I've done a lot of supply chain network design projects and consider myself to be an expert. Had I had this book from the start, I may have got to expert status a lot faster.
With experience in supply-chain and an academic background that includes mathematical-optimization, when the need arose to build supply chain network optimization models I just did it. Then I learned many, valuable, real-world lessons the hard way- by getting it wrong.
There are a number of books available that cover this area: I have dipped into a few, as needed, and I have not read most of them so I really can't say this is the best book available on the subject. I can say that this is one of the very few analytic books on any subject that I have read cover to cover.
Network design is perhaps not as hot a topic now as it was 10 years ago. That's just my perception, but while the hype right now is around "big data", network design continues to deliver major savings to organizations. Network design finds where your facilities should be and how product should flow through them to support your business at the lowest cost. The more rapidly your business is changing the more often this is worthwhile: an acquisition or divestment will almost always justify the expense with a significant ROI. A 10% reduction in supply chain cost is common.. Even on a stable business there can be significant saving (transportation, labor and warehousing) in adjusting product flow on a relatively frequent, annual basis.
Note that while the authors (all from IBM) have extensive experience building software products to help you do supply-chain network optimization this book is not a sales brochure for LogicNet, in fact, it's barely mentioned.
The math needed to run an optimization model is not simple but it is accessible to those who want to learn and this book does take you through step by step a mathematical programming model that gets increasingly sophisticated. The necessary theory is all there.
What attracted me was that it goes beyond the theory and has lots of details around project execution:. the need for sensitivity analysis; the difficulty of getting reliable transportation rates ; sensible data aggregation strategies; why you must have an optimized "baseline"; and numerous others. These are all areas that analysts get wrong - as I did. Some learn from the experience, others send out the results anyway.
Managers who hope to become better buyers/consumers of network-design projects (remembering that your analysts may also be making newbie mistakes) skip the math sections and you can still understand what can be modeled and why you would want to.
For analysts actively involved in building optimization-models the mathematical formulations are extremely helpful. Even if you choose to build models with a software package that tries to hide the harder math from you, the guidance around data and the art of modeling is worth the price and the time to read it.
If you have a network design project in mind and a plane journey coming up - make the investment.
by Michael Watson, Sara Lewis, Peter Cacioppi and Jay Jayaraman (Sep 1, 20112)