The first highlights the discrepencies in the number of local authorities offering cheaper bus fares to disadvantaged groups: people who are young and unemployed, compared with people who are disabled and older people.

The second diagram looks at bus use versus car use, and highlights the similarities between bus use in the young and the old, and the massive increase in car use (and decline in bus use) in mid-thirties and middle age.

No Smoking Day is a tricky prospect. It doesn’t have the freedom of other no smoking campaigns to berate and bully smokers into becoming non-smokers — quite the opposite. The mandate of No Smoking Day is to support smokers to quit — if and when they want to. So our online game had to be non-judgemental and non-scary, but still effective.

The results speak for themselves — we had 30,000 plays in two weeks.

The design process

I wanted the mechanism to be simple and intuitive. When the initial designs came back they involved intro and outro screens, multiple clicks to get where you wanted to be, in other words, distractions.

I did away with as much of that as possible. Keeping it clean, simple, and easy to use were the top priorities.

We had a very tight budget, and had to use the creative assets that had already been produced — we couldn’t afford to make any more.

I crowdsourced what people would want to spend their money on if they had any to spare, dividing them into four categories: technology, luxuries, holidays, and ticketed items and made them into the underlying database for the game.

We also wanted players to be able to grasp the amount of money they would save, so deciding the time scales for the game was important — the amount you might save in a day may not feel worth it, over 5 years may seem like an unattainable goal. So we display a range of options — from the small but achievable ‘what would happen if I gave up smoking for a week’ to the major accomplishment — and potential major savings of a whole year without smoking.

The other considerations were mostly technical — it had to work on all devices, of all sizes. And Absolutely No Flash. Our designers were stars at getting in all the necessary tweaks for the smallest screens and inconvenient interfaces.

What I learned

I learned that communicating what you want from a game mechanism — even one as simple as this — is a challenge.

We needed a certain level of randomisation to make the game interesting, and this took a while to achieve. We also wanted people to share their results, and figuring out the timing for when certain options display on screen took a fair amount of time. 

I think next time, I’ll ask for more face to face meetings. There’s only so far you can go with static mockups and telephone calls!

NHS Commissioning

How the NHS is monitored

I hope this comes in handy to patients, doctors, nurses, commissioners and whoever else is out there who wants to understand a bit more about what’s going on with the NHS, what commissioning and the various Commissioning Boards and groups mean, and a little bit of who looks after what.

Over the year I’ve been to three so-called ‘hack days’, one of which me and my team accidentally won (Hack the Government). The last of which my team just as accidentally lost didn’t win (Girl Geek Hack Day). The one in between however was the most intriguing, perhaps because it wasn’t a competition at all.

Held in Whitehall on a blustery Autumn day, it was run by a bunch of people called Datakind, and some sponsors who I’ve already forgotten the name of (sorry). Datakind used to be called Data Without Borders but changed their name a few years ago — I’m not sure why — and this was their first British event. They’d invited stats bods from around the country to come help some charities get the most out of their data, and I thought I’d see whether I could help, despite not being a stats bod.

You can read all about it in the Guardian. Pay special attention to the bits about the girl who arrived early and then left to go clubbing, because that was me… ahem.

My first, bleary eyed, work-fatigued impression was that they were Very Definitely American. They were so damn cheerful and sincere it was infectious. Even to a cynical and occasionally slightly suspicious Brit like me. At this point (inbetween pastries) I got talking to some people who actually knew about statistical analysis, and got a little downhearted — I had nothing like their expertise! I’m just some oddball information designer in need of a bit of practice.

I plumped for Place2Be as my project. They were all very worthy but this one had the most potential for impact that I saw — the data was all about treatments for kids with behavioural problems and our mission was to find out what worked, and what didn’t. There was a lot of Heavy Discussion about data cleansing and appropriate formats and software which was way beyond me, so I did some extremely rudimentary pivot tabling to see if I could generate some questions we might want to answer — and came up with what I thought were some intriguing curiosities. Did girls really do better in the programme if they had single dads? etc, etc.

