Across the country, the grocery and food ecosystem is a highly fragmented segment, with respect to both demand and supply. Adding to the woes of the sector is the lack of transparency on pricing and demand, which leads to huge inefficiencies for both farmers and consumers. Even in cases where there exists a steady demand, there has been a lack of reliable payment methods and efficient supply chain infrastructure. This has led the food sector to witness colossal delays, lost opportunities, and huge wastages across the ecosystem.

In order to combat this, the advent, and advancement in technology has come as a boon to the sector, especially in terms of supply chain management. AI, in particular has revolutionized the sector and is being used widely in various business applications. From forecasting the weather to identifying demand opportunities and challenges, it also helps in increasing operational efficiency in various facets of businesses. Here are some ways through which Artificial Intelligence is transforming the face of supply chain systems:

Predictions that allow meticulous demand forecasting
A gap between the current inventory and demand can lead to enormous losses. Trouble not only arises when stock levels are lesser than the demand, but excessive hoarding can also negatively impact the profitability of a firm. AI is inducing efficacy in the arenas of network planning and predictive demand, consequently making the products more proactive. By having a clear idea of what can be expected, entrepreneurs can adjust the number of vehicles as well as direct them to markets where maximum demand is bound to arise.

These eventually lead to a reduction in operational costs.

ChatBots to provide seamless customer support
These are computer programs designed to stimulate interaction with consumers, especially over the internet. These bots are so result-oriented that a recent study reported – 80% of buyer engagement can be handled by them. It helps in establishing a liaison between the client and the logistics providers, as the parties can effortlessly converse over the portal. Further, it brings down the delivery time and ensures greater personalization by increasing communication clarity.

Enhances efficiency with smart warehouses>
Unlike traditional warehouses, they are completely automated facilities wherein a huge chunk of the work and management takes place through the usage of automation coupled with high-tech software. These new-age storehouses simplify tedious tasks and operations become more cost-effective. In many facilities, robots tend to work alongside humans to boost productivity. Additionally, machines that are tailor-made to package goods help in making the process increasingly strategic and automated.

Advanced algorithms to improve delivery time and reduce costs
When it comes to the supply segment, every single mile and each minute counts. The technological disruptions have introduced companies to route planners based on genetic algorithms. These planners help organizations to chalk out optimum routes for faster deliveries, consequently avoiding any damage to product quality during transit. Routes can be optimized with the help of GPS tools, after factoring elements like traffic, weather conditions amongst others. Further, the identification of shorter paths fuels the reduction of costs by lowering the overhead expenditure.

Enables structured demand planning
The applications used for this purpose rely on a series of algorithms to draw out historical shipment data and convert it into a forecast. It entails varied elements that focus on key areas like promotion, end life of products and several others. Under this method, the result obtained is compared to the actual shipment; the conclusions hence drawn are used to determine when to move from one algorithm to another, for a particular stock unit.

Provision of Transportation Management Systems (TMS)
These systems promise an assured rate of interest and are primarily used by logistics providers to lower their freight spend. They induce savings by driving home stimulation, network design, load consolidation, lower cost mode selections, and multi-stop route optimization. Further, it keeps service quality in check by understanding the origin to destination lead times along with using apt constraints during optimization runs.