Super Bowl Logistics Planning: Lessons from a Supply Chain Consultant

My friend and I entered Penn Station a little after 2:30pm, ready for a quick, 25 minute ride to East Rutherford.

We got tickets last minute for the Super Bowl and wanted as much of the game day experience as possible.

However, our planned short commute turned into an over two hour ordeal of crowded trains, overwhelmed lines, and less walking than waiting. We finally got into the secure stadium grounds at 5pm.

After the game ended, we had another hour of lines and disorganized transit back to Manhattan as described in this article. I asked myself repeatedly…with years of planning, what mistakes were made along the way?

Working in supply chain optimization led me to the first cause: faulty assumptions can break any system. Holding a football game for a sell-out crowd at MetLife Stadium is not an uncommon occurrence. Sixteen times a year fans of the Jets & Giants use cars, trains and even cabs to get to the game.

From this experience assumptions were made about current state usage, and extrapolated outwards. However, the Super Bowl organizers fundamentally changed the nature of the system in two ways. First, cabs and other “drop offs” were banned. It was assumed that drivers would just park at distant lots. However, tailgating was also not allowed. Many people heard of these issues and left extra early for the stadium, making problems worse as crowds were earlier than expected.

A corollary to the previous point: Don’t estimate one number, rather plan for a range of outcomes. It has been mentioned that the planners thought 16,000 people would ride public transit to the game. The actual turnout was twice as much, and came much earlier. Using a model to predict how a system – or a supply chain – reacts to demand surges solidifies planning for a range of outcomes. Once it was clear that estimates were off, there were only hasty reactions to the waves of attendees in both the transfer station and at stadium security lines.

Related: The Logistics of Putting on the Super Bowl

A simulation model could have exposed bottlenecks and pain points. Reporting on the transit issues at the Super Bowl cited only estimated crowds and throughputs. Even at current volumes, the staffing seemed to be insufficient. We took too much direction from higher ups in nice clothes pointing which way to go. The exiting train had a line sufficient for a couple hundred people, and really no “start”. Once you have built a system simulation one can easily run “worst case scenarios” and plan for pain points.

Much was made about securing the Super Bowl, and rightfully so. Plan for a range of risks, not just one or two. From my perspective, the risk management policies at the Super Bowl focused overwhelmingly on anti-terrorism on the stadium perimeter (airport level security, military presence) and keeping them safe within the stadium (staying warm courtesy Super Bowl schwag). 

However, the risks actualized were safety in transit (multiple collapses in the overcrowded transit system) and an imposter in the post-game conference. The imposter bypassed security by saying that he was running late and flashing a credential. When a team outlined all the process and failure points for all aspects of the event, the team did not plan for these types of events. Quantifying probability and impact is difficult, but is a necessary step for detailed mitigation and implementation plans.

The overall impact was hours wasted in lines when fans could have been enjoying the festive atmosphere and purchasing products. The detailed planning effort approach should have relied on scenario analysis using modeling.

Planning for a range of possibilities, and testing your assumptions, leads to better outcomes for all.