“Like for Like” or “Comparative” sales analysis is a common requirement in the Retail sector. The objective is to assess growth from the underlying “business” by comparing the business on a “like-for-like” basis with the business in the previous period.
The comparable basis can be manifold and will depend upon the business analysis requirement:
Like for Like Store Sales
This compares the stores open in the current period with the same stores in the previous period
Like for Like Brand Sales
this compares the sales from the same brands in the current period with the same brands in the previous period
Methodology – Transaction Flags
The conceptual basis of the “like-for-like” analysis is to identify or “flag” the transactions that are relevant for the comparison (i.e. are comparable sales). This simple approach has significant benefits
- Easily validated in the data table
- Simple to express in expressions
- Low RAM usage in the application
Taking the example of the Like for like store sales, where the requirement is that the store was “open(1)” in the both "periods"(2), we can take the following logical approach:
Calculate two Like For Like Flags
- Flag TY - Identify those transactions in the previous year which are comparable to the current year (TY); AND
- Flag LY - identify those transactions in the current year which are comparable to the previous year (LY).
Image 1: Illustrative example of Like-For-Like Flag Method
The methodology can be applied to create any like-for-like analysis and with the use of set analysis can be dynamic in the application.
The analytical result of this is
- Sales growth of 18% (659 / 557 - 1); but
- Like-for-Like sales growth of 32% (387 / 512 -1)
(1) "Open" - can be defined in many ways. In this example it is that the store had sales in the comparable period.
(2) "Period" - this will require careful definition. The period could be the same "week" last year or on the same calendar date. Where the company uses the 52 week retail calendar (4-5-4) there will be a week 53 every 7 years!
Explore & Enjoy,