An interesting case study of inventory. You can see that it still is an issue of great importance to businesses.
Accurate knowledge of demand flow is very important in predicting the amount of inventory to carry, if the product is selling fairly frequently.
The authors found that a few big customers were placing unusual big orders and that was driving outages. We’ve known this for 30 or more years; I observed it at a disk drive company I was product manager for in Silicon Valley. Manage the big orders and you manage inventory.
But that does not reduce the value of inventory models and predictions of service level.
via Are You Keeping the Right Amount of Inventory?
Not everyone thinks assembling big data is a good idea! Perhaps they have alternative facts.
I just subscribed to this source. Even though they do not disclose who they are, it might provide interesting information.
Labor-related concerns were cited by the Senate, but the project will likely move forward without the funding.
Source: FMC plan to develop pilot information portal fails to receive Senate funding | Supply Chain Dive
Posted in Advanced Computing, Logistics, Ports, Production Operations, Quantitative Methods, Supply Chains
Tagged analytics, computing, container shipping, intermodal, Logistics, ocean shipping, ports, Production Operations, Shipping, supply chains, technology
This approach to rate analysis is interesting. I know from experience, having seen how hard it is to deduce correct truckload rates for a given simulation. We spent a lot of time divining these rates for a specific need. A generic econometric approach would be useful. I hope Chris Caplice has a public access paper on the subject.
The Myth of a Single Market Truckload Rate: Part 2.
The same issue applies to rail rates as well. And they are even more obscure, since one cannot get info on them easily.