I feel truly proud. My friend Akshit and I created "ROOTS", a platform to reduce food waste and CO2 footprint and save money by using deep learning to improve from past orders.

In this project, we've worked faster and more efficiently than ever before, and we ended up with an impactful result. We learned a lot about time management while creating such an amazing platform.

We came up with this idea originally while participated in a great Hackathon.

EUR 2000 million in Food waste is generated for AgroChain in the Netherlands (Source: Ministry of Agriculture, Nature and Food Quality)

Restaurants account for 60-100 million of this waste.

A typical restaurant wastes around 18% of the fresh food it purchases.

Most of this food waste is generated due to sub-optimal ordering practices. Where the supply chain orders are placed using gut feeling and experience instead of actionable data.

This situation is further worsened during the current coronavirus crisis. With restaurants struggling to survive, wasting resources during covid 19 is not an option.

Roots is a platform that aims to reduce these inefficiencies in the supply chain for restaurants.

With Roots, we reduce the food waste in restaurants while increasing the profits for them and farmers. Our platform leverages machine learning to forecast future amounts of supplies to order based on previous sales.

To do this, we first break down each of the restaurant dishes into ingredients. 

Then we use past sales data to predict future sales.

We take into account multiple parameters for prediction; these include total sales per day, the time of the year, and the holidays.

Our test on a restaurant dataset shows we are 86% accurate, which is 16% more than the industry practice of ordering based on gut feeling and experience. This accuracy is expected to improve as our algorithm is always training.

This generates multiple benefits for various stakeholders involved.

The stakeholders include; lower operating costs for the restaurant, a reduction in their food wastage, and a reduced carbon footprint.

As multiple restaurants use our platform, we can leverage group buying power to order the supplies directly from the farmers. Thus, Bypassing the traditional entities in the supply chain.

And this is how it looks:

 

We plan to deploy this platform in the city of delft at small restaurants like Pasta2go and Doner kingdom.

A typical small restaurant like Pasta2Go spends around 3000 Euros every month ordering fresh supplies from the distributors.

Using the rough figure of 18.5% of wasted fresh food leads to a savings of around 550 euros per month for the restaurant owners. Our platform takes a small cut from these monthly savings, roundabout 5%.

Our main revenue is generated from the restaurants that are using our platform.

We generate a monthly revenue based on a cut based pricing model.

Later on, With group buying in volume, small farmers can also act as key stakeholders. Thus, generating supplies directly to the restaurants.

We are changing the traditional behavior of ordering supplies by restaurants. Our algorithm has increased accuracy by utilizing actionable data.

In higher stages of the supply chain, supermarkets use an ERP system to order supplies from distributors.

Further, for group buying, our end users are volume buyers instead of individual households.

In the future, we also plan to show our demand insights for each crop to the farmers to plan their production accordingly.

If you are interested in this project or want to know more, feel free to contact me.