How to Use Your Service History to Forecast Your Chemical Needs

To learn how to use your service history to forecast future chemical needs with Google Sheets, see the video below. Or, if you prefer, scroll past the video to view our step-by-step text instructions.

Step-by-step instructions . . .

1

Export your Service History and Import it to Google Sheets

  • Navigate to Settings > Exports in Skimmer's web app. Choose the range of dates you want to use and click Export to Excel to save

  • Now take that file and open it in Google Sheets File > Import > Upload.

2
Add a Slicer
  • In Google Sheets go to Data > Add a Slicer. 
  • Pick a chemical to monitor. In this example, we use Tabs. Set your column to the chemical you want to monitor.

3
Get a sum total
Highlight the chemical column by clicking Shift + CMD + down arrow on a mac or Shift + CTRL + down arrow. In the bottom right-hand corner of the window, you will see the total of all the highlighted numbers. This total represents the sum of all the chemicals you have highlighted. You can use this number to estimate how much of the chemical you will need over a similar period of time. For example, if you were looking at your total chemical use for Tabs in June, this sum could help you predict how many Tabs you'll need in July. 

4
Create Pivot Table for gallonage

Start by creating a Pivot Table. To do this go to Insert > Pivot Table.

5
Pick your range of values

Set your value to your Service History.

6
Figure in gallonage

Then we set our row to Gallons. Now your table should be listing pools by size. 

7
Add your chemical as a value

Here we've used Tabs again. Now your table will show how many Tabs were used based on pool size. You can also enter a formula to average the amount of Tabs used per gallon.

And that's it! Now you have a way to help see the sum values and averages of your chemical usage to help you navigate chemical forecasting. This is just one way to utilize your Service History in Google Sheets to help make predictions for the future or see trends from the past.