Formula Fixer | M (Power Query)

Store Sales Growth Ranking

This analysis addresses the correction of DAX code used to rank stores based on monthly sales growth. The revised code ensures accurate calculations of current and previous month's sales, computes growth, and ranks stores accordingly.


Empty image or helper icon

This Query related with thread "Insights into Store Sales and Simplified DAX Ranking"

Prompt

StoreRank = 
RANKX(
    ALL(Store[StoreName]), 
    CALCULATE(
        CALCULATE(SUM(Sales[TotalSales]), DATESINPERIOD(Date[Date], LASTDATE(Date[Date]), -1, MONTH))
    ), 
    , 
    DESC, 
    DENSE
)

Answer

User Concerns Analysis

The user is concerned that the provided code might not accurately calculate the ranking of stores by their monthly sales growth.

Code Inspection

  1. The primary measure within the RANKX function is nested CALCULATE calls.
  2. The inner CALCULATE statement may not be correctly capturing the sales growth for the past month.
  3. The use of DATESINPERIOD might not align with the intended calculation of monthly sales growth.
  4. The logical flow of capturing the total sales for each store and then ranking them needs careful handling.

Original Code

StoreRank =
RANKX(
    ALL(Store[StoreName]), 
    CALCULATE(
        CALCULATE(SUM(Sales[TotalSales]), DATESINPERIOD(Date[Date], LASTDATE(Date[Date]), -1, MONTH))
    ), 
    , 
    DESC, 
    DENSE
)

Identified Issues

  1. Nested CALCULATE statements may lead to unexpected results.
  2. Incorrect use of DATESINPERIOD might not properly reflect the past month's sales data.
  3. The formula needs to ensure that it calculates the sales difference month-over-month before ranking.

Code Rectification

To accurately rank stores by monthly sales growth, we need to:

  1. Calculate the total sales for the current month.
  2. Calculate the total sales for the previous month.
  3. Compute the growth (current month sales - previous month sales).
  4. Rank the stores based on this computed growth.

Corrected Code

StoreRank = 
VAR CurrentMonthSales = 
    CALCULATE(
        SUM(Sales[TotalSales]), 
        DATESMTD(Date[Date])
    )

VAR PreviousMonthSales = 
    CALCULATE(
        SUM(Sales[TotalSales]), 
        DATESMTD(DATEADD(Date[Date], -1, MONTH))
    )

VAR SalesGrowth = CurrentMonthSales - PreviousMonthSales

RETURN 
    RANKX(
        ALL(Store[StoreName]), 
        SalesGrowth, 
        , 
        DESC, 
        DENSE
    )

Commenting on Corrections

  1. Computation of Current Month Sales: The use of DATESMTD ensures that we only consider sales data for the current month.

    VAR CurrentMonthSales = 
        CALCULATE(
            SUM(Sales[TotalSales]), 
            DATESMTD(Date[Date])
        )
  2. Computation of Previous Month Sales: The DATEADD function is applied with DATESMTD to shift back one month and capture sales for the entire previous month.

    VAR PreviousMonthSales = 
        CALCULATE(
            SUM(Sales[TotalSales]), 
            DATESMTD(DATEADD(Date[Date], -1, MONTH))
        )
  3. Sales Growth Calculation: Subtracting previous month's sales from current month's sales provides the required growth metric.

    VAR SalesGrowth = CurrentMonthSales - PreviousMonthSales
  4. Ranking by Sales Growth: The RANKX function ranks the stores based on the computed SalesGrowth, sorted in descending order, with dense ranking.

    RETURN 
        RANKX(
            ALL(Store[StoreName]), 
            SalesGrowth, 
            , 
            DESC, 
            DENSE
        )

Summary

  • The revised code is structured to first compute the sales for the current and previous months.
  • It then calculates the growth in sales and ranks stores based on this growth.
  • The corrected approach ensures that the data interval is correctly handled, and the ranking reflects the changes in monthly sales accurately.

Create your Thread using our flexible tools, share it with friends and colleagues.

Your current query will become the main foundation for the thread, which you can expand with other tools presented on our platform. We will help you choose tools so that your thread is structured and logically built.

Description

This analysis addresses the correction of DAX code used to rank stores based on monthly sales growth. The revised code ensures accurate calculations of current and previous month's sales, computes growth, and ranks stores accordingly.