A reoccurring challenge in comparing and combining diverse time series in demand forecasting is the “scale” – as it is in combining metrics. Rescaling is a powerful but simple method to help with this issue enabling demand planners to focus on similarities of shape. This blog provides an example of one method called normalization.
In this blog, we point the reader to a recent article “Humachine”, which identifies the general challenge of implementing decision technology to improve SCM decision making resulting in improved organizational performance and the importance of experience in the trenches.
In this blog we briefly cover some key insights for successful time series forecasting: (a) Profiling the Shape of the Curve is the first stage, and the first step is assessing if the time series is stationary. (b) The forecast method identified must capture the shape and be able to project the shape across time. (c) There are limits in historical and no amount of “fancy math” can overcome them.
Learn when it is time to move from RCCP to LP Genie for your CPE as part of your organization’s journey pulling from years in the trenches and current ongoing activities with clients.
The purpose of this blog is to explain a basic costing challenge in factories and their impact on critical SCM analysis and decisions.
An earlier Sudoku blog recognizing Puzzle Day, provided an overview of solving Sudoku using MILP optimization and mentions these methods are helpful to find solutions in supply or central planning. This blog elaborates on “binary variables” which is the connecting technology between Sudoku and Supply Chain Management (SCM).
With the holiday season, everyone is making their wish list and checking it twice. Here are some ideas to add to any director of supply chain's wish list.
For a new technology to be successful it requires the correct seasoning which requires time in the trenches. This blog captures lessons from two past gurus.
Today we will discuss a few of the logistics challenges from the perspective of an industry expert with lots of time in the trenches. Arkieva is ready to help Delaware.
Data Science Without Modeling Impact is a Path to Disaster – Simulation to Explore the Impact of Group Size on COVID-19 Spread
In this blog post, we will briefly review some examples of being “COVID-19 adrift” with just data and then focus on the primary task – demonstrating how modeling can be used to understand the impact of group size on COVID-19 spread.