Food supply chains (food chains) are made up of multiple enterprises (producers, packers, transporters, processors, distributors and retailers) each with very different sets of activities to perform. There is limited “vertical integration” in food chains since rarely are more than a few of these enterprises controlled by a single entity.
However in order to function effectively, it is essential that there be an acceptable level of “supply chain integration” among these enterprises. This simply means that these entities within the food chain must cooperate to achieve certain desired results, such as assuring no delays at the transfer points.
The optimum extent of this integration depends on both the desired outcome and the cost of integration.
Greater Levels Of Integration
There are three current trends that will force a much greater level of integration on food chains. The first of these is the pending food safety legislation. This legislation is likely to require that time limits be imposed on product tracing. Current tracing capability is predominately dependent on paper records augmented with spreadsheets. Any regulation on “trace time” will require that the tracing process be automated.
This in turn requires cooperation among the food chain entities to standardize the data requirements and to develop processes to provide this data in a timely fashion.
Food chains are typically open systems with sometimes very large numbers of different entities participating in the chains. There is also great diversity among these entities in terms of size, geographic location, experience, resources and technical sophistication.
This creates tremendous challenges in developing a tracing system that can trace forward and back in a relatively short time. It is not simply a matter of designing and building software. It will involve understanding the capabilities of each of the food chain participants and the various processes involved in moving product through the chain in order to design the combination of processes and technology to enable tracing in restricted time.
The second trend is the increasing availability of technologies to monitor and control products throughout the supply chain. This provides potential to capture new data regarding shelf-life in the store, when the harvest occurred, how the product is treated prior to arrival, and where delays occurred.
By working together, the various entities in the chain can use this data to improve perishable inventory management by more accurately estimating the period from post-harvest life to end of shelf-life. They can also monitor status at various points throughout the food chain to reduce delays and reduce variability in shelf-life estimates.
By monitoring temperature it can be determined where integration is needed to improve product quality and reduce energy costs.
Also, by monitoring conditions that the product is exposed to, risk profiles can be developed to aid in decision support for assessing safety risks.
Lastly, these technologies may expose opportunities for improving integration of transfer points in the food chain and facilitating disintermediation.
The third trend forcing integration is the need for better analytics to address the dramatic increases in complexity occurring in food supply chains. This complexity is the result of food chains with more perishable food products, more participants, more transportation, more processes, more technology, more international shipments, more security requirements and more regulation.
This complexity requires the development of new models to better predict the status of products when they arrive at the retail outlet in order to manage replenishment effectively.
Failure to accurately estimate shelf-life is extremely costly for the retail outlets. If for example, the store plans for their strawberries to last six days and they only last three days, about half of the strawberries will be wasted and half of the time the store will be out of product.