Data Science In Supply Chain Transforming The Way Kiranas Function

For every Indian, there is most certainly a memory of going to a nearby kirana store for a last-minute purchase for groceries. Kirana stores form a crucial cog of the Indian retail ecosystem that is entirely based on demand and supply. The supply chain, however, until very recently, faced a multitude of issues such as delays, wastage, and unreliable payment mechanisms, all of which resulted in lost opportunities/customers.

Today, when innovative technology has taken over almost all aspects of our life, these stores are also increasingly adopting new technologies to ensure little to no disruptions in the supply chain, and at the core of this tech-driven way of functioning, is data science.

Ecommerce platforms and aggregators are the key elements powering this transformation in the fundamental way that kirana stores operate. Let us take a look at some aspects which have been simplified for kirana stores through the incorporation of cutting-edge new-age technology such as data science.

Inventory Management

One of the main aspects of the business that kirana stores tend to struggle with is inventory management. Sourcing and managing inventory have always been a challenge for kirana stores. Since investing in additional working capital might not be feasible for most kirana stores, ecommerce players and aggregators are now leveraging data science to help with increasing the variety with the same amount of inventory and working capital. For any brand, customer satisfaction is key and for this, there needs to be a decrease in stockouts. With data science, kirana stores will be able to keep track of their stock and reduce stockouts to improve customer satisfaction.

Optimisation Of Products, Prices And Procurement

For any business, the customer is the king. Constantly updating oneself about the latest trends and consumer behaviour are some of the steppingstones to success. Discovering the product trends and acting accordingly will drive the sales and promotions upwards. Additionally, to facilitate optimal buying, it is necessary to compare the prices of products. And, another important aspect is procurement. To increase procurement efficiency, setting up notifications and real-time tracking of availability will optimise both time and cost. Tying together all these elements and helping to fortify the business is data science.

Customisation

In today’s rapidly evolving tech-led world, everyone is opting for personalised products and services. Customisation adds to customer satisfaction, retention, and acquisition, and for this, data is the foundation. Analysing purchase history, items browsed for earlier, or items on the wish list – these are all data collected systematically and meticulously to help make for a tailor-made shopping experience.

Apart from this, machine learning-based recommendations for discovering products relevant to the customers’ interests will save time and energy while simultaneously increasing efficiency.

Undoubtedly, with technology progressing at a breakneck pace, businesses must utilise automation to its fullest potential. Automation of certain processes such as stocking and managing warehouses will increase operational efficiency and reduce overlap-buying from multiple vendors. Automation will result in an upsurge of sales and reduction of manual labour, thus saving cost.

Access To Structured Credit Systems

Among the many problems faced by small and medium businesses across the country, access to structured credit has been a persistent problem, particularly in tier-II and tier-III cities. To help address this issue, players are leveraging Big Data to help streamline the process by building transaction history to help kirana stores avail credit from lenders. Also, to reduce the overall cost of capital, they are introducing the concept of daily interest to replace that of monthly interest.

To sum it up, there is unimaginable scope and opportunity for brands to reinvent the way kirana stores function to help them thrive in today’s highly competitive business environment. Despite technological adoption being slower as compared to other industries such as fin-tech, the past two years have witnessed immense progress.

With an estimated 12 Mn stores scattered across the country, it is imperative that there is sufficient support in terms of technology such as AI, ML, and data science to help reorganise the industry and enable it to reach new heights.

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