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Spudder112's avatar
Spudder112
Helper I
3 years ago
Solved

Trying to Calculate How Many Employees Worked on Multiple Customers in Given Time Period

I had asked a similar question, but decided to take a different route after re-working some data...

 

Table 1

Order ID

Order Date

Order Amount

Employee ID

Customer ID

 

I want to figure out how many Employee worked on a different customer idea on each date.

 

Example data:

 

Employee ID   Employee Name    Customer    Date

1212                Jon                         5133           1/1/2023

2455                Sam                       1344           1/2/2023

2455                Sara                       11111          1/2/2023

9559                Charles                  3553           1/1/2023

2455                Sam                       4949           1/1/2023

2455                Sam                       1344           1/1/2023

 

Finished product:

 

Date:                                                                   1/1/2023    1/2/2023

Employees working more than 1 customer        33%            0%

 

Need Help
  • Spudder112's avatar
    Spudder112
    3 years ago

    Thank you for the quick response Greg_Deckler!

     

    This is giving me 98% across the board for every week (which I would expect to see around 30%). Something I accidentally omitted in my example data was that customer numbers will often repeat, and I can only count each unique customer once, sorry for the confusion!

  • Greg_Deckler's avatar
    Greg_Deckler
    3 years ago

    Spudder112 Well that certainly makes a difference but should be an easy fix. PBIX is attached with ammended data to demonstrate a duplicate.

    Employees Working More Than 1 Customer Measure = 
    VAR __NumEmployees = COUNTROWS(DISTINCT('Table'[Employee ID]))
    VAR __Table = SUMMARIZE('Table',[Date],[Employee ID],"__Count",COUNTROWS(DISTINCT(SELECTCOLUMNS('Table',"__Customer",[Customer]))))
    VAR __Result = DIVIDE( COUNTROWS(FILTER(__Table, [__Count] > 1)), __NumEmployees) + 0
RETURN
    __Result

     

4 Replies

  • Greg_Deckler's avatar
    Greg_Deckler
    Community Champion
    3 years ago

    Spudder112 Your sample data won't give you the results you expect because you have duplicate ID's for Sam and Sara but if you correct that this will work:

    Employees Working More Than 1 Customer Measure = 
    VAR __NumEmployees = COUNTROWS(DISTINCT('Table'[Employee ID]))
    VAR __Table = SUMMARIZE('Table',[Date],[Employee ID],"__Count",COUNTROWS('Table'))
    VAR __Result = DIVIDE( COUNTROWS(FILTER(__Table, [__Count] > 1)), __NumEmployees) + 0
RETURN
    __Result
    • Spudder112's avatar
      Spudder112
      Helper I
      3 years ago

      Thank you for the quick response Greg_Deckler!

       

      This is giving me 98% across the board for every week (which I would expect to see around 30%). Something I accidentally omitted in my example data was that customer numbers will often repeat, and I can only count each unique customer once, sorry for the confusion!

      • Greg_Deckler's avatar
        Greg_Deckler
        Community Champion
        3 years ago

        Spudder112 Well that certainly makes a difference but should be an easy fix. PBIX is attached with ammended data to demonstrate a duplicate.

        Employees Working More Than 1 Customer Measure = 
    VAR __NumEmployees = COUNTROWS(DISTINCT('Table'[Employee ID]))
    VAR __Table = SUMMARIZE('Table',[Date],[Employee ID],"__Count",COUNTROWS(DISTINCT(SELECTCOLUMNS('Table',"__Customer",[Customer]))))
    VAR __Result = DIVIDE( COUNTROWS(FILTER(__Table, [__Count] > 1)), __NumEmployees) + 0
RETURN
    __Result