Sunday, October 26, 2014

Holiday Forecasting at UPS & FedEx

As the holiday season approaches, organizations like UPS and FedEx are scrambling to prepare for their peak season.  I found two very interesting articles from last holiday season that explain how these companies forecast and prepare for the season and how they made some serious forecasting errors last year.  Since this week’s classes will focus on forecasting, I thought that these articles would add to our discussion and understanding of the topic.

The first article, “UPS's Holiday Shipping Master: They Call Him Mr. Peak,” described UPS’s preparation for their peak season.   Interestingly, UPS forecasted that it would carry 3.6 million boxes last December 23rd alone.  Scott Abell, who focuses on one to three day deliveries at UPS, begins to plan for UPS’s holiday rush in January. The article discusses the forecasting process, which involves numerous revisions throughout the year that continue all the way into December.  Abell mentions a number of things that impact forecasting, which include: Internet shopping (that often happens last minute), the number of shopping days between Thanksgiving and Christmas, winter storms (especially ice which causes problems for trucks and increases online shopping), and demand from 25 or more retailers.  Accurate forecasting is essential because it dictates how many extra employees the company will hire and what equipment and supplies the company will need to purchase.  However, forecasting is not always accurate, so UPS has a contingency team on staff to deal with issues that arise from inaccurate forecasts.

Below is a graph that shows peak season shipping data for both UPS and FedEx.  This type of data indicates holiday trends and would be a part of UPS’s forecast.

The second article, “UPS Holiday Season Fiasco: A Failure of Strategic Planning,” explained that both UPS and FedEx made errors when forecasting holiday demand last year, and this caused the companies to fail to meet some of their delivery promises.  The article explains that many customers did not receive their holiday packages before December 25th, and the author attributes this to planning failures that relate to automated sorting systems as opposed to manual facilities.  In automated systems, once demand is underestimated, it is often too late to make any substantial corrections, which would require leasing planes and installing additional sorting equipment.  The author brings up a dilemma that UPS and FedEx must deal with – how can they deal with the holiday rush without destroying their budgets?  The rush requires additional expenditures on equipment and employees, and those costs need to be made up through shipping prices.  However, if either company raises shipping prices, they risk losing business to the other company.

I thought these articles were particularly interesting because they came out just two weeks apart.  The first article almost praised UPS for their forecasting methods, and the second explained that their forecasts were seriously flawed.  What I take away from this is that forecasting is complex and extremely hard to get right. 


1.  Given the costs associated with overestimating customer demand, does it make sense to make conservative estimates and risk upsetting customers?

2.  Can you think of other factors that would affect forecasting for the peak season (for UPS and FedEx)?

3.  Do you think customers would be upset if the shipping companies raised prices during the peak season to cover their extra costs?  Would it be better to raise prices throughout the year to cover the costs?  How do you think price increases would affect the shipping industry during the peak season?


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