Creating a Statistic

When creating a statistic, you can choose from different types depending on how the value is obtained and displayed.

Simple Statistic

A simple statistic stores values that you enter manually. This is the most common type for any metric collected directly from your operations.

Examples:

• Daily sales revenue — enter the amount collected each day
• Customer support tickets — count received per day
• Hours worked — record hours logged by an employee
• Production units — count items manufactured

Use when: you have raw data to record and want full control over each value.

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Combined Statistic

A combined statistic calculates its value automatically from one or more other statistics (its children or source statistics). No manual entry is needed — the value updates whenever the source data changes.

Combination Types

Type	Behavior	Example
Sum	Adds all source values	Total Revenue = Online Sales + In-Store Sales
Difference	Subtracts one value from another	Net Profit = Revenue - Costs
Percentage	Calculates a percentage of a single value	Commission = Revenue × 10%

Examples

Total Revenue (Sum = Online Sales + In-Store Sales)
├── Online Sales
└── In-Store Sales

Net Profit (Difference = Revenue - Costs)
├── Revenue
└── Costs

Commission (Percentage = Revenue × 10%)
└── Revenue

Use when: you want to derive a metric from existing data automatically, without manual entry.

Nested Combinations

Combined statistics can be nested. A combined statistic can use other combined statistics as sources:

Total Company Revenue (Sum)
├── Region North (Sum)
│   ├── Store A
│   ├── Store B
│   └── Store C
└── Region South (Sum)
    ├── Store D
    ├── Store E
    └── Store F

This way you can build a hierarchy of auto-calculated metrics.

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Inverted Statistic

An inverted statistic displays values where lower is better, reversing the typical "higher is better" assumption. The chart and indicators automatically adapt to reflect this.

Examples:

• Customer complaints — fewer is better
• Error rate — fewer defects means higher quality
• Absenteeism — less absence means better attendance
• Delivery delays — fewer delays means better service

Use when: you track a negative or inverse metric and want the visual feedback to match the business logic (greener = better, even though the number is lower).