Question 1
Why is beer flavor important to Coors' profitability?
People are ready to accept and try new flavors. The companies are in high competition to make new flavors to fulfil the customer needs and satisfaction. Most of the companies are making new flavors considering the customer trend and taste. Drinker’s choice depends on various factors, including mood, venue and occasion. Coors goal is to ensure that the customer select the Coors brand no matter what the circumstances. To be the customer’s choice brand, Coors needs to be creative and anticipate customer changing moods. There are different flavors and each have a particular flavor and these are detected through a panel tests. As this test take time, to achieve the customer satisfaction Coors have to understand the beer flavor based chemical composition. This may help to satisfy the customer taste and may help to increase the profitability of the firm. The people are ready to accept the new products in the market if it is reasonable and affordable price with the quality.

Question 2
What is the objective of the neural network used at Coors?
Neural networks was used to create a link between chemical composition and sensory analysis. The neural network was designed to understand the relationship between the input and output. The neural network consists of a MLP architecture with two hidden layers. Data were normalized within the network and enabling comparison between the results for the various sensory outputs.

Question 3
Why were the results of Coors' neural network initially poor, and what was done to improve the results?
The results were poor because of two factors. The first reason was concentrated on a single products quality meant that the variation in the data was low. This couldn’t help the neural network to extract useful relationships from the data. Second was subsets of provided input