How data analytics might reduce food waste

Like it or not, we all are living in a world where many people are starving while in the same time a tremendous amount of food is wasted by consumers, retailers, manufacturers, etc. Food wastage is a problem not just because is a missed opportunity for people in need. It is an issue because wasted food is incinerated in combustion facilities or is stored in landfills. Once in landfills, the food breaks down to methane, which is a strong contributor to the greenhouse effect boosting hazardous climate change. Speaking of food waste we should know that throwing an apple means we are spilling about 100 liters of water, needed for its growth. The water footprint of a beef is more than 7 tons of water.

How big is the food waste problem?

Nearly one of every 3 food products finishes its life cycle as a waste. You can see detailed break down as staggering infographic created by the UN Food and Agricultural Organization (FAO). Their data shows clearly that the problem is really pressing in the fruits and vegetable sectors, where losses are estimated at 45%.

food waste infographic FAO already published report displaying a clear link between climate change and food losses. But in a way smaller perspective, this problem affects the business. Tesco, one of the big British grocery retailers is targeting this issue in a pretty interesting way.

How Tesco applies data analytics to reduce food waste?

Tesco managed to reduce its food wastage by 2%, even though the problem got worse in its bakery departments last year. To cut waste, the British grocery brand tried to limit the time that food sits in its supply chain so that it can sell longer lasting products. Tesco improved its supply chain by data analytics pointing efficiency-boosting opportunities.

The British grocery brand also is more careful with stock planning. We all have the business gut feeling that if the weather goes well, the salads consumption will raise. Data analytics is capable of answering the how much question – 42% in warm weekends during the summer. By establishing a successful balance between stock and consumer demand you are not going to miss sales opportunities while the cost of the stock is reduced to its optimum. This is how data analytics is utilizing weather forecast in projecting future business performance.

Tesco also developed an algorithm to determine how aggressively to reduce pricing on items approaching the end of their shelf life. The aim of this task is to move as much as possible products with closing expiration dates.

On top of this, the grocery chain of stores declared that by the end of 2017, it will donate good enough foods to different charity organizations to prevent its complete wastage.

How your grocery business can get access to a similar analytics solution?

A4RetailStores web-based analytical application is addressing exactly this particular issue. By providing extremely accurate sales forecasts while utilizing weather forecast for a particular location, A4RetailStores will let you know easily what you are going to sell tomorrow or the day after or even by the end of the week or month with amazing accuracy, 95% or more if there is sufficient historical sales data. The analytical application, developed by A4E is much more complicated than projecting simple statistical trends because it is capable of detecting trends, recurrent customer behavior and to differentiate workdays from weekends and bank holidays. A4RetailStores relies on complex mathematical and analytical algorithms similar to those used by Tesco.

Test a4RetailStores for free right here:

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