Hi,
How can we do RAG Analysis on PRE and POST data for the month? If I have to show this in a graphical representation, then how to present that using Excel, specifically using which graph?
Primarily, the requirement is to gauge if we assumed initially that this resource is in Amber status; however, at the end, the resource stays back, and our assumption goes wrong. How can we represent this in PRE and POST RAG Analysis in Excel, showing it in a graphical representation?
**Location**: Delhi, India
rag analysis, City-India-Delhi, Country-India
From India, Delhi
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How can we do RAG Analysis on PRE and POST data for the month? If I have to show this in a graphical representation, then how to present that using Excel, specifically using which graph?
Primarily, the requirement is to gauge if we assumed initially that this resource is in Amber status; however, at the end, the resource stays back, and our assumption goes wrong. How can we represent this in PRE and POST RAG Analysis in Excel, showing it in a graphical representation?
**Location**: Delhi, India
rag analysis, City-India-Delhi, Country-India
From India, Delhi
Acknowledge(0)Amend(0)
To perform RAG (Red, Amber, Green) Analysis on PRE and POST data for the month in Excel and represent it graphically, you can follow these steps:
1. Data Preparation:
- Organize your data with columns for resource names, initial status (PRE), final status (POST), and any relevant metrics.
- Assign Red, Amber, and Green statuses based on your criteria.
2. Calculating Changes:
- Calculate the difference between PRE and POST data to determine if the assumption was correct or not.
3. Graphical Representation:
- Use a Column Chart in Excel to visually represent the RAG Analysis.
- Assign different colors to Red, Amber, and Green statuses for clarity.
- Plot the initial (PRE) and final (POST) status for each resource on the chart.
4. Highlighting Assumption Changes:
- Use conditional formatting in Excel to highlight instances where the assumption changed from Amber to another status.
- This will visually emphasize where the initial assumption was incorrect.
5. Interpreting the Graph:
- Analyze the chart to identify resources where the assumption was incorrect based on the color changes from Amber to another status.
- This visual representation will help in understanding the impact of incorrect assumptions.
6. Regular Review:
- Conduct RAG Analysis regularly to track changes and ensure assumptions align with actual outcomes.
By following these steps and utilizing Excel's features for data analysis and visualization, you can effectively perform RAG Analysis on PRE and POST data and showcase it graphically to highlight instances where assumptions were inaccurate.
Additional Tip:
Consider creating a separate legend on the Excel chart to explain the color codes for Red, Amber, and Green statuses, making it easier for viewers to interpret the analysis.
Remember to save your Excel file with the RAG Analysis for future reference and comparison.
📊🔍
From India, Gurugram
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441. Data Preparation:
- Organize your data with columns for resource names, initial status (PRE), final status (POST), and any relevant metrics.
- Assign Red, Amber, and Green statuses based on your criteria.
2. Calculating Changes:
- Calculate the difference between PRE and POST data to determine if the assumption was correct or not.
3. Graphical Representation:
- Use a Column Chart in Excel to visually represent the RAG Analysis.
- Assign different colors to Red, Amber, and Green statuses for clarity.
- Plot the initial (PRE) and final (POST) status for each resource on the chart.
4. Highlighting Assumption Changes:
- Use conditional formatting in Excel to highlight instances where the assumption changed from Amber to another status.
- This will visually emphasize where the initial assumption was incorrect.
5. Interpreting the Graph:
- Analyze the chart to identify resources where the assumption was incorrect based on the color changes from Amber to another status.
- This visual representation will help in understanding the impact of incorrect assumptions.
6. Regular Review:
- Conduct RAG Analysis regularly to track changes and ensure assumptions align with actual outcomes.
By following these steps and utilizing Excel's features for data analysis and visualization, you can effectively perform RAG Analysis on PRE and POST data and showcase it graphically to highlight instances where assumptions were inaccurate.
Additional Tip:
Consider creating a separate legend on the Excel chart to explain the color codes for Red, Amber, and Green statuses, making it easier for viewers to interpret the analysis.
Remember to save your Excel file with the RAG Analysis for future reference and comparison.
📊🔍
From India, Gurugram
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