Sameer Kumar, David Choe and Shiv Venkataramani
The purpose of this study is to highlight a key strategic initiative within the former ADC Company (now part of TE Connectivity) called “Lean Pull Replenishment”, designed and…
Abstract
Purpose
The purpose of this study is to highlight a key strategic initiative within the former ADC Company (now part of TE Connectivity) called “Lean Pull Replenishment”, designed and implemented to achieve Six Sigma customer service excellence. This case study would also help facilitate problem‐based learning pedagogy.
Design/methodology/approach
The study showcases implementation of the Lean Pull Replenishment approach using the define, measure, analyze, improve and control (DMAIC) framework. Key input variables were analyzed that contributed to historically inconsistent and unsatisfactory customer delivery performance. Analysis resulted in improving the allocative efficiency of critical input variables through pilot programs on strategic value streams by deploying dozens of kaizen events, and sustaining the gains through leveraging best practices and effective change management principles.
Findings
The study presents a strong case for the team work and the cultural transformation that occurred during the course of implementing this initiative across ADC supply chain. The paper also summarizes the improvement in customer service metrics and financials of the company.
Originality/value
Through this study, it has been established that with consistency of purpose, using the right tools for solving problems and through teaching Lean principles, remarkable results can be achieved, which can be sustained for the long‐term and become a self‐sustaining business philosophy.
Details
Keywords
M Anand Shankar Raja, Keerthana Shekar, B Harshith and Purvi Rastogi
The COVID-19 pandemic has recently had an impact on the stock market all over the globe. A thorough review of the literature that included the most cited articles and articles…
Abstract
The COVID-19 pandemic has recently had an impact on the stock market all over the globe. A thorough review of the literature that included the most cited articles and articles from well-known databases revealed that earlier research in the field had not specifically addressed how the BRIC stock markets responded to the COVID-19 pandemic. The data regarding COVID-19 were collected from the World Health Organization (WHO) website, and the stock market data were collected from Yahoo Finance and the respective country’s stock exchange. A random forest regression algorithm takes the closing price of respective stock indices as target variables and COVID-19 variables as input variables. Using this algorithm, a model is fit to the data and is visualised using line plots. This study’s findings highlight a relationship between the COVID-19 variables and stock market indices. In addition, the stock market of BRIC countries showed a high correlation, especially with the Shanghai Composite Stock Index with a correlation value of 0.7 and above. Brazil took the worst hit in the studied duration by declining approximately 45.99%, followed by India by 37.76%. Finally, the data set’s model fit, which employed the random forest machine learning method, produced R2 values of 0.972, 0.005, 0.997, and 0.983 and mean percentage errors of 1.4, 0.8, 0.9, and 0.8 for Brazil, Russia, India, and China (BRIC), respectively. Even now, two years after the coronavirus pandemic started, the Brazilian stock index has not yet returned to its pre-pandemic level.