In the simplest inventory situation, the only variability is in the quantity of demand for a single day. There is no trend up or down or seasonal effect. The demand today is independent of the demand for tomorrow. Additionally, we will assume replenishment time is zero. That is when we place an order for additional
Most folks involved in Sales and Operations Planning (S&OP) for supply chain management have heard the terms “optimization” or “linear programming” with regards to supply planning and have cringed at the sound. Over the past few years a new “cringe” worthy term has emerged – “machine learning” which is sometimes used with the term predictive
The term ‘optimization’ can and does have different meanings to different groups. For the folks who build and develop scheduling algorithms, creating the best schedule is defined in terms of cost criteria – perfectly logical. For business settings (from manufacturing to hospitals) optimization refers to the entire process. Let’s look at the scheduler’s world to
Each year I work with new bright-eyed future experts in planning and scheduling as they make the transition from their academic studies to the murky world of applied planning and scheduling. One of the first rules of thumb I suggest is to ensure everyone has the same view of the problem. Is this a planning
One value of supply chain modeling is the ability to explicitly model capacity or constrained resources. Which products get what capacity in what amount at what time? How does this impact on-time delivery? Where do I add capacity? These types of questions are custom made for a “little bit of math” and difficult to do
Your demand planning process is complete and demand statement is created; excellent, but the sales and operation planning journey is far from complete – the next critical step is matching or balancing assets (capacity, materials, people and projected supply of finished goods) with demand to answer three questions that are part of being a responsive