearer decisions by quantifying the key factors that influence every choice. It transforms subjective decision-making into objective analysis through structured evaluation and real-time insights.

How It Works

Rate Variables

Score 5 key factors from 1-10

Get Insights

See real-time metrics and patterns

Make Decisions

Act with confidence and clarity

Core Ingredients

The five fundamental variables that shape every decision (rated 1-10 each)

Impact

Upside/importance if it works

1-3:Low impact

4-6:Moderate impact

7-10:High impact

Cost

Time • money • effort • focus

1-3:Low cost

4-6:Moderate cost

7-10:High cost

Risk

Downside, what could go wrong

1-3:Low risk

4-6:Moderate risk

7-10:High risk

Urgency

How soon action is needed

1-3:Low urgency

4-6:Moderate urgency

7-10:High urgency

Confidence

Evidence & readiness to execute

1-3:Low confidence

4-6:Moderate confidence

7-10:High confidence

Scoring Guidelines

Scoring is in-the-moment: 1 = minimal, 10 = maximum. You’re rating how it feels right now — tomorrow’s “10” might change with new info or context.

Derived Signals

Three key metrics calculated from your core variables to reveal decision patterns

Return

Impact − Cost

Value after cost

PositiveGain

NeutralBreak-even

NegativeLoss

Stability

Confidence − Risk

Survivability

Stable≥ 0

Uncertain≈ 0

Fragile< 0

Pressure

Urgency − Confidence

Execution stress

Calm< 0

Balanced≈ 0

Pressured> 0

Strategic Insight

We group these signals to expose different risks: Return (unit economics),Stability (survivability), Pressure (execution risk). Strategic short-term negative return can be fine — keep stability ≥ 0 and prevent runaway pressure.

Merit & Energy

The two fundamental components that make up the D-NAV score

Merit

Impact − Cost − Risk

Inherent quality of the bet (unit economics minus risk drag)

High Merit:Strong value proposition

Low Merit:Weak or risky bet

Energy

Urgency × Confidence

Applied energy — how hard & how ready you’ll push now

High Energy:Ready to execute

Low Energy:Not ready or urgent

D-NAV Formula

The core calculation that combines Merit and Energy

D-NAV = Merit + Energy

(Impact − Cost − Risk) + (Urgency × Confidence)

D-NAV blends Merit (quality of the bet) with Energy (execution momentum). High D-NAV = a strong bet and/or a strong push — always read Return,Stability, and Pressure to avoid hidden traps and slow bleeds.

Compare Mode

Side-by-side comparison between a Base scenario and a Scenario you adjust with sliders

Delta Calculations

Delta (Δ)

ΔX = X_Scenario − X_Base. Positive = Scenario is higher.

ΔR

ΔReturn

Δ(Impact − Cost) — net value change after cost.

ΔS

ΔStability

Δ(Confidence − Risk) — survivability change.

ΔP

ΔPressure

Δ(Urgency − Confidence) — execution stress change.

ΔD

ΔD-NAV

Δ[(Impact − Cost − Risk) + (Urgency × Confidence)] — overall quality × push change.

Smallest Nudge (Optimizer)

Recommends the single 1-point slider change that maximizes ΔD-NAV while respecting a pressure posture. By default we avoid sustained Pressured states (target Pressure ≤ 0) and keep Stability ≥ 0 when possible.

Narrative insight explains why ΔD-NAV moved: e.g., “Return ↑ via Impact (cost unchanged). Stability flat. Pressure +1 — acceptable short-term given clear upside.”

Learning & Momentum

Track short-, mid-, and long-horizon learning signals across your decision stream and by category

Learning Curve Index (LCI)

Rebound / Drawdown

Recovery efficiency after dips

>1.0Over-recovery

≈1.0Full recovery

<1.0Under-recovery

Momentum_n

slope(MA_n(D-NAV))

Trend velocity over the last n decisions via least-squares slope on a moving average

Also calculated for Return, Stability, Pressure

Additional Metrics

Moving Averages

MA_n(X) = rolling average

EMA_n(X) = faster, recent-weighted

Cross-Category Effects

Decisions in one arena can influence another (attention/energy budgets). We show both global momentum and per-category momentum.

Defaults: short = 15, mid = 50, long = 100 decisions. Short = steering; mid = course; long = climate.

Decision Archetypes

Each outcome is defined by the signs of Pressure, Stability, and Return (P•S•R)

Breakthrough

P+S+R+

Gain with stable footing; pressured execution.

Advance

P0S+R+

Gain with stable footing; balanced execution.

Harvest

P-S+R+

Gain with stable footing; calm execution.

Sprint

P+S0R+

Gain with uncertain footing; pressured execution.

Build

P0S0R+

Gain with uncertain footing; balanced execution.

Coast

P-S0R+

Gain with uncertain footing; calm execution.

Gamble

P+S-R+

Gain with fragile footing; pressured execution.

Moonshot

P0S-R+

Gain with fragile footing; balanced execution.

Prospect

P-S-R+

Gain with fragile footing; calm execution.

Grind

P+S+R0

Flat with stable footing; pressured execution.

Maintain

P0S+R0

Flat with stable footing; balanced execution.

Idle

P-S+R0

Flat with stable footing; calm execution.

Firefight

P+S0R0

Flat with uncertain footing; pressured execution.

Routine

P0S0R0

Flat with uncertain footing; balanced execution.

Drift

P-S0R0

Flat with uncertain footing; calm execution.

Strain

P+S-R0

Flat with fragile footing; pressured execution.

Wobble

P0S-R0

Flat with fragile footing; balanced execution.

Teeter

P-S-R0

Flat with fragile footing; calm execution.

Overreach

P+S+R-

Loss with stable footing; pressured execution.

Erode

P0S+R-

Loss with stable footing; balanced execution.

Complacency

P-S+R-

Loss with stable footing; calm execution.

Burn

P+S0R-

Loss with uncertain footing; pressured execution.

Waste

P0S0R-

Loss with uncertain footing; balanced execution.

Leak

P-S0R-

Loss with uncertain footing; calm execution.

Meltdown

P+S-R-

Loss with fragile footing; pressured execution.

Collapse

P0S-R-

Loss with fragile footing; balanced execution.

Decay

P-S-R-

Loss with fragile footing; calm execution.

Notation Guide

Mathematical symbols and abbreviations used throughout D-NAV

ΔX

Delta (change)

Compare: X_Scenario − X_Base. Time series: X_t − X_t−1.

MA_n(X)

Moving Average

Rolling average over the last n decisions

EMA_n(X)

Exponential Moving Average

More weight on recent points

Momentum_n(X)

Momentum

Least-squares slope of MA_n(X) (positive = trending up)

LCI

Learning Curve Index

Rebound / Drawdown around local dips

Loss Streak

Loss Streak

Consecutive count of Return < 0