Feeding Future Demands: Using Data Analytics to Drive Down Food Waste
A recent United Nations report, How to Feed the World in 2050, found that food production may need to increase up to 70% by 2050 to feed the 9.7 billion people who will live on Earth by that time. Reducing waste and ensuring healthy and sustainable products are becoming hot topics in a bid to protect our planet and its inhabitants. Meeting these challenges will necessitate extensive changes to the traditional food supply chain. This will place buyers and suppliers under increasing pressure to cut down on waste to lower costs, improve return on investment, manage resource scarcity and reduce the environmental impact of operations.
Food waste is an ever-growing concern
According to the United States Department of Agriculture, the US as a whole wastes more than $160 billion in food a year and grocery stores are responsible for tossing 10% of that food. Across the globe, more than one-third of food that is grown and produced for human consumption ends up lost or wasted. Key reasons for food waste are:
- Overplanting of crops to guarantee supply
- Edible crops left in the field due to diminishing returns on investments in harvesting
- Damage, contamination, or inefficiencies in harvest, storage, processing, and distribution
- High cosmetic standards leading to culling of visually imperfect products
- Overstocked product displays at stores
- Inconsistent date labels that confuse consumers, leading to premature disposal
- Over-preparation, large portion sizes and aversion to eating leftovers
- Lack of awareness about the occurrence and impacts of food waste
Ultimately, excessive waste will decrease food availability in the market, resulting in increased food prices and limiting low-income consumers' ability to access food. Moreover, if the quality of food deteriorates so badly that the food has to be sold at a lower price or even discarded, the livelihood of farmers and producers is adversely affected.
The supply chain, underpinned by data analytics, plays a key role in food waste reduction
Opportunities for efficiency improvements exist at every stage of the supply chain, from improved packaging to better cold-chain technology. Deploying data analytics and data science techniques can unlock actionable insights to identify where in the supply chain waste is most likely to occur allowing producers to take action to avoid rot. This may be through early preservation (freezing) or reduced prices at the source, such as the farm from where the produce is cultivated.
Data analytics can determine inefficiencies in the supply chain, benchmark key performance indicators and implement the best practices that improve efficiency and drive profitability. The use of advanced analytics can also be extremely powerful for engaging suppliers, employees, customers, around the impact food waste has on costs including environment and social consequences. Developing maturity in predictive analytics and harnessing big data can contribute to a successful balance between food supply and consumer demand. With the growing amount of waste and a need to optimize costs, analytics is becoming an essential part of operating successfully in the market.
Scan Based Trading (SBT)
One way of reducing food waste is to experiment with Scan Based Trading (SBT), in which suppliers maintain ownership of food items until purchase. Think of it as traditional vendor management inventory (VMI) except with the checkout scan data serving as the channel to pay for the goods to the distributor. Large retailers maintain the displays until the food is sold. Suppliers can replenish directly at stores, rather than have to dispense their products through a distribution center.
SBT has continued to grow in popularity in the retail world as it takes the responsibility and ownership of the merchandise away from retailers. In turn, this helps retailers reduce inventory holding costs, minimize risks of spoilage and shrinkage and have more control over their relationship with manufacturers and distributors. This gives them the flexibility to easily shift in accordance with changing consumer needs.
On the supplier side, SBT is mostly seen as a negative. Mainly due to the fact that the supplier is responsible for the product and shrinkage and is dependent on the accuracy of data sent by retailers. It definitely can be frustrating for suppliers. Nevertheless, food waste management is one of key trends in the market and suppliers need to address it.
The best way for suppliers to overcome SBT challenges is take advantage of data analytics coupled with the discipline of a Management Operating System (MOS). By combining SBT data with their own insights and analytics, they will be able to spot errors, reconcile inventory levels maintained at the retailer and identify shrinkage issues. Additionally, the data allows a manufacturer or distributor to spot systemic issues. This shift in accountability and visibility will enable end-to-end supply chain collaboration.
Food waste management for future growth
In summary, across the globe more than one-third of food that is grown and produced for human consumption ends up lost or wasted. In America alone, $218 billion is spent growing, processing, transporting and disposing of food that is never eaten. Food waste management can help to reduce costs for farmers, suppliers, retailers and end consumers, manage resource scarcity and reduce the environmental impact of operations. Suppliers need to look at innovative ways to approach this challenge and are increasingly turning to data analytics to solve industry problems.