How long is a Dublin minute? Adventures in waiting around, with ‘real-time’ bus predictions

It definitely said five minutes. Passengers awaiting a bus in Dublin, 2010. Image: Getty.

It’s one of the little quirks of our postmodern wonderland that slight imperfections in a quasi-utopian service are complained about far more than the absence of the same thing: you’d rather no WiFi than slow WiFi, that kind of thing.

In a similar vein, until quite recently all the humble bus user had to go on when waiting on their chariot were timetables and some educated guesswork. How quaint it must have felt. In the last few years, though, the development of various breeds of real-time software means you can see your bus’s ETA down to the minute, via apps and on-street displays.

That’s the idea, anyway.

Dublin’s version of this, the Real Time Passenger Information system (RTPI), was launched in 2011, supplying travel information to a network responsible for 128m passenger journeys in 2016. And it has a bit of a reputation.

Every commuter has a story about buses supposedly coming closer before receding into the distance, or showing up on the displays, only to vanish entirely. “That thing’s been saying ‘6 minutes’ for a quarter hour now” sits alongside “shite weather, isn’t it?” in the annals of Irish small-talk. Different countries have their own version of the same popular discontent - some a little better, some a little worse.

Basically, RTPI works by inserting a GPS signal into a bus and working out how far it is from each subsequent stop along the route. Jeremy Ryan, head of public transport contracts with Ireland’s National Transport Authority, says that the system is fed with regularly-updated ‘profiles’ of how long a bus should take to get from stop to stop, with different profiles for different days and times. These profiles are aware of normal traffic and pre-planned roadworks, but can’t know about ad-hoc things like heavy rain or emergencies, which leaves the predictions a little sticky.

The NTA carries out quarterly surveys to assess the system’s accuracy. According to this research, about 97 per cent of Dublin buses arrive within three minutes of the scheduled time, which the NTA and Dublin Bus say is “well above industry norms”. Reassuringly for people convinced that their own area is cursed with malevolent software, there apparently aren’t significant variations between routes, directions, or times of day.

Approaching these assertions with the swivelled eye of healthy scepticism, I decided to engage in a bit of citizen’s quality assessment. I walked to some strategically-placed bus stops around central Dublin, waited for a bus’s expected arrival time to tick over to “5 minutes”, and measured how long it took to roll up beside me.

Not having all day, I limited myself to clusters in Phibsboro and Rathmines, 2-3km north and south of the city centre respectively, and to the city centre itself from O’Connell Street to South Great George’s Street.

And what do we find? Well, probably unsurprisingly, on the whole the RTPI system does indeed appear to be remarkably accurate. Averaged across 62 buses, the average time it took for one to arrive after the ticker moved to “5 minutes” was a lean 5:58. Bearing in mind that nowhere is it claimed that “5 minutes” should be taken to mean 5:00 exactly, keeping the average error down to less than 20 per cent is not too shabby a performance.

This makes all kinds of sense. A system with much more of an inbuilt error would be nigh-pointless to continue using from a passenger’s perspective. And it’s easy to see how a system with even a 3 per cent error would develop a negative reputation, considering how many people it stands to annoy every time there’s a slip-up.


That said, at different points of my experiment, “5 minutes” could have meant either 2:32 or 11:21. If you arrived at a stop proclaiming “5 minutes” on a given day last week, it seems there was about a 1 in 4 chance of the bus being more than 2 minutes early or late. Insofar as there was any variation between areas, buses heading into the city centre from the south side averaged 6:41, though there were hardly enough trials here to be statistically significant.

In sum however, we’d probably be advised to give the software some credit. For all I know, it may well have a conception of time divorced entirely from our idea of reality – but for the most part, when RTPI tells you your bus is 5 minutes away, it’s not exactly lying to you.

 
 
 
 

“Stop worrying about hairdressers”: The UK government has misdiagnosed its productivity problem

We’re going as fast as we can, here. Image: Getty.

Gonna level with you here, I have mixed feelings about this one. On the one hand, I’m a huge fan of schadenfreude, so learning that it the government has messed up in a previously unsuspected way gives me this sort of warm glow inside. On the other hand, the way it’s been screwing up is probably making the country poorer, and exacerbating the north south divide. So, mixed reviews really.

