Retail Fresh

Ca 931 millioner tonn mat ble kastet i 2019. Ferske produkter (brød, frukt og grønt, kjøtt, fisk og varmeskap/deli) stod for en betydelig andel av dette. Bestillingen må ta høyde for og håndtere store svingninger i etterspørsel, usikkerhet i beholdning og varierende holdbarhet på produktene. Dette gjør det vanskelig for Retailere å redusere svinnet. I gjennom dette prosjektet sikter vi på å redusere svinnet av ferske produkter, samt opprettholde eller øke salget. Som en del av denne prosessen har vi også som mål å bedre lagerstyring av ferske produkter. Vi vil nå disse målene ved å ta i bruk toppmoderne maskinlæringsmetoder.

For 2019, food waste specifically amounted to 931 million tonnes of food, of which 13% occurred at retailers. The Norwegian Institute for Sustainability Research calculates that largest waste categories in Norwegian grocery trade in 2019 were (in descending order) fresh baked goods (9.9% of economic value), fresh fruit (4.5%), fresh fish (4.5%), vegetables (4.3%) and fresh meat (2.9%). Dry goods represented only 0.5%. While there has been a total reduction of 14% of tons of food wasted in retail stores from 2015-2019, waste of fresh baked goods and fruit and vegetables has changed little during this period. The rapid deterioration rate of fresh produce gives it short and variable shelf life. Therefore, fresh produce is typically not supported by automated goods supply systems. Manual ordering has to take into account the large demand variations, high sales volume and particular high-quality product requirements, which in turn may explain the high degree of waste for fresh produce. To reach the UN Sustainable Development Goal target of 50% reduction in tons of food waste by 2030, retailers must implement waste reduction measures for fresh produce that are much more efficient that the state-of-the-art. Link Retail AS specializes in using data analysis, advanced calculations, and scientific methods to help retailers improve their results. In the project, Link Retail and the University of Bergen will develop a scalable system based on machine learning to minimize wastage of fresh goods while sustaining sales. The software will be tested iteratively on different categories (bread, fruit and vegetables, and then meat, fish and deli) in close collaboration with Meny.