Options Comparator

Structured comparison of competing options with weighted scoring matrices, trade-off analysis, decision frameworks, and recommendation templates. Use when evaluating alternatives, making purchase decisions, or comparing strategies.

travisjneuman Updated Sep 9, 2026

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Options Comparator

Structured frameworks for systematically comparing alternatives, scoring options, and producing defensible recommendations.

Weighted Scoring Matrix

Standard Weighted Matrix Template

WEIGHTED SCORING MATRIX:

STEP 1: Define criteria and weights (must sum to 100%)

| Criterion       | Weight | Option A | Option B | Option C |
|-----------------|--------|----------|----------|----------|
| [Criterion 1]   |   25%  |   [1-5]  |   [1-5]  |   [1-5]  |
| [Criterion 2]   |   20%  |   [1-5]  |   [1-5]  |   [1-5]  |
| [Criterion 3]   |   20%  |   [1-5]  |   [1-5]  |   [1-5]  |
| [Criterion 4]   |   15%  |   [1-5]  |   [1-5]  |   [1-5]  |
| [Criterion 5]   |   10%  |   [1-5]  |   [1-5]  |   [1-5]  |
| [Criterion 6]   |   10%  |   [1-5]  |   [1-5]  |   [1-5]  |
|-----------------|--------|----------|----------|----------|
| WEIGHTED TOTAL  |  100%  |  [sum]   |  [sum]   |  [sum]   |

STEP 2: Calculate weighted scores
  Weighted score = Raw score x Weight
  Total = Sum of all weighted scores

STEP 3: Interpret results
  4.5-5.0: Excellent fit
  3.5-4.4: Good fit
  2.5-3.4: Acceptable with trade-offs
  1.5-2.4: Poor fit — significant concerns
  1.0-1.4: Disqualified

SCORING RUBRIC:
  5 = Exceeds requirements / best in class
  4 = Fully meets requirements
  3 = Partially meets requirements
  2 = Significant gaps
  1 = Does not meet requirements / disqualifying

Weight Assignment Methods

Method	How It Works	Best For
Direct assignment	Stakeholders allocate 100 points across criteria	Small groups, quick decisions
Pairwise comparison	Compare criteria two at a time, derive weights	Rigorous prioritization
MoSCoW ranking	Must/Should/Could/Won't, then assign within tiers	Requirements-driven decisions
Swing weighting	Rate criteria by how much best-to-worst matters	Complex multi-attribute decisions
Stakeholder voting	Each stakeholder distributes 10 votes	Democratic team decisions

Weight Validation Checklist

BEFORE FINALIZING WEIGHTS:

- [ ] Weights sum to exactly 100%
- [ ] No single criterion exceeds 40% (unless justified)
- [ ] No criterion is below 5% (drop it if irrelevant)
- [ ] Weights reflect stated priorities (not just habit)
- [ ] Stakeholders reviewed and approved weights
- [ ] Weights were set BEFORE scoring options
      (prevents reverse-engineering to a preferred choice)

Pairwise Comparison

Pairwise Comparison Matrix

PAIRWISE COMPARISON TEMPLATE:

Compare criteria A through E. For each pair, indicate
which is more important (mark the winner):

         A      B      C      D      E    WINS  WEIGHT
A  [--]   [ ]    [A]    [ ]    [A]     2     25%
B  [B]    [--]   [B]    [B]    [B]     4     40%
C  [ ]    [ ]    [--]   [ ]    [C]     1     10%
D  [D]    [ ]    [D]    [--]   [D]     3     25%
E  [ ]    [ ]    [ ]    [ ]    [--]    0      0%

Weight = Wins / Total comparisons x 100
Total comparisons = n(n-1)/2 = 5(4)/2 = 10

INSTRUCTIONS:
1. Compare each pair: "Is criterion X more important than Y?"
2. Mark the winner in the matrix
3. Count wins for each criterion
4. Calculate weights from win percentages
5. Adjust if any criterion has 0% but should remain

Forced Ranking

FORCED RANKING METHOD:

List all options and rank from best to worst on each criterion.
No ties allowed (forces differentiation).

| Criterion     | Rank 1 (Best) | Rank 2 | Rank 3 | Rank 4 (Worst) |
|---------------|---------------|--------|--------|-----------------|
| Price         | Option C      | Option A| Option D| Option B       |
| Quality       | Option B      | Option D| Option A| Option C       |
| Speed         | Option A      | Option B| Option C| Option D       |
| Support       | Option D      | Option C| Option B| Option A       |

