How to replace Minitab with Python to perform a Chi-Squared Test to explain a shortage of drivers impacting your transportation network
Lean Six Sigma (LSS) is a method based on a stepwise approach to process improvements.This approach usually follows 5 steps (Define, Measure, Analyze, Improve and Control) for improving existing process problems with unknown causes.
Find in the link below a short animated explained video to understand the concept behind this solution
In this Article, we will explore how Python can replace Minitab (Software widely used by LSS experts) in the Analysis step to test hypotheses and understand what could improve the performance metrics of a specific process.
You are the Inbound Transportation Manager of a small factory in the United States. Your transportation network is simple, you have two routes:
- Route 1: coming from your northern regional hub (with difficult road conditions and busy traffic)
- Route 2: coming from your southern regional hub (with no traffic and a beautiful modern road)
Transportation is managed by an external service provider with a fleet of three trucks (with three different drivers: D1, D2, D3).
When an order is allocated to the northern regional hub the lead time to get the request accepted is 35% higher than the southern hub.
Are there drivers avoiding as much as possible to be allocated to the north route?
We have analyzed the shipments of the last 18 months to build a sample of 269 records.
This repository code you will find all the code used to explain the concepts presented in the article.
Senior Supply Chain Engineer with an international experience working on Logistics and Transportation operations.
Have a look at my portfolio: Data Science for Supply Chain Portfolio
Data Science for Warehousing📦, Transportation 🚚 and Demand Forecasting 📈