FINANCIAL FORECASTING.pptx
- 2. FINANCIAL FORECASTING IS PREDICTING A COMPANY’S FINANCIAL FUTURE BY EXAMINING HISTORICAL PERFORMANCE DATA, SUCH AS REVENUE, CASH FLOW, EXPENSES, OR SALES. THIS INVOLVES GUESSWORK AND ASSUMPTIONS, AS MANY UNFORESEEN FACTORS CAN INFLUENCE BUSINESS PERFORMANCE.
- 3. There are two primary categories of forecasting: Quantitative ◦ Percent of Sales ◦ Straight Line ◦ Moving Average ◦ Simple Linear Regression ◦ Multiple Linear Regression Qualitative ◦Delphi Method ◦Market Research
- 5. 1. Percent of sales The percentage of sales method is a forecasting tool that makes financial predictions based on previous and current sales data. This data encompasses sales and all business expenses related to sales, including inventory and cost of goods. To forecast the percent of sales, examine the percentage of each account’s historical profits related to sales. To calculate this, divide each account by its sales, assuming the numbers will remain steady. For example, if the cost of goods sold has historically been 30 percent of sales, assume that trend will continue.
- 6. How to calculate step by step 1. Locate and determine your current numbers: Before doing any calculating, you need to have your current finances ready and available. These numbers will serve as a baseline for future budget comparisons and will give you a sense of what your business is looking like financially. 2. Choose what you want to forecast: Not every business expense or account is influenced by sales. Of course, if you are seeing high expenses in areas that are not backed up by revenue return, those are worth looking into through a budget analysis, they’re just not applicable to this formula. Some accounts you may want to forecast include: •Cash •Accounts receivable •Accounts payable •Fixed assets •Cost of goods sold •Net income 3. Write out the balances of each account and their percentage in relation to revenue: Depending on the size of your business, this can take some time. The hope in this step is that you will end up with positive percentages in every account. If not, it means you have a negative net income. We’ll go into this further in the walk-through example. 4. Calculate the forecasted sales: Your company should have an ideal increase forecast based on current sales and realistic KPI goals. Let’s say you expect sales to increase 20 percent. Using the following formula, you can determine the approximate value of your forecasted sales: If your current sales are at $75,000 and you expect a 20-percent increase, your formula would look like this: 75,000 (1+20/100) = 75,000 (1.2) = $90,000 If your sales increase by 20 percent, you can expect your total sales value in the upcoming quarter or year to be $90,000. 5. Apply your new sales value to the percentages calculated in step 3: By taking the percentage of revenue relevant to each account and applying it to your forecast number, you’ll be able to see approximately how much money will be gained or lost in each account.
- 7. 2. Straight Line The Straight-line method assumes a company's historical growth rate will remain constant. Forecasting future revenue involves multiplying a company’s previous year's revenue by its growth rate. For example, if the previous year's growth rate was 12 percent, straight-line forecasting assumes it'll continue to grow by 12 percent next year. Although straight-line forecasting is an excellent starting point, it doesn't account for market fluctuations or supply chain issues.
- 8. 3. Moving Average Moving average involves taking the average—or weighted average—of previous periods to forecast the future. This method involves more closely examining a business’s high or low demands, so it’s often beneficial for short-term forecasting. For example, you can use it to forecast next month’s sales by averaging the previous quarter. Moving average forecasting can help estimate several metrics. While it’s most commonly applied to future stock prices, it’s also used to estimate future revenue. To calculate a moving average, use the following formula: A1 + A2 + A3 … / N Formula breakdown: A = Average for a period N = Total number of periods
- 9. Steps 1. Establish the time frame you want to review The first step to calculate the simple moving average of a commodity is to consider the length of time in which you want to pull data from. For example, you could determine the desired time frame to be five days, 50 days, 100 days or 200 days. 2. Look at the highest price points for each time interval Say you decide to pull price data for seven days. This means that each day, you review stock prices for a commodity and select the highest price point to represent that time interval (one day). Because you want to determine the simple moving average for seven days, you need to check back on stock prices each day, recording the highest price point for the remaining six days. Here is an example that shows price fluctuations for a coffee brand's stock: •Day one: $8.95 •Day two: $8.50 •Day three: $8.85 •Day four: $9.00 •Day five: $8.70 •Day six: $8.55 •Day seven: $8.65 3. Add each price point together Once you record the highest stock prices for a particular commodity over a desired time frame, you need to add each price point to one another. For example: $8.95 + $8.50 + $8.85 + $9.00 + $8.70 + $8.55 + $8.65 = $61.20 4. Divide the total by the number of time intervals established After adding each price point together and getting your answer, you need to divide the total by the number of time intervals you recorded for. For example: $61.20/7 = $8.74 Therefore, $8.74 is the average stock price for a coffee brand over the course of one week.
- 10. 4. Simple Linear Regression Simple linear regression forecasts metrics based on a relationship between two variables: dependent and independent. The dependent variable represents the forecasted amount, while the independent variable is the factor that influences the dependent variable. The equation for simple linear regression is: Y = BX + A Formula breakdown: Y = Dependent variable (the forecasted number) B = Regression line's slope X = Independent variable A = Y-intercept
- 11. 5. Multiple Linear Regression If two or more variables directly impact a company's performance, business leaders might turn to multiple linear regression. This allows for a more accurate forecast, as it accounts for several variables that ultimately influence performance. To forecast using multiple linear regression, a linear relationship must exist between the dependent and independent variables. Additionally, the independent variables can’t be so closely correlated that it’s impossible to tell which impacts the dependent variable.
- 13. 6. Delphi Method The Delphi method of forecasting involves consulting experts who analyze market conditions to predict a company's performance. A facilitator reaches out to those experts with questionnaires, requesting forecasts of business performance based on their experience and knowledge. The facilitator then compiles their analyses and sends them to other experts for comments. The goal is to continue circulating them until a consensus is reached.
- 14. 7. Market Research Market research is essential for organizational planning. It helps business leaders obtain a holistic market view based on competition, fluctuating conditions, and consumer patterns. It’s also critical for startups when historical data isn’t available. New businesses can benefit from financial forecasting because it’s essential for recruiting investors and budgeting during the first few months of operation.