Pravin Venkatesh* has been running a modest kirana store in a corner of Bengaluru’s Malleswaram for approximately two decades, but over the last two years, he’s taken a technological leap.
Armed with just a mobile phone, a Point of Sale system and a barcode scanner, Venkatesh is able to assemble his stocks based on daily estimates of demand that are made possible through software provided by global wholesaler Metro Cash and Carry.
Rather than trudge to individual dealers across the city, Venkatesh compares prices of products across online suppliers such as NinjaCart, Jumbotail, Amazon and Udaan. He then orders different products from different companies, depending on who gives him the best deal.
These products are delivered directly to his store. This allows for tight store operations, minimum wastage and higher profits.
Venkatesh said that the software not only helps him to keep tabs on his inventory, but also allows him to remind customers of products they have purchased in the past and may have forgotten to buy on subsequent visits.
Some people see these changes as a step towards eliminating the inefficiencies and corruption attributed to the functioning of the state-regulated Agricultural Produce Marketing Committees. These online systems ostensibly cut out middlemen, allowing for better prices for producers and consumers. Across India, thousands of other small retail stores across are benefitting from such dramatic technological changes.
This streamlining of supply chains through the use of such technologies as predictive analytics, which forecasts supply and demand needs, has obvious benefits, especially for small retail stores and consumers.
But the deployment of these technologies raises important questions about data privacy – and possible misuse. In the absence of clear regulation, many are concerned that the data gathered by these may be misappropriated by both corporations and states.
To understand changes in the food landscape and the role of these new technologies in reshaping agri-supply chains, my colleagues and I at the Indian Institute for Human Settlements in Bangalore, an education and research institution that studies urbanisation, spoke to 51 people in the sector over a period of seven months, starting in September 2018.
They included founders and staff of e-commerce and more conventional firms, members of labour unions, investors, data intermediaries, farmers and government officials. The survey was done as part of the Hungry Cities Partnership project.
Our findings indicated that these technological shifts in supply chains have far-reaching impacts across its entire length – not just for kirana stores.
At the other end of the chain from Venkatesh, Ravindran Reddy, a young farmer from the Doddballapur region on the outskirts of Bengaluru, was enthusiastic about the opportunity to sell his horticultural produce to companies such as NinjaCart that operate collection centres near his village.
Selling to NinjaCart reduces his transportation costs and assures him of quick payments. This is a contrast to some of the hurdles he faces selling his product at the state-run Agricultural Produce Marketing Committee markets located in Bengaluru.
Reddy’s produce is taken to NinjaCart centres within the city, where it is divided into lots based on orders from retail stores, merged with other produce, and delivered to stores like Pravin Venkatesh’s and their customers.
How much produce will be procured from farmers like Ravindran every day as well as over a season depends on a dance of algorithms and mountains of data.
More than 570 million smallholder farmers around the world could benefit from the use of digital solutions in agriculture and allied sectors, according to a report by the International Telecommunication Union and the Food and Agriculture Organisation of the United Nations in 2019.
Among the significant online retailers in India are Udaan, Jumbotail and NinjaCart. Their teams have been instrumental in developing supply chain technologies such as demand forecasting. This is a technology that uses algorithms that draw from historical and existing trends in weather, sales, crop production, festivals, neighbourhood buying patterns and much more to predict requirements on any given day.
The sensitivity of the predictions to individual products and locations – which may be as small as a neighbourhood kirana store – makes these technologies potentially powerful aids in helping retail stores trim wastage and cater to specific local preferences by keeping track of each customer’s purchase history.
The granularity of data may have also helped stores tide over potential inventory shortages during the coronavirus lockdown.
Precision in forecasting is made possible by the increasing use of what is called “Big Data” – large data sets that are characterised by size, the speed at which they are added to and processed, and their complexity.
Big Data is currently being used for environmental management and to streamline agricultural production through precision farming and by collecting data about factors such as location, market changes, weather data and diagnostics for pests and diseases.
In agri-value chains, Big Data technologies allow firms to capture large-scale and granular information and predict supply and demand over the years along the length of the food supply chain.
A common belief among the people who run these initiatives is that “the data itself will speak”, indicating it is a neutral decision-making tool. However, though collecting this data may appear to be mundane, useful and necessary, it soon becomes part of much larger data infrastructures whose use and management need governance and oversight.
Questions have been asked about whether participants have given informed consent, equity between various actors in the chain, and privacy.
A 2018 study of retail firms in the US, for example, indicates how supermarkets collect details about personalised shopping preferences and history through the use of loyalty cards to “nudge” customers to make purchases through alerts via text messages when supermarket systems sense customers are in the vicinity.
Among the most obvious implications of this is the potential effects such practices have on food choices, even as countries around the world struggle with increasing rates of obesity and lifestyle diseases.
At the other end of the chain, farmer data in countries like Kenya is used to determine eligibility for crop insurance. Farmers in many countries including India tend to be the most disenfranchised actors in food supply chains, and without state oversight about the conditions under which farmers should be able to access crop insurance, many may be excluded.
In the case of fresh produce, the supply chain as well as farm data is built on a very vulnerable actor – the farmer – whose mobility and access to capital is limited.
There is also a data asymmetry here. Corporate big data solutions may not always work in favour of farmers who may be excluded from decision-making about how their data is used and shared.
Some traders in our study were anxious about how the data would be used and the implications for their own businesses.
These start-up companies don’t want to do business, said the president of a traders association in Bengaluru: “They just want to do database, data entry. That is, customer data.”
Other traders also suggested that far more important than trade or revenue to firms was access to these large, consolidated data sets that would be sold to larger companies. This was akin to colonisation by the British empire, they argued.
The European Union’s General Data Protection Regulation and Singapore’s Personal Data Protection Act already make provisions to govern use of private data, accounting for the need for proper informed consent procedures so that people are aware of the uses their data is put to and who has access to it.
The GDPR explicitly prohibits the collection of sensitive personal data and includes the “right to be forgotten”. India’s Personal Data Protection Bill is currently in draft form, and it remains to be seen how private and state entities will be charged with addressing similar questions.
Concurrently, of interest is what this will mean for the functioning of corporate-run food supply chains that depend on this very data.
Rather than being the subjects of decisions made elsewhere, farmers, small businesses and even consumers should be allowed to exercise autonomy through shared control over the ownership of their data.
This will admittedly be a challenging road for many who may not be equipped to process this data. But it would allow farmers and small businesses more access to information to use in their own decision-making processes about what and how to grow, buy and sell.
All names have been changed to protect the privacy of the people interviewed.
Natasha Susan Koshy is an Assistant Professor at the Tata Institute of Social Sciences, Hyderabad.
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