Our world can be defined as a series of interconnections. Interpersonal, international and other relationships dictate the global economy and infrastructure and with the advent of the internet, the threshold of connectivity became limitless.
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.
Naturally, supply chain optimization in supply planning can feel counterintuitive. Here’s why you should combat that feeling to create the best plan possible.
In recent webinars and presentations, I have been talking about Early Warning Systems within the context of supply chains. The news story above made me think of several examples where a supply chain would use similar concepts to develop early warning metrics.
Using Descriptive Analytics to Improve Supply Chain Visibility for Variability, Velocity, Volume, and Variety.
In this guest blog series titled: “Memoirs of a Black Belt,” Stephen Boyd a Lean Six Sigma Black Belt and 30-year supply chain veteran, shares his insights on achieving higher levels of performance using data from existing systems. All opinions expressed in guest authors may not reflect Arkieva’s view on the subject.
Artificial Intelligence (AI) has been making its rounds in world news for the last few years. With considerable advancements in the field, the concept of AI has garnered its share of fans and critics alike. While many believe AI is the next step in the industrial revolution with its potential for complete automation and an
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
Setting up a supply chain performance measurement system? Here are 5 things to know
How does Walmart’s new supplier delivery policy affect suppliers? Here’s a take from Arkieva CEO on how suppliers can respond to market variability as a result of the policy change.