Regression analysis is a statistical technique for modelling the connection between a dependent variable (the outcome of interest) and one or more independent variables (predictors). By estimating the impact of a predictor on the dependent variable, regression analysis aids in both prediction and the identification of causal relationships.
Regression analysis can be useful in the context of lean six sigma process improvement projects for doing things like pinpointing the factors that affect process performance and predicting the impact of changes in those factors on process outcomes. Prioritizing improvement efforts and making data-driven process change decisions become possible with this knowledge.
Regression analysis could be used in a lean six sigma manufacturing project, for instance, to determine what aspects of the process are responsible for the highest defect rates. Defect rates may be predicted using a regression model, and the results may point to shift size, automation, and raw material type as the most significant factors. In order to reduce defects and boost process performance, this data could be used to determine where to put the most effort into implementing changes like adding more automation or providing employees with additional training.
Reviewing the literature on regression analysis’s application to lean six sigma projects requires an examination of the studies’ methods, findings, and overall conclusions. You could look at other research that has used regression analysis in a similar setting and compare the outcomes and conclusions.
Regression analysis can help someone in product management identify what aspects of a product are most important to its end users. For instance, Li et al(2019) .’s study modelled the connection between product characteristics and customer reviews by means of a regression analysis. According to the data, product characteristics most linked to customer satisfaction were cost, battery life, and display size. Product designers could use this data to make adjustments aimed at increasing buyers’ happiness with the final wares they purchase.
Overall, regression analysis is a helpful tool for product management and lean six sigma process improvement projects, as it sheds light on causal relationships between variables and the effects of experimental manipulations.
