Auditing a BSI Scorecard: Where Is the Valuation Leaking?
Objective: Given a five-metric Brand Strength Index scorecard with real weights, calculate the weighted BSI score, determine which royalty-rate band it falls into, and identify the single metric dragging the score down.
You're on the brand team at Snowflake ahead of the annual royalty-relief valuation refresh. The consumer BSI survey just came back and the data team needs the weighted score before the finance meeting.
Score the five BSI metrics against their weights, determine whether the brand clears the 75-point top-royalty-rate threshold, and flag which single metric is costing the most points.
Before you start
What you'll need
Free path (everything below is enough to finish)
A five-row weighted sum needs nothing more than a spreadsheet
The process
1 step
Step 01 of 01
The lesson's BSI table weights five metrics: Familiarity (20%), Consideration (20%), Preference (20%), Loyalty (25%), and Advocacy (15%). A score above 75 pushes the royalty rate to the sector ceiling; below 40 compresses it below the floor.
Snowflake's raw BSI sub-scores came back as Familiarity 82, Consideration 79, Preference 68, Loyalty 61, Advocacy 74. What is the weighted BSI, which royalty band does it land in, and which metric is dragging it down the most?
Procedure
- List the five metrics with their raw scores and the lesson's fixed weights
- Multiply each raw score by its weight to get the weighted contribution
- Sum the five weighted contributions to get the final BSI
- Compare each raw score to the category's typical range to spot the biggest underperformer relative to the others
Familiarity: 82 x 20% = 16.4 Consideration: 79 x 20% = 15.8 Preference: 68 x 20% = 13.6 Loyalty: 61 x 25% = 15.25 Advocacy: 74 x 15% = 11.1 Weighted BSI = 72.15
Healthy
The weighted BSI lands close to but below 75, and the audit correctly names Loyalty as the largest drag both because its raw score (61) is the lowest and because it carries the heaviest weight (25%).
Unhealthy
Treating Familiarity as the concern because it 'sounds important,' when the raw data shows Familiarity is the strongest metric at 82, or averaging the five raw scores unweighted (72.8) instead of applying the weights.
What this means
At 72.15, Snowflake sits just under the 75-point top-royalty-rate threshold. Loyalty is both the lowest raw score and the highest-weighted metric, so it has an outsized effect on the final number, closing even a 5-point gap there would likely clear the threshold.
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| Weighted BSI sits within 5 points of the 75 threshold | Prioritize research into the lowest-scoring, highest-weighted metric before the next survey wave | half day |
| BSI calculated as a simple average instead of weighted | Rebuild the scorecard with the lesson's fixed weights before presenting to finance | 5 min |
Final deliverable
A completed weighted BSI scorecard with the final score, the royalty-band determination, and a one-line note identifying the biggest drag metric.
See a reference example
Grab Holdings BSI scorecard (excerpt) Familiarity 74 x 20% = 14.8 Consideration 58 x 20% = 11.6 Preference 55 x 20% = 11.0 Loyalty 49 x 25% = 12.25 Advocacy 62 x 15% = 9.3 Weighted BSI = 58.95, mid-band, below the 75 ceiling and above the 40 floor. Loyalty is the biggest drag at 49.
Success criteria
You're done when you can:
- Uses the correct fixed weights (20/20/20/25/15), not an unweighted average
- Correctly determines whether the score clears 75 or falls below 40
- Identifies the metric with the largest combined effect of low score and high weight, not just the lowest raw number