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.
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.
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.
Lessons From the Operating Curve for the Dual Government COVID-19 Objectives: Reopen the Economy and Eliminate COVID-19
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.