Introduction
Every enterprise is highly dependent on the revenue generated. The revenue mainly depends on the sales made by the firm. Market demand analysis is vital in maximizing sales, and therefore continuous utilization of available data is necessary for tracking changes in market behaviors. Reviving the competitive nature of Whalot Company would require extensive analysis of factors such as demand. Such reports would be vital in guiding the decision-making process that relates to areas such as production, advertising, inventory holding, and cost allocation. Diversification and growth of Whalot company would highly depend on the response of the market to the product offered. A situation whereby production exceeds demand as it has been the case requires maintenance of balance between the two. Whatalot should base its attention to the nature of its output and analyze if the production meets the demand. Through such analysis, estimation of future demand can be made, and verdicts on inventories can be achieved.
Cost analysis would be another critical component that would enhance the rapid revival of the Whatlot company. Understanding the interaction of various elements related to cost within the management team would be vital in determining the output of the Whalot company. Such communications and relationships would be critical in determining the optimal level of production. Having an explicit knowledge of how such factors interact would guide decisions in cost control, pricing of the product, profit maximization, and product promotion.
Regression Analysis
Demand Analysis
| SUMMARY OUTPUT | |
| Regression Statistics | |
| Multiple R | 0.674218246 |
| R Square | 0.454570243 |
| Adjusted R Square | 0.374359985 |
| Standard Error | 8915.502975 |
| Observations | 40 |
| ANOVA | |||||
| df | SS | MS | F | Significance F | |
| Regression | 5 | 2.25E+09 | 4.5E+08 | 5.667233 | 0.000663 |
| Residual | 34 | 2.7E+09 | 79486193 | ||
| Total | 39 | 4.95E+09 |
| Coefficients | Standard Error | t Stat | P-value | |
| Intercept | 112161.546 | 54647.112 | 2.052 | 0.048 |
| OwnPr | -62.789 | 25.532 | -2.459 | 0.019 |
| AcmeP | -79.934 | 18.761 | 4.261 | 0.000 |
| BezoP | -29.616 | 86.045 | -0.344 | 0.733 |
| ConsP | -108.473 | 39.733 | -2.730 | 0.010 |
| Advert | 6.983 | 16.767 | 0.416 | 0.680 |
To analyze market demand, regression analysis was used. Regression analysis is a technique used to check the influence of the independent variable on the dependent variable. In our case, the dependent variable is the quantity demanded, while the independent variable is the cost of advertisement, Whatalot price, and the price of the competitors. The summary output table provides the value of the coefficient of determination in which the variability in quantity demanded is explained. The coefficient of determination value is 0.45, which means that 45% of the variability in quantity demanded is defined by the price of competitors, firms’ price, and the cost of the advertisement. The ANOVA table provides the significance of the regression model. The regression model is significant as the p-value is less 0.05. The coefficient table provides the coefficient values for the predictor variable.
Whatalot price, the price of the competitors, is a significant predictor of the quantity demanded. As per the p-value, advertisement cost is not a significant predictor of the amount demanded. This implies that a shift in demand for the quantity for Whatalot company has majorly been impacted by its price and that of its competitors. The coefficient value for Whatalot indicates that increasing price by one unit would lead to a decrease in quantity demanded by 62.79 units. An increase in price for AcmeP by one unit would lead to a drastic reduction in quantity demanded by 80 units. An increase in price for commodities for BezoP and ConsP by a unit would lead to a decrease in quantity demanded by 30 and 108, respectively.
Cost Analysis
| SUMMARY OUTPUT | |
| Regression Statistics | |
| Multiple R | 0.806052 |
| R Square | 0.64972 |
| Adjusted R Square | 0.640502 |
| Standard Error | 1079044 |
| Observations | 40 |
| ANOVA | |||||
| df | SS | MS | F | Significance F | |
| Regression | 1 | 8.20679E+13 | 8.20679E+13 | 70.4847 | 3.4757E-10 |
| Residual | 38 | 4.42448E+13 | 1.16434E+12 | ||
| Total | 39 | 1.26313E+14 |
| Coefficients | Standard Error | t Stat | P-value | |
| Intercept | 15007474 | 598557.6983 | 25.07272726 | 3.04E-25 |
| Advert | 14324.87 | 1706.251924 | 8.395516505 | 3.48E-10 |
Cost analysis was done using regression analysis in which the fixed variable cost was derived from the regression model. The model indicates the significance of the cost of advertisement as its impacts on the overall cost of operations. The fixed variable cost from the model is estimated at 15,00, 7474. Increasing the value of advertisement by a unit increases the cost of production by 14324.87
Conclusion and Recommendation
From the findings of the analysis, the quantity demanded Whatalot company is influenced by the price of the competitors and its pricing. It is, therefore, essential to consider a better pricing strategy for the company products to avoid a negative shift in the demand curve. A point of concern is the factor of advertisement as the analysis has proved that advertisement has no impact on the quantity demanded. Whatalot should, therefore, develop a good marketing policy that will attract more customers. A change of marketing strategy would enhance a positive shift in demand of the commodity irrespective of how the competitors would price their commodities.
Demand analysis complements the findings of the cost analysis.Whatlot should consider change of cost structure specifically the cost assigned to advertisement as the previous data has proved that advertisement has not largely impacted to change in quantity demanded. It is, therefore, essential for the company to consider a strategy for the next quarter that will analyze the behavior for the consumers and come up with a better advertisement approach that is cost-effective.
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