Seth Godin just gave a riveting talk at the Global Health and Innovation Conference. You may have read some of his books, like Purple Cow and Tribes. Inspired by his talk, I applied some of Seth's key points to innovation in communicating health data. If you have data that you want used more broadly, here are some basic thoughts to guide you:
Target specific audiences first. A data product cannot appeal to all audiences at once. There is a shrinking "middle of the market" as people get used to having their specific information needs addressed by tailored products. So start with presenting your data in ways that appeal to those small audiences that are most likely to embrace and use your data.
Make it easy to talk about your data. People have to be able to discuss your data easily to be able to talk about and recommend them to others. It is important to give potential users a sense that "people like me use these data". Ultimately, word of mouth will lead to broader adoption.
Make your data product "remarkable" (i.e. worth making remarks about). This is Seth Godin's "purple cow". If people see a cow, it's not remarkable. If they were to see a purple cow, they would talk about it (or about Milka, but that's a different story). For health data, that purple cow could be a new form of visualization, a surprising story, a provocative infographic, or a useful smartphone app that people will talk about.
Go out on a limb. If you are trying to innovate, you can't avoid failure. If "failure is not an option", you are not innovating. Fail fast and iterate quickly, until you get it right.
To get more inspiration, follow Seth's blog or subscribe to this blog (feed is here); there will be follow-ups to this post in the near future.
Can you manage a revolution? In a 2013 report, a high-level panel at the UN called for a data revolution to "fully integrate statistics into decision making, promote open access to, and use of, data and ensured increased support for statistical systems." Today's workshop "Managing the Data Revolution" at UN Headquarters in New York City assembled speakers from the UN, central statistical organizations (CSOs), non-governmental organizations (NGOs), academia, civil society groups and the private sector. The discussion highlighted some key challenges and opportunities inherent in this data revolution, with a focus on the changing role of CSOs and government statisticians:
There is a quickly increasing number of data sources and volume of data (sensor data, social media, transactions data, quantified self etc) that compete with official statistics.
This data deluge - sometimes available in (near) real-time - creates a competitive marketplace for data, providing opportunities for new data products, and prompting innovation.
In this environment, CSOs should focus on what they do best and create partnerships for other tasks with private sector, academia, civil society, and NGOs (although not many examples of such partnerships came up today) and turn from owners of data into promoters of data.
To maximize the value and impact of data, and to meet increasing demand for data, every CSO should have an open data platform and - this was brought up multiple times - share microdata as open data.
There is political commitment to open government and open data in governments around the world, which should empower CSOs to drive their open data agenda.
An interesting quote during the day about working with all these other data sources was "if Google can do it, if the NSA can do it, why can't statistical offices do it?" I suspect that limited resources and ethical considerations have something to do with that, but there is certainly ample opportunity for CSOs to innovate in terms of collecting and providing data, engaging with partners, and making data actionable.
Yesterday, our team at the Institute for Health Metrics and Evaluation (IHME) launched the results of a comprehensive analysis of data on smoking prevalence and cigarette consumption around the world. The results are quite staggering. While smoking prevalence decreased in men and women between 1980 and 2012, the number of daily smokers increased by 41% in men and 7% in women, due to population growth.
In 2012, people around the world smoked a total of over 6 trillion (!) cigarettes. The results are available by age, sex, country, and year with several metrics (smoking prevalence, cigarettes consumed, number of smokers). Quite a comprehensive dataset.
To encourage the use of these numbers, we published the data in different formats for different purposes and audiences:
Interactive data visualization on the IHME website The visualization (pictured above) explores all aspects of the paper. It provides a global perspective with international comparisons on a map, in a sunburst diagram, and via line charts. It also enables country deep-dives and a closer look at all the input datasets used for the analysis. Click through to the visualizatoin and see for yourself. Hopefully, policy and decision makers, funders, and many others will find the functionality useful to explore trends and patterns of smoking and cigarette consumption around the world, and devise ways to further decrease the prevalence of smoking to reduce the loss of health and lives to smoking.
Infographic providing key insights A tobacco infographic focuses on global trends, rankings of countries with highest increase/decrease in smokers, and some specific examples. This graphic should capture the attention of just about anyone. After all, who knew that 6 trillion cigarettes can be smoked in one year?
In sum, hopefully everyone interested in smoking trends, reducing cigarette consumption and it's impact on health in general will find access to data that is useful to them.
What about you? Did you find a format of the tobacco data that appealed to you? Do you have ideas for other ways to share the data? Or suggestions for improvement? Please leave a comment or send me a note via email or Twitter. I'd be happy to hear your ideas.
Our team at the Institute for Health Metrics and Evaluation (IHME) is now able to share the data from the Global Burden of Disease (GBD) 2010 study for download at the country level. First presented in a dedicated triple issue of the Lancet last December and made available in innovative data visualizations on the IHME website, the data can now be downloaded freely in three easily accessible places:
GBD Compare - the flagship visualization for GBD results now has a "download" button that provides CSVs for any chart that is being viewed in the tool
Data visualizations provide fabulous opportunities to make large amounts of data accessible. Sophisticated controls can allow users to work their way from high-level views into great degrees of detail. I wrote a few days ago about the role of visualizations in making the country-level results of the Global Burden of Disease (GBD) 2010 study accessible and useful. The GBD visualization tools make over one billion results accessible by choosing any combination of cause of disease or injury, risk factor, country, age, gender or year, and explore various metrics.
Visualization tools can also be used very effectively to tell stories. I would guess that the GBD data contain millions of stories worth telling. Videos can be a very effective way to share these stories. A recent article by Robert Kosara (@eagereyes) provides several examples for great data storytelling in video. Videos from public presentations can be very powerful, but simple screen grabs with tools like SnagIt let you tell your stories from the privacy of your own home (or office) and provide a much clearer view of the visualizations themselves.
Below, I'm adding four videos. The first shows Christopher Murray, Director of IHME and inventor of the concept of Global Burden of Disease, use the new visualization tools to explain GBD and show key findings from GBD 2010. In the second video, Bill Gates talks about the value of visualizations and provides great feedback on the GBD visualizations. The third is my first attempt to explain the functionality of the GBD flagship visualization, GBD Compare, in a video tutorial. And the fourth is a quick video that Tom Paulson from Humanosphere took when we talked about GBD and visualizations (see the resulting article here).
Have a look. And if you have been playing with visualizations, why don't you record your own stories, e.g. with the GBD visualization tools? Let me know about them, and I'll feature the best ones on this blog.
Christopher Murray using the GBD visualization tools to share findings
Bill Gates on GBD and the visualization tools
Tutorial for GBD Compare, the GBD flagship visualization