If you are looking to improve your supply chain management systems in 2018, you most likely have asked the common question: How do I assess my current efficiency? This is a good starting point for anyone looking to add functionality or identify loopholes within current processes. There is no single perfect method that meets all needs and has no flaws. However, the good news is, supply chain assessments have proven to be very advantageous for many businesses.
The use of optimization in supply chain management is widespread, just not in supply planning. Regular use of optimization occurs in inventory management and demand forecasting. “Best-fit straight line” is one of the most common uses of optimization. With this method, you enter or pull into Excel (or your favorite statistics software) a set of “x values” (the independent value e.g. the number of cars in a train) and a set of “y values” (dependent value e.g. the fuel cost for each train), click a few buttons and you get a “best-fit” straight line – a slope (b1), a y-intercept (b0), a measure of goodness, and a straight line drawn through your scatter plot.
An optimization model does the same; it calculates the decisions based on the stated preferences and constraints in the model. That can sometimes have the inadvertent effect of finding new pathways, a road less, if ever, traveled.
In my role as the Director of Analytics, I enjoy working with the Arkieva team and our clients, in building optimization models which help organizations make intelligent decisions with regards to meeting demand, capacity allocation, inventory levels, factory schedules, forecasting, and cancer research. These models are built using a variety of mathematical methods including Boolean