Harmon Foods, Inc Case Solution And Analysis, HBR Case Study Solution & Analysis of Harvard Case Studies

Harmon Foods, Inc Case Study Solution

Regression analysis with seasonally-adjusted case shipments

The regression analysis is performed with the seasonally adjusted case shipment using the case shipment as the dependent variable and consumer pack as the independent variable. The F value of the test 11.33 percent, which means that the model is best fit and there is a significant impact of the consumer pack on the case shipment.The R square in the table of the regression R square is 0.197percent which that if the variation occurs in one variable; it will allow around 19.7percent change in other variable. Additionally, the multiple R square is 0.44 percent, which means that the data is 44.4 percent close to the fitted regression line. Furthermore, the significance level of consumer pack is lower than 5%, hence providing strongstatistical evidence to reject the null hypothesis that there is not any relationship between the case shipment and the consumer pack.

In the similar way, the regression analysis is performed with the seasonally adjusted case shipment using the case shipment as the dependent variable and dealer allowance as the independent variable. The F value of the test 28.8 percent, which means that the model is best fit as well as there is a significant impact of the dealer allowance on the case shipment. The R square in the table of the regression R square is 0.385 percent, which indicates that if the variation will occur in one variable; it will allow around 38.5 percent change in other variables. Additionally, the multiple R square is 0.62 percent, which means that the data is 62.05 percent close to the fitted regression line. Furthermore, the significance level of dealer allowance is lower than 5%, hence providing strong statistical evidence to reject the null hypothesis that there is not any relationship between the case shipment and the dealer allowance(Gallo, 2015).

Forecasted Case Shipments

With the use of the residual results, the Forecasted Case Shipments is created by multiply the residual results by the respective monthly Seasonality Index. The ‘Forecasted Case Shipments (NSA)’ shows an increasing trend of the sales of the Treat product in the forthcoming years with removing the seasonal fluctuation through de-seasonalizing the databy keeping the focus towards predicting the sales or demand of the Treat product of the company. The ‘Forecasted Case Shipments (NSA)’ can be seen in the Appendix D.

Regression with significant variables

Using the significant variables(consumer pack and dealer allowance)provides strong statistical evidence to reject the null hypothesis, which states that there isn’t any relationship between dependent and independent variable. It is because of the fact that the company must assess the overall influence of the promotional activities either in the shape of the consumer pack of the dealer allowance on the sales of the product. The ultimate objective of the analysis is to test the advertising impact on the sales of the product. The f value of the test is 69.13 which means that the model is best fit as well as there is a significant impact of the independent variables on the dependent variable.Themultiple R square is 0.86, which means that the data is 86.85 percent close to the fitted regression line. Additionally, the R square in the table of the regression R square is 0.7544 percent demonstrates the positive relation between the consumer packs, dealer allowance and case shipment.

Set of recommendations

Taking into consideration the quantitative and qualitative analysis of the independent variables, including dealer allowance and the consumer pack on the sales of the product; the analysis of the f value and p value of the regression ran between the dealer allowance and the case shipment shows that the impact of the dealer allowance on the sales of the Treat product is more than the impact of the consumer pack on the case shipment due to which the management of the company is advised to put major focus on the dealerallowance as it generatedsufficientsales to the company. By pushing dealer to sell the products, the company would be able to generate more sales and profit returns.

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