In many areas of supply chain management, analytic methods generate estimates with “pesky decimals”. The traditional method to eliminate the decimals is rounding. In this blog, we demonstrate the importance of this method and how to calculate these improved integer estimates.
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.
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.
For a new technology to be successful it requires the correct seasoning which requires time in the trenches. This blog captures lessons from two past gurus.
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.
There are a number of data analysis “tools of the trade” that have proven effective in exploring data to get it to tell a story. One such method is the first-order difference (FOD). The purpose of this blog is to provide an overview of FOD with respect to profiling demand history.
Inventory comes in many forms and flavors; it is the critical element of supply chains that enable a firm to respond quickly and take advantage of scale. However, managing inventory is one of the most...
Inventory management (IM) is a critical component of any successful organization where the mechanics of measuring and monitoring inventory involve KPIs, dashboards, and data science...
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.