SCORING:
  Rank 1 = 4 points, Rank 2 = 3, Rank 3 = 2, Rank 4 = 1
  (Or weight the ranking scores by criterion importance)

Pros/Cons with Weights

Structured Pros/Cons Template

WEIGHTED PROS/CONS ANALYSIS:

OPTION: [Name]

PROS:
| # | Advantage                    | Impact | Certainty | Score |
|---|------------------------------|--------|-----------|-------|
| 1 | [Pro description]            | H/M/L  | H/M/L    | [1-9] |
| 2 | [Pro description]            | H/M/L  | H/M/L    | [1-9] |
| 3 | [Pro description]            | H/M/L  | H/M/L    | [1-9] |

CONS:
| # | Disadvantage                 | Impact | Certainty | Score |
|---|------------------------------|--------|-----------|-------|
| 1 | [Con description]            | H/M/L  | H/M/L    | [1-9] |
| 2 | [Con description]            | H/M/L  | H/M/L    | [1-9] |
| 3 | [Con description]            | H/M/L  | H/M/L    | [1-9] |

SCORING GUIDE:
  Impact:    High=3, Medium=2, Low=1
  Certainty: High=3, Medium=2, Low=1
  Score = Impact x Certainty (range: 1-9)

NET SCORE = Sum of Pro scores - Sum of Con scores
  Positive: Pros outweigh cons
  Negative: Cons outweigh pros
  Near zero: Trade-off decision (needs judgment)

Comparative Pros/Cons

Factor	Option A	Option B	Option C
Best for	[ideal use case]	[ideal use case]	[ideal use case]
Worst for	[poor fit scenario]	[poor fit scenario]	[poor fit scenario]
Top Pro	[strongest advantage]	[strongest advantage]	[strongest advantage]
Top Con	[biggest drawback]	[biggest drawback]	[biggest drawback]
Risk level	Low / Medium / High	Low / Medium / High	Low / Medium / High
Reversibility	Easy / Hard / Impossible	Easy / Hard / Impossible	Easy / Hard / Impossible

Decision Matrix Template

Comprehensive Decision Matrix

DECISION MATRIX:

DECISION: [Clear statement of what you are deciding]
DATE:     [Date of analysis]
OWNER:    [Decision maker(s)]
DEADLINE: [When decision must be made]

OPTIONS UNDER CONSIDERATION:
  A. [Option name and brief description]
  B. [Option name and brief description]
  C. [Option name and brief description]
  D. [Status quo / do nothing]

MUST-HAVE CRITERIA (pass/fail — eliminates options):
| Requirement          | Option A | Option B | Option C | Option D |
|----------------------|----------|----------|----------|----------|
| [Hard requirement 1] | Pass/Fail| Pass/Fail| Pass/Fail| Pass/Fail|
| [Hard requirement 2] | Pass/Fail| Pass/Fail| Pass/Fail| Pass/Fail|
| [Hard requirement 3] | Pass/Fail| Pass/Fail| Pass/Fail| Pass/Fail|

NICE-TO-HAVE CRITERIA (scored and weighted):
| Criterion    | Weight | Opt A | Opt B | Opt C | Opt D |
|-------------|--------|-------|-------|-------|-------|
| [Criterion] |   X%   | [1-5] | [1-5] | [1-5] | [1-5] |
| [Criterion] |   X%   | [1-5] | [1-5] | [1-5] | [1-5] |
| [Criterion] |   X%   | [1-5] | [1-5] | [1-5] | [1-5] |
|-------------|--------|-------|-------|-------|-------|
| TOTAL       |  100%  | [sum] | [sum] | [sum] | [sum] |

RECOMMENDATION: [Option letter] because [1-2 sentence rationale]

RISKS OF CHOSEN OPTION:
1. [Risk and mitigation plan]
2. [Risk and mitigation plan]

NEXT STEPS:
1. [Action item, owner, deadline]
2. [Action item, owner, deadline]

Trade-Off Analysis Framework

Trade-Off Mapping

TRADE-OFF ANALYSIS:

STEP 1: Identify the key trade-off dimensions
  Common trade-offs:
  - Cost vs Quality
  - Speed vs Thoroughness
  - Flexibility vs Standardization
  - Control vs Convenience
  - Short-term vs Long-term
  - Risk vs Reward
  - Simplicity vs Capability

STEP 2: Map options on trade-off axes

              HIGH QUALITY
                  |
                  |    Option B
                  |       *
                  |
  LOW COST -------+--------- HIGH COST
                  |
          Option A|
              *   |
                  |    Option C
                  |       *
              LOW QUALITY

STEP 3: Identify the efficient frontier
  Options on the frontier are rationally competitive.
  Options below the frontier are dominated
  (another option is better on all axes).

