Glossary
"Shared vocabulary enables shared understanding."
This glossary defines key terms used in the 6D Foraging Methodology and Cormorant Foraging framework.
Core Methodology Terms
6D Foraging Methodology
The comprehensive framework for analyzing unmeasured effects across six dimensions of business impact: Customer, Employee, Revenue, Regulatory, Quality, and Operational. Extends traditional analysis by mapping cascade effects and reaching a cited, verifiable verdict (DRIFT and FETCH) rather than stopping at the origin dimension.
Related: Framework Overview
3D Lens
The analytical framework borrowed from Cormorant Foraging that evaluates any problem across three dimensions:
- Sound (ChirpIQX): Urgency — How immediate is the signal?
- Space (PerchIQX): Scope — How widespread is the impact?
- Time (WakeIQX): Trajectory — Is it improving or degrading?
Formula: Dimension Score = (Sound × Space × Time) ÷ 10
Related: Cormorant Integration
The Six Dimensions
D1: Customer Impact
Definition: The effect of a problem on the people who pay for your products or services.
Key observables: Support ticket volume, NPS scores, churn signals, renewal hesitation, usage decline
Related: Customer Dimension
D2: Employee Impact
Definition: The effect of a problem on the people who work for your organization.
Key observables: Overtime hours, engagement scores, turnover, absenteeism, knowledge concentration
Real example: UC-246 — Starbucks' $500M+ "coffeehouse coach" investment, scored 88/100 as the origin dimension.
Related: Employee Dimension
D3: Revenue Impact
Definition: The effect of a problem on money coming into the organization.
Key observables: Invoice disputes, AR aging, discount requests, pipeline slippage, margin compression
Related: Revenue Dimension
D4: Regulatory Impact
Definition: The effect of a problem on compliance, legal standing, and regulatory obligations.
Key observables: Audit findings, compliance gaps, violations, fines, certification status
Related: Regulatory Dimension
D5: Quality Impact
Definition: The effect of a problem on what the organization delivers (products, services, outputs).
Key observables: Defect rates, rework hours, customer complaints, warranty claims, returns
Related: Quality Dimension
D6: Operational Impact
Definition: The effect of a problem on how the organization works (processes, systems, workflows).
Key observables: System downtime, bottlenecks, manual workarounds, cycle time increases, capacity issues
Related: Operational Dimension
Note: earlier versions of this glossary listed a "primary cascade" probability percentage per dimension (e.g. "Customer → Revenue, 70%"). Those percentages were invented, not measured — see Cascade Pathways for why. Real cascade paths are case-specific and cited, not predicted by a fixed table.
Signal Detection Terms
Observable Signal
A measurable indicator that a problem exists in a particular dimension. Signals can be:
- Immediate: Detected in real-time (hours)
- Behavioral: Detected through pattern changes (days-weeks)
- Silent: Not directly visible, requires investigation (weeks-months)
Example: A support ticket spike is an immediate observable signal of Customer impact.
Related: Observable Properties Framework
Trigger Keyword
A specific word or phrase that indicates severity level and dimension impact. Used for automated detection and human escalation.
Urgency levels:
- High (8-10): "lawsuit", "breach", "system down", "critical"
- Medium (4-7): "defect", "delayed", "concerned", "audit finding"
- Low (1-3): "minor", "someday", "inefficient", "could be better"
Example: The keyword "canceling" in a customer email is a high-urgency trigger indicating Customer dimension impact with Sound score of 8-10.
Related: Trigger Keywords Reference
Data Source
The system, tool, or repository where observable signals are detected.
Examples:
- Customer dimension: CRM (Salesforce), Helpdesk (Zendesk), Survey platform (Qualtrics)
- Employee dimension: HRIS (Workday), Pulse surveys, Timesheets
- Operational dimension: APM tools (Datadog, New Relic), JIRA, Process dashboards
Related: Observable Properties by Dimension
Detection Speed
The time lag between when a problem occurs and when it becomes observable in your systems.
Categories:
- Real-time: Minutes to hours
- Fast: Hours to days
- Medium: Days to weeks
- Slow: Weeks to months
- Delayed: Months to quarters
Example: System downtime has a detection speed of minutes (APM alerts). Employee morale degradation has a detection speed of weeks (pulse survey cycles).
Cascade Analysis Terms
Cascade Pathway
The route a problem or event follows as it propagates from one dimension to another, expressed as cited cascade notation, not a predicted probability.
