Forecasting a single number is dangerous. GPR is a "non-parametric" Bayesian approach that provides a probability distribution for every prediction, giving you a measure of "cluelessness" where data is scarce.
"Where is our forecast least reliable?"
"What is the confidence range for next month?"
"Does the data support this prediction?"
It assumes that similar inputs produce similar outputs. It defines a "prior" over functions and updates that distribution as it sees data points.
The Problem
Over-confident excel projections.
What It Reveals
Widening uncertainty bands as you project further out.
Decision Enabled
Plan contingencies for the variance.
Adds rigor to our Forecasting Module, ensuring we don't present guesses as facts.
A forecast plot where the shaded region (Uncertainty) balloons where data is missing, visually warning you of risk.