KPI dashboard example: actual versus target
A KPI dashboard puts a defined performance measure next to the target and reporting period used to judge it. This synthetic revenue example contains 270,000 of actual revenue against a 300,000 target across two teams and three months: 90% attainment.
Updated
How can I try this KPI dashboard with my CSV?
The live view opens the clearly marked synthetic sample. Choose Use my CSV or paste a CSV to replace it, then match the category, period and measure fields. Continue editing in xmetric carries the current view into the app.
Synthetic sample · January–March 2026 · illustrative currency units
Use a header row, one category column, one reporting-period column and a numeric measure. Use a numeric reporting period, YYYY-MM (for example 2026-01), or YYYY-MM-DD (for example 2026-01-31). Labels such as Q1 or Q2 are not supported; convert them to a numeric period or an explicit date before importing. Choose fields after importing. CSV limits: 32 MiB on lower-memory devices or 160 MiB on higher-memory devices, and 3.5 million source rows. Views support up to 10,000 marks per sheet. Continue editing supports up to 100,000 source rows.
Opening the synthetic sample. Your own CSV replaces it.
The live view aggregates the selected primary and comparison fields, calculates the defined comparison, and charts the primary measure by category and period. The linked sample record defines the expected values for the initial SUM settings. A ratio with a zero denominator is undefined.
What question does this dashboard example answer?
Review revenue performance against a target for the same teams and reporting periods.
Use the month trend to locate a change, then the team split to identify the revenue slice to investigate. A revenue gap does not identify its cause; compare the source transactions and the target-setting assumptions before deciding what to change.
Which fields and row grain does this sample use?
Each of the six synthetic rows is one category-month summary for January–March 2026. The fields below define this example; importing a CSV does not import hidden Power BI measures or Tableau calculations.
| Field | Definition |
|---|---|
| Period | Reporting month in YYYY-MM format; actual and target cover the same month. Your own CSV may use numeric periods, YYYY-MM or YYYY-MM-DD; Q1/Q2 labels are not supported. |
| Team | Team responsible for this monthly revenue slice; North and South are synthetic labels. |
| Actual | Actual revenue in illustrative currency units for this team-month; sum across non-overlapping rows. |
| Target | Revenue target in the same units and team-month grain; sum across the same rows. |
How are the worked sample metrics calculated?
The formulas below define this sample using all six rows, with no additional filters. They are independently checkable arithmetic expectations, rather than a claim of native Tableau or Power BI parity.
Download the exact synthetic sample CSV · Read the definitions and expected values (JSON)
| Metric | Formula | Defined sample value | Definition |
|---|---|---|---|
| Actual revenue | SUM(Actual) | 270,000 | Sum all six actual-revenue rows. |
| Revenue target | SUM(Target) | 300,000 | Sum the six matching team-month targets. |
| Target attainment | 100 × SUM(Actual) / SUM(Target) | 90% | 270,000 / 300,000 × 100; a zero target leaves this ratio undefined. |
| Gap to target | SUM(Actual) − SUM(Target) | −30,000 | 270,000 − 300,000; a negative gap is below this revenue target. |
January contributes 80,000, February 90,000 and March 100,000. North contributes 155,000 and South 115,000. Adding team or month totals gives the same 270,000 actual-revenue total; do not add both sets of totals together.
Which exact rows produce those sample numbers?
The following rows are the complete authored sample behind this page, not customer data or an industry benchmark. Use the linked CSV and JSON record to reproduce the defined totals.
Download the exact synthetic sample CSV · Read the definitions and expected values (JSON)
| Period | Team | Actual | Target |
|---|---|---|---|
| 2026-01 | North | 45000 | 50000 |
| 2026-01 | South | 35000 | 50000 |
| 2026-02 | North | 50000 | 50000 |
| 2026-02 | South | 40000 | 50000 |
| 2026-03 | North | 60000 | 50000 |
| 2026-03 | South | 40000 | 50000 |
How do I prepare and inspect my own dashboard data?
Use one consistent row grain, identify the category and reporting-period columns, and select the numeric measure whose aggregation answers your question.
- Remove precomputed total rows when your CSV also contains their underlying detail.
- Use a numeric reporting period, YYYY-MM (for example 2026-01), or YYYY-MM-DD (for example 2026-01-31). Labels such as Q1 or Q2 are not supported; convert them to a numeric period or an explicit date before importing.
- Choose Use my CSV or paste the header and rows; match the category, period and measure controls to your columns.
- Start with SUM for additive measures. AVG is a mean of input rows, not a weighted ratio.
- Compare the total, category split and period view with the source export before continuing in xmetric.
What can change the interpretation of this dashboard?
A KPI name does not supply a definition. Keep revenue units, recognition rules and the target's team-month grain consistent. Averaging row attainment percentages can change the answer when target sizes differ; use total actual divided by total target for the defined overall ratio.
This CSV example supplies only the explicitly listed fields. A Power BI Desktop .pbix or Tableau .twbx workbook may contain additional calculations, filters and relationships; the CSV is not a replacement for those governed definitions.
Which dashboard example can I inspect next?
Choose a different example when its row grain and metric definitions better match the review you need to perform.
How do the measures in this dashboard differ?
These measures answer different questions over the same sample rows. A total, a count and a ratio have different definitions; changing the selected column does not create a new governed calculation.
| Measure | Question it answers | Formula | Defined sample value |
|---|---|---|---|
| Actual revenue | What revenue is recorded? | SUM(Actual) | 270,000 |
| Revenue target | What revenue was planned for those rows? | SUM(Target) | 300,000 |
| Target attainment | What share of the total target was achieved? | 100 × SUM(Actual) / SUM(Target) | 90% |
What else do people ask?
This KPI dashboard uses the explicitly defined sample fields above. The answers below clarify which measures are live, which are worked calculations, and which source files are available.
Which KPIs should this revenue dashboard include?
This example defines actual revenue, revenue target, attainment and gap at the team-month grain. Choose measures that answer your review question and document their units, period and aggregation; the CSV supplies no hidden company KPI definitions.
Does the live KPI panel calculate target attainment?
The panel uses the selected primary and target fields to calculate attainment alongside their totals, then charts the primary measure by team and month. With the sample's default SUM settings, Actual is 270,000, Target is 300,000 and attainment is 90%. A zero target leaves attainment undefined; changing the fields or aggregation changes the calculation.
Which reporting-period values can I use in my CSV?
Use a numeric reporting period, YYYY-MM (for example 2026-01), or YYYY-MM-DD (for example 2026-01-31). Labels such as Q1 or Q2 are not supported; convert them to a numeric period or an explicit date before importing.
Can I download this example as a Power BI .pbix file?
This page provides the exact synthetic CSV and its definition record. It does not provide a Power BI .pbix download. Continue in xmetric to inspect the actions available for the current workbook.
Are the sample numbers measured customer or native workbook results?
No. These are authored synthetic inputs and defined arithmetic expectations. They are neither customer results nor evidence of native Tableau or Power BI compatibility. Reconcile the live result to your own source after replacing the sample.