For those that work regularly in the supply chain or managing the demand-supply network (DSN) models are commonplace to help with similar questions. This blog will provide some basics about models that all will find helpful...
We see graphs of COVID-19 events on a regular basis. One of the most common is a bar chart for daily new events (COVID-19 cases, hospitalizations, deaths). Recently in presentations, smoothing methods used to overcome limitations is presenting the raw daily data. This blog will take some of the mystery out of smoothing methods.
This blog provides some basic information on the curve, relates statistical concepts to policy and actions, and examines policy options for a safe restart relating them to the APEX curve. There are three essential groups of action to begin a safe restart: testing, detailed understanding of the impact of mitigation actions, and the ability to do detailed tracking.
We see graphs of COVID-19 events on a regular basis these days. Two common ones are bar charts for daily new events (COVID-19 cases, hospitalizations, deaths) and the “sweeping curve” to capture a cumulative number of events. Additionally, log transformations are mentioned. The purpose of this blog is to shed a bit of light on these curves and the role of the log transformation.
There is plenty of material being written and posted on the challenges, estimating the growth in COVID19 incidences, and thoughts about the economy. The purpose of this is to pull from experiences in the trenches in shifting OPCURVE to provide some guidance on actions to take to help the nation achieve both critical goals.
An ongoing challenge for any firm is estimating demand for new products. This is especially true when the product has new technology or is replacing an existing product and the additional function in the new product is limited. Often a mathematical construct called an S curve is helpful. This blog provides an overview of S curves and why they can be helpful.
The spread of the COVID19 virus is a major concern of everyone. Typically, two critical questions are being asked: why it seemed to grow so quickly over the last few weeks and what is the impact of social distancing. This blog provides a kitchen table explanation of “rapid growth” and how social distancing might dampen growth.
Probabilities are persuasive in supply chains and analytic methods – especially in machine learning where conditional probability is a dominant underlying structure that makes or breaks the success of an application. In this blog, we will learn how to take the mystery out of the term ‘conditional probability’.
A common question is how to best manage safety stock for critical raw materials that are critical to the production of the exit product...
Two ongoing questions are: (1) when an organization migrates from an Excel-based central/supply/master plan is it best to go to a rule-based method or an optimization-based method and (2) is optimization a compass that identifies true north or is it an advanced navigation system. This blog outlines my view and alternative views on each question.