AoS & STR knowledge refresh deck Market Research

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1. Pipeline Age of Stock(AOS) & Stock Turnover Ratio (STR) July’22 Presented By: DSci MACE India

2. Contents India Trade overview and supply chain What is Age of Stock (AOS) & Stock turnover ratio (STR)?  How is it captured? Factors affecting Pipeline Limitations for AOS  Case studies – Reading the AOS

3. India Trade overview and supply chain Age of stock :  How long does the product take to reach the retail shelf , after being shipped from the company Age Of Stock  (AOS) Stock Turnover Ratio (STR) Consumer STR:  Once the product reaches the retail shelf, how long does it take to translate into the sales Pipeline = AoS + STR Factory (Mfg. Date) Wholesalers/ Distributors Retailer (Audit Date)

4. H ow are they captured? Date of manufacture: Select two SKUs at random and check the date of manufacture.  If both are the same, enter in HHT and consider as the latest manufactured date. If they are different, select another SKU at random. Select the latest date and enter in LHHT and consider as the latest manufactured date. This information captured end of the quarter month.

5. H ow are they captured? Age of Stock(AOS): Age of stock = no. of days from latest manufactured date captured to the date of audit. Once the age is captured from individual store, the contribution of the age is computed by multiplying the age by the stock volume(kg). Therefore, the final age of stock is a weighted average.  Date of manufacture: Select two SKUs at random and check the date of manufacture.  If both are the same, enter in HHT and consider as the latest manufactured date. If they are different, select another SKU at random. Select the latest date and enter in LHHT and consider as the latest manufactured date. This information captured end of the quarter month

6. AOS Calculation Age of Stock = Sum of New stock volume / Sum of stock volume AOS = 97 SKUs Brand Manufacturing date Audit Quarter Stock Volume Months Intervals weights New stock volume SKU1 Brand A Dec-21 Mar-22 100 3 1-3 months 60 6000 SKU2 Brand A Sep-21 Mar-22 50 6 3-6 months 135 6750 SKU3 Brand A Dec-21 Mar-22 60 3 1-3 months 60 3600 SKU4 Brand A Aug-21 Mar-22 30 7 6-9 months 225 6750

7. No of days for which stock in market would last Indicates sufficiency of stock in stores Business outcome: Stock carriage days of Shanti Amla are consistently lower than Dabur Amla This could either be due to fast replenishment cycle for Shanti Amla or better trade preference for Dabur Amla Hair Oil Category, All India (U+R) Stock turnover rate (STR) STR  Jan-19 Feb-19 Mar-19 Apr-19 May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-20 Jan-20 Feb-20 Mar-20 Dabur Amla 46.6 48.3 44.3 46 43.3 44.9 44.7 47.6 46.5 45.5 44 43.4 44 45.3 40.1 Shanti Amla 39.6 45.6 37.5 40.3 38.8 41.4 38.8 41.1 40.9 40.3 38.2 34.6 35.1 36.9 33.4 STR = (Stock Volume / Sales Volume) X 30  days

8. Factor affecting Pipeline TIMEPOINT TOWNCLASS BRANDS Pipeline   may change with shipment increase/decrease, season time, market factors etc. Metros are reached earlier as they are serviced directly Stock reaches upcountry later as it is predominantly serviced indirectly All brands have a lag and It vary basis their distribution channels, consumption pattern, shelf life etc.

9. Pipeline(AOS+STR) lag for Different Brands AOS STR Pipeline 37 12 48 AOS STR Pipeline 80 21 101 AOS STR Pipeline 239 46 286 AOS STR Pipeline 130 21 151 Only for internal reference and not to be shared with the client

10. AoS - Limitations Low Penetration : According to NIQ norms, one SKU/brand needs to be present in approximately 20 stores from the panel for reporting market breakdown to share the Age of Stock. Reason : High fluctuations noticed in the Age if the SKU is low penetrated because of stock pile-up taking place in some of the store's vis-a-vis stores where the movement of the same SKU is high . Store Details: Since Age of Stock is on panel stores, store details and batch code details will not be shared Reason: Security of the panel stores Note : Basis the sample sufficiency the data cuts for different MBD levels can be reported

11. Low Penetration : According to NIQ norms, one SKU/brand needs to be present in approximately 20 stores from the panel for reporting market breakdown to share the Age of Stock. Reason : High fluctuations noticed in the Age if the SKU is low penetrated because of stock pile-up taking place in some of the store's vis-a-vis stores where the movement of the same SKU is high . Store Details: Since Age of Stock is on panel stores, store details and batch code details will not be shared Reason: Security of the panel stores Note : Basis the sample sufficiency the data cuts for different MBD levels can be reported Avg. age of stock in days is dependent on both age of stock and the stock level.​ Answer : True True or False AoS - Limitations