STEP 4: Choose based on priorities
  "We are optimizing for [dimension] while keeping
  [other dimension] above [minimum threshold]."

Trade-Off Decision Rules

Rule	When to Use	How It Works
Maximize one, threshold others	Clear primary objective	Set minimums for secondary criteria, then pick highest on primary
Satisfice	Time-pressured, good enough is fine	Pick first option that meets all minimum thresholds
Lexicographic	Clear priority ordering	Sort by most important criterion first, break ties with second
Minimax regret	High uncertainty	Choose option that minimizes worst-case disappointment
Expected value	Quantifiable outcomes and probabilities	Probability x payoff for each scenario, pick highest EV

Sensitivity Analysis for Decisions

Weight Sensitivity Testing

SENSITIVITY ANALYSIS:

PURPOSE: Test if the recommendation changes when weights shift.

BASELINE WEIGHTS:
  Cost: 30% | Quality: 25% | Speed: 20% | Support: 15% | Risk: 10%
  Winner: Option B (score: 3.85)

SCENARIO 1 — Cost-focused (Cost +15%, others proportionally reduced):
  Cost: 45% | Quality: 20% | Speed: 16% | Support: 12% | Risk: 7%
  Winner: [recalculate]

SCENARIO 2 — Quality-focused (Quality +15%):
  Cost: 24% | Quality: 40% | Speed: 16% | Support: 12% | Risk: 8%
  Winner: [recalculate]

SCENARIO 3 — Risk-averse (Risk +20%):
  Cost: 22% | Quality: 19% | Speed: 15% | Support: 14% | Risk: 30%
  Winner: [recalculate]

INTERPRETATION:
  If the same option wins in all scenarios → ROBUST decision
  If winner changes in 1 scenario → Note the sensitivity
  If winner changes in 2+ scenarios → Decision depends on priorities

Score Sensitivity Testing

BREAKEVEN ANALYSIS:

"How much would Option A's score on [criterion] need
to improve to overtake Option B?"

Current:
  Option A total: 3.45
  Option B total: 3.85
  Gap: 0.40

Criterion X (weight 25%):
  Option A score: 2
  Required score to close gap: 2 + (0.40 / 0.25) = 3.6 → round to 4
  Is this plausible? [Yes/No]
  If yes → decision is sensitive to this criterion
  If no → decision is robust on this dimension

Recommendation Memo Template

Executive Decision Memo

DECISION RECOMMENDATION MEMO

TO:       [Decision maker(s)]
FROM:     [Analyst / Team]
DATE:     [Date]
RE:       Recommendation: [Decision topic]

─────────────────────────────────────────────

EXECUTIVE SUMMARY:
We recommend [Option X] for [one-sentence rationale].
This option scores highest across our evaluation criteria,
particularly in [top 2 criteria]. Estimated [cost/timeline]:
[key number]. Key risk: [top risk and mitigation].

─────────────────────────────────────────────

BACKGROUND:
[2-3 sentences on why this decision is needed now]

OPTIONS EVALUATED:
  A. [Option and one-line description]
  B. [Option and one-line description]
  C. [Option and one-line description]

EVALUATION CRITERIA AND WEIGHTS:
  [Criterion 1] (X%) | [Criterion 2] (X%) | [Criterion 3] (X%)

SCORING SUMMARY:
| Option | Score | Rank | Key Strength         | Key Weakness        |
|--------|-------|------|----------------------|---------------------|
| A      | 3.45  | 2    | [strength]           | [weakness]          |
| B      | 3.85  | 1    | [strength]           | [weakness]          |
| C      | 2.90  | 3    | [strength]           | [weakness]          |

RECOMMENDATION: Option B
Rationale: [3-5 sentences explaining why, addressing trade-offs]

SENSITIVITY: This recommendation holds under all tested scenarios
except [edge case], which would require [condition].

