Forecasting, Pt 1

Forecasts are no more than a cog in a Prediction Process

Any process that ends in a decision involves forecasting the future. No decisions can be made that do not account for possible future actions. At their most basic level, forecasts are simply predictions of what will occur in the future.

Every C-level executive has a job that almost exclusively involves making numerous business decisions. Sometimes they use crude tools such as gut feel or personal preference and sometimes they use highly sophisticated, probabilistic models involving multitudes of disparate variables. The sophistication of a model does not necessarily make it better than its lower level brethren.

Moving Average forecasts are still around for a reason – they work. In environments not prone to sudden, dramatic changes a moving average forecast holds a lot of appeal: it adjusts fairly quickly to new conditions and it is easy to understand/fix. It will never predict future market condition changes but that’s understood when it is implemented.

Sophisticated Monte Carlo simulations that account for internal and external pressures are more likely to predict future condition changes. The issue with using this style model is that it is dependent on the variables it makes decisions on. Forecaster bias is a significant risk with complex forecasts. Forecaster bias is the condition where the forecaster includes only the variable he/she believes will impact the outcome. There is no way to include every possible variable and someone has to make the selection.