Using Predictive Analysis Enhance The Productivity of Garment Industry Employees, Assignments of Data Analysis & Statistical Methods

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P r e p a r e d B y :

j i y a ( B F T / 2 0 / 1 2 0 0 )

Srijan Mallik(BFT/20/538)

Data Analytics

& R

Productivity of Garment Industry Employees

Flowchart Objective Problem Statement About Dataset Predictor Variable And Target Variable Plots R Code Overview

PROBLEM STATEMENT The Garment Industry is one of the key examples of the industrial globalization of this modern era. It is a highly labour-intensive industry with lots of manual processes. Satisfying the huge global demand for garment products is mostly dependent on the production and delivery performance of the employees in the garment manufacturing companies. So, it is highly desirable among the decision makers in the garments industry to track, analyse and predict the productivity performance of the working teams in their factories

DATASET

INDEPENDENT VARIABLE DEPENDENT VARIABLE Team targeted_productivity smv over_time incentive no_of_workers actual_productivity

R CODE

BOX PLOTS

BAR CHARTS

CORREALATION SCORE Incentive and targeted_productivity have high correlation, even tough smv, wip, and team have low correlation. Ideal time and no_of_worker and over_time has Zero correlation

SCATTERPLOT

REGRESSION GRAPHTS

COCLUSION Companies often set a target production value but often they don't meet their required production due to low productivity and it causes delay in order and company loose their trust from customers. This model will help in predicting the approx accurate production figures.