Structure: Origin > Target+Target > Target (> reads "cascades to," + reads "simultaneously")
Example: UC-246: D3 > D1+D5 > D2 > D6 > D4 — Starbucks' Employee investment cascading through Customer and Quality, then Revenue, Operational, and Regulatory.
Related: Cascade Pathways
Cascade Depth
The number of levels a cascade propagates through.
Levels:
- Level 0: Origin dimension (where problem starts)
- Level 1: Primary cascades (direct impacts on other dimensions)
- Level 2: Secondary cascades (impacts from Level 1 dimensions)
- Level 3+: Tertiary and beyond
Example: Billing error → Quality (Level 1) → Customer (Level 2) = 2 levels of cascade depth
Related: Cascade Analysis Guide
Cascade Velocity
The speed at which a problem propagates from one dimension to another.
Types:
- Immediate: <24 hours (e.g., system outage → customer impact)
- Fast: 1-7 days (e.g., quality issue → customer complaints)
- Medium: 1-4 weeks (e.g., employee burnout → quality degradation)
- Slow: 1-3 months (e.g., revenue decline → hiring freeze)
- Delayed: 3+ months (e.g., regulatory → market reputation)
Related: Cascade Pathways - Velocity Section
Why There's No "Cascade Probability" Term Here
Earlier versions of this glossary defined Cascade Probability, Primary Cascade, Secondary Cascade, and Tertiary Cascade as percentage-based categories (e.g. "Employee → Quality, 80% probability, Primary"). Those percentages were invented — no case library tracks enough repeated instances of identical events to support a number like that honestly. See Cascade Pathways for what replaced them: real, cited cascade notation from actual published cases, read as a documented trace of one real event, not a statistical prediction.
Related: Cascade Analysis
Scoring and Quantification Terms
Dimension Score
The quantified severity of impact in a particular dimension, scored 0–100 against cited evidence — the 3D Lens is one way to build this score, not the only one.
Formula (3D Lens variant): (Sound × Space × Time) ÷ 10
Range: 0–100
Interpretation:
- 1–25: Low
- 26–50: Medium
- 51–75: High
- 76–100: Critical
Real example: UC-246's origin dimension (Employee) scores 88/100 — critical, evidence-backed, not a hypothetical.
Related: Scoring Methodology
DRIFT
The gap between diagnosis and proof: DRIFT = |METHODOLOGY − PERFORMANCE|, both scored 0–100. A low DRIFT means the reasoning and the evidence for it are close together; a high DRIFT means a real, unresolved gap — often the more interesting cases, because they're a genuine bet rather than a description of something already settled.
Related: Scoring Methodology
FETCH
The verdict calculation: FETCH = CHIRP × DRIFT × CONFIDENCE, compared against a THRESHOLD (commonly 1,000) to reach a verdict — EXECUTE, MONITOR, WATCH, depending on the margin. This is what replaced the "Direct Cost / Cascade Cost / Total Impact / Multiplier" concepts that appeared in earlier versions of this glossary: no real published case sums cascade dollars into a total or multiplies a direct cost by a factor — see Scoring Methodology for why, worked through a real example (UC-246: FETCH 2,632 vs. THRESHOLD 1,000 → EXECUTE).
Related: Scoring Methodology, Cascade Analysis Guide
Cormorant Foraging Integration
Cormorant Foraging
The 3D analytical methodology developed for content analysis that evaluates information across Sound (urgency), Space (reach), and Time (trajectory). 6D Foraging Methodology extends this framework to business impact analysis.
Origin: Biomimicry of cormorant bird hunting patterns
Application: Strategic analysis, content evaluation, business intelligence
Related: Cormorant Integration
ChirpIQX (Sound)
The urgency dimension of the 3D lens. Measures how immediate or critical a signal is.
Scale: 1-10 (low to high urgency)
In 6D context:
- 1-3: Future risk, monitoring needed
- 4-6: Current issue, plan response
- 7-10: Crisis, immediate action required
Mapping to trigger keywords: High-urgency keywords score 8-10, medium 4-7, low 1-3.
Related: ChirpIQX Deep Dive
PerchIQX (Space)
The scope dimension of the 3D lens. Measures how widespread an impact is.
Scale: 1-10 (isolated to enterprise-wide)
In 6D context:
- 1-3: One person/customer, single system
- 4-6: Department, customer segment
- 7-10: Enterprise-wide, all customers, market-wide
Measurement: Population counting, system coverage, customer base percentage
Related: PerchIQX Deep Dive
WakeIQX (Time)
The trajectory dimension of the 3D lens. Measures whether a situation is improving or degrading over time.
