This year's hurricane season in the U.S. Gulf was just getting under way as of early September, and while it appeared to be making a relatively slow start, there are no guarantees it will remain calm. Prescient Applied Intelligence, West Chester, Pa., the vendor of supply chain software for retailers and suppliers, is cautioning that companies had better be ready for another onslaught. The health and safety of employees is the top priority, says Prescient chief executive officer Jane Hoffer, but the needs of the supply chain shouldn't be ignored. "Retailers and suppliers who first serve the public by meeting the challenges of supply chain disaster preparedness will enjoy year-round customer loyalty and brand equity," Hoffer says. Alternatives for supply chain flexibility and replenishment should be built into disaster and crisis planning. They should include plans for collaborating between trading partners. Analyzing point-of-sale (POS) data will help companies to identify those products that are most likely to be affected by an emergency; separate plans, including route optimization, should be drawn up for them. Hoffer speaks of "beeline products," the kind of items that consumers rush out to buy the moment disaster looms. The top 10 are milk, bread, toilet paper, medicine, toothpaste, eggs, coffee, meat, fruit and cigarettes. The same kind of POS analysis can be used to reduce supply pipelines for items that experience a drop in demand during crises. One client of Prescient, Reily Foods, is a supplier of private-label coffee to major grocery retailers. This year, it is moving inventories during hurricane season to guarantee product availability in the event of a major storm.
Technology should be figured into the mix as well. Retailers and suppliers must make sure that their existing systems can take a hit, with a particular emphasis on data vulnerability. In some cases, companies should consider relocating servers to safer areas. At the minimum, Hoffer says, managers should create backup and alternative IT and data warehousing systems. Then, "test everything; test it again."
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