In a recent blog on Inventory Forecasting the core challenges and business importance of estimating inventory are outlined. A projected inventory position across time (plan) is a natural co-product of most central or master planning models that match assets with the demand to create a projected supply line linked to demand.
The tragic outbreak of the Coronavirus has again demonstrated the need for ever vigilant health care services and fast response. It has demonstrated that supply chain interruptions from a manufacturing excursion to a port strike to an infectious disease outbreak require two actions from any firm: preparation and response.
In this blog, you will learn some basic guidelines to determine if the data is quantitative or qualitative with a focus on...
Shutdown days are either planned well in advance or inadvertent and unwelcome manufacturing excursion- this is a factory issue, not a demand issue. The answer is simple...
In Part 1 of this blog, we closed with the following question: “OK, intermittent demand creates a challenge, but I still need a demand estimate, what do I do!” Below we will provide an answer, but with a different orientation that begins with the question: “what is the purpose of the demand estimate?”
Where did the terms RCCP and MPS come from? Reading the recent blog “RCCP versus MPS – Can They Be Connected?” it struck me whether this question represents the current best in class or do they represent old terms as well as an old way of thinking that should not be the end goal of an organization any more when it comes to supply chain planning.
Community Intelligence synchronizes the use of technologies in a manner that is focused on closing gaps in critical decision-making processes in the ongoing journey of more intelligent supply chains to improve organizational performance.
Historically, most of the key planning and computational activities (models, time series, machine learning, and other analytics) that support extended supply chain management (SCM) are “deterministic models”.
Stop using traditional forecast accuracy metrics to measure forecast for sporadic demand patterns. Use this method instead.
Most of us have had some exposure to the “AI Awakening” wave that has emerged over the past few years. Of particular interest to Arkieva and its customers is how this “new technology” integrates with the ongoing journey of creating more intelligent supply chain decision-making process to improve organizational performance.