Every season there is a new bugbear for retailers in India, whether it be competition local, domestic, discounting, luxury or a fickle customer. But one of the key reasons why we as a group are struggling is due to lack of respect for data and measurement. Data analysis is not a back-office part-time job, it needs a full-fledged team and resources. i.e. Computers, ERP systems like Ginesys and people who can analyze and summarize data for others.
Forget Demming and Six-sigma retail today is not even at 1-sigma. Poor fill rates, master data mismatch, no shelf-life information, items with missing vendor / supplier information all of this and other data errors could cumulatively lead to Rs. 40 – 50 billion loss over the next 5 years according to a GS1 India report.
In the study it was observed that three out of four retailers had 28 to 53% of their internal item codes associated with two or more GS1 codes. The average exact match of data received from four retailers for the same SKU was less than 50% across parameters / attributes, barring a few attributes like MRP and product dimensions which showed close to 0% match.
In effect we are duplicating data multiple times even after introduction of GS1 and with more errors each time. This is a sure recipe for inefficiency.
Instead we could reuse data from Global data synchronization network and also enter information completely and correctly. Once we start getting the basics in place there is a whole different level to which we can take our analysis e.g. shelf fill ratio, shelf fill plan, dimensional data for logistics support, basket analysis and much more.
Currently we are focused on making profits from given set of options i.e. MRP, tax, sale, traffic, cost price but we need to move to a way of thinking about creating new options and opportunities.