Supply Chain Stories: Forecasting and Fast Fashion

Photo by Conrad

Recently I read a story on how Wal-Mart forecasted an unusual need when sifting through their trillions of bytes’ worth of consumer data in preparation for Hurricane Frances as it marched its way towards Florida’s Atlantic coast.

Wal-Mart’s chief information officer discovered that during Hurricane Charley which happened a few weeks earlier, strawberry Pop-Tarts had jumped in sales to seven times their normal sales rate.

Wal-Mart quickly sent trucks full of strawberry Pop-Tarts to the nearby stores in preparation of the storm and quickly sold out.

That story is a good example of business intelligence used effectively to accurately predict consumer behaviour, turbocharge the supply chain and create greater efficiencies.

Spanish Fashion retailer Zara is another example of a responsive supply chain. Zara has been able to avoid costly over-production by doing three things: shipping limited inventory to its stores, carrying limited stock at any time, and by making information transfer fast.

Zara has a centralized, flat hierarchy with no sequestering of staffs. It’s 200 clothing designers work right in the midst of the manufacturing process whilst the factory laborers work. The distance between management and production, both physically and bureaucratically, is basically non-existent and allows the easy flow of information.

For Zara, it results in higher sales and less unsold items in an industry rife with overstocking and discounting.

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