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Gateway Estate Lawn Equipment Co. Performance Lawn Equipment Case Solution & Answer

Gateway Estate Lawn Equipment Co. Performance Lawn Equipment Case Solution 

Question: 1

This case is about the producer as well as the designer of the traditional lawn. The company is named “Gateway Estate lawn equipment Co.” It is a private company located in St Louis Missouri. The target group of the company are home-movers. The firm expanded its product line by producing other products, such as: medium-sized lawn tractors with diesel power etc. The firm sells products through dealers, and dealers sell directly to the consumers of the product. PLE has almost 1660 employees worldwide. The Gateway Estate Lawn Equipment Co has numerous suppliers who supply raw materials for production. Since 2010, the company has been facing an increased number issues related to the employees’ retention, because there is employees turnover in the company, with an inclusion of product quality issues, which is due to the defects in raw material supplied by the suppliers. They implemented some checks and balances that decreased the number of defects, but is had reversed.

In 2010,Elizabeth Burke was facing quality issues in the performance of lawn equipment, but these quality issues were coming from the suppliers’ input, as the result of which, Elizabeth Burke started an investigation. As per the initiative, in 2010, the number of defects decreased as shown in the graph below, but soon she witnessed that the defects’ number was increasing again.  Previously she worked with supplier to enhance quality so that the defects of raw material can be reduced. She also worked with suppliers to perform re engineering production polices, so that they can improve the quality of   product.

As she wants to forecast that how the number of defects might decrease further,soon. So to know that or to forecast that; we have performed a time series forecasting. We used ARIMA model (autoregressive integrated moving average), for this time series data. In this model, we adjusted the seasonality effects as well as the trends. The results of forecasting is shown below, in the graph, and appendix:1 . From the forecasting results; we can predict that the defects can be reduced in the near future.The number of defects in actual data is in range from 1200 to 1800, the defects number in foretasted data is in range from 600 to 1000. So the quality can be improved by large number.

We have performed a regression analysis to determine the significance of our prediction, so the results show the significance as the p-value is less than 5%.The intercept is 931.313, and the R Square value is 95.6%, so the 95.6% variation in defects’ value is determined by the time effect.Following is the result of the regression analysis:

Regression Statistics  
Multiple R 0.978  
R Square 0.956  
Adjusted R Square 0.955  
Standard Error 25.887  
Observations 60  
 
ANOVA  
  df SS MS   F Significance F
Regression 1 839412.3 839412.3   1252.6 0.00
Residual 58 38869.1 670.2  
Total 59 878281.4        
 
  Coefficients Standard Error t Stat   P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 931.313 6.769 137.595   0.000 917.764 944.861 917.764 944.861
X Variable 1 -6.830 0.193 -35.392   0.000 -7.216 -6.444 -7.216 -6.444

 

If the supplier will initiate programs to improve quality of raw material. As the impact of initiatives on number of defects is significant, the equation is Y=931.313-6.830X. which means that one unit increase in quality will decrease the defects by 6.83. the t-states is also greater than 2 so it also shows significance of hypothesis. The confidence interval does not contain zero so it is also showing significance…………………

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