The Curious Case of the York Street Median — Part III
In this instalment, I’m going to tell you about how spending a little time crafting the data you worked so hard to collect can go a long way to ensuring that your message is heard.
But first, a little rant about the importance of well-crafted graphs.
Having data is half the battle. Now, it must be paired with a story to allow us to get our point across.
Think of data storytelling like a food publication. Sure, you can publish a magazine filled with written descriptions of amazing culinary spreads, but shouldn’t we be able to see it? Alternatively, a food mag with only pictures and no description of the ingredients or the chef’s inspiration takes away half of the story. Words and images go together like peanut butter and jelly. For the most immersive experience, it’s best that the image compliments the words just as much as the words compliment the image.
This seems to get thrown right out the window as soon as graphs and charts are brought up. Why are graphs treated so poorly if they’re exactly that, an image? I’ll be taking some tips from a data crusader Cole Nussbaumer Knaflic who’s book Storytelling with Data is a must-read for anyone who cringes at the sight of a pie-chart.
Take the following graph as an example. Sure it’s overkill, but just try to think about what story its creator was trying to tell us.
I have no idea.
That graph is the storytelling equivalent of that person you know who’s really terrible at telling a good story but insists on telling you about that one time they did that thing with those people at that place, or was it at that other place? Did they mention the other character that has no part being in the story but was described to you in great detail for far too long? Half-baked thoughts, scattered ideas, and a non-sensical time scale.
Graphs are supposed to make sense of complicated data, not make it more confusing. They should also be quick to digest and the reader should be able to recall your point.
It’s up to you as the storyteller and graph user to ensure that you’re highlighting the points of interest that you want to convey with maximum visibility and clarity.
We will now return to our regularly scheduled program.
Imagine now that an automatic radar traffic counter has been installed on Kings College Road for a week. All the data points are neatly organized in a long spreadsheet and ready to confront anyone who wants to challenge the data. The easiest way to present it would be in its raw form.
But there’s a problem.
Most people don’t think in spreadsheets.
So in order to tell them about your data, you need to put it in a graphical form. Here’s where things get fun.
In order to effectively deliver a message, the images you use to accompany your voice should be complimentary. If you’re trying to get a point across by speaking LOUDLY, then your image should be smaller to ensure that people are listening to you and not distracted by your images. The opposite is true if you’ve got extremely powerful imagery that speaks for itself. At that point, take a step back and let the sheer power of the numbers speak for you.
For this technique to work, you must respect the graph and design it in such a way that it follows the narrative that you have created. It should be easy enough for people to understand that they can glance at it and know what it means.
Let’s go through a couple points of interest using made up data to show how we can tell the York Street story with numbers.
Let’s start with a simple bar graph showing how many vehicles drove by the automatic counter by the hour of day. We will be using a 24 hour clock for these graphs, meaning that zero is midnight, 23 is 11PM.
The first thing that can be noticed about this graph is that there are spikes throughout the day where the count is higher.
To make a point of these interesting data points, let’s highlight them.
Add a short description with visual cues to really hit home your point and remove unnecessary gridlines. Remember, the point of this graph is to show that there are differences in traffic peaks throughout the day, not to show exactly how many cars there actually are.
Et voila! A clean, concise, and visually appealing graph that tells a story and nothing more.
We can now visibly see that the times of peak traffic are during the morning commute (07:00–09:00), lunch time (12:00–14:00), and again on the commute back home (17:00–19:00). While this may not be ground breaking stuff, now we have both the theory AND the proof.
All of a sudden the wild claims of their being a dangerous amount of traffic at noon can be seen. Residents know that, but now they can see that they know what they thought they knew, you know?
The posted speed limit on Kings College Road is 50 km/h, but according to some local residents it may as well be the Autobahn.
How fast are vehicles actually travelling along Kings College?
Not too bad. So why the complaints? Averages can be deceiving. What happens when we add the outliers?
Now we can see that while the average speed isn’t far off from the speed limit, some people are going way too quickly.
With these two graphs, we can now craft our accompanying problem statement:
Our solution must maintain traffic flow during peak hours, while reducing excessive speeding.
Now that we know the areas where the highest likelihood of speeding occur, and how much traffic is passing through on a daily basis, we can find a solution that matches the requirements to keep traffic flowing while deterring excessive speeding.
A limitation that we will need to keep in mind is that we have snow for what feels like the majority of the year, so our solution must allow snowplows and emergency vehicles to be able to pass without restrictions.
Here are a few of many solutions that are possible:
- Narrowing traffic lanes and widening sidewalks — By giving motorists a smaller amount of room to drive, they will need to reduce their speeds.
- Chicanes — A fun new word to add to your vocabulary and to your roads! These indentations require motorists to follow the slowly winding paths, all while making new spaces for roadside trees or benches.
- Rumble strips — Surface treatments to the road can give auditory and physical sensation to the driver, possibly waking them from their zombie-like trans as they make their way to work in the morning. Applications can be made to resemble brick, adding to the residential aesthetic.
These cost-sensitive solutions can reduce speeding along residential streets, while still allowing for smooth traffic flow throughout the day. They can also be combined in areas of high importance to maximize their traffic calming effects.
By using data to ensure that the problem is correctly identified, we can then work together to find a solution that fits within the constraints. I am not pretending to be a traffic engineer or a city planner, but I am a citizen who finds these kinds of issues interesting.
By opening up the conversation to new perspectives, solutions could be found that may have never been thought of before.
Thanks for following along on this three-part tangent about a fairly unknown topic. The reason that I am putting so much emphasis on this particular situation is because it shows that even hyper-localized civic issues have data breadcrumbs that can lead us to finding a solution that fits just right. No longer are we limited to finding solutions to problems based on gut-feelings and instincts. We now have tools that will continue to change the way we think and solve problems, no matter how small or specific they may be.
There are processes within city planning and by-law modifications to ensure that the required due-diligence is completed before a decision is made. While these meetings and readings are essential, they too can be improved upon so that data can be baked right into the decision making process. This will free up time and resources so that public officials can spend more time fostering civic engagement, rather than sitting through meeting after meeting.
At The Go Do Project we believe that the authenticity that data carries paired with human-centric values allows us to create stories worth spreading.