Reflection- Learning Launch to test the POS Systems in Small Grocery Stores in India

Challenge

In India, there are approx. 12 million small grocery retail shops what we call them as “Mom and Pop”  stores also, they constitute approx. 98% of grocery retail market in India in terms of market size but  almost 95% of them do not use any kind of digital tool or Point of Sales (POS) Machine for their business  operations. This results in various challenges to these retailers like slow speed of operations with slower  check outs, virtually no control on their inventories or purchase, no customer data or analysis to fall  back upon for selection of their product assortments, no control on promotions offered by large brands  and FMCG companies at these stores and last but not the least all this culminates in to no shopping  experience to their consumers despite them controlling such huge pie of the market.

An absence of a structured Point of Sales (POS) system with order taking terminals, QR code scanner and  receipt printer etc. acts as a steep barrier in their business growth compared to super markets and  convenience stores of the organized chains which are now eating in to their market share even in rural  and semi-rural Indian market.

My company in to Franchise Retail Network of small Grocers have completed a detailed assimilation of  Retailers paint point through interviews, market research, specific requirements of Indian grocers for  the POS machine, established hypothesis and key assumptions to create a POS system as per Indian  market needs and conditions as most of these stores have very limited space. We had completed our  first prototype, prioritize our key assumptions for customers, execution and dependability along with  scalability and were ready to experiment with our POS machine in real market place.

Selection and Application

Since we have already completed our core hypothesis, had prioritized our key assumptions and finalized  the design test for our POS, we had decided to use the Learning launch tool to quickly experiment with  select 10 stores in different geographies with different consumer base and SEC income groups.

Our primary objective was to give a very seamless POS solution to these Retailers as most of them are  family run stores and often managed by senior citizens or people with basic understanding of  technology, Our first two primary targets were to solve their huge problems of taking orders by scanning  the bar codes so as to accurately record sales data, brand wise data in to the data base tables and also  to enable very simple feature for them to take in to account their purchases as in absence of purchase  and sales entries , they often do not know when to replenish their 20% stocks that gives them 80% sales  and how to avoid unnecessary stock up of slow moving sku’s to eliminate their small capital flow.

Clearly our objective was to design an India centric product and some hardware that could even stand  the heat and dust at these stores spread across this vast country, so the common feedback which we  had gathered during the data immersion and collection process, we had created very bold font for  favorite sku’s which these retailers can tag and move to the right hand of their POS screens, ideally

there are 200-250 items that generates 85% of sales in these stores and we put all those items in to  favorite category so that the retailers can easily find them on right hand side on their POS with easy  search options. We used bright Red and Green colors for products in good quantity in stocks or products  with low quantity in stocks.

We had also put one of our Designers at each of these 10 stores for full 16 hours of operations to  carefully monitor the key assumptions and how they are faring in real time operations as people who  have written the code can easily understand the dynamics of any exclusion or inclusion of features.

We gave some basic features that were not available in established POS companies and they were  purely based on the retailer’s feedback only:

1. Generally these stores are manned by 1 person only and sometime there are 2-3 customers at

the counter, so we had given them the options to open new sales entry window and even to  hold the window of any existing customer in case he or she needs to select more items, at one  point of time, retailer can open 10 windows.

2. In India, there is a norm of offering monthly credit to the customers by these retailers and by

now they have recorded them in their manual diaries, where there was a potential risk of  forgetting any entry and thus a significant loss is highly probable, so we have given them a  feature in which they can check out a kart as paid in cash or card or “By Credit “. This feature  enables them to record and receipt of their credit amounts with 100% accuracy.

3. Perhaps globally, only India is a country where there is a culture of Maximum Retail Price (MRP)

that comes as printed price on the product pack and Sales price (The price offered by the  retailer after some discount, often it comes out from their own margin), so here we had  introduced a feature where they can adjust their Sales price whenever they scan any product  and save it in their local data base to analyze and maintain price parity with their competitors.

So we had lot of confirming data and appreciations coming both at our end from these retailers about  our POS after 45 days of trials, we have successfully applied the learning launch tool and establish the  fact that the product by us is better than the alternatives available in the market and it clearly addresses  the specific needs of the consumers or the Indian grocers. All the key assumptions and design criteria  were tested in the real time market conditions where a select group of 10 retailers run their stores on  these POS machines and had created substantial data on their sales, consumer, product movement,  purchase trends etc. and for the first time they had been able to create their provisional P&L’s.

Insight

During this pilot at 10 Stores, we had gained more specific insights to our design process and one thing  that came up as a surprise and a revolution both was the sheer fact that despite FMCG brands spending  millions of dollars in marketing their offers at these stores , there was no clear visibility to both retailer  and the consumers about various price offers and buy 1 get 1 scheme etc. etc., We saw with our own  eyes that retailers were not offering the right promotions to the customers unintentionally .

We immediately jotted this core insight and started working on our visualization process for a new  feature which got launched few months that enabled the retailer to discover the related offer on any  product once they scan their bar codes and the system also tells them the inventory of the offer on go at

the same time on the POS screen, this had resulted in high penetration and awareness of these offers  and acted as win win for both customer and retailers.

Approach

The successful trial and learning launch of our POS system at these 10 stores have opened various other  dimensions for our entire team and we have got a huge pile of data that was previously not visible in the  absence of any digitization at these retailers, the data about customers, brands, products, price  mapping, geographic dimensions and demographic dimensions was so robust that we could do wonders  in further product enhancements , this paved way to use “Mind Mapping “ Tool in our next set of  developments specially in the “MIS” system that we are designing now to look for the specific patterns  and trends per store, city, state, zone, brand, sku and market wise.

