Applying data science within the food supply chain isn’t something you’d usually talk about at a dinner party. Right now, however; the disruptions across the entire global food supply chain mean that supply chain challenges are something everyone is noticing, and the topic is more relevant. You’ve seen the issues at the local level: fast food restaurants are out of menu items, restaurants have no French fries, shelves are missing variety (or sometimes entire categories of food products), and there are meat shortages at stores. While there are many factors that lead to these troubles that are hard to disentangle, there are some causes that can be understood, modeled, and mitigated using data science.
Data science can inform changes you make to your food shipping plans
The availability of cold storage trucks means that getting products around the country is now far more expensive than in the past (if you can even get a truck). This requires thinking out of the box when scheduling your logistics, as the old shipping rules of thumb no longer apply. In addition, understanding and modeling these logistics challenges is required to correctly cost your product, as transportation is becoming a higher portion of the spend. So much higher, in fact, that even companies like Johnsonville are buying their own fleets to try to work around shipping related volatility and companies like Walmart and Home Depot are utilizing air freight, shipping on smaller vessels, buying their own ships, and using spot purchasing to try to take control of the shipping delay problem.
Another significant driver in disruption is the lack of labor. This can be seen at the customer facing end of many businesses, but is also present further back in the supply chain. This means that companies have to make tough choices about what to make based on the labor input required as well as the value to the consumer. The price for products that are labor intensive has to be increased, and the selection decreased. Determining the best way to do this while satisfying the customer and making a profit is not easy.
It is tempting to think that these are all short term disruptions caused by the lockdown, but the persistence is evidence that the global supply chain is more fragile than people realized. Every year there are small shocks to the system that can usually be resolved without the consumers noticing. The ability to model scenarios and quickly respond to changes is not just important now, but through all the smaller disruptions that happen every year.
Data science and machine learning can help your business adjust to handle any unknown or unforeseen volatility and thrive even when conditions are turbulent. Contact us to find out how.
