Anything that supports your executive in making appropriate plans for the company barring any kind of unforeseen circumstances, can be termed as financial forecasting. With such plans, businesses can improve over areas such as budgeting, hiring, sales goals, and earning predictions for guiding them across their financing decisions and institutional investment goals. Thus every decision made if backed up by financial forecasting can eliminate chances of blindly leading businesses to problems. Not being one-size-fits-all, financial forecasting comprises techniques and methods depending on the data they use and the purpose of the output. Each approach offers its advantages and disadvantages and it is critical for businesses to choose the appropriate forecasting method that suits best their requirements their goals in projecting future finances. But businesses must understand that none of the financial forecasts is foolproof. When a business organization makes future predictions by compiling information from the past, there are always chances for the occurrence of errors irrespective of the approach they incorporate. Identifying a forecasting approach that offers general reliability helps businesses with framing and informing financial decisions such as budgeting and hiring. Generally classified into two broad categories such as qualitative and quantitive forecasting, these leading forecasting options help businesses to achieve desired results but with a risk factor. OURS GLOBAL’s Finance and Accounting Services helps businesses predict their financial future with monthly financial statements of income, cash flow, and balance sheets of their past.
Following are the Two Ways How Businesses can Financial Forecast:
Qualitative Forecasting Methods
Compilation of soft data from expert estimation corroborated by historical data, such as qualitative data of costs predicted by executives as per newer regulatory laws. But it is critical for employees for being credit with their predictions and must reinforce them with their vast experience and insights. As businesses could get the advantage of supporting their predictions from limited data, even qualitative forecasting is quite less reliable for predicting the future. The popularity and effectiveness of their approach can be fruitful for short term situations and the following are the models for qualitative forecasting:
Executing evaluation of potential business scenarios, businesses can use market researching for analyzing the chances if they are looking forward to opening businesses in a brand new location, testing marketing & packaging an upcoming product. With thorough market research, businesses can generate data for informing financial forecasting. But attending to many variables and unreliable circumstances increases the unreliability of data accuracy. Extensive data collection enhances the trustworthiness of data, but it’s surely a time-consuming and costly process that demands high investment. This process also can’t guarantee much over small research biases and inconsistencies in data collection & uncontrolled variables.
Sourcing data from experts with proper knowledge over evaluated subjects can be termed the Delphi method. Seeking outside sources along with in-house expert insights helps businesses in the compilation of data with questionnaires for the identification of consensus opinions about various financial matters. This approach for qualitative long-term forecasting discusses the industry or market growth or attempts to project the value of real estate investments with market variations over the years.
Quantitative Forecasting Methods
Driving straightforward approaches generating forecasts based on hard data, quantitive forecasting helps businesses to be effective while dealing with data points such as future sales growth & tax topics and avoiding less insightful subject matters. Eliminating the guesswork out of the process, this approach requires human skills & expertise as this is critical in causing deficit over critical contexts that may alter the overall forecasting results. As an effective tool for several business scenarios, if historical business data is reliable for projecting future results.
Following are the top Quantitive Models:
A. Straight line
Much easier for implementation, straight-line requires basic mathematics and reasonable estimation that drive businesses in anticipating futuristic financial scenarios for businesses who are looking forward to financial growth in the future. Most businesses make use of revenue growth rates of the past for the same. The rise that has been experienced over the past few years is a clear indication that nature will continue to towards the preceding years too. While there will be variables that influence the revenue growth, it is also compatible with the net profits over the period.
B. Moving average
This method is ideal for businesses that set financial goals and budgets for developing plans based on the expectation of where your company must be. Analyzing the average performance of a specific metric over a specific period, the moving average method can be useful in evaluating revenues, profits, sales growth, stock prices, and other common financial metrics. Smoothening out business performance over time, moving average helps businesses to get a thorough understanding of their financial trends. These methods can be compatible with businesses in industries where sales and revenue fluctuations are normal. Moving average method helps businesses in getting awareness of peaks and valleys of the future financial months to come.
C. Time series
Putting forward comprehensive approaches of financial forecasting, time-series strategy helps businesses identify patterns in historical data that remain to continue in the future, enabling data-driven forecasting across a diverse range of financial metrics. The application of such approaches can be appropriate for businesses that have steady financial performance. Using sales and revenue growth from prior months for estimation of performance in the upcoming months, the direct translation of such trends can’t deliver accurate business results. Shifting to time series forecasting helps businesses in forecasting time-bound future performance patterns. Fighting amongst seasonal trends that can influence forecasting, the time-series approach helps adjustment for the same.
D. Linear Regression
Graphically representing the relationship with multiple data points, the linear aggression method uses the relationship of the variables for charting trend lines that illustrates the relationship between the two.
In case of the increase in sales, profits are supposed to increase too, businesses develop a linear regression revealing a positive correlation between the two. The decrease in profits even with more sales indicates other problems of rising expenses or other increased costs per conversion that cut down the company’s sales efforts. the trend line by these regressions can be incorporated for forecasting future results that help businesses with better budgeting and guidance for strategic decision making for improvement of business performance.
Thus the use of such approaches drives financial forecasting helps businesses with planning, budgeting, and other financial activities within the company. Businesses trouble much for management of cash reserves, employee payrolls, and others to drive the expansion of their business. Outsourcing financial forecasting service requirements to an ideal services provider such as OURS GLOBAL’s Finance and Accounting Services helps businesses with such result-oriented and tested forecasting methods for insights that can improve their decision-making process. Ping us right away and accelerate the financial planning process by improvement of data management and forecasting initiatives.