Scale: 1-10 (one-time event to accelerating crisis)
In 6D context:
- 1-3: Isolated incident, first occurrence
- 4-6: Recurring pattern, sustained pressure
- 7-10: Accelerating trend, chronic condition
Analysis: Trend lines, pattern recognition, momentum indicators
Related: WakeIQX Deep Dive
Metrics and Measurement Terms
Leading Indicator
A predictive metric that signals potential problems before they fully manifest.
Characteristics:
- Real-time or near-real-time
- Actionable (can intervene)
- Directly observable
Examples:
- Support ticket velocity (predicts customer churn)
- Overtime hours (predicts employee burnout)
- Code coverage (predicts quality issues)
Related: Dimension-Specific Metrics
Lagging Indicator
A historical metric that confirms a problem has occurred.
Characteristics:
- Backward-looking
- Harder to act on
- Often reported monthly/quarterly
Examples:
- Actual churn rate
- Voluntary turnover
- Revenue growth rate
Related: Observable Signals by Dimension
Bus Factor
The number of people who would need to be "hit by a bus" before a project/process becomes critically impaired.
Risk levels:
- Bus factor = 1: High risk (single point of failure)
- Bus factor = 2-3: Medium risk
- Bus factor = 4+: Low risk (good redundancy)
6D Relevance: Employee dimension — knowledge concentration multiplier factor
Tool: HEAT heatmap (Human Expertise & Accountability Topology)
Related: Employee Impact - Multiplier Factors
Industry-Specific Terms
HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems)
Patient satisfaction survey used in healthcare to measure Customer (Patient) dimension.
Related: Healthcare Variations
NRR (Net Revenue Retention)
SaaS metric measuring revenue retention + expansion from existing customers. Key Revenue dimension metric.
Formula: (Starting ARR + Expansion - Churn) / Starting ARR × 100%
Target: >100% (indicates expansion exceeds churn)
Related: Revenue Impact, SaaS Variations
OEE (Overall Equipment Effectiveness)
Manufacturing metric measuring Operational dimension efficiency.
Formula: Availability × Performance × Quality
Target: >85%
Related: Manufacturing Variations
AUM (Assets Under Management)
Financial services metric measuring Customer (Client) dimension in wealth management.
6D Relevance: Client trust issues cascade to AUM outflows, often disproportionately given how concentrated wealth-management relationships tend to be
Related: Financial Services Variations
Analysis Process Terms
Origin Dimension
The dimension where a problem first occurs — the starting point for cascade analysis.
Identification: Look for earliest observable signals, root cause analysis
Example: A billing calculation error originates in Operational dimension (system/process issue).
Related: Step 1: Identify Origin
Cascade Mapping
The process of tracing how a problem propagates from origin dimension through multiple cascade pathways.
Steps:
- Identify the origin dimension
- Score the origin
- Map primary cascade pathways (cited evidence, not predicted probability)
- Map further cascades, as far as the evidence actually reaches
- Reach a verdict — DRIFT, FETCH, THRESHOLD
Related: 5-Step Cascade Mapping Process
Evidence
Observable data or signals that confirm a cascade pathway is occurring.
Types:
- Quantitative: Metrics, counts, measurements
- Qualitative: Keywords, feedback, observations
- Systems data: Logs, reports, tickets
Example: Evidence of Quality → Customer cascade: 18 support tickets mentioning "billing accuracy", 3 enterprise customers questioning invoices in QBRs.
Related: Step 3: Map Primary Cascades
Action and Response Terms
Containment Strategy
Tactical actions taken to prevent or limit cascade propagation.
Examples:
- Customer → Revenue: Proactive retention outreach
- Employee → Quality: Temporary quality checks
- Operational → Employee: Overtime limits, resource reallocation
Related: Preventing Cascade Multiplication
Preventive Measures
Systemic changes implemented to prevent future occurrences or reduce cascade likelihood.
Categories:
- Detection (earlier warning signals)
- Containment (circuit breakers)
- Elimination (fix root cause)
Example: Automated billing reconciliation (daily vs. monthly) prevents 3-month detection delay.
Related: Preventing Cascade Multiplication
Quick Lookup
Most Common Searches:
| Looking for... | See term... |
|---|---|
| How to calculate impact score | Dimension Score |
| How a case reaches a verdict | DRIFT, FETCH |
| How problems spread | Cascade Pathway |
| What keywords mean | Trigger Keyword |
| Sound/Space/Time explained | 3D Lens, ChirpIQX, PerchIQX, WakeIQX |
| Where to find signals | Observable Signal, Data Source |
| Industry-specific terms | Industry variations section |
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