Monte Carlo Discrete Event Computer Simulation is a particularly powerful and flexible “tool of the trade” for a wide range of challenges in supply chain and operations management. This blog provides some basics on MCDECS, the next blog will use MCDECS to explain why limiting the size of a gathering helps reduce the spread of COVID-19.
Over the past six months, significant progress has been made in understanding COVID-19 and reducing its health and economic impact. In this blog, we will not rehash this information, but to identify open issues in handling the current challenge of tackling COVID-19 and relate this to the challenge of managing supply chains.
The risk of viruses is often a topic of conversation in current times. One of the dominant questions at social gatherings is - what is a bigger risk (defined as serious illness) this fall and winter: regular virus (REGVIR) or COVID-19...
For most involved in Supply Chain Management, optimization is viewed as one of the three primary methods to create a supply or central plan that matches or balances assets with demand. Historically effective use of space involved minimizing unused space or maximizing revenue from a fixed amount of space. COVID-19 has upset the social order.
If you are thinking “machine learning and AI” will save you from data disasters – think again as the pandemic behavior is playing havoc with machine learning models.
As previously discussed, being only data-driven can be a road to disaster for COVID-19 or supply chain management. To avoid this disaster requires skill sets from operations management (OM). In this blog we demonstrate that the probability a person actually has COVID-19 antibodies depends heavily on other factors besides the “raw data” of the test results.
An often-heard theme in supply chain management (SCM) and COVID-19 is “data-driven” – being data-driven is the path to success. For COVID-19 “science-driven” is often said in the same sentence. For SCM demand or customer-driven replaces “science”. This blog will point out a few examples in the COVID-19 challenge demonstrating COVID-19 is an OM challenge.
The current COVID-19 situation highlight the supply chain management challenges in any turbulent time. In this blog we identify five key points: preparedness, larger good, anticipate, and not react to events, responsiveness, and an intelligent stochastic estimate of demand.
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.