How can inaccurate data hurt optimization efforts?

Garbage in produces garbage prices. Wrong inventory counts start discounts when shelves are empty. Mis‑tagged transactions distort elasticity curves and margins. Moreover, forecasting errors cascade: one bad demand spike fouls the model for weeks. You need to reduce risk by cleansing usage logs and reconciling financial, CRM, and web analytics feeds before the algorithms train. When you do so, decisions rest on verified numbers and you cut both revenue leakage and customer frustration. Even a one‑percent mismatch between billed and recorded usage can erase months of gains.