Most of which turned out to be nonsense, because I simply don’t know enough about statistics. But I felt helpful. Sometimes.

In the end it turned out we had the Wrong Sort of Data anyway — which is much like the Wrong Sort of Snow and about as helpful, so our findings didn’t end up being spectacular or transformative.

But it piqued my curiousity, so now I’ve signed up for a Coursera data … erm… course. Lets hope it helps.

We’re used to the idea that most of the time, truth is black and white. But when scientists talk about their experiments, they’re using a scale of truth that uses many colours. Find out how that compares to what we usually think of as truth:

But as part of my dissertation I was looking at the different ways researchers have tried to affect the way people think about their health, and some very clear downsides to optimism came out.

The perils of optimism

In four separate studies of perception of health risk, researchers Weinstein and Klein found that in general, even if they were objective about health risks in general. the participants in their study were slightly too optimistic about their own health risks.

1. They used obesity and alcoholism as examples of conditions where people might be more optimistic than they should be about their health and habits. For their first study, they asked the people taking part to tell them how healthy their habits were — before and after reading about the major downsides of the condition.

Verdict: No noticeable change in their judgement of their risk.

2. The second experiment, unlike the typical health approach where people are asked to compare their behaviour against unfavourable examples of the same, those taking part in the study were asked questions based on ‘perfect’ behaviour – an imaginary person who exercised 4 times a week, or never got drunk.

Verdict: Far from encouraging better behaviour, this technique in fact increased optimism about current personal lifestyle choices.

3. In the third study, the people taking part were specifically asked to project a mental image of the worst or best case scenarios for these conditions, then combine them onto a single individual who was ‘like’ themselves. Study participants had the biggest problems when it came to visualising the best case scenario. They found it much easier to visualise the worst case.

Verdict: Once again, this resulted in more optimism about the participants’ personal behaviours.

4. In the final study, participants were asked to come up with their own list of activities that would raise or lower their risk of the conditions in question. Those asked to formulate risk-lowering activities became more optimistic about their current level of behaviour, and listing risk-increasing activities had no noticeable effect on their original slightly inflated optimism.

Verdict: Increased optimism, or no change.

So there you have it. Whether we’re visualising the perfect us, imagining the worst, or even constructing the steps that would help us be healthier, we either see ourselves in a favourable light, or what we’re doing has no effect on our motivation to get healthier.

Well, I’m depressed now!

The lovely Unicef responded, and while this isn’t strictly official so I can’t use their logos, these were both designed for their report into child poverty and child mortality.

A3 poster

Report spread

What do you think?

I present for your delectation the no doubt Slightly Inaccurate and Inclined Toward Hyperbole history of the British Government. Witness the interchangeability of early party loyalties, the bitter schisms, the fist-fights, the gradual drift to the centre, then the surprise left hook as Labour comes out of nearly nowhere.

Exciting stuff!

Handsome Atlas

I wanted to make a note of a conversation I keep having with people. Enough that I’m tempted to record my answer with a dictaphone and just play it at them when asked. It goes something like this:

“This new infographics trend is amazing. Such a great way to present information. They’re so engaging and tell great stories.”

Me: “Yes, they’re lovely things, aren’t they?”

Internal monologue: “New? New?! Graphics that show information have been around since the dawn of art. And don’t get me started on them being so engaging and such a great way to present information, because that depends entirely on your audience, their ability to process that information and the level of education required to interpret what you’re showing.”

Anyway, this mini-rant was prompted by the discovery of a website devoted to a 140 year old book almost entirely made of infographics:

Handsome Atlas: Beautiful Data Visualizations from the 19th Century.

via information aesthetics — Data Visualization & Information Design

Tasty AND informative

This is quite ridiculous, but more people should see it.

Visualisation by cookery!

Open Data Cooking: Data Visualization that You Can Eat

via information aesthetics — Data Visualization & Information Design