How to Compare Actual Data with Manually Defined Target Values in Bold BI

Use Case

Organizations often track actual business performance against predefined targets such as sales quotas, revenue goals, departmental budgets, or KPI benchmarks. While actual performance data is usually available in transactional systems and can be connected directly to Bold BI, target values are often maintained separately in spreadsheets, planning systems, or internal business documents. In such situations, it becomes necessary to bring both actual and target values together to measure performance, monitor goal attainment, and visualize variances effectively. This article explains the available approaches in Bold BI to compare actual data with manually defined target values, enabling meaningful performance analysis and KPI tracking.

Approach 1: Maintain Target Values in a Separate Data Source

If target values need to be maintained for multiple business entities, such as employee sales quotas, regional revenue goals, product-wise targets, or monthly budget allocations, and these values are updated regularly, it is recommended to store them in a separate data source such as:

• Excel or CSV
• Database table
• Google Sheets
• Web API

Add the target dataset to Bold BI as a new data source and create a relationship with the existing transactional data source used for reporting. This allows actual and target values to be analyzed and compared together using common dimensions such as Employee, Product, Region, or Date.

By maintaining targets in a separate data source, business users can update goals independently without modifying the transactional data. This approach is particularly useful when managing a large number of target values or when targets are revised periodically, such as monthly, quarterly, or annually.

This approach is recommended for scenarios where target values change frequently or are managed outside Bold BI.

Approach 2: Define Fixed Target Values Using an Expression Column

This approach is suitable when the target values are relatively fixed and do not require frequent updates.

Since an Expression Column derives values from the existing dataset, it serves as an alternative approach for scenarios where maintaining a separate target data source is unnecessary.

Step 1: Create an Expression Column

Create an expression using conditional logic to assign the required target values.

SUM(
   CASE
       WHEN EmployeeName = 'Kelly' THEN 10000000
       WHEN EmployeeName = 'Jess' THEN 4000000
       ELSE 0
   END
) 

The expression returns the configured target value based on the corresponding data.

Step 2: Configure the Widget

Configure a comparison widget, such as a KPI Card or Gauge with:

• Actual Value – Value retrieved from the connected data source.
• Target Value – Value created using the Expression Column.

The configured values can then be used to visualize actual performance against the defined target.

Conclusion

Bold BI provides flexible options for comparing actual performance against target values, even when the targets are not available in the transactional data source.

• Use a separate data source when managing multiple target values, such as sales quotas, budgets, or KPI goals, that are updated periodically and maintained independently of the transactional data.
• Use an Expression Column when target values are fixed, limited in number, and do not require ongoing maintenance.

By selecting the appropriate approach, organizations can effectively monitor performance, measure goal attainment, and build meaningful KPI dashboards that provide accurate insights into business outcomes. The recommended approach depends on the scale of target management, the frequency of updates, and how closely the target data needs to align with the underlying transactional data.