Overview
The Answer Distribution widget visualizes the distribution of responses for a specific question on a checklist. It uses a clear and intuitive pie chart to represent answer categories (e.g., "OK" vs. "NOT OK"), enabling users to quickly assess performance or compliance levels.
Features and Conditional Formatting
Answer Categories: Each response category (e.g., "OK" and "NOT OK") is displayed as a proportional segment of the chart.
Conditional Formatting: The widget allows filtering based on specific conditions, such as only showing results where related questions have particular answers.
Dynamic Updates: Filters and conditions dynamically adjust the displayed data to focus on relevant insights.
Setup and Configuration
Add the Widget:
Navigate to your Dashboard.
Select the Answer Distribution widget and add it to your preferred location.
Set Filters:
Click the filter icon to select a checklist and a specific question.
Use the "Conditions" section to define additional criteria. For example:
Filter by a related question (e.g., "Inspect each seat unit") and set a condition (e.g., "OK").
Apply the filter to refine the data visualization.
Customize Display:
Toggle between different time periods using the timeframe selector.
Adjust location-based filters for targeted analysis.
Tips for Effective Use
Use the widget during operational reviews to highlight key trends in compliance or performance.
Combine with conditional filters to isolate problem areas, such as high percentages of "NOT OK" responses.
Share filtered views with maintenance or operations teams to address specific issues.
Example Use Case: A safety manager reviews the distribution of responses for the question, "Check seat unit restraints for overall condition." By applying a filter to focus on results where another checklist question specifies "Inspect each seat unit," the manager identifies a higher-than-expected percentage of "NOT OK" responses. This insight prompts immediate action to inspect and resolve issues in specific areas.
This setup ensures data-driven decision-making for operational and safety improvements.