Tuesday, August 27, 2019
Generating forecasts Essay Example | Topics and Well Written Essays - 2000 words
Generating forecasts - Essay Example Since the current and future customers have more money to buy the companyââ¬â¢s goods and services, it is possible to predict an increase in the purchase of the storesââ¬â¢ product sales and services revenues. Statistical tools help make more informed store management decisions. In the same manner, the increase in certain independent factors may indicate a possible decline in the dependent factor. For example, an increase in the governmentââ¬â¢s taxes will reduce the workersââ¬â¢ take home pays or salaries. Consequently, the reduced take home pays will reduce the workersââ¬â¢ purchasing power. Consequently, the decision makers must expect a decline in the storesââ¬â¢ sales and service revenues. With the reduced take home pay, the employees must cut down their avoidable expenses. The table 1 data shows the company can generate the future weeksââ¬â¢ projected revenues (Johnson, 2010). The expected future sales are grounded based on the above multiple independent variables. The dependent variable is the revenues. As dependent variable, the sales output is normally dependent on the many independent variables. The above table shows that the competitors often sell their products at prices that are reasonable. A reasonable price takes into consideration several relevant factors. One of the relevant factors is the demand for the products. A high customersââ¬â¢ demand for the products will encourage the stores to increase their selling prices. However, a low demand for the storesââ¬â¢ products and services persuades the store managers to offer discounted prices. With the discounts, the customers will take advantage of the price reductions. A price reduction will normally trigger a higher demand for the storesââ¬â¢ products and services (Johnson, 2010). The above table 2 shows the summary of the statistical findingsââ¬â¢ regression analysis for the ten weeks. The Multiple regression output is shown to be 0.63. The R Squared figure is 0.40. The Adjusted R squared figure is -.0950.
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