RISKS AND MITIGATIONS:
1. [Risk]: [Mitigation plan]
2. [Risk]: [Mitigation plan]

IMPLEMENTATION PLAN:
1. [Step, owner, date]
2. [Step, owner, date]
3. [Decision review checkpoint, date]

─────────────────────────────────────────────

APPENDIX: Detailed scoring matrix, sensitivity analysis

Vendor Evaluation Scorecard

Vendor Assessment Template

VENDOR EVALUATION SCORECARD:

VENDOR:          [Company name]
EVALUATED BY:    [Names]
DATE:            [Date]
PRODUCT/SERVICE: [What you are evaluating]

CATEGORY 1: PRODUCT FIT (30% weight)
| Criterion                  | Score (1-5) | Notes                |
|----------------------------|-------------|----------------------|
| Feature completeness       |             |                      |
| Integration capability     |             |                      |
| Scalability                |             |                      |
| Customization options      |             |                      |
| User experience / UI       |             |                      |
| Category subtotal          |     /25     |                      |

CATEGORY 2: COMMERCIAL (25% weight)
| Criterion                  | Score (1-5) | Notes                |
|----------------------------|-------------|----------------------|
| Total cost of ownership    |             |                      |
| Pricing transparency       |             |                      |
| Contract flexibility       |             |                      |
| Payment terms              |             |                      |
| ROI timeline               |             |                      |
| Category subtotal          |     /25     |                      |

CATEGORY 3: SUPPORT AND SERVICE (20% weight)
| Criterion                  | Score (1-5) | Notes                |
|----------------------------|-------------|----------------------|
| Implementation support     |             |                      |
| Training resources         |             |                      |
| Ongoing customer support   |             |                      |
| SLA commitments            |             |                      |
| Account management         |             |                      |
| Category subtotal          |     /25     |                      |

CATEGORY 4: COMPANY VIABILITY (15% weight)
| Criterion                  | Score (1-5) | Notes                |
|----------------------------|-------------|----------------------|
| Financial stability        |             |                      |
| Market position            |             |                      |
| Product roadmap            |             |                      |
| Customer references        |             |                      |
| Industry reputation        |             |                      |
| Category subtotal          |     /25     |                      |

CATEGORY 5: RISK (10% weight)
| Criterion                  | Score (1-5) | Notes                |
|----------------------------|-------------|----------------------|
| Data security / compliance |             |                      |
| Vendor lock-in risk        |             |                      |
| Migration complexity       |             |                      |
| Business continuity plan   |             |                      |
| Reference check results    |             |                      |
| Category subtotal          |     /25     |                      |

OVERALL WEIGHTED SCORE: [calculated] / 5.0
RECOMMENDATION: Proceed / Shortlist / Reject

Technology Selection Framework

Technology Evaluation Criteria

TECHNOLOGY SELECTION MATRIX:

FUNCTIONAL FIT:
- [ ] Meets core requirements (pass/fail list)
- [ ] Handles expected scale (users, data, transactions)
- [ ] Integrates with existing stack
- [ ] Supports required platforms/environments

DEVELOPER EXPERIENCE:
- [ ] Documentation quality and completeness
- [ ] Community size and activity (GitHub stars, forums)
- [ ] Learning curve for the team
- [ ] Tooling and IDE support
- [ ] Error messages and debugging experience

OPERATIONAL:
- [ ] Deployment model fits infrastructure
- [ ] Monitoring and observability support
- [ ] Backup and disaster recovery
- [ ] Security track record and patching cadence

STRATEGIC:
- [ ] Aligned with technology direction
- [ ] Vendor/project longevity (not abandonware)
- [ ] Hiring market (can you find people who know it?)
- [ ] Exit strategy (migration path if you switch later)

TOTAL COST:
- [ ] License / subscription fees
- [ ] Infrastructure costs
- [ ] Training and ramp-up time
- [ ] Maintenance and operations
- [ ] Opportunity cost of alternatives

Build vs Buy Decision

Factor	Build	Buy	Hybrid
Core differentiator?	Yes — build it	No — buy it	Customize a platform
Team has expertise?	Yes	No	Partial
Time to value	Months	Weeks	Weeks-Months
Long-term cost	Higher (maintenance)	Predictable (subscription)	Mixed
Control	Full	Limited	Moderate
Risk	Technical debt	Vendor dependency	Both
Best when	Unique requirements, strategic IP	Commodity functionality	80/20 fit

Decision Anti-Patterns

COMMON DECISION MISTAKES:

1. ANALYSIS PARALYSIS
   Symptom: Endless evaluation, no decision made
   Fix: Set a decision deadline and "good enough" threshold

2. ANCHORING TO FIRST OPTION
   Symptom: First option evaluated becomes the default
   Fix: Evaluate all options before scoring any

3. CONFIRMATION BIAS
   Symptom: Seeking data that supports preferred option
   Fix: Assign a devil's advocate for each option

4. SUNK COST FALLACY
   Symptom: Sticking with an option because of past investment
   Fix: Evaluate options on future value only

