Stopping Wastage of Food with Analytics – New Twist to an Age-Old Problem

Jul 6, 2017


Analytics is a useful tool to help examine the information from various sources and identify the root causes of every challenge and thereby devise strategies to overcome it. Food wastage is a result of increasing consumer demands and the inability of food manufacturers to accurately forecast demand. It necessitates a data-driven approach coupled with retail and supply chain analytics to eliminate or at least curb the waste levels across the globe. Usually, these wastes or un-used items end up in combustion facilities or landfills that in turn facilitates the emission of greenhouse gases and climatic changes and depletion of scarce non-renewable resources.

How Big is the Food Waste Problem?

We know the impact of food wastage on the environment. But it is much more than just a social responsibility, as it demands manufacturers to adhere to various statutory compliance standards for waste management and has a direct impact on its financials. Even countries like Italy and France have passed legislation that bans supermarkets and grocery stores from throwing away unsold food and ordered them to donate it to food banks and charities. In order to tackle this issue and reduce food waste across the supply chain, organizations can leverage big data analytics to derive actionable insights thereby driving profitability by optimizing costs.

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According to a recent United Nations Food and Agriculture Organization (FAO) report, that analyzes the impact of food wastage over the environment and other environmental resources, approximately one-third of the food produced in the world is either lost or gets wasted, which in turn has an impact on the carbon emissions and water and land usage. Thus, making it essential for manufacturers and retailers to take recourse to big data analytics.

Big Data and Analytics Help Curb Waste

Big data is a catch-all phrase that includes structured and unstructured data that is obtained from a variety of internal as well as external sources captured in real-time to identify trends and demand-supply patterns. Organizations often fail to leverage the information that is readily available to them which results in over-production and leads to wastage. Big data analytics helps in addressing business problems, benchmarking performance metrics, and thereby implementing best practices across the organization, improving efficiency, and driving profitability. Analyzing a business’s waste stream by combining the information of what goes out (waste) and what comes in (supply chain) provides a clearer picture of sustainability and profitability.

For more information on big data analytics and its impact on the food industry, request a free proposal.

In order to curb food waste, manufacturers and retailers must-

1. Leverage data analytics- Retailers and/or food manufacturers can identify stores or locations that generate high waste levels, thereby improving the supply chain and reducing food waste.

2. Manufacturers can utilize supply chain analytics, sales information, weather forecasts, and seasonal trends – This helps determine optimum inventory level, predict the changes in consumer demand for food products and plan aggressive promotions to sell products that approach their sell-by and expiration dates.

Thus, in order to address this issue in the food supply chain, Quantzig helps organizations to leverage the information through the supply chain and sales analytics and derive actionable insights that help in pricing strategies, targeted promotions, and accurate demand planning.

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