For those of you looking for a good introductory overview of decision optimization for strategic sourcing, two new resources hit the bit-stream today.
First of all, there’s the 2-Part “What is Supply Chain Optimization?” podcast, part of the Next Level Purchasing’s (now the Certitrek NLPA) podcast series that features Charles Dominick (a Supply And Demand Chain Executive Pro to Know), President of Next Level Purchasing (a Supply & Demand Chain Executive 100 Company) and yours truly. (For more details, see today’s edition of the Next Level Purchasing newsletter.) Clocking in at just under an hour, we try our best to convey the basics of strategic sourcing decision optimization and why it’s important to you as a sourcing / procurement / supply mananagement professional. For those of you who find the podcast quite dense (it is!), and wish to review one or more sections, you’ll be pleased to know that a free transcript (basic or with editorial notes) is available, sponsored by Sourcing Innovation.
Secondly, over on the eSourcing Wiki [WayBackMachine] (which, as of today, has 18 wiki-papers on various topics relevant to you as a sourcing professional with more on the way), the Strategic Sourcing Decision Optimization wiki-paper is now available, sponsored by Iasta (acquired by Selectica, merged with b-Pack, rebranded Determine, acquired by Corcentric). Along with an introduction to optimization, including strategic sourcing decision optimization, it also overviews the benefits and ten strategies for success.
When you add both of these resources to the ever increasing archive of decision optimization blog posts here on Sourcing Innovation, I believe (or at least I hope that) you finally have the resources you need to start understanding what strategic sourcing decision optimization is, is not, and why it’s important. Especially when you consider that Emptoris (acquired by IBM, sunset in 2017) gives you nothing and CombineNet (acquired by Jaggaer) primarily gives you academic papers in their learning center, which, although great, are too advanced for those of you looking for an introduction that you can understand as a non-academic and non-optimization researcher.