Question

When making decisions business people are searching for accurate data to base their models on. However, sometimes implicit and explicit biases can affect not only what data sources are selected but also how that data is interpreted.

Think of a business example of how a bias created a poor analysis, decision or outcome.

How could this have been avoided?

Answer 1

A very common example is Grocery Business. In grocery business the forecasting is really difficult, even with past 2 years historical data because consumer's consumption pattern is highly volatile, Lots of wastage, improper time and quantity of delivery. Due to all these factors the forecasted data and actual order has a huge bias, leading to either loss of business or higher cost per unit of material sold.

To avoid this the organziation has to invest some good amount of initial capital in order to set up a system that is well integrated vertically from vendors to logistics and also acts as per demand sensing.