Political Science homework
3PL for the World
| 3PL for the World, Inc. | ||||||
| Revenue | Cost per Package | Inventory Turns | Service Level | Perfect Order Rate | ||
| January | $ 920,987 | $ 8.70 | 18.2 | 98% | 82% | |
| February | $ 865,254 | $ 7.80 | 21.2 | 96% | 77% | |
| March | $ 921,456 | $ 7.70 | 22.4 | 93% | 75% | |
| April | $ 930,231 | $ 8.25 | 25.9 | 90% | 62% | |
| Objective | $ 920,000 | $ 7.90 | 24 | 95% | 75% | |
| How good are you at creating graphs? If the data table is formatted well, then the automatic graph-building functions in Excel will make your job much easier! Let's practice: | ||||||
| 1. Create a Line graph using one of the performance metrics. | ||||||
| 2. Column (or bar) graph using the same data from #1. | ||||||
| 3. Create a Radar chart using all the metrics during the most recent period. | ||||||
| HINT: In Excel, all variables must use a single scale, so you can't mix $ and %. Can you think of a way to convert every metric into a single unit? Consider applying the Objective to each metric. | ||||||
| 4. Create a Scatter (X,Y) chart -- with data in columns side-by-side | ||||||
| 5. Create a Scatter (X,Y) chart -- with data in columns that are NOT side-by-side |
1 - Line graph
| Optional data shown here. | ||||||||||||||||||||||||||||
| Target Revenue | Revenue | Cost per Package | Inventory Turns | Service Level | Perfect Order Rate | |||||||||||||||||||||||
| $ 920,000 | January | $ 920,987 | $ 8.70 | 18.2 | 98% | 82% | ||||||||||||||||||||||
| $ 920,000 | February | $ 865,254 | $ 7.80 | 21.2 | 96% | 77% | EXTRA OPTION: Use Select Data to ADD a new line, like the Objective | |||||||||||||||||||||
| $ 920,000 | March | $ 921,456 | $ 7.70 | 22.4 | 93% | 75% | ||||||||||||||||||||||
| $ 920,000 | April | $ 930,231 | $ 8.25 | 25.9 | 90% | 62% | ||||||||||||||||||||||
| Objective | $ 920,000 | $ 7.90 | 24 | 95% | 75% | |||||||||||||||||||||||
| EXTRA OPTION: Use Select Data to ADD a new line, like the Objective |
Revenue for Jan-Apr 2020
Revenue January February March April 920987 865254 921456 930231 Target Revenue 920000 920000 920000 920000
Revenue, $
2 - Column graph
| Target Revenue | Revenue | Cost per Package | Inventory Turns | Service Level | Perfect Order Rate | |||||||||||||||||||||||||
| $ 920,000 | January | $ 920,987 | $ 8.70 | 18.2 | 98% | 82% | ||||||||||||||||||||||||
| $ 920,000 | February | $ 865,254 | $ 7.80 | 21.2 | 96% | 77% | EXTRA OPTION: Use Select Data to ADD a new line, like the Objective | |||||||||||||||||||||||
| $ 920,000 | March | $ 921,456 | $ 7.70 | 22.4 | 93% | 75% | To change the Target to a line, use CHART TYPE, find the series, and set it to a line graph. | |||||||||||||||||||||||
| $ 920,000 | April | $ 930,231 | $ 8.25 | 25.9 | 90% | 62% | ||||||||||||||||||||||||
| Objective | $ 920,000 | $ 7.90 | 24 | 95% | 75% | |||||||||||||||||||||||||
| EXTRA OPTION: Use Select Data to ADD a new line, like the Objective | ||||||||||||||||||||||||||||||
| To change the Target to a line, use CHART TYPE, find the series, and set it to a line graph. |
Revenue for Jan-Apr 2020
Revenue January February March April 920987 865254 921456 930231 Target Revenue 920000 920000 920000 920000
Revenue, $
3 - Radar
| Revenue | Cost per Package | Inventory Turns | Service Level | Perfect Order Rate | ||||||||||||||||||||||
| January | $ 920,987 | $ 8.70 | 18.2 | 98% | 82% | |||||||||||||||||||||
| February | $ 865,254 | $ 7.80 | 21.2 | 96% | 77% | |||||||||||||||||||||
| March | $ 921,456 | $ 7.70 | 22.4 | 93% | 75% | Convert each metric to a percentage to be on the same scale as each other. | ||||||||||||||||||||
| April | $ 930,231 | $ 8.25 | 25.9 | 90% | 62% | |||||||||||||||||||||
| April % | 101% | 104% | 108% | 94% | 83% | |||||||||||||||||||||
| Objective | $ 920,000 | $ 7.90 | 24 | 95% | 75% | |||||||||||||||||||||
| Convert each metric to a percentage to be on the same scale as each other. | ||||||||||||||||||||||||||
| Some Radar charts can accept unique scales on each axis (here there are 5 metrics so 5 axes.) | ||||||||||||||||||||||||||
| If the category labels (metrics) do not automatically transfer in, use the Select Data menu to edit the range for the "Horizontal (category) axis labels". |
April Performance Metrics as Percent of Objective
Revenue Cost per Package Inventory Turns Service Level Perfect Order Rate Revenue Cost per Package Inventory Turns Service Level Perfect Order Rate 1.0111206521739131 1.0443037974683544 1.0791666666666666 0.94210526315789478 0.82666666666666666
4 - X,Y
| Revenue | Cost per Package | Inventory Turns | Service Level | Perfect Order Rate | ||
| January | $ 920,987 | $ 8.70 | 18.2 | 98% | 82% | |
| February | $ 865,254 | $ 7.80 | 21.2 | 96% | 77% | |
| March | $ 921,456 | $ 7.70 | 22.4 | 93% | 75% | |
| April | $ 930,231 | $ 8.25 | 25.9 | 90% | 62% | |
| Objective | $ 920,000 | $ 7.90 | 24 | 95% | 75% | |
| Use Change Chart Type to select "Secondary Axis" | ||||||
| Note -- X,Y needs quantitative values for X and Y. With time-series data like this (in order), the difference between a Line graph and XY graph is not noticable, but with unsorted Xs the results are very different. |
Inventory Turns vs. Cost per Package
Inventory Turns 8.6999999999999993 7.8 7.7 8.25 18.2 21.2 22.4 25.9
Cost per Package
Inventory Turns
5 - X,Y
| Revenue | Cost per Package | Inventory Turns | Service Level | Perfect Order Rate | ||
| January | $ 920,987 | $ 8.70 | 18.2 | 98% | 82% | |
| February | $ 865,254 | $ 7.80 | 21.2 | 96% | 77% | |
| March | $ 921,456 | $ 7.70 | 22.4 | 93% | 75% | |
| April | $ 930,231 | $ 8.25 | 25.9 | 90% | 62% | |
| Objective | $ 920,000 | $ 7.90 | 24.0 | 95% | 75% | |
| Use Change Chart Type to select "Secondary Axis" | ||||||
| I just copied the #4 chart and then clicked on a line to highlight it's data, then moved the data blocks to the new data. | ||||||
| Or, you may need to start the graph from scratch and Select Data manually -- drag X-data, then hold CONTROL KEY while click-drag on Y-axis. |
Perfect Order Rate vs. Inventory Turns
Perfect Order Rate 18.2 21.2 22.4 25.9 0.82 0.77 0.75 0.62
Inventory Turns
Perfect Order Rate