Post by nafizcristia99 on Mar 11, 2024 5:08:02 GMT -5
their own predictive analytics technologies for retail, including in the fresh produce space. Brandtner mentions that he has worked with large supermarket chain Aldi, for example. The data he and his fellow researchers gathered in recent years revealed huge shifts in purchasing behaviour during Covid- lockdowns. That is to be expected but he points out that such information could be used to predict consumer activity in the future if a new, similarly disruptive, epidemic or pandemic emerges. Brandtner praises Freshflow and BlakBear for their efforts at more accurately predicting real demand and tracking food freshness, respectively. However, he notes that users should treat AI tools with caution. Demand forecasting systems might get their predictions right much of the time but if they fail in situations where footfall or customer behaviour just happens to diverge from the norm, then their benefits could be limited.
Once implemented, it does not mean that it will always run smoothly, it has to constantly be monitored,” says Brandtner. Harvest fare Machine learning tools aren’t just influencing what retailers decide to buy Uruguay Mobile Number List in, they’re also in the hands of suppliers. Mihai Ciobanu is founder and director of Freshcast, which currently has a staff of two people. The firm has raised £, so far. Freshcast is active in Europe and the US and Ciobanu says suppliers moving , tonnes of food annually are using its technology. This ranges from fresh blackberries to prepared soups and salads. The Freshcast system allows users to experiment with “what ifs”, says Ciobanu.
A supplier might use the system to simulate what would happen if they bring a retail promotion forward in time, for instance. The supplier might then suggest this approach to their customer, the retailer themselves. Some data that could influence sales, such as the weather forecast, the software sucks up automatically, whereas information about the sudden failure of a crop, the software user might consider on the fly. To take an example, say there’s a smaller-than-expected harvest of raspberries. The supplier might use Freshcast to estimate how much more effective it would be to sell the available raspberries in smaller punnets for the remaining months of the season, thereby reaching a higher number of individual customers despite having less fruit on hand than they thought they would.
Once implemented, it does not mean that it will always run smoothly, it has to constantly be monitored,” says Brandtner. Harvest fare Machine learning tools aren’t just influencing what retailers decide to buy Uruguay Mobile Number List in, they’re also in the hands of suppliers. Mihai Ciobanu is founder and director of Freshcast, which currently has a staff of two people. The firm has raised £, so far. Freshcast is active in Europe and the US and Ciobanu says suppliers moving , tonnes of food annually are using its technology. This ranges from fresh blackberries to prepared soups and salads. The Freshcast system allows users to experiment with “what ifs”, says Ciobanu.
A supplier might use the system to simulate what would happen if they bring a retail promotion forward in time, for instance. The supplier might then suggest this approach to their customer, the retailer themselves. Some data that could influence sales, such as the weather forecast, the software sucks up automatically, whereas information about the sudden failure of a crop, the software user might consider on the fly. To take an example, say there’s a smaller-than-expected harvest of raspberries. The supplier might use Freshcast to estimate how much more effective it would be to sell the available raspberries in smaller punnets for the remaining months of the season, thereby reaching a higher number of individual customers despite having less fruit on hand than they thought they would.