5. RECENCY BIAS
   Symptom: Overweighting the last demo or reference call
   Fix: Standardize evaluation timing and criteria

6. GROUPTHINK
   Symptom: Team converges without genuine debate
   Fix: Independent scoring before group discussion

7. FEATURE COUNTING
   Symptom: Most features = best option (ignoring fit)
   Fix: Weight criteria by importance, not count

8. IGNORING STATUS QUO
   Symptom: Not comparing options against doing nothing
   Fix: Always include "do nothing" as Option D

See Also

--- name: options-comparator description: Structured comparison of competing options with weighted scoring matrices, trade-off analysis, decision frameworks, and recommendation templates. Use when evaluating alternatives, making purchase decisions, or comparing strategies. --- # Options Comparator Structured frameworks for systematically comparing alternatives, scoring options, and producing defensible recommendations. ## Weighted Scoring Matrix ### Standard Weighted Matrix Template ``` WEIGHTED SCORING MATRIX: STEP 1: Define criteria and weights (must sum to 100%) | Criterion | Weight | Option A | Option B | Option C | |-----------------|--------|----------|----------|----------| | [Criterion 1] | 25% | [1-5] | [1-5] | [1-5] | | [Criterion 2] | 20% | [1-5] | [1-5] | [1-5] | | [Criterion 3] | 20% | [1-5] | [1-5] | [1-5] | | [Criterion 4] | 15% | [1-5] | [1-5] | [1-5] | | [Criterion 5] | 10% | [1-5] | [1-5] | [1-5] | | [Criterion 6] | 10% | [1-5] | [1-5] | [1-5] | |-----------------|--------|----------|----------|----------| | WEIGHTED TOTAL | 100% | [sum] | [sum] | [sum] | STEP 2: Calculate weighted scores Weighted score = Raw score x Weight Total = Sum of all weighted scores STEP 3: Interpret results 4.5-5.0: Excellent fit 3.5-4.4: Good fit 2.5-3.4: Acceptable with trade-offs 1.5-2.4: Poor fit — significant concerns 1.0-1.4: Disqualified SCORING RUBRIC: 5 = Exceeds requirements / best in class 4 = Fully meets requirements 3 = Partially meets requirements 2 = Significant gaps 1 = Does not meet requirements / disqualifying ``` ### Weight Assignment Methods | Method | How It Works | Best For | | --- | --- | --- | | **Direct assignment** | Stakeholders allocate 100 points across criteria | Small groups, quick decisions | | **Pairwise comparison** | Compare criteria two at a time, derive weights | Rigorous prioritization | | **MoSCoW ranking** | Must/Should/Could/Won't, then assign within tiers | Requirements-driven decisions | | **Swing weighting** | Rate criteria by how much best-to-worst matters | Complex multi-attribute decisions | | **Stakeholder voting** | Each stakeholder distributes 10 votes | Democratic team decisions | ### Weight Validation Checklist ``` BEFORE FINALIZING WEIGHTS: - [ ] Weights sum to exactly 100% - [ ] No single criterion exceeds 40% (unless justified) - [ ] No criterion is below 5% (drop it if irrelevant) - [ ] Weights reflect stated priorities (not just habit) - [ ] Stakeholders reviewed and approved weights - [ ] Weights were set BEFORE scoring options (prevents reverse-engineering to a preferred choice) ``` ## Pairwise Comparison ### Pairwise Comparison Matrix ``` PAIRWISE COMPARISON TEMPLATE: Compare criteria A through E. For each pair, indicate which is more important (mark the winner): A B C D E WINS WEIGHT A [--] [ ] [A] [ ] [A] 2 25% B [B] [--] [B] [B] [B] 4 40% C [ ] [ ] [--] [ ] [C] 1 10% D [D] [ ] [D] [--] [D] 3 25% E [ ] [ ] [ ] [ ] [--] 0 0% Weight = Wins / Total comparisons x 100 Total comparisons = n(n-1)/2 = 5(4)/2 = 10 INSTRUCTIONS: 1. Compare each pair: "Is criterion X more important than Y?" 2. Mark the winner in the matrix 3. Count wins for each criterion 4. Calculate weights from win percentages 5. Adjust if any criterion has 0% but should remain ``` ### Forced Ranking ``` FORCED RANKING METHOD: List all options and rank from best to worst on each criterion. No ties allowed (forces differentiation). | Criterion | Rank 1 (Best) | Rank 2 | Rank 3 | Rank 4 (Worst) | |---------------|---------------|--------|--------|-----------------| | Price | Option C | Option A| Option D| Option B | | Quality | Option B | Option D| Option A| Option C | | Speed | Option A | Option B| Option C| Option D | | Support | Option D | Option C| Option B| Option A | SCORING: Rank 1 = 4 points, Rank 2 = 3, Rank 3 = 2, Rank 4 = 1 (Or weight the ranking scores by criterion importance) ``` ## Pros/Cons with Weights ### Structured Pros/Cons Template ``` WEIGHTED PROS/CONS ANALYSIS: OPTION: [Name] PROS: | # | Advantage | Impact | Certainty | Score | |---|------------------------------|--------|-----------|-------| | 1 | [Pro description] | H/M/L | H/M/L | [1-9] | | 2 | [Pro description] | H/M/L | H/M/L | [1-9] | | 3 | [Pro description] | H/M/L | H/M/L | [1-9] | CONS: | # | Disadvantage | Impact | Certainty | Score | |---|------------------------------|--------|-----------|-------| | 1 | [Con description] | H/M/L | H/M/L | [1-9] | | 2 | [Con description] | H/M/L | H/M/L | [1-9] | | 3 | [Con description] | H/M/L | H/M/L | [1-9] | SCORING GUIDE: Impact: High=3, Medium=2, Low=1 Certainty: High=3, Medium=2, Low=1 Score = Impact x Certainty (range: 1-9) NET SCORE = Sum of Pro scores - Sum of Con scores Positive: Pros outweigh cons Negative: Cons outweigh pros Near zero: Trade-off decision (needs judgment) ``` ### Comparative Pros/Cons | Factor | Option A | Option B | Option C | | --- | --- | --- | --- | | **Best for** | [ideal use case] | [ideal use case] | [ideal use case] | | **Worst for** | [poor fit scenario] | [poor fit scenario] | [poor fit scenario] | | **Top Pro** | [strongest advantage] | [strongest advantage] | [strongest advantage] | | **Top Con** | [biggest drawback] | [biggest drawback] | [biggest drawback] | | **Risk level** | Low / Medium / High | Low / Medium / High | Low / Medium / High | | **Reversibility** | Easy / Hard / Impossible | Easy / Hard / Impossible | Easy / Hard / Impossible | ## Decision Matrix Template ### Comprehensive Decision Matrix ``` DECISION MATRIX: DECISION: [Clear statement of what you are deciding] DATE: [Date of analysis] OWNER: [Decision maker(s)] DEADLINE: [When decision must be made] OPTIONS UNDER CONSIDERATION: A. [Option name and brief description] B. [Option name and brief description] C. [Option name and brief description] D. [Status quo / do nothing] MUST-HAVE CRITERIA (pass/fail — eliminates options): | Requirement | Option A | Option B | Option C | Option D | |----------------------|----------|----------|----------|----------| | [Hard requirement 1] | Pass/Fail| Pass/Fail| Pass/Fail| Pass/Fail| | [Hard requirement 2] | Pass/Fail| Pass/Fail| Pass/Fail| Pass/Fail| | [Hard requirement 3] | Pass/Fail| Pass/Fail| Pass/Fail| Pass/Fail| NICE-TO-HAVE CRITERIA (scored and weighted): | Criterion | Weight | Opt A | Opt B | Opt C | Opt D | |-------------|--------|-------|-------|-------|-------| | [Criterion] | X% | [1-5] | [1-5] | [1-5] | [1-5] | | [Criterion] | X% | [1-5] | [1-5] | [1-5] | [1-5] | | [Criterion] | X% | [1-5] | [1-5] | [1-5] | [1-5] | |-------------|--------|-------|-------|-------|-------| | TOTAL | 100% | [sum] | [sum] | [sum] | [sum] | RECOMMENDATION: [Option letter] because [1-2 sentence rationale] RISKS OF CHOSEN OPTION: 1. [Risk and mitigation plan] 2. [Risk and mitigation plan] NEXT STEPS: 1. [Action item, owner, deadline] 2. [Action item, owner, deadline] ``` ## Trade-Off Analysis Framework ### Trade-Off Mapping ``` TRADE-OFF ANALYSIS: STEP 1: Identify the key trade-off dimensions Common trade-offs: - Cost vs Quality - Speed vs Thoroughness - Flexibility vs Standardization - Control vs Convenience - Short-term vs Long-term - Risk vs Reward - Simplicity vs Capability STEP 2: Map options on trade-off axes HIGH QUALITY | | Option B | * | LOW COST -------+--------- HIGH COST | Option A| * | | Option C | * LOW QUALITY STEP 3: Identify the efficient frontier Options on the frontier are rationally competitive. Options below the frontier are dominated (another option is better on all axes). STEP 4: Choose based on priorities "We are optimizing for [dimension] while keeping [other dimension] above [minimum threshold]." ``` ### Trade-Off Decision Rules | Rule | When to Use | How It Works | | --- | --- | --- | | **Maximize