Prediction is the art of taking information about the past and applying it to future circumstances to understand what is likely to happen. It is premised on the fact that the future will follow the same or similar rules as the past. Behavior is expected to remain largely consistent over time.
For many applications this works really well. Purchasing and retail wouldn’t work well at all without prediction forecasting. Population changes by geography are largely predictable.
But often knowledge of the past changes the future. Knowing that they are losing the youth population to larger cities a smaller community may undertake initiatives to retain or attract population by offering incentives for businesses to locate there. Or knowing competitor trends a company revises their business strategy to attract new customers. The past changes the future in unpredictable ways.
The future also can vary from predictions because new information becomes available. Who could have predicted the impact of the iPhone in 2005 before it was released? It completely changed the course of several industries within 3 years let alone a full decade.
Predictions using data (especially the buzzwordy “Big Data”) sometimes feel like they are more certain than qualitative predictions. This is often untrue. No data set can completely encapsulate a scenario or situation regardless of how large or unique the data set is.
Risk and the new. Those may not be the centerpiece of prediction but they sure better be included if the prediction is going to have any worth at all.