Choosing the right metric reveals the story behind the subway mess in NYC

I forgot who sent this chart to me - it may have been a Twitter follower. The person complained that the following chart exaggerated how much trouble the New York mass transit system (MTA) has been facing in 2017, because of the choice of the vertical axis limits.

This chart is vintage Excel, using Excel defaults. I find this style ugly and uninviting. But the chart does contain some good analysis. The analyst made two smart moves: the chart controls for month-to-month seasonality by plotting the data for the same month over successive years; and the designation "12 month averages" really means moving averages with a window size of 12 months - this has the effect of smoothing out the short-term fluctuations to reveal the longer-term trend.

The red line is very alarming as it depicts a sustained negative trend over the entire year of 2017, even though the actual decline is a small percentage.

If this chart showed up on a business dashboard, the CEO would have been extremely unhappy. Slow but steady declines are the most difficult trends to deal with because it cannot be explained by one-time impacts. Until the analytics department figures out what the underlying cause is, it's very difficult to curtail, and with each monthly report, the sense of despair grows.

Because the base number of passengers in the New York transit system is so high, using percentages to think about the shift in volume underplays the message. It's better to use actual millions of passengers lost. That's what I did in my version of this chart:

The quantity depicted is the unexpected loss of revenue passengers, measured against a forecast. The forecast I used is the average of the past two years' passenger counts. Above the zero line means out-performing the forecast but of course, in this case, since October 2016, the performance has dipped ever farther below the forecast. By April, 2017, the gap has widened to over 5 million passengers. That's a lot of lost customers and lost revenues, regardless of percent!

The biggest headache is to investigate what is the cause of this decline. Most likely, it is a combination of factors.

Comments

[E.]

I honestly think your version is - for certain purposes - a "Verschlimmbesserung" of the original, depending on what message should be transported.

While more attractive to look at, the visual effect is not as alarming as in the original. While the original chart reveals the way you end up with a conclusion, the second one only shows the result - leaving out the visual comparison to the previous years by treating them as the 0.

However, I like the message in the title, strongly supported by the absolute scale.

[YV]

Re metrics on the NYc subway, there are more in last week's long piece on the MTA's declining performance in the NYT
https://www.nytimes.com/2017/11/18/nyregion/new-york-subway-system-failure-delays.html

A few graphcs have a lot of information and are still succinct, graphically. The decreasing on-time performance of each line is helpful.

Other ones that combine multiple graphs together are somewhat confusing.
https://static01.nyt.com/newsgraphics/2017/11/09/subway-graphics/04e5ba5039db249b6a3c396c7662baf83e5fe48c/ridership_v_maintenance-720.png