one, threshold others** | Clear primary objective | Set minimums for secondary criteria, then pick highest on primary | | **Satisfice** | Time-pressured, good enough is fine | Pick first option that meets all minimum thresholds | | **Lexicographic** | Clear priority ordering | Sort by most important criterion first, break ties with second | | **Minimax regret** | High uncertainty | Choose option that minimizes worst-case disappointment | | **Expected value** | Quantifiable outcomes and probabilities | Probability x payoff for each scenario, pick highest EV | ## Sensitivity Analysis for Decisions ### Weight Sensitivity Testing ``` SENSITIVITY ANALYSIS: PURPOSE: Test if the recommendation changes when weights shift. BASELINE WEIGHTS: Cost: 30% | Quality: 25% | Speed: 20% | Support: 15% | Risk: 10% Winner: Option B (score: 3.85) SCENARIO 1 — Cost-focused (Cost +15%, others proportionally reduced): Cost: 45% | Quality: 20% | Speed: 16% | Support: 12% | Risk: 7% Winner: [recalculate] SCENARIO 2 — Quality-focused (Quality +15%): Cost: 24% | Quality: 40% | Speed: 16% | Support: 12% | Risk: 8% Winner: [recalculate] SCENARIO 3 — Risk-averse (Risk +20%): Cost: 22% | Quality: 19% | Speed: 15% | Support: 14% | Risk: 30% Winner: [recalculate] INTERPRETATION: If the same option wins in all scenarios → ROBUST decision If winner changes in 1 scenario → Note the sensitivity If winner changes in 2+ scenarios → Decision depends on priorities ``` ### Score Sensitivity Testing ``` BREAKEVEN ANALYSIS: "How much would Option A's score on [criterion] need to improve to overtake Option B?" Current: Option A total: 3.45 Option B total: 3.85 Gap: 0.40 Criterion X (weight 25%): Option A score: 2 Required score to close gap: 2 + (0.40 / 0.25) = 3.6 → round to 4 Is this plausible? [Yes/No] If yes → decision is sensitive to this criterion If no → decision is robust on this dimension ``` ## Recommendation Memo Template ### Executive Decision Memo ``` DECISION RECOMMENDATION MEMO TO: [Decision maker(s)] FROM: [Analyst / Team] DATE: [Date] RE: Recommendation: [Decision topic] ───────────────────────────────────────────── EXECUTIVE SUMMARY: We recommend [Option X] for [one-sentence rationale]. This option scores highest across our evaluation criteria, particularly in [top 2 criteria]. Estimated [cost/timeline]: [key number]. Key risk: [top risk and mitigation]. ───────────────────────────────────────────── BACKGROUND: [2-3 sentences on why this decision is needed now] OPTIONS EVALUATED: A. [Option and one-line description] B. [Option and one-line description] C. [Option and one-line description] EVALUATION CRITERIA AND WEIGHTS: [Criterion 1] (X%) | [Criterion 2] (X%) | [Criterion 3] (X%) SCORING SUMMARY: | Option | Score | Rank | Key Strength | Key Weakness | |--------|-------|------|----------------------|---------------------| | A | 3.45 | 2 | [strength] | [weakness] | | B | 3.85 | 1 | [strength] | [weakness] | | C | 2.90 | 3 | [strength] | [weakness] | RECOMMENDATION: Option B Rationale: [3-5 sentences explaining why, addressing trade-offs] SENSITIVITY: This recommendation holds under all tested scenarios except [edge case], which would require [condition]. RISKS AND MITIGATIONS: 1. [Risk]: [Mitigation plan] 2. [Risk]: [Mitigation plan] IMPLEMENTATION PLAN: 1. [Step, owner, date] 2. [Step, owner, date] 3. [Decision review checkpoint, date] ───────────────────────────────────────────── APPENDIX: Detailed scoring matrix, sensitivity analysis ``` ## Vendor Evaluation Scorecard ### Vendor Assessment Template ``` VENDOR EVALUATION SCORECARD: VENDOR: [Company name] EVALUATED BY: [Names] DATE: [Date] PRODUCT/SERVICE: [What you are evaluating] CATEGORY 1: PRODUCT FIT (30% weight) | Criterion | Score (1-5) | Notes | |----------------------------|-------------|----------------------| | Feature completeness | | | | Integration capability | | | | Scalability | | | | Customization options | | | | User experience / UI | | | | Category subtotal | /25 | | CATEGORY 2: COMMERCIAL (25% weight) | Criterion | Score (1-5) | Notes | |----------------------------|-------------|----------------------| | Total