A scorecard is a valuable chart for measuring and tracking performance against specific goals, whether in business, project management, or personal development. It provides a clear framework for assessing progress by using key performance indicators (KPIs) or predefined criteria. By offering a visual and structured way to evaluate success, a scorecard enables informed decision-making, continuous improvement, and goal achievement.
Create a Chart
to add a new chart:
Within the table, click on the "+" sign above the search bar.
From the drop-down menu, select Chart view.
A box will appear to enter a name for the view—choose a descriptive name that reflects its content.
Select who can edit:
Collaborative for team access and editing.
Personal for individual use. note: you can't add it in dashboards
Click "Add".
Click Chart type .
from the list Choose Score Card Chart.
Build a Score Card Chart
Choose X-Axis: Select a column from the drop-down list to define the measured variable for the chart.
Choose a Measure: Once a column is selected, choose the appropriate measure to apply.
Dynamic Measures: The available measures will be automatically populated based on the selected column type, ensuring relevant calculations and insights.
Add Sub-Header (optional): write a description for KPI, as it helps break up content, making it easier to read and understand.
Score Cards Setup:
🔴 X-Axis | a drop-down list consist of columns of the table. |
🟢 Measures | available measures will be automatically populated based on the selected column type, ensuring relevant calculations and insights. |
🔵 Sub-headers | helps break up content, making it easier to read and understand. |
🟠 Currency | Currencies and Number format always follow the column setup within the table. |
Available Measures Based on Column Types:
Numbers:
Count – Counts the number of entries in the selected column.
Sum – Adds up all numerical values.
Avg – Calculates the average of the values.
Min/Max – Retrieves the minimum or maximum value in the dataset.
Other Column Types:
Count ONLY – Non-numeric columns can only be counted.
Numbers formats always follow the column setup within the table.
Examples:
If you want to calculate the total number of projects, you can select the project id column and apply the Count measure.
If you need to analyze a project budget, you can choose the budget column and apply Sum, Average, Min, or Max as needed.
Filter a Score Card:
Within the view, click on the funnel icon in the view bar.
A box will appear; click on "Add filter."
Three fields will be displayed:
Choose a Column
Choose a Condition
Choose a Value to Filter by
The filter will be applied directly to the view, updating the displayed data based on the selected criteria.
Example:
you can filter ONLY Completed Projects. but don't forget to add sub-header to explain the filtered data.
Sharing a Score Card
to Share Chart internally with users that have access to the Charts table:
Click Share Chart icon at the top corner of the view.
Copy the link.
Share it.
note: Only people with access permission to this view can see it using this link. You can use. to learn more about access click here.
Publishing a Chart
Once your Chart is designed and tested, publishing it involves making it accessible to audience.
to Publish a Chart:
Click Share Chart icon at the top corner of the view.
Go to publish tab.
Click Publish.
Copy the link.
Share it.
note: there are options to Restrict Access with Password, Change the Link or Unpublish the Link.
For more details, visit the public sharing article.
Fields Availability
If certain fields don’t appear in the list when creating charts, it's because some field types are not supported for visualization on both the x-axis and y-axis. These include:
Long text: Typically not suitable for numerical or categorical representation in charts.
File: Contains attachments or documents, which cannot be plotted on a chart.
Multiple select: Stores multiple values, making it difficult to plot in a single axis format.
Collaborator: Represents users rather than measurable data.
Link to table: References another table instead of containing direct numerical or categorical data.
Lookup: Pulls values from another table but isn’t always structured for charting.
Formula containing lookup output: Derived data that depends on lookups, which may not be supported in chart rendering.
AI: AI-generated outputs may be complex and not directly usable in charts.
Formula containing AI output: Similar to AI fields, these often contain generated text or complex logic not suited for visualization.
These limitations exist to ensure that only structured, quantifiable data is used for meaningful chart representation.