Learn how a simple binomial model can help anticipate the future including COVID-19 breakthrough cases just as models help a firm estimate it's future.
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.
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.