12. Low Penetration : According to NIQ norms, one SKU/brand needs to be present in approximately 20 stores from the panel for reporting market breakdown to share the Age of Stock. Reason : High fluctuations noticed in the Age if the SKU is low penetrated because of stock pile-up taking place in some of the store's vis-a-vis stores where the movement of the same SKU is high . Store Details: Since Age of Stock is on panel stores, store details and batch code details will not be shared Reason: Security of the panel stores Note : Basis the sample sufficiency the data cuts for different MBD levels can be reported Avg. age of stock in days is dependent on both age of stock and the stock level.​ Lower stock levels that are very old can skew the avg. age of stock for a given SKU though recent stock is of higher percentage : Answer : True : Average is affected by extreme values, so, though the older stock might be on the lower side it can skew the avg age of stock to be on the higher side. Answer : True True or False AoS - Limitations

13. Low Penetration : According to NIQ norms, one SKU/brand needs to be present in approximately 20 stores from the panel for reporting market breakdown to share the Age of Stock. Reason : High fluctuations noticed in the Age if the SKU is low penetrated because of stock pile-up taking place in some of the store's vis-a-vis stores where the movement of the same SKU is high . Store Details: Since Age of Stock is on panel stores, store details and batch code details will not be shared Reason: Security of the panel stores Note : Basis the sample sufficiency the data cuts for different MBD levels can be reported Avg. age of stock in days is dependent on both age of stock and the stock level.​ Lower stock levels that are very old can skew the avg. age of stock for a given SKU though recent stock is of higher percentage : We can add age of stock of two or more SKUs to arrive at a combined age of stock. Answer : True : Average is affected by extreme values, so, though the older stock might be on the lower side it can skew the avg age of stock to be on the higher side. Answer : False : We cannot add age of stock of two or more SKUs. However, overall brand level age of stock can be computed using weighted average age of stock of each SKU . ​ Answer : True SKU Brand Stock AoS SKU Additive AoS Avg AoS SKU 1 Brand A 100 45 45 + 50 = 95 = 47 SKU 2 Brand A 70 50 SKU Brand Stock AoS SKU Additive AoS Avg AoS SKU 1 Brand A 100 45 45 + 50 = 95 SKU 2 Brand A 70 50 True or False AoS - Limitations

14. Low Penetration : According to NIQ norms, one SKU/brand needs to be present in approximately 20 stores from the panel for reporting market breakdown to share the Age of Stock. Reason : High fluctuations noticed in the Age if the SKU is low penetrated because of stock pile-up taking place in some of the store's vis-a-vis stores where the movement of the same SKU is high . Store Details: Since Age of Stock is on panel stores, store details and batch code details will not be shared Reason: Security of the panel stores Note : Basis the sample sufficiency the data cuts for different MBD levels can be reported Avg. age of stock in days is dependent on both age of stock and the stock level.​ Lower stock levels that are very old can skew the avg. age of stock for a given SKU though recent stock is of higher percentage : We can add age of stock of two or more SKUs to arrive at a combined age of stock. All stocks(i.e., on shelf, in store storage area, etc …) present in the shop is considered while recording the manufacturing date. Answer : True : Average is affected by extreme values, so, though the older stock might be on the lower side it can skew the avg age of stock to be on the higher side. Answer : False : We cannot add age of stock of two or more SKUs. However, overall brand level age of stock can be computed using weighted average age of stock of each SKU . ​ Answer : True Answer : False : Stocks not on shelf are not considered when computing age of stock (however these are reported in retail audit stock estimates).​ True or False AoS - Limitations

15. Few scenarios where AoS can be leveraged

16.   Problem Statement:   NIQ continues to show upward trend in sales despite decline in shipment in Apr’22.   BRAND COVERAGE STABILITY GR vs YA GR GAP MAT APR21 MAT APR22 NIELSEN SHIPMENT BRAND B 63 71 8 49 32 16 -7 -6 -6 -5 -2 -4 -4 1 3 4 9 8 Coverage Stability 80-110 +/-15 50-80 & 110-120 >75% and <=110% <50 & >120 >15

17. Trade Pipeline: Around 3 months (93 days) based on the average age of latest 4 quarters Brand B Avg. AoS STR Pipeline 73 20 93

18. Growth gaps are better aligned considering the lag period 7 13 13 13 11 7 3 5 6 4 Coverage level & stability is also improving with lag ALL INDIA -7 -6 -6 -5 -2 -4 -4 1 3 4 9 8 BRAND B BRAND B WITH LAG Calculation Example

19. Questions!

20. “Learn continually – there’s always “one more thing” to learn.”  – Steve Jobs