Methods and Financial Model
Sales are the lifeblood of any company, and getting a reasonable estimate of sales revenue scale and growth is highly critical in any ensuring business planning exercise, such as capital investment decisions, hiring of staff, expansion of business operations and allocation of operating budgets, etc.
Hence, forecasting demand for a company’s products and services, and the resulting revenues accrued is probably the most critical step a financial analyst needs to undertake when building a financial model.
In order to arrive at a realistic and reasonable revenue forecast for a business, a good financial analyst should conduct a detailed revenue modeling / demand analysis of a company’s products and services, by examining its usage potential and a customer’s willingness and ability to pay.
A demand analysis would entail determining current demand and using assumptions for demand build up to predict future demand over the time period of the financial model. There are a number of qualitative and quantitative methods that can be used to conduct a demand analysis.
Sales Forecasting Using Qualitative Methods
These methods rely essentially on the qualitative judgment and information of highly experienced practitioners or experts in a specific area, and translate their opinions into quantitative estimates of the revenue model of a specific business, product or service.
* Jury of Executive Opinion Method: Very popular in practice, this method calls for a group of experienced executives and experts to get together in a structured discussion forum, and in which a moderator would work towards pooling the contrasting views of these executives on expected future sales and demand and combines them into a revenue and demand estimate that they can all agree on.
* Delphi Method: The Delphi method also relies on the views of a pool of experts, but they do not interact face to face, and the demand forecast and revenue model is constructed through an iterative process. The advantage of this method is that it avoids “group-think”, which may sometimes creep into the Jury of Executive Opinion method, when the pool of executives start agreeing with one another without through independent and objective thinking.
Sales Forecasting Using Time Series Projection Methods
Demand projection methods based on time series generate sales and revenue forecasts on the basis of historical data and trends. The important time series projection methods include:
* Trend Projection Method: The trend project method involves the direct extrapolating historical sales and revenue trends in the future, primarily those of growth and customer conversion rates. This method works well for stable businesses that have not experienced significant change in their financial profile in the past years, and expect to continue on a similar track going forward.
* Exponential Smoothing Method: In exponential smoothing, sales and revenue forecasts are modified by examining potential bumps or errors in observed historical demand data trends, to ensure that historical demand rates that are exceptionally high or exceptionally low due to a one-off event are not carried into future revenue projections. This method is useful for discounting the impact of exceptional events (such as a sudden spike in sales due to an unsustainable trend) on the historical sales performance of a business.
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* Moving Average Method: In the moving average method, a simple arithmetic average or a weighted arithmetic average of a reasonable historical sales data window are used to forecast future demand. This method works well for businesses which periodically experience adjustments in their revenue profile or structure, but bounce back to similar historical levels after a certain time period.