Create A PivotTable And PivotChart To Analyze Agent Performa

Create a PivotTable and PivotChart to analyze agent performance in resolving disaster recovery support calls

Open the workbook named e05r1NCCTS and save it as e05r1NCCTS_LastFirst. Use the range A4:K39 on the March Hours worksheet to create a blank PivotChart and PivotTable on a new worksheet. Name this worksheet Disaster Recovery Analysis. Place the Call Type and Customer ID fields in the Rows area. Add the Hours Logged, Days Open, and Amount Billed fields as Values, setting the Hours Logged and Days Open fields to summarize by average with a number format of 2 decimal places. Name the PivotTable Summary Table and apply the Light Blue, Pivot Style Medium 20 style.

Insert a slicer based on Call Type, positioning it with its top-left corner in cell F3, and set its size to 3.5 inches height and 2.5 inches width. Select the Disaster Recovery slice to filter the PivotTable accordingly. Reposition the top-left corner of the PivotChart in cell A, and change its type to Pie, applying Style 3. Format the Amount Billed data as Accounting Number Format.

Switch to the March Hours worksheet and create GETPIVOTDATA functions to display the average Disaster Recovery hours in cell K1 and the total Disaster Recovery amount billed in cell K2, referencing the filtered data from the PivotTable. Insert a footer with your name on the left, the worksheet name in the center, and the filename code on the right. Save and close the workbook. Then, submit the completed file according to your instructor’s directions.

Paper For Above instruction

The analysis of agent performance in resolving disaster recovery support calls is a critical aspect of understanding operational efficiency and customer service quality within technical support services. Using PivotTables and PivotCharts in Excel provides a comprehensive method to synthesize large datasets, visualize key metrics, and facilitate data-driven decision-making. This paper discusses the step-by-step process to create an effective PivotTable and PivotChart in Excel, focused specifically on evaluating disaster recovery calls, supported by best practices and functional recommendations.

The initial step involves preparing the dataset within the Excel workbook titled e05r1NCCTS, specifically focusing on the range A4:K39 within the March Hours worksheet. The data contains pertinent fields such as Call Type, Customer ID, Hours Logged, Days Open, and Amount Billed. Creating a PivotTable and PivotChart starts with selecting this data range, then inserting a blank PivotTable and PivotChart in a new worksheet. The worksheet is aptly named "Disaster Recovery Analysis" to facilitate easy identification and organization of the analysis focus.

Placing the Call Type and Customer ID fields in the Rows area allows for categorization of data based on the type of call and customer identification, establishing a hierarchical structure. Incorporating the Hours Logged, Days Open, and Amount Billed fields into the Values area enables quantitative analysis, with Hours Logged and Days Open configured to display averages. Setting their number format to two decimal places enhances readability and data consistency, aiding precise interpretation of service performance metrics.

The subsequent step is to name the PivotTable “Summary Table,” which aids in managing multiple PivotTables within the workbook, and to apply a styled format—specifically, the Light Blue, Pivot Style Medium 20—to improve visual clarity and professional appearance. This styling choice ensures that the PivotTable remains easily distinguishable in reports and dashboards, contributing to effective presentation of data insights.

Adding a slicer based on Call Type introduces interactive filtering capabilities, allowing users to dynamically explore data subsets. Positioning this slicer with its top-left corner at cell F3 and sizing it to 3.5 inches height and 2.5 inches width ensures it integrates seamlessly within the worksheet layout. Selecting the Disaster Recovery slice automatically filters the PivotTable and PivotChart, providing a focused view of disaster recovery calls. Repositioning the PivotChart’s top-left corner to cell A ensures proper alignment within the worksheet for clarity and aesthetic consistency.

Changing the chart type to Pie, and applying Style 3, transforms the visual into an intuitive, easy-to-understand graphic that highlights the proportional distribution of metrics such as hours or costs associated with disaster recovery calls. Formatting the Amount Billed as Accounting Number Format standardizes monetary data presentation, aligning with accounting conventions and facilitating financial interpretations.

In the final steps, transitioning back to the March Hours worksheet involves building GETPIVOTDATA functions in cells K1 and K2. These functions extract specific metrics from the PivotTable—namely, the average Hours Logged and total Amount Billed for disaster recovery calls—providing immediate, dynamic updates as the PivotTable filters change. Including a footer with personal identification, worksheet name, and filename makes the report complete and ready for submission, ensuring clarity and attribution.

In conclusion, effective use of PivotTables and PivotCharts in Excel transforms raw operational data into actionable insights. The outlined process optimizes data visualization, facilitates interactive analysis, and enhances reporting accuracy—key components in managing and improving technical support functions and resource allocation within organizations.

References

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