cost of ownership | | | | Pricing transparency | | | | Contract flexibility | | | | Payment terms | | | | ROI timeline | | | | Category subtotal | /25 | | CATEGORY 3: SUPPORT AND SERVICE (20% weight) | Criterion | Score (1-5) | Notes | |----------------------------|-------------|----------------------| | Implementation support | | | | Training resources | | | | Ongoing customer support | | | | SLA commitments | | | | Account management | | | | Category subtotal | /25 | | CATEGORY 4: COMPANY VIABILITY (15% weight) | Criterion | Score (1-5) | Notes | |----------------------------|-------------|----------------------| | Financial stability | | | | Market position | | | | Product roadmap | | | | Customer references | | | | Industry reputation | | | | Category subtotal | /25 | | CATEGORY 5: RISK (10% weight) | Criterion | Score (1-5) | Notes | |----------------------------|-------------|----------------------| | Data security / compliance | | | | Vendor lock-in risk | | | | Migration complexity | | | | Business continuity plan | | | | Reference check results | | | | Category subtotal | /25 | | OVERALL WEIGHTED SCORE: [calculated] / 5.0 RECOMMENDATION: Proceed / Shortlist / Reject ``` ## Technology Selection Framework ### Technology Evaluation Criteria ``` TECHNOLOGY SELECTION MATRIX: FUNCTIONAL FIT: - [ ] Meets core requirements (pass/fail list) - [ ] Handles expected scale (users, data, transactions) - [ ] Integrates with existing stack - [ ] Supports required platforms/environments DEVELOPER EXPERIENCE: - [ ] Documentation quality and completeness - [ ] Community size and activity (GitHub stars, forums) - [ ] Learning curve for the team - [ ] Tooling and IDE support - [ ] Error messages and debugging experience OPERATIONAL: - [ ] Deployment model fits infrastructure - [ ] Monitoring and observability support - [ ] Backup and disaster recovery - [ ] Security track record and patching cadence STRATEGIC: - [ ] Aligned with technology direction - [ ] Vendor/project longevity (not abandonware) - [ ] Hiring market (can you find people who know it?) - [ ] Exit strategy (migration path if you switch later) TOTAL COST: - [ ] License / subscription fees - [ ] Infrastructure costs - [ ] Training and ramp-up time - [ ] Maintenance and operations - [ ] Opportunity cost of alternatives ``` ### Build vs Buy Decision | Factor | Build | Buy | Hybrid | | --- | --- | --- | --- | | Core differentiator? | Yes — build it | No — buy it | Customize a platform | | Team has expertise? | Yes | No | Partial | | Time to value | Months | Weeks | Weeks-Months | | Long-term cost | Higher (maintenance) | Predictable (subscription) | Mixed | | Control | Full | Limited | Moderate | | Risk | Technical debt | Vendor dependency | Both | | Best when | Unique requirements, strategic IP | Commodity functionality | 80/20 fit | ## Decision Anti-Patterns ``` COMMON DECISION MISTAKES: 1. ANALYSIS PARALYSIS Symptom: Endless evaluation, no decision made Fix: Set a decision deadline and "good enough" threshold 2. ANCHORING TO FIRST OPTION Symptom: First option evaluated becomes the default Fix: Evaluate all options before scoring any 3. CONFIRMATION BIAS Symptom: Seeking data that supports preferred option Fix: Assign a devil's advocate for each option 4. SUNK COST FALLACY Symptom: Sticking with an option because of past investment Fix: Evaluate options on future value only 5. RECENCY BIAS Symptom: Overweighting the last demo or reference call Fix: Standardize evaluation timing and criteria 6. GROUPTHINK Symptom: Team converges without genuine debate Fix: Independent scoring before group discussion 7. FEATURE COUNTING Symptom: Most features = best option (ignoring fit) Fix: Weight criteria by importance, not count 8. IGNORING STATUS QUO Symptom: Not comparing options against doing nothing Fix: Always include "do nothing" as Option D ``` ## See Also - [Business Strategy](../business-strategy/SKILL.md) - [Product Management](../product-management/SKILL.md) - [Risk Management](../risk-management/SKILL.md)

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