Le Club Case Study

Le Club has a problem with aligning their forecasts with consumer demands. They must work hard to determine the correct forecast for demand of each bottle of wine and place orders with the suppliers, while maximizing their profits. Previously, Le Club has had mismatches between forecasts and actual demand, such as in 2004-as you can see by the numerous outliers (Exhibit 1). Stephane Zanella needs to lessen or minimize the differences between the predicted forecast and actual order quantity for each bottle of wine ordered as related to the consumer demand in years past.

Both the empirical and normal distributions were calculated to determine which would be the best model to use to maximize order quantity. The empirical distribution is helpful because it shows/reflects the historical forecasting capability. It does, however, have many shortcomings. First of all, it only predicts a limited amount of possible outcomes-this is because it is a discrete distribution. Also, the historical data is limited to only the wines from the 2004 catalog, which is only 45 items, thus adding to the limitations of possible outcomes. Each A/F ratio was calculated in relation to the critical ratio for each wine and the percentile ranking. These A/F ratios were then applied to the forecast quantity and the profit maximizing order quantity was determined. In my opinion, in order for the empirical model to be the most useful, there would have to be more items to include and analyze.

I also used the normal distribution model to determine profit maximizing order quantities. The upside of this model is that there are more possible outcomes and less variation between actual and forecasted demand. I calculated the mean and standard deviation of each wine's historical demand and then applied those to the forecast of each wine to obtain the expected actual demand. I also calculated the z-value and then the profit maximizing order quantity for each wine. I used the normal distribution of the percentile CDF and possibility of a normal CDF and found that the normal distribution is quite normal and a very good fit (see Exhibit 2).

It is my opinion that Le Club use the profit maximizing order quantities obtained from the normal distribution. These numbers are more accurate because the normal distribution model provides a greater number of possible outcomes.

The normal distribution model leads to a much smaller variation between forecasting and actual demand. Therefore, costs (overage, shipping costs) can all be decreased or saved on if Le Club does not overstock merchandise. Also, they will be better able to match the demands of the customers if they actually order enough of each wine. This will lead to increased sales and profits. In addition, customer satisfaction will increase greatly if Le Club is able to have the appropriate amount of each wine available.

A performance metric