This blog covers new pull supply chain responsiveness and logistics concepts for hubs with good air and sea-freight connectivity like Singapore. Big data and web analytics are creating new demand opportunities, and help operations meet growing global regulatory standards. Very often, my work also involves helping online retailers improve operations. Discussions spans from raw materials serialization, to manufacturing, marketing and sales. Visualization and analysis techniques are also shared.
Monday, August 12, 2013
Thursday, August 8, 2013
Assortment quantity decision to fill containers
For many small and medium sized companies looking to buy associated products from the same supplier to fill up shipping containers, many still use gut feel rotate among products to stock up just to fill the container. This gut feel may or may not take into account variability of past sales or sales forecast ahead.
A scientific approach to apportioning how much extra stock to carry will be using the safety stock factor approach. Where we say the proportion of extra stock to buy for one SKU relative to another SKU is in a ratio of z*stdev of demand for one SKU / z*stdev of demand for another SKU. This is suitable for SKUs that are already in the market for some time and has reliable historical sales numbers. The multiples of SKU purchase would of course, we governed by MOQs and/or order multiples.
If it is a new product, then we should look at it from a cost of overstocking vs cost of understocking. It's ratio will give it the proportion beyond or under demand.
If the SKU is a combination of new and old products, then we have to combine the ratios of the different SKUs together. It is possible because the underlying normal assumption probabilities is the same.
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