The food industry is a tough and complex business as meals need to always remain fresh. Most meals once prepared cannot be carried forward. Hence, meals once prepared have to be sold, and delivered quickly. Predicting the right quantity of meals that will be ordered or consumed is also tough, as meal preferences change frequently.
Can technology play a role? Eatfresh, a food technology player, is banking on its technology expertise to better understand meal preferences. Launched in August 2015, Eatfresh is an online platform which delivers high quality meals created by top rated chefs. The startup has sold more than 1 lakh meals till date. Similar to Uber in the cab industry, the startup has a chef-centric marketplace. It improves quality through a feedback and rating mechanism that is integrated in every order.
The firm uses technology in a big way – right from procurement to delivery. It uses analytics to predict item wise menu and preferences on a daily and hourly basis. For example, it uses analytics to plot the historic data of meals ordered up to 10 am, 11 am,12 noon etc, in a particular hub, which tells it how many meals the firm needs to have ready at a particular time on any given day. This algorithm further adjusts the production patterns based on hub location, time of day, weekend/ weekday/holiday based on weightage and formula.
From the predicted quantities obtained, the information flows to a recipe management system which maps raw materials to quantities so they can be procured from certified, local vendors. Each chef’s recipe is mapped to a detailed weight based formula which drives the entire production process.
Explaining the challenges of a food e-commerce business, Jipy Mohanty, CTO, Eatfresh.com, says, ”FoodTech or food-
commerce is a very unique e-commerce business. Our product catalog changes daily, the inventory is replenished on the hour, we produce what we sell, and deliver in under 30 mins. That’s little crazy for an e-commerce business isn’t it? Unlike traditional e-commerce, we have two huge spikes of order volume right around 12 pm for lunch and 8 pm for dinner. And, delivery has to be done within 20-30 minutes. So, imagine a system that has to orchestrate taking hundreds of orders each hour, routing it to the delivery hub closest to the customer, then helping the chef prepare and pack the right food for the right order, and then having a rider get it to the customer, all within 30 minutes or so.” The firm has ensured that order related data and other consumer data flows seamlessly through to planning, sourcing of each ingredient, and to production control.
IoT for ensuring quality
Eatfresh has 6-8 devices (ovens and freezers) at each delivery hub that need to maintain their temperature within a very narrow error margin throughout the day. A significant temperature change means that the firm loses quite a bit of food and turns away lot of customers. With the constant flow of orders, it is humanely impossible to keep track of the functioning of these devices. To monitor the temperature, the firm has placed high quality sensors (tolerant of the heat and humidity inside devices) that monitor the temperature every minute of the day and alert the firm as soon as there is a variation. This also helps in ensuring food safety at every step of the product cycle and maintain product quality.
The system also auto-allocates and transfers order details and GPS coordinates to the delivery rider app, which allows the firm to track location of each delivery rider, performance, and delivery times. The real-time geolocation data of every delivery driver flows back into central systems for monitoring and escalation whenever an order gets delayed.
