Here is a TED talk that I think most anyone would enjoy. It's a presentation by David McCandless, a journalist and self-proclaimed 'data detective'. He presents excellently, just focuses on a couple points and provides plenty of examples. He of course wishes to convey that information is beautiful when it's presented graphically. I wholeheartedly agree. Some lines he said that I quite enjoyed:

"data is the new soil" In that case, call me a data farmer.
"two languages both working at the same time" in reference to understanding concepts and visuals.
"figures are not as true as they could be" that one made me chuckle.
"knowledge compression"   It's incredible thinking about how much information can be presented in a single visualization.

Here's the presentation:

I recently downloaded Tableau Public's software (they have a private version as well) and I'd like to take the time to present my first visualization. 

This is Vancouver's postal codes displaying the median donation in the sizing of the bar chart and the average donor age by colour. Note that downtown Vancouver (V6B) has young donors who don't give much and that young is 40. No surprises that there's a correlation between age and average giving. 

More visualization to come.

Many Eyes is a website created by IBM to open up, or "democratize" as they say, visualization for data analysis. All of the data sets and visualizations are open for everyone and anyone can upload data and create visualizations. You can even make your own visualization from someone else's data. Anyway, Many Eyes is great, but I wanted to talk about one of the visualization types available: treemaps.

Each data item, or row in the data set, is represented by a rectangle. The rectangles have different sizes, with the area being proportional to a user-defined attribute. All of the rectangles fit into one giant rectangle (being that all the different sized rectangles equal 100%). It's the same principle as pie charts, but much easier to visualize smaller values.

Why care? Treemaps work best with very complex information. Do you have a budget that includes departments, sub-departments, and multiple categories? Do you have multiple sales people or fundraisers with multiple clients or donors? Finally, do you recognize that it's extremely difficult to convey meaning through spreadsheets? Then it's time for treemaps.

Treemaps allow our brains to quickly grasp very complex information using shape and colour and proportion. On Many Eyes you can see completed visualization comparing the city v. highway mileage of every vehicle, sortable by manufacturer, car line, transmission and class. There's even a visualization of the books of the Bible, by testament, type and size.

I've attached some snapshots of some treemaps I made  with Many Eyes (then edited to look awesome) to help my key stakeholders understand the important data of our operations.

Note, the context of the images is deliberately excluded. However, you can see that red is bad, and blue is good.

Albert Bartlett, a teacher and physicist, thinks sustainable growth is a contradiction. More importantly, he's become famous for this line,

Do you agree? If you want to understand better the idea of Power Laws and the long tail, this video series is bar none, the best.

Here's my list of reasons why charities with strong fundraising departments shouldn't undervalue their volunteers:

1.   Donors and volunteers are frequently the same people.

3.   Volunteering can include development activities (soliciting donations, thank-a-thons).

4.   Money may follow volunteers: matching funds from employers and from family and friends who want to support a volunteer's special interest.[i]

5.   The highest rates of volunteering are young Canadians, higher education and household income, and the religiously active.[ii]

6.   Giving and volunteering have strong linkages, such that participation in one is associated with participation in others.[iii]

7.   The top 25% of donors ($364 a year +) who volunteered contributed 59% of total donations and 40% of total volunteer hours.[iv]

8.   Volunteers who also donate contribute more hours and more dollars.[v]

9.   Americans who volunteer donate 10 times more money than those who don’t.[vi]

10. Volunteers know you. They’ve already given their time. With a volunteer, there's no need to "make the case".[vii]

11. Volunteers understand you. They see the work, and donations would impact their work tool.[viii]

12. Volunteers can tell your story in a way staff can’t. They have personal stories to share about why they feel connected to you.[ix]

13. A recent study reports that 67% of Americans who volunteered in the past year say they donate to the same organizations where they volunteer.[x]

14.  Donors lose interest over time, but being asked to share their time and talent revitalizes their commitment even if they do not accept.[xii] 

15.  Insights:
     a.   young people build loyalty through volunteering, then give
     b.   retired persons on fixed income volunteer, then give via estate planning[xi]

I love visualizing information. It helps people, all people, better understand systems, financial data, and life. This website does something amazing. It visualizes all the links, tables, tags, images, forms on a website and visualizes it as a graph. It's tough explain but here's a cheat sheet with some examples:

blue: for links
red: for tables
green: for the DIV tag
violet: for images
yellow: for forms
orange: for linebreaks and blockquotes
black: the HTML tag, the root node
gray: all other tags

Not only is this video the best summation of current understanding about work, salary and motivation, it's dead simple. Perhaps all management concepts need to be delivered with animation like this?

This is one of the best TED Talks I've ever seen about data analysis. The presenter is very good, and the visualization is incredible. Note that this presentation is from early 2006. Have you seen any TED Talks or otherwise that you think compare?

Pretty Cool.