Behavior Mapping

Behavior Mapping

Map optimization targets to the daily behaviors that produce them.

Purpose

Targets are lagging indicators — they change slowly. This skill identifies the leading indicators (behaviors) that actually move the targets. Track behaviors daily, outcomes weekly/monthly.

Core Concept: Leading vs. Lagging

Type	Definition	Track Frequency
Leading	Behaviors (inputs you control)	Daily
Lagging	Outcomes (results of behaviors)	Weekly/Monthly

Key insight: You cannot directly control lagging indicators. Control leading indicators and trust the algorithm.

The Process

1. Identify the Algorithm

For each target, determine: What behaviors actually produce this outcome?

Domain	Target	Known Algorithm (Behaviors)
Productivity	Deep work hours	Time blocking + environment design + energy management
Learning	Skill acquisition	Deliberate practice + spaced repetition + application
Finance	Savings rate	Automated transfers + spending awareness
Writing	Published output	Daily writing habit + editing process + shipping
Health	Body composition	Nutrition + resistance training + sleep
Coding	Features shipped	Focused blocks + reduced meetings + clear priorities

Research evidence-based approaches. Do not guess.

2. Extract Trackable Behaviors

For each algorithm component, identify the minimum trackable unit:

Target	Algorithm Component	Trackable Behavior
Deep work capacity	Time blocking	Deep work hours logged
Deep work capacity	Environment design	Distraction-free session? (Y/N)
Skill acquisition	Deliberate practice	Practice sessions completed
Skill acquisition	Spaced repetition	Anki reviews done? (Y/N)
Savings rate	Automated transfers	(Automated — no tracking needed)

3. Apply Minimum Viable Tracking

Choose the simplest tracking that provides useful signal:

Level	Type	Example	When to Use
1	Automated	Syncs from device/app	When possible
2	Boolean	Did I do it? Y/N	Default choice
3	Simple count	How many?	When quantity matters
4	Duration	How long?	When time matters
5	Detailed log	Full description	Only if truly necessary

Start with boolean. Add detail only if needed for feedback.

4. Verify the Connection

For each behavior → target mapping, check:

• Is there evidence this behavior produces this outcome?
• How long until results expected? (Set expectations)
• What could interfere? (Confounding factors)

5. Output: Tracking Schema

domain: [domain]
target: [target name]

behaviors:
  - name: [behavior name]
    type: [boolean|count|duration|rating]
    unit: [unit if applicable]
    frequency: daily
    target_connection: [direct|indirect]
    expected_lag: [time to see results]

outcomes:
  - name: [outcome name]
    type: [aggregation|measurement]
    source: [how calculated]
    frequency: [weekly|monthly]

Database Schema

-- Behaviors table
CREATE TABLE behaviors (
  id UUID PRIMARY KEY,
  domain TEXT,
  name TEXT,
  type TEXT, -- boolean, count, duration, rating
  frequency TEXT, -- daily, weekly
  target_id UUID REFERENCES targets(id),
  created_at TIMESTAMPTZ
);

-- Daily logs table
CREATE TABLE daily_logs (
  id UUID PRIMARY KEY,
  date DATE,
  behavior_id UUID REFERENCES behaviors(id),
  value JSONB, -- {completed: true} or {minutes: 90}
  notes TEXT,
  created_at TIMESTAMPTZ
);

Anti-Patterns

Do not track:

• Behaviors with no clear connection to targets
• Things that can be automated instead of logged
• Detailed data that will never be analyzed
• More than 5-7 daily inputs (friction kills compliance)

Do track:

• Minimum behaviors that produce targets
• At simplest level providing feedback
• Only what will actually be reviewed