Overview
Based on Software Requirements by Karl Wiegers & Joy Beatty - the Wiegers Priority Matrix that scores options across 4 factors (relative benefit, relative penalty, relative cost, relative risk) to produce a data-driven ranking. Also draws on Business Analysis Techniques by James Cadle for Decision Tables, Decision Trees, and Force-Field Analysis, and Lean Business Analysis by Mark Sherrington for Real Options thinking - deferring irreversible decisions until the last responsible moment. The key insight from Wiegers: gut-feel prioritization always favors the loudest stakeholder. A structured matrix makes trade-offs visible and defensible.
Workflow
Step 1: Define the decision and options
DECISION: [What are we choosing between?]
CONTEXT: [Why this decision matters now]
OPTIONS:
A: [option name and brief description]
B: [option name and brief description]
C: [option name and brief description]
DECISION MAKER: [who has final authority]
DEADLINE: [when must this be decided]
Step 2: Define evaluation criteria
List criteria that matter for this decision. Common categories:
- Value criteria: business benefit, user impact, strategic alignment, revenue potential
- Cost criteria: development effort, operational cost, opportunity cost
- Risk criteria: technical risk, adoption risk, compliance risk, reversibility
Step 3: Assign weights to criteria
Each criterion gets a weight reflecting its importance (must total 100%):
| Criterion | Weight | Rationale |
|-----------|--------|-----------|
| Business impact | 30% | Primary driver per sponsor |
| Implementation cost | 25% | Budget-constrained project |
| Time to deliver | 20% | Regulatory deadline in Q3 |
| Technical risk | 15% | New technology stack |
| Scalability | 10% | Growth expected in Year 2 |
Get stakeholder agreement on weights before scoring. The weights reflect organizational priorities.
Step 4: Score each option (Wiegers Priority Matrix)
Rate each option against each criterion on a consistent scale (1-5 or 1-10):
| Criterion (Weight) | Option A | Option B | Option C |
|---------------------|----------|----------|----------|
| Business impact (30%) | 8 | 6 | 9 |
| Implementation cost (25%) | 5 | 8 | 3 |
| Time to deliver (20%) | 7 | 9 | 4 |
| Technical risk (15%) | 6 | 7 | 5 |
| Scalability (10%) | 4 | 5 | 9 |
For the Wiegers 4-factor variant, score each option on:
- Relative Benefit (1-9): Value of including this option
- Relative Penalty (1-9): Cost of NOT including it
- Relative Cost (1-9): Effort to implement
- Relative Risk (1-9): Technical/delivery uncertainty
Priority = (Benefit% + Penalty%) / (Cost% + Risk%)
Step 5: Calculate weighted scores
For each option: Sum of (score x weight) across all criteria.
Option A: (8x0.30) + (5x0.25) + (7x0.20) + (6x0.15) + (4x0.10) = 6.45
Option B: (6x0.30) + (8x0.25) + (9x0.20) + (7x0.15) + (5x0.10) = 7.15
Option C: (9x0.30) + (3x0.25) + (4x0.20) + (5x0.15) + (9x0.10) = 5.90
Step 6: Apply Force-Field Analysis for close calls
When scores are close (within 10%), use Cadle's Force-Field Analysis:
DRIVING FORCES (for change) | RESTRAINING FORCES (against)
=============================== | ===============================
[force] ------> strength: 4 | strength: 3 <------ [force]
[force] ------> strength: 5 | strength: 2 <------ [force]
The option with stronger net driving forces is preferred.
Step 7: Document the recommendation
RECOMMENDATION: [Option X]
SCORE: [weighted score]
KEY TRADE-OFFS: [what you're giving up by choosing this option]
REVERSIBILITY: [can this decision be changed later? at what cost?]
DISSENTING VIEWS: [any stakeholder disagreements to note]
Anti-Patterns
1. Choosing criteria after seeing the scores
Bad: Adding or removing criteria to justify a preferred option.
Good: Define and weight criteria before scoring. Lock them with stakeholder agreement.
2. Equal weights on everything
Bad: All criteria weighted 20% each - hides the real priorities.
Good: Force-rank criteria. If everything is equally important, nothing is important.
3. Scoring without evidence
Bad: "I feel like Option A is an 8 on scalability."
Good: "Option A uses a horizontally scalable architecture tested to 10K concurrent users - score 8."
4. Ignoring reversibility (Sherrington's Real Options)
Bad: Treating all decisions as permanent.
Good: If a decision is easily reversible, it may not need a full matrix. Invest analysis time proportional to the cost of being wrong.
5. Matrix replaces judgment
Bad: "The matrix says Option B, so we go with B."
Good: The matrix informs the decision. If the result feels wrong, the weights or criteria may be wrong - revisit them.
Quality Checklist