trend-modeling

name	trend-modeling
description	Use when the user asks to "model trends with limited data", "three-valued logic analysis", "scenario generation", "transitional graphs", "qualitative trend analysis", "uncertain data analysis", "minimal-information modeling", or needs trend-based modeling with INC/DEC/CONST logic, scenario planning with little quantitative data, or transitional scenario graphs.
version	0.4.2

Trend Modeling with Three-Valued Logic

Apply three-valued logic — increasing (INC), decreasing (DEC), constant (CONST) — to analyze markets when precise numerical data is unavailable. Enables meaningful directional analysis with minimal information.

Required Frameworks

Framework	Output Section	Required
Variables Table	Variables	yes
Relationship Matrix	Relationship Matrix	yes
Scenario Generation	Generated Scenarios	yes
Transitional Graph	Transitional Scenario Graph (Mermaid stateDiagram)	yes
Terminal Scenario Analysis	Terminal Scenario Analysis	yes
Multi-Objective Trade-offs	Trade-offs	yes

When to Use

Choose three-valued logic when data is scarce or unreliable, relationships are qualitative, uncertainty is high, or quick directional insight is needed.

The Three Values

Each variable is assigned INC, DEC, or CONST. A formal-notation variant expresses pairwise relationships as INC(X, Y) (X and Y move together) or DEC(X, Y) (X and Y move oppositely). An extended notation adds acceleration/deceleration modifiers: AG (accelerating growth), DG (decelerating growth), AD (accelerating decline), DD (decelerating decline).

When the user provides correlation data, you MUST

1. Label each correlation "positive" or "negative".
2. Convert it to INC(X, Y) or DEC(X, Y) notation.
3. Show the conversion before building the matrix.

Example:

• Market size & competition → positive correlation → INC(Market Size, Competition): if Market Size = INC then Competition = INC; if DEC then DEC.
• Price & demand → negative correlation → DEC(Price, Demand): if Price = INC then Demand = DEC; if Price = DEC then Demand = INC.

Construction

1. Identify variables — e.g., market size, competition intensity, price pressure, innovation rate, customer adoption, regulatory burden.

2. Determine relationships — for each pair, find the correlation direction and convert to INC/DEC.

3. Build the trend matrix:

   Variable	Market Size	Competition	Price	Innovation
   Market Size	-	INC	DEC	INC
   Competition	INC	-	DEC	CONST
   Price	DEC	DEC	-	DEC
   Innovation	INC	CONST	DEC	-

4. Generate scenarios — a scenario is a consistent assignment of INC/DEC/CONST to all variables satisfying every relationship.

5. Identify terminal scenarios — equilibrium states where all relationships hold, the system is stable, and no further transitions occur.

Transitional Scenario Graph

Show scenario evolution as a Mermaid state diagram:

stateDiagram-v2
    [*] --> S1: Initial conditions
    S1: Scenario 1<br/>Market=INC, Comp=INC<br/>Price=DEC, Innov=INC
    S2: Scenario 2<br/>Market=CONST, Comp=INC<br/>Price=DEC, Innov=CONST
    S3: Scenario 3 (Terminal)<br/>Market=DEC, Comp=CONST<br/>Price=CONST, Innov=DEC
    S4: Scenario 4 (Terminal)<br/>Market=INC, Comp=INC<br/>Price=DEC, Innov=INC
    S1 --> S2: Market saturation
    S1 --> S4: Sustained growth
    S2 --> S3: Commoditization
    S2 --> S4: Innovation breakthrough

Multi-Objective Trade-offs

No scenario satisfies all objective functions simultaneously. For terminal scenarios: identify competing objectives, map which scenarios favor which objectives, highlight required trade-offs, and recommend based on priority alignment.

Worked Example: New Market Entry

Variables: Market Growth (MG), Competitive Intensity (CI), Entry Barriers (EB), Customer Awareness (CA). Relationships: INC(MG, CI) (growth attracts competitors), INC(MG, CA), DEC(EB, CI) (lower barriers increase competition), INC(CA, MG). Scenarios: (1) Explosive growth — MG=AG, CI=AG, EB=DEC, CA=AG. (2) Mature equilibrium — MG=DG, CI=CONST, EB=CONST, CA=CONST. (3) Consolidation — MG=DEC, CI=DEC, EB=INC, CA=CONST.

Output Structure

## Trend Model Summary
### Variables                  [name | current state | trend | confidence]
### Relationship Matrix        [INC/DEC relationships]
### Generated Scenarios        [per-variable assignment | terminal?]
### Transitional Graph         [Mermaid state diagram]
### Terminal Scenario Analysis [conditions, trade-offs, recommendation]
### Key Insights               [transitions, trade-offs]

Best Practices

• Start with 4-6 variables; validate relationships with domain experts.
• Document where relationships are speculative; refine iteratively as information emerges.
• Focus on transitions — the paths between scenarios often matter more than endpoints.
• Large models (7+ variables): keep the matrix to direct relationships only (CONST for unclear pairs), generate 3-5 key scenarios rather than enumerating exhaustively, and prioritize terminal scenarios and likely transitions.

Advantages

No numerical constants or parameters are required; a complete list of all futures/histories is obtained; results stay understandable without sophisticated mathematical tools.

Confidence Tiers

High = inputs validated by 3+ independent dimensions' findings. Medium = inputs from 2 dimensions with reasonable assumptions. Low = speculative or single-dimension basis. All other dimensions supply input variables for scenario modeling. Alert on a scenario with >50% probability of adverse outcome, a bifurcation point within the planning horizon, or a terminal scenario that invalidates core business assumptions.