Here’s the story. This week the Centre for Cities (CfC) published a major report on Britain’s productivity problem. For the last 200 years, ever since the industrial revolution, this country has got steadily richer. Since the financial crash, though, that seems to have stopped.

The standard narrative on this has it that the problem lies in the ‘long tail’ of unproductive businesses – that is, those that produce less value per hour. Get those guys humming, the thinking goes, and the productivity problem is sorted.

But the CfC’s new report says that this is exactly wrong. The wrong tail: Why Britain’s ‘long tail’ is not the cause of its productivity problems (excellent pun, there) delves into the data on productivity in different types of businesses and different cities, to demonstrate two big points.

The first is that the long tail is the wrong place to look for productivity gains. Many low productivity businesses are low productivity for a reason:

The ability of manufacturing to automate certain processes, or the development of ever more sophisticated computer software in information and communications have greatly increased the output that a worker produces in these industries. But while a fitness instructor may use a smartphone today in place of a ghetto blaster in 1990, he or she can still only instruct one class at a time. And a waiter or waitress can only serve so many tables. Of course, improvements such as the introduction of handheld electronic devices allow orders to be sent to the kitchen more efficiently, will bring benefits, but this improvements won’t radically increase the output of the waiter.

I’d add to that: there is only so fast that people want to eat. There’s a physical limit on the number of diners any restaurant can actually feed.

At any rate, the result of this is that it’s stupid to expect local service businesses to make step changes in productivity. If we actually want to improve productivity we should focus on those which are exporting services to a bigger market.  There are fewer of these, but the potential gains are much bigger. Here’s a chart:

The y-axis reflects number of businesses at different productivities, shown on the x-axis. So bigger numbers on the left are bad; bigger numbers on the right are good. 

The question of which exporting businesses are struggling to expand productivity is what leads to the report’s second insight:

Specifically it is the underperformance of exporting businesses in cities outside of the Greater South East that causes not only divergences across the country in wages and standards of living, but also hampers national productivity. These cities in particular should be of greatest concern to policy makers attempting to improve UK productivity overall.

In other words, it turned out, again, to the north-south divide that did it. I’m shocked. Are you shocked? This is my shocked face.

The best way to demonstrate this shocking insight is with some more graphs. This first one shows the distribution of productivity in local services business in four different types of place: cities in the south east (GSE) in light green, cities in the rest of the country (RoGB) in dark green, non-urban areas in the south east in purple, non-urban areas everywhere else in turquoise.

The four lines are fairly consistent. The light green, representing south eastern cities has a lower peak on the left, meaning slightly fewer low productivity businesses, but is slightly higher on the right, meaning slightly more high productivity businesses. In other words, local services businesses in the south eastern cities are more productive than those elsewhere – but the gap is pretty narrow. 

Now check out the same graph for exporting businesses:

The differences are much more pronounced. Areas outside those south eastern cities have many more lower productivity businesses (the peaks on the left) and significantly fewer high productivity ones (the lower numbers on the right).

In fact, outside the south east, cities are actually less productive than non-urban areas. This is really not what you’d expect to see, and no a good sign for the health of the economy:

The report also uses a few specific examples to illustrate this point. Compare Reading, one of Britain’s richest medium sized cities, with Hull, one of its poorest:

Or, looking to bigger cities, here’s Bristol and Sheffield:

In both cases, the poorer northern cities are clearly lacking in high-value exporting businesses. This is a problem because these don’t just provide well-paying jobs now: they’re also the ones that have the potential to make productivity gains that can lead to even better jobs. The report concludes:

This is a major cause for concern for the national economy – the underperformance of these cities goes a long way to explain both why the rest of Britain lags behind the Greater South East and why it performs poorly on a

European level. To illustrate the impact, if all cities were as productive as those in the Greater South East, the British economy would be 15 per cent more productive and £225bn larger. This is equivalent to Britain being home to four extra city economies the size of Birmingham.

In other words, the lesson here is: stop worrying about the productivity of hairdressers. Start worrying about the productivity of Hull.


You can read the Centre for Cities’ full report here.

Jonn Elledge is the editor of CityMetric. He is on Twitter as @jonnelledge and on Facebook as JonnElledgeWrites

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