weighted-scoring-matrix

Weighted Scoring Matrix

The Problem

Multi-factor decisions become arbitrary without explicit weights:

• "We chose Option A because it felt better"
• No audit trail for why factors mattered
• Inconsistent decision-making across time

The Solution

Explicit scoring matrix with normalized weights.

// Define factors and weights (must sum to 1.0)
const factors = {
  performance: { weight: 0.30, description: 'Response time, throughput' },
  maintainability: { weight: 0.25, description: 'Code clarity, test coverage' },
  cost: { weight: 0.20, description: 'Infrastructure, licensing' },
  security: { weight: 0.15, description: 'Vulnerability surface' },
  userExperience: { weight: 0.10, description: 'Ease of use, learning curve' }
};

// Score each option (1-5 scale)
const options = {
  optionA: { performance: 4, maintainability: 5, cost: 3, security: 4, userExperience: 4 },
  optionB: { performance: 5, maintainability: 3, cost: 2, security: 5, userExperience: 3 },
  optionC: { performance: 3, maintainability: 4, cost: 5, security: 3, userExperience: 5 }
};

// Calculate weighted scores
function calculateScore(scores) {
  return Object.entries(factors).reduce((total, [factor, { weight }]) => {
    return total + (scores[factor] * weight);
  }, 0);
}

Object.entries(options).forEach(([name, scores]) => {
  console.log(`${name}: ${calculateScore(scores).toFixed(2)}`);
});
// optionA: 4.05, optionB: 3.70, optionC: 4.00

Optional Boosts

For factors that can disqualify or strongly prefer:

const boosts = {
  mustHave: (score) => score < 3 ? 0 : score,  // Zero if below threshold
  preferred: (score) => score >= 4 ? score * 1.1 : score  // 10% boost if high
};

Output Format

Option	Perf (0.30)	Maint (0.25)	Cost (0.20)	Sec (0.15)	UX (0.10)	Total
A	4 (1.20)	5 (1.25)	3 (0.60)	4 (0.60)	4 (0.40)	4.05
B	5 (1.50)	3 (0.75)	2 (0.40)	5 (0.75)	3 (0.30)	3.70
C	3 (0.90)	4 (1.00)	5 (1.00)	3 (0.45)	5 (0.50)	3.85