案例库 · 产品与设计 · 运营决策 · 2011–2013
这条还没译成中文，下面是英文原文。
Kroger stopped over-ordering and under-ordering pharmacy stock with a simulation
Kroger's pharmacies produce on simulation-and-optimization demand forecasts, saving the grocer over $170M a year.
Kroger
那一手
A pharmacy's inventory problem is a mismatch between uncertain demand and a finite shelf of drugs that also expire. Overshoot and money is sunk into stock that goes unused; undershoot and the customer walks to a competitor.
Kroger built, with Wright State's Xinhui Zhang, a set of intuitive demand models and fast calculation routines to project pharmacy demand more accurately and set stock accordingly. A simulation-and-optimization engine tests ordering rules against the range of possible demand.
By treating demand as a distribution rather than a single guess, the model lets Kroger hold less stock while cutting the out-of-stock events that lose customers.
为什么管用
- It modelled the uncertainty directly, so it could balance overstock and stock-out rather than guess.
- Quick computation made the models usable day-to-day, not a periodic review.
- It reduced inventory cost and out-of-stocks at the same time, instead of trading one for the other.
- The work showed a university partner could build a system a big retailer runs every day.
可以搬走什么
When demand is uncertain, don't forecast a single number and stock to it — simulate the distribution and optimize the order policy against the risk of both overstock and stock-out.
后来呢
Kroger was already saving more than $170 million a year when the project was named a finalist for the 2013 INFORMS Franz Edelman Award. The Interfaces paper also reported an $80 million a year rise in revenue, more than $120 million cut from inventory, and a $10 million a year reduction in labor cost.
资料来源
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