Expert Systems Essay Example

ratio of 26%. The required level of fixed assets is then calculated by multiplying this ratio by the projected 1996 sales, resulting in $17.52 million. As this amount is lower than the 1995 fixed asset amount, it is concluded that no new assets are needed. The excess funds can be utilized for increasing dividends, pursuing growth opportunities, or reducing debt.

Our suggestion is to use the surplus funds for growth opportunities, as the company intends to maintain its current capital structure while increasing dividends by $0.10. The case also mentions that there are "other products in the pipeline," which suggests that the excess funds could be allocated towards these products. If we assume that ESI was operating at 90% capacity in 1995, we would need to adjust the previous calculations mentioned earlier (detailed in the attached spreadsheet) and determine that fixed assets should be increased by $1.3 million in 1996. This adjustment would result in an AFN of $0.54 million.

To maintain competitiveness in various industries, it is vital for firms to incorporate lumpy assets - sizable and distinct units - due to technological factors. These assets greatly influence the fixed assets-to-sales ratio at different sales levels, thereby impacting financial statements. When a firm operates at full capacity, even a slight rise in sales necessitates doubling fixed asset quantities, resulting in significant financial requirements. Thus, accurately determining a business's operating capacity percentage is crucial for future success.

A higher dividend payout ratio decreases internal funds and increases the need for additional funds. Conversely, higher profit margins boost internal funds and reduce the need for additional funds. Similarly, higher capital intensity ratios raise

asset requirements and also increase the need for additional funds. The percent-of-sales method is a technique used by analysts to forecast financial data for strategic planning, budgeting, or creating pro forma financial statements. Through the percent-of-sales method, reasonable projections for certain key data can be established.

The aim is to analyze the past connection between a financial statement account item and sales figures. This analysis helps in predicting the future value of these items based on projected sales estimates. It is essential for accurate forecasting that these items show a strong correlation with changes in sales figures. If there is no evident correlation, an alternative forecasting technique should be employed.

Using historical financial statement data, an analyst estimates inventory levels based on sales forecast. If the analyst determines that inventory levels are usually 30% of sales and the projected sales for the upcoming year is $100,000, then the estimated inventory would be $30,000 - equivalent to 30% of the projected sales. The process of percent-of-sales forecasting involves three steps. The first step entails analyzing historical financial statement data in order to identify correlations between items and sales figures.

The percent-of-sales method can accurately predict or forecast items that are correlated with sales figures. However, items not related to sales must be estimated differently. The next step is to forecast sales for the desired fiscal period. It is crucial to obtain an accurate sales forecast as all projections in the percent-of-sales method rely on the connection between financial statement items and sales figures.

Other forecasting methods, such as Sales Forecasts, The Additional Funds Needed Formula, and Forecasting Financial Requirements when the Balance

Sheet ratios are subject to change, can be used in addition to the percentage of sales method. The third step in this method involves combining the sales forecast with the historical relationship between specific financial statement items and the sales figure to forecast their values.

Sales forecasts are crucial for businesses in various sectors and sizes as they offer essential insights for planning and management. By evaluating sales records, businesses can analyze past and current sales levels, track their growth, and compare their performance with industry peers. Forecasting empowers businesses to establish policies that effectively manage profits through monitoring prices and operating costs. Additionally, analyzing historical data enables businesses to identify and tackle minor issues before they significantly impact sales.

In order to achieve precise forecasts, businesses need to have knowledge of their historical sales figures in terms of dollar amounts. This important data is already well-organized within the company's accounting records and financial statements. Analyzing the sales volume by seasons, quarters, months, or weeks allows for increased accuracy. Additionally, a comprehensive sales forecast should take into consideration all internal and external factors that can impact sales.

Sales forecasts can be prepared by businesses for individual products or entire business units. The frequency and time frame of these forecasts may vary depending on the industry and management practices. When a business aims to expand, it employs the concept of Additional funds needed (AFN). This implies that in order to increase sales, the business requires additional assets to achieve its goals. Therefore, arrangements must be made to accommodate the changes in assets. In essence, the business must devise a plan to finance the

new assets necessary for sales growth.

When forecasting balance sheet ratios, economies of scale are crucial due to their impact on cost advantages obtained through expansion. These advantages cause a producer's average cost per unit to decrease as output scale increases. Economies of scale occur in the long run and involve reductions in unit cost as facility size and input usage levels increase. Each method for forecasting balance sheet ratios differs in processing time and output. However, all methods require data from the company's balance sheet and income statement to be used.

The statement does not imply a discrepancy in the capital structure, but rather suggests that the market value is lower than the book value. Our research shows that the ideal ratio of debt should be approximately 30 to 31%, with equity making up around 69 to 70%. However, if interest expense is calculated solely based on year-end debt and ignores additional debt throughout the year, it will lead to an overestimation of interest expense. This situation creates a cycle known as financial circularity, where increased debt causes higher interest expenses which then decrease net income and retained earnings, ultimately resulting in more debt.

When interest expense is calculated, adding debt throughout the year instead of on December 31st underestimates the expense if beginning-year debt is used. However, this does not create circularity. Conversely, calculating interest expense based on the average of beginning and ending debt accurately estimates payments when debt is gradually added during the year. Nonetheless, this method may introduce circularity. Please refer to the chart below for ratio values that executives may find useful during their retreat.