A company wants to reward top-performing employees based on the volume of work completed (e.g., number of cases handled, sales made, or units processed). The top 3 performers across all departments will be rewarded with monetary bonuses and department performers will be rewarded with vacation. Management wants a Power BI dashboard to track performance rankings & identify top performers.
Key Requirement:
Users would love to see a detailed daily report using powerBI
✅ Volume
Total workload completed by the employee. Represents the combined weight or size of tasks handled, regardless of task count.
✅ Units Processed
Slightly correlated with volume, but more granular. An employee could handle a few large-volume tasks or many small ones.
🗣️ Feedback Score
Average score (1 to 5) from internal/external reviews.
⏱️ Efficiency Score (Tasks per Hour)
Higher efficiency = higher ranking in case of volume tie.
📋 Task Accuracy (%)
Could simulate task error rate or rework needed. Higher accuracy is better.
Dax Formula Created in powerbi:
EmployeeRankTie =
RANKX(
ALL('Employee Performance Tracker'[EmployeeName]),
CALCULATE(
[Total Volume] * 1000000 +
DIVIDE(1, SUM('Employee Performance Tracker'[UnitsProcessed])) * 10000 +
// [Total Unit Processed] * 10000 +
[AverageFeedbackScore] * 100 +
[Average TaskAccuracy] +
[Average Efficiency Score] / 100
),
,
DESC,
Dense
)
Logic behind formula
| Metric | Weight | Purpose |
| Volume | ×1,000,000 | Primary ranking factor |
| UnitsProcessed | ×10,000 | Secondary tie-breaker |
| FeedbackScore | ×100 | More weight than accuracy/efficiency |
| TaskAccuracy | ×1 | Fine-tunes tie resolution |
| EfficiencyScore | ÷100 | Minor influence, last tie-breaker |
These weights ensure that Volume dominates the ranking, but if there’s a tie, the system looks next at UnitsProcessed, then FeedbackScore, and so on.
Why We Use Different Weights (Multipliers)
Not all metrics are on the same scale. Here’s why we scale each one:
Metric | Typical Range | Weight Used | Why This Scaling? |
Volume | 0–2,000+ | ×1,000,000 | Makes Volume the dominant factor |
UnitsProcessed | 0–2,500+ | ×10,000 | Strong secondary influence in tie-breaks |
FeedbackScore | 1.0–5.0 | ×100 | Gives enough impact without overpowering volume |
TaskAccuracy | 85–100% | ×1 | Already a decent scale |
EfficiencyScore | 5–15 | ÷100 | We want this to have light influence only |
Example
Volume | UnitsProcessed | Feedback | Accuracy | Efficiency |
100 | 120 | 4.8 | 96.2 | 12.1 |
100 | 119 | 4.9 | 96.5 | 12.0 |
Then the first one wins due to higher UnitsProcessed, even though the second one has better feedback.
Metric | Weight | Purpose |
Volume | ×1,000,000 | Primary ranking factor |
UnitsProcessed | ×10,000 | Secondary tie-breaker |
FeedbackScore | ×100 | More weight than accuracy/efficiency |
TaskAccuracy | ×1 | Fine-tunes tie resolution |
EfficiencyScore | ÷100 | Minor influence, last tie-breaker |
These weights ensure that Volume dominates the ranking, but if there’s a tie, the system looks next at UnitsProcessed, then FeedbackScore, and so on.