Scoring Model: Template, Example, and Step-by-Step Guide

Which tool should we use? Which vendor should we choose? Which solution is best? For complex decisions with multiple criteria, a scoring model (also called weighted decision matrix) helps you objectively determine the best option.

In this guide, you'll learn how scoring models work, when to use them, and how to create one step by step.

What is a Scoring Model?

A scoring model is a method for evaluating alternatives based on multiple criteria. It makes complex decisions transparent and traceable.

The principle:

1. Define criteria that matter to you
2. Weight the criteria by importance
3. Rate each alternative for each criterion
4. Calculate a total score
5. The alternative with the highest score wins

When to Use a Scoring Model

Scoring models are particularly useful for:

• Vendor selection: Which service provider to hire?
• Tool decisions: Which software to implement?
• Make or buy: Build internally or purchase?
• Location decisions: Which office/data center?
• Hiring decisions: Which candidate to hire?
• Project prioritization: Which project first?

Not suitable for:

• Purely financial decisions (use ROI analysis instead)
• Decisions with only one criterion
• Trivial decisions

Step-by-Step Scoring Model Guide

Step 1: Define Alternatives

List all options you want to compare.

Example – CRM Selection:

• Alternative A: Salesforce
• Alternative B: HubSpot
• Alternative C: Pipedrive
• Alternative D: Custom development

Tip: 3-5 alternatives are ideal. More becomes unwieldy.

Step 2: Establish Criteria

What aspects are relevant for the decision?

Example – CRM Selection:

• Feature set
• User friendliness
• Integrations (API, interfaces)
• Cost (license + implementation)
• Support & documentation
• Scalability
• Data privacy (GDPR)

Tips for good criteria:

• Measurable or at least ratable
• Independent of each other (no overlap)
• Relevant for the decision
• 5-10 criteria are optimal

Step 3: Weight the Criteria

Not all criteria are equally important. Assign weights that total 100%.

Example:

Criterion	Weight
Feature set	25%
User friendliness	20%
Integrations	15%
Cost	15%
Support	10%
Scalability	10%
Data privacy	5%
Total	100%

Weighting methods:

• Direct assignment: Experts assign percentages
• Pairwise comparison: Compare each criterion against each other
• Ranking: Sort criteria, then derive weights

Step 4: Define Rating Scale

Define a uniform scale for all ratings.

Common scales:

• 1-5 points (simple)
• 1-10 points (more differentiated)
• 0-100 points (very differentiated)

Example with 1-5:

• 5 = Excellent / Fully met
• 4 = Good / Largely met
• 3 = Satisfactory / Partially met
• 2 = Adequate / Barely met
• 1 = Poor / Not met

Step 5: Rate Alternatives

Rate each alternative for each criterion.

Example:

Criterion	Weight	Salesforce	HubSpot	Pipedrive	Custom
Feature set	25%	5	4	3	4
User friendliness	20%	3	5	5	3
Integrations	15%	5	4	3	5
Cost	15%	2	4	5	2
Support	10%	4	4	3	1
Scalability	10%	5	4	3	4
Data privacy	5%	3	4	4	5

Step 6: Calculate Scores

Multiply each rating by its weight and sum up.

Calculation for Salesforce:

(5 × 0.25) + (3 × 0.20) + (5 × 0.15) + (2 × 0.15) + (4 × 0.10) + (5 × 0.10) + (3 × 0.05)
= 1.25 + 0.60 + 0.75 + 0.30 + 0.40 + 0.50 + 0.15
= 3.95

All scores:

Alternative	Score
Salesforce	3.95
HubSpot	4.25
Pipedrive	3.80
Custom	3.35

Result: HubSpot has the highest score and would be the recommended choice.

Step 7: Sensitivity Analysis

Check how robust the result is:

• What happens if a weight changes?
• Are there criteria that could flip the result?
• How close are the alternatives to each other?

With close results (like Salesforce vs. HubSpot here), a closer look at decisive criteria is worthwhile.

Scoring Model Template

SCORING MODEL / DECISION MATRIX

Decision: ________________________________
Date: ____________  Created by: ____________

ALTERNATIVES:
A: ________________
B: ________________
C: ________________

RATING SCALE: 1 (poor) to 5 (excellent)

┌─────────────────────┬────────┬─────┬─────┬─────┐
│ Criterion           │Weight  │  A  │  B  │  C  │
├─────────────────────┼────────┼─────┼─────┼─────┤
│                     │    %   │     │     │     │
├─────────────────────┼────────┼─────┼─────┼─────┤
│                     │    %   │     │     │     │
├─────────────────────┼────────┼─────┼─────┼─────┤
│                     │    %   │     │     │     │
├─────────────────────┼────────┼─────┼─────┼─────┤
│                     │    %   │     │     │     │
├─────────────────────┼────────┼─────┼─────┼─────┤
│                     │    %   │     │     │     │
├─────────────────────┼────────┼─────┼─────┼─────┤
│ TOTAL               │  100%  │     │     │     │
└─────────────────────┴────────┴─────┴─────┴─────┘

SCORES:
A: ______  B: ______  C: ______

RECOMMENDATION: ________________________________

RATIONALE:
_____________________________________________
_____________________________________________

Example: Vendor Selection

A company is looking for an IT service provider for a migration project. Three proposals have been received.

Starting Point:

	Vendor A	Vendor B	Vendor C
Price	$85,000	$120,000	$95,000
Duration	4 months	3 months	5 months
Team	2 consultants	4 consultants	3 consultants
References	3 similar	8 similar	1 similar

The Scoring Model:

Criterion	Weight	A	B	C
Expertise	30%	3	5	3
Price	25%	5	2	4
References	20%	3	5	2
Duration	15%	4	5	3
Availability	10%	4	3	5

Calculation:

Vendor A: (3×0.30) + (5×0.25) + (3×0.20) + (4×0.15) + (4×0.10) = 3.65

Vendor B: (5×0.30) + (2×0.25) + (5×0.20) + (5×0.15) + (3×0.10) = 4.05

Vendor C: (3×0.30) + (4×0.25) + (2×0.20) + (3×0.15) + (5×0.10) = 3.25

Result:

Vendor B wins despite the highest price – because expertise and references were heavily weighted, and they scored best in those areas.

Advantages of Scoring Models

• Transparency: Decision is traceable
• Objectivity: Reduces gut decisions
• Documentation: Decision basis is recorded
• Communication: Stakeholders understand the logic
• Comparability: Different aspects become comparable

Disadvantages and Limitations

• Pseudo-objectivity: Weights and ratings are subjective
• Effort: Time-intensive with many criteria/alternatives
• Manipulation: Weights can be chosen to fit desired outcome
• Quantification: Not everything can be captured in numbers
• Compensation: Weaknesses can be offset by strengths

Tips for Better Scoring Models

1. Pre-filter with Must-Have Criteria

Some requirements are non-negotiable. Filter by must-have criteria first, then analyze remaining options.

2. Involve Multiple People

Have different stakeholders rate independently. This reduces bias and increases acceptance.

3. Document Rating Rationale

Write down why you gave a rating. This helps in later discussions.

4. Set Weights Before Rating

Otherwise, there's temptation to adjust weights afterward to get a desired result.

5. Question the Result

Does the result feel right? If not, something might be off with criteria or weights.

Scoring Models in Proposals

As a freelancer or consultant, you can use scoring models in proposals too:

For the client:

"We recommend Solution B. Our scoring model shows this option performs best on your most important criteria – scalability and integrations."

In the proposal: An attached scoring model shows the client:

• You worked systematically
• The recommendation is justified
• You understand their priorities

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Present Decisions Professionally

A scoring model is only as good as its presentation. When you give your client a recommendation, it needs to look professional.

With SimpleProposals, you create proposals and recommendations that convince – clearly structured, professionally formatted, with traceable arguments.

Create professional proposals now