How can we do RAG Analysis on PRE and POST data for a month? If I have to show this in 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, and our assumption goes wrong then how can we represent this in PRE and POST RAG Analysis in Excel showing in graphical representation.
Location: Mumbai, India
Tags: Country-India, RAG analysis, City-India-Mumbai, attrition analysis
From India, Mumbai
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Location: Mumbai, India
Tags: Country-India, RAG analysis, City-India-Mumbai, attrition analysis
From India, Mumbai
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To conduct RAG (Red, Amber, Green) Analysis on PRE and POST data for a specific month in Excel, particularly to showcase the change in status of a resource from Amber to a different category, you can follow these steps:
1. Data Preparation:
- Organize your data with columns for the resource, the initial status (PRE), and the final status (POST) for the month you are analyzing.
2. Calculate Status Change:
- Create a new column to calculate the change in status for each resource. You can use formulas like IF statements to determine if the status has changed from Amber to another color.
3. Graphical Representation:
- Select the data range that includes the resource names and their status change.
- Go to the 'Insert' tab in Excel and choose the appropriate graph type for comparison, such as a Clustered Column Chart or a Stacked Column Chart.
4. Color-Coding:
- Utilize conditional formatting in Excel to color-code the columns representing the resource status changes. You can assign Red for negative changes, Green for positive changes, and Amber for neutral changes.
5. Legend and Labels:
- Include a legend in your graph to explain the color codes used for different status changes. Add clear labels to make the graph easy to understand.
6. Analyzing the Graph:
- Analyze the graph to identify resources where the assumption of staying in Amber status was incorrect, and the status changed in the POST period. This visual representation will help in understanding the impact of assumptions.
By following these steps and creating a visually appealing graph in Excel, you can effectively present the RAG Analysis on PRE and POST data for the month, showcasing the status changes of resources in an easily understandable format.
https://support.microsoft.com/en-us/...f-3f931f4f7f88
From India, Gurugram
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401. Data Preparation:
- Organize your data with columns for the resource, the initial status (PRE), and the final status (POST) for the month you are analyzing.
2. Calculate Status Change:
- Create a new column to calculate the change in status for each resource. You can use formulas like IF statements to determine if the status has changed from Amber to another color.
3. Graphical Representation:
- Select the data range that includes the resource names and their status change.
- Go to the 'Insert' tab in Excel and choose the appropriate graph type for comparison, such as a Clustered Column Chart or a Stacked Column Chart.
4. Color-Coding:
- Utilize conditional formatting in Excel to color-code the columns representing the resource status changes. You can assign Red for negative changes, Green for positive changes, and Amber for neutral changes.
5. Legend and Labels:
- Include a legend in your graph to explain the color codes used for different status changes. Add clear labels to make the graph easy to understand.
6. Analyzing the Graph:
- Analyze the graph to identify resources where the assumption of staying in Amber status was incorrect, and the status changed in the POST period. This visual representation will help in understanding the impact of assumptions.
By following these steps and creating a visually appealing graph in Excel, you can effectively present the RAG Analysis on PRE and POST data for the month, showcasing the status changes of resources in an easily understandable format.
https://support.microsoft.com/en-us/...f-3f931f4f7f88
From India, Gurugram
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