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mbuhary Helper I
Helper I

Annualize current year Sales and rank top gainers and losers against last year

I need to RANKX in my database based on Sales this year vs Last year top Gainers and Losers.

 

But since my current fiscal year is still incomplete I would like to annualize my current yeat numers before comparing for Ranking.

 

Also I would like to Rank only my VIP Customers so I need to filter in that condition as well.

 

[StoreCode] [StoreName] [Date] [Year] [CustomerID] [CustomerName] [VIP_Yes/No] [Sales]

 

Any help is appreciated

4 REPLIES 4
Super User I
Super User I

Re: Annualize current year Sales and rank top gainers and losers against last year

Hi @mbuhary

 

Please upload some sample data and the output desired to googledrive or onedrive and share the link to find a solution.

 

 

Cheers

 

CheenuSing

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mbuhary Helper I
Helper I

Re: Annualize current year Sales and rank top gainers and losers against last year

Super User I
Super User I

Re: Annualize current year Sales and rank top gainers and losers against last year

Hi @mbuhary

 

Got your data set.  Need the follwing clarifications.

 

a)  Is the year based on calendar year Jan - Dec or different ?

b) What is the logic for generating the annualised sales for remaining months of current year ?

c) Can you do a manual computation of the result expected from the dataset shared and send it .

 

You could send me a private message instead of replying here to avoid too many conversations until a solution is found.

Cheers

 

Cheenusing

 

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mbuhary Helper I
Helper I

Re: Annualize current year Sales and rank top gainers and losers against last year

a) yes the year is Jan to Dec

 

b) current year sales divided by (max date - 31st Dec Last year) Times 365

 

c) based on the current available data if we apply the above calculation to Year on Year Growth the Ranks should be as follows:

A Bnk Rank 1 (Growth 128%)

IC BK U Rank 2 (Growth 56%)

 

 Similarly we have to rank if there are any negative number as well, ranking the lowest as Rank 1 most loser and so on.

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