KITRO, an early stage startup aiming to reduce food waste in restaurants came to us with the challenge of creating an internet connected device that identifies and quantifies food that is thrown away by restaurants.
* Disclosure: some parts of this article have been removed due to a pending patenting process of our clients. The full article will be published as as soon as possible.
Two-thirds of all the wasted food in the world could have been avoided. What if we could use technology to reduce this enormous global inefficiency?
This is the challenge that Anastasia Hofmann and Naomi MacKenzie, two entrepreneurs who recently graduated from École Hôtelière de Lausanne, are tackling right now. The objective of their startup, KITRO, is to reduce food waste in restaurants by providing insights about the food that is thrown away, and make recommendations on reducing this unnecessary waste.
There is no seamless, fully automated, simple, state of the art solution to gather food waste information from restaurants. However, if there would be a way, the entrepreneurs with their work experience and studies background assure that restaurants could reduce avoidable food waste by up to 70%!
KITRO came to us with the challenge of building a device which can detect and classify food as it is thrown away, as well as measure the quantity.
We accepted the challenge of our first client and set the date for the breeding: from Friday afternoon to Sunday evening to build the MVP. For a good job, the right people need to be brought on-board: we contacted another ETH Zürich student to help us (the core Unicorn Labs team) during the breeding. He has a broad knowledge in electrical engineering, which we knew would be very useful. Selecting the right people is one of the most important steps – a good team consists of persons with different fields of expertise, complementing each other.
Every breeding starts with a design thinking workshop like “the wallet project” from Stanford: in this phase, together with our client, we apply several design thinking methods to challenge the participants perception on how to solve the problem of capturing, quantifying and classifying food waste in restaurants. First, we diverge, imagining many different and sometimes crazy solutions. All solutions are organized in a morphological table, after which the converging phase starts: the ideas are classified according to criteria such as feasibility, seamless customer experience and robustness. Finally, we all must agree on what will be delivered at the end of the breeding process.
In the morning, we acquired additional necessary hardware at various stores. We had pre-ordered most of the electronic components. Half of the team focused on CAD, as parts for the housing and interface for the electronics were planned to be 3D-printed. The printing takes quite some time so we prioritized this task from the start. The other half of the team concentrated on the scale electronics, figuring out how to read the data and coming up with a calibration strategy.
At 19:00 on Sunday, we made the MVP handover: we showed our client the work results and how it worked. It was critical for them to test it intensively in the coming weeks, during which we remotely fixed a few remaining bugs.
When KITRO was ready to install the MVP at their first client, we assisted in the process.
With the MVP, KITRO can place the device at their customer’s kitchen and seamlessly monitor everything that lands in the garbage bin. With the pictures, they can classify the wasted food and create reports for the restaurant.
This way, KITRO can validate their hypothesis without over-developing and wasting resources to find out if restaurants are willing to pay for their service. Once this is validated, there is room for improvement, but, most importantly, in this first phase, they know there is a valid business for them.
It was an amazing experience working with our first client. And we were delighted to see that with our MVP, they were able to get into an accelerator program, win several competitions, and are on track to get funding and finding technical co-workers.
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