How To Evaluate The Accuracy Of A Business Forecast

If forecasts allow us to implement long-term strategic objectives and quantify future risk, how do we know if our forecasts are accurate?  Making strategic decisions based upon an erroneous forecast could after all, materially and adversely impact the financial health of our business.  Take the cash flow forecasting methods previously discussed: If these projections were to determine your company’s future hiring, and if they were grossly inaccurate, you might find yourself with a serious cash flow problem.  So how do you determine the accuracy of business forecasts?

Forecasting Sales Without Historical Data (Part IV)

This post is a continuation of

• An Overview of Business Forecasting
• Forecasting Sales Without Historical Data (Part I)
• Forecasting Sales Without Historical Data (Part II)
• Forecasting Sales Without Historical Data (Part III)

A Comparison of the Linear, Exponential, and Modified Exponential Models

In the previous posts, we provided examples of the Linear, Exponential, and Modified Exponential Models.  For the purposes of this post, lets assume we are a new small business looking to sell our new product named MyCoolProduct.   Our market research suggests that the market saturation point for MyCoolProduct is 250,000.  Let us further assume that we estimated sales in time period 1 to equal 1,000 units and would like to reach 25,000 in 24 months.

Forecasting Sales Without Historical Data (Part III)

This post is a continuation of

• An Overview of Business Forecasting
• Forecasting Sales Without Historical Data (Part I)
• Forecasting Sales Without Historical Data (Part II)

The Modified Exponential Model

Although the Linear and Exponential Model are excellent for short-term forecasting, they are not appropriate for long-term forecasting.  Neither methodology accounts for market saturation.  The Modified Exponential Model and the Bass Model address this limitation.

Forecasting Sales Without Historical Data (Part II)

This post is a continuation of

• An Overview of Business Forecasting
• Forecasting Sales Without Historical Data (Part I)
  

The Exponential Model

In the exponential model, the sales forecast has a fixed rate of growth.  Sales volume for time period t(n) is calculated using the formula:

• t(n) = t(n-1) * [1 + g]^n

where

• g = the growth rate in decimal form, i.e. 0.15 (a 15% growth rate)
• n = the time period

and where the starting value is

• t(1) = a, the starting sales volume for the growth curve.

Forecasting Sales Without Historical Data (Part I)

This post is a continuation of:

• An Overview of Business Forecasting
  

Forecasting sales for a new product is required to determine ROI, conduct a break-even analysis, and budget for required resources.  Since most quantitative forecasting techniques utilize historical data, forecasting sales for a new product can be rather challenging.  New products simply lack historical data.   Fortunately, we can build sales forecasts and then benchmark actual sales data against them to help plan for the future.  The follow techniques are worth mentioning:

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