Forecasting Vs. Predictive Analytics
The purpose of forecasting or prediction is to take an informed decision today based on the past historical information that we have.
Most often, I think what can be the differences between forecasting and prediction or predictive analytics. Are you too confused? Please read on…
Apart from being the buzzwords among the business people, are there any differences in their definitions, usage? Based on what I explored by going through few articles on the web, these are my findings:
- Forecasting is a generic term used by professionals across various disciplines. It applies at the high-level. For ex: What could be the total sales for a particular product line in next quarter? It uses time series data. Another classic example could be weather forecasting for next week. It involves time as a dependent variable.
- Predictive analytics is a term hugely became popular in the analytics space. It can be done at a much granular level: For ex: A credit card company would be interested to predict – Which customers might default during the New Year festival session? Notwithstanding that, predictive analytics helps us in understanding the relationship between variables using regression method.
Another interesting perspective on the difference which I read is as follows:
Forecasting is all about numbers – Again, the total sales example which I pointed above. Prediction is more on the behavior – In Amazon website, you must have seen the recommendation engine. Although it involves more of Machine Learning concepts (which improves/learns by itself), it recommends, say, the books based on what I had earlier purchased on the same website. The latter categorizes based on what genre, author I would be interested to read. In fact, I discovered some amazing books thanks to Amazon’s intelligent recommendation engine!
What’s your take on Forecasting vs. Predictive Analytics?
