While I was a member of the Dell Worldwide Operational Strategy organization I met Dr. Koray Dogan who introduced me to i2’s Supply Chain Strategist. SCS is a traditional mixed integer program (MIP) used primarily for supply chain network optimization.
In the SCS years we talked about things we wished we could do such as demand forecasting, inventory target setting, production planning and replenishment planning. For that matter, any type of planning would have been revolutionary in an environment where strategic network optimization was pretty much the limit of our analytical scope. We were having FUN with OR but we knew there was more to be done if somebody would put their mind to it.
Koray put his brilliant mind to it. He had told me he was going to do it and I remember thinking “That’s great Koray, everyone has to have a dream. We once dreamed of going to the moon.” Believe me, that was and to a large degree still is the position of thought leaders in our field … incorporating non-linear functions and planning decisions in a linear optimization model is like going to the moon.
So now that I’m a member of the Solvoyo team (you know the old saying “I liked it so much a bought (joined) the company!”), I’m here to say not only did Koray get us to the moon it’s where we prefer to live! By live on the moon, I mean we optimize the network flow model as a core requirement in our data structure (you know, because who wants to plan in a suboptimal fulfillment system?) but we use that as input to and the foundation of optimal planning from beginning to end.
Demand – Supply matching, inbound order frequency optimization, replenishment planning, not to mention street-level transportation optimization where every trailer is sequenced with the optimal store-level replenishment quantities, that’s where we’re most comfortable.
Next up – Get your head INTO the Cloud(s)
Logistics are part of supply chains. The purpose of a supply chain is to do one thing – enable a company to grow. However, focusing only on transportation will reduce costs but invariably will cause issues in other areas.