The Cappuccino Congestion Index

April First falls on Saturday, and that’s a good reason to revisit an old favorite, the Cappuccino Congestion Index

We’re continuing told that congestion is a grievous threat to urban well-being. It’s annoying to queue up for anything, but traffic congestion has spawned a cottage industry of ginning up reports that transform our annoyance with waiting in lines into an imagined economic calamity. Using the same logic and methodology that underpins these traffic studies, its possible to demonstrate another insidious threat to the nation’s economic productivity: costly and growing coffee congestion.

cappuccino_line

Yes, there’s another black fluid that’s even more important than oil to the functioning of the U.S. economy: coffee. Because an estimated 100 million of us American workers can’t begin a productive work day without an early morning jolt of caffeine, and because one-third of these coffee drinkers regularly consume espresso drinks, lattes and cappuccinos, there is significant and growing congestion in coffee lines around the country. That’s costing us a lot of money. Consider these facts:

  • Delays waiting in line at the coffee shop for your daily latte, cappuccino or mocha cost U.S. consumers $4 billion every year in lost time;
  • The typical coffee drinker loses more time waiting in line at Starbucks than in traffic congestion;
  • Delays in getting your coffee are likely to increase because our coffee delivery infrastructure isn’t increasing as fast as coffee consumption.

Access to caffeine is provided by the nation’s growing corps of baristas and coffee bars. The largest of these, Starbucks, operates some 12,000 locations in the U.S. alone. Any delay in getting this vital beverage is going to impact a worker’s start time–and perhaps their day’s productivity. It’s true that sometimes, you can walk right up and get the triple espresso you need. Other times, however, you have to wait behind a phalanx ordering double, no-whip mochas with a pump of three different syrups, or an orange-mocha frappuccino. These delays in the coffee line are costly.

To figure out exactly how costly, we’ve applied the “travel time index” created by the Texas Transportation Institute to measure the economic impact of this delay on American coffee drinkers. For more than three decades TTI has used this index to calculate the dollar cost of traffic delays–here we use the same technique to figure the value of “coffee delays.”

The travel time index is the difference in time required for a rush hour commute compared to the same trip in non-congested conditions. According to Inrix, the travel tracking firm, the travel time index for the United States in July 2014  was 7.6, meaning that a commute trip that took 20 minutes in off-peak times would take an additional 91 seconds at the peak hour.

We constructed data on the relationship between customer volume and average service times for a series of Portland area coffee shops.  We used the 95th percentile time of 15 seconds as our estimate of “free flow” ordering conditions—how long it takes to enter the shop and place an order.  In our data-gathering, as the shop became more crowded, customers had to queue up. The time to place orders rose from an average of 30 to 40 seconds, to two to three minutes in “congested” conditions. The following chart shows our estimate of the relationship between customer volume and average wait times.

Coffee_Speed_Volume

Following the TTI methodology, we treat any additional time that customers have to spend waiting to place their order beyond what would be required in free flow times (i.e. more than 15 seconds) as delay attributable to coffee congestion.

Based on our observations and of typical coffee shops and other data, we were able to estimate the approximate flow of customers over the course of a day. We regard a typical coffee shop as one that has about 650 transactions daily. While most transactions are for a single consumer, some are for two or more consumers, so we use a consumer per transaction factor of 1.2. This means the typical coffee shop provides beverages (and other items) for about 750 consumers. We estimate the distribution of customers per hour over the course of the day based on overall patterns of hourly traffic, with the busiest times in the morning, and volume tapering off in the afternoon.

We then apply our speed/volume relationship (chart above) to our estimates of hourly volume to estimate the amount of delay experienced by customers in each hour.  When you scale these estimates up to reflect the millions of Americans waiting in line for their needed caffeine each day, the total value of time lost to cappuccino congestion costs consumers more than $4 billion annually. (Math below).


 

This is—of course—our April First commentary, and savvy readers will recognize it is tongue in cheek, but only partly so.  (The data are real, by the way!) The real April Fools Joke here is the application of this same tortured thinking to a description and a diagnosis of the nation’s traffic problems.

The Texas Transportation Institute’s  best estimate is that travel delays cost the average American between one and two minutes on their typical commute trip. While its possible–as we’ve done here–to apply a wage rate to that time and multiply by the total number of Americans to get an impressively large total, its not clear that the few odd minutes here and there have real value. This is why for years, we and others have debunked the TTI report. (The clumping of reported average commute times in the American Community Survey around values ending in “0” and “5” shows Americans don’t have that precise a sense of their average travel time anyhow.)

The “billions and billions” argument used by TTI to describe the cost of traffic congestion is a rhetorical device to generate alarm. The trouble is, when applied to transportation planning it leads to some misleading conclusions. Advocates argue regularly that the “costs of congestion” justify spending added billions in scarce public resources on expanding highways, supposedly to reduce time lost to congestion. There’s just no evidence this works–induced demand from new capacity causes traffic to expand and travel times to continue to lag:  Los Angeles just spent a whopping billion dollars to widen Interstate 405, with no measurable impact on congestion or traffic delays.

No one would expect to Starbucks to build enough locations—and hire enough baristas—so that everyone could enjoy the 15 second order times that you can experience when there’s a lull. Consumers are smart enough to understand that if you want a coffee the same time as everyone else, you’re probably going to have to queue up for a few minutes.

But strangely, when it comes to highways, we don’t recognize the trivially small scale of the expected time savings (a minute or two per person) and we don’t consider a kind of careful cost-benefit analysis that would tell us that very few transportation projects actually generate the kinds of sustained travel time savings that would make them economically worthwhile.

Ponder that as you wait in line for your cappuccino.  We’ll be just ahead of you ordering a double-espresso macchiato (and holding a stopwatch).


Want to know more?

Here’s the math:  We estimate that a peak times (around 10am) the typical Starbucks makes about 100 transactions, representing about 120 customers.  The average wait time is about two and one-half minutes–of which about two minutes and 15 second represents delay, compared to free flow conditions.  We make a similar computation for each hour of the day (customers are fewer and delays shorter at other hours).  Collectively customers at an typical store experience about 21 person hours of delay per day (that’s an average of a little over 90 seconds per customer).  We monetize the value of this delay at $15 per hour, and multiply it by 365 days and 12,000 Starbucks stores.  Since Starbucks represents about 35 percent of all coffee shops in the US, we scale this up to get a total value of time lost to coffee service delays of slightly more than $4 billion.