DAO Web Page of Fame

Celebrating Summer Successes Since 2006

  INDUCTEE:  Christopher Richins

YEAR:   2008

CATEGORY: Regression

 


When Christopher Richins heard what his work stream would be during his internship with Bain & Company, he knew that taking DAO had been a good choice. 

Christopher was asked to develop a pricing strategy for a new business based on a model that would predict refrigerated produce truck rates from the Western U.S. to the Eastern U.S.  

To begin, Christopher quickly found a source of historical weekly refrigerated truck rates and U.S. average diesel prices for the last 4 years and got to the task of building a regression model. He was able to quickly run a regression of truck rates with respect to diesel prices. The results were surprising fuel price alone resulted in an adjusted R^2 of only 44%, much lower than he anticipated. After analyzing the residuals, he found that there was a cyclical pattern in the results. It was clear that in addition to the influence of fuel prices, there was a seasonal component to truck rates. 

Considering the nature of the product being shipped (fresh produce), it came as no surprise that there would be a seasonal component to the price. In order to capture the seasonal component of the truck rates, he generated a dummy variable for each of the 52 weeks of the year, and reran the regression with diesel price in the mix. 

The results of the improved regression were surprising. The R^2 of the model increased to over 94%, and the residuals looked normal. This had significant implications for the pricing model Christopher was developing. From the low point in March, he found that truck rates in June could be as much as $2000 dollars higher just because of the seasonal nature of demand (an increase of 50%).  

As a result of his regression analysis, the pricing model for this new business includes inputs for the current diesel price, and the week of the year to accurately model produce truck rates from the Western U.S. to the Eastern U.S. This model  will enable the client to accurately price their substitute offering and maximize the economic value of their service. Further, because of the excellent data analysis skills he had acquired in DAO, Christopher was able to complete the pricing task in 40% of the time predicted for the project.