Question

What is a business problem in business management that could be solved using a forecasting solution? State what the issue is and how forecasting could aid in solving this problem, and the type of data that would be need to collect to solve this problem. Would there possibly be seasonal or trend factors in forecasts?

Answer 1

Challenges in business forecasting, such as increasing accuracy and reduc-
ing bias, are best met through effective management of the forecasting
process. Effective management, we believe, requires an understanding
of the realities, limitations, and principles fundamental to the process. When
management lacks a grasp of basic concepts like randomness, variation, uncer-
tainty, and forecastability, the organization is apt to squander time and resources
on expensive and unsuccessful fixes: There are few other endeavors where so
much money has been spent, with so little payback.
This chapter provides general guidance on important considerations in the
practice of business forecasting. The authors deal with:
■ Recognition of uncertainty and the need for probabilistic forecasts
■ The essential elements of a useful forecast
■ Measurement of forecastability and bounds of forecast accuracy
■ Establishing appropriate benchmarks of forecast accuracy
■ The importance of precisely defining demand when making demand forecasts
■ Guidelines for improving forecast accuracy and managing the forecasting function.

The first problem is that, if we take the error measure over just one period
(say, the next period), we may be lucky and forecast the value exactly, giv-
ing a forecast error of zero. Clearly, such luck is not sustainable over the long
term. To overcome this difficulty, we can amend the definition of forecast-
ability to “the lowest level of forecast error that is achievable, on average, in
the long run.”
This definition of forecastability is not restricted to one particular error
measure but can be applied to any forecast error metric for which the word
smallest is interpreted appropriately. Nor is this definition of forecastability
restricted to a “basic time-series method”.

A second problem: The definition depends on the achievement of the
smallest forecast error. It is possible that a series is difficult to forecast and will
yield high forecast errors unless a particular method is identified, in which
case the forecast errors are small. In cases such as these, it would be helpful to
specify both a lower bound and an upper bound on forecast errors.

Forecasting with seasonality and a trend is obviously more difficult than forecasting for a trend
or for seasonality by itself, because compensating for both of them is more difficult than either one
alone.
There are other methods a person could find to use for taking into account both a trend and
seasonality, but the approach we will follow is the following:
1. Estimate the amount of seasonality - the seasonal relatives (or factors or indices)
2. Estimate the trend (the rate demand is growing at)
3. Make a straight-line prediction of future demand
4. Adjust straight-line projection for seasonality to get a seasonalized forecast.