Tools of the Trade: How to Compare / Combine Diverse Time Series – “Normalizing”

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.

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.

Data Science Tools of the Trade: Monte Carlo Computer Simulation

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.

By |2020-11-23T19:58:42-05:00November 24th, 2020|COVID-19, Data Science, Machine Learning|0 Comments

Statistical Forensics – The Danger of Being Data and Not Operations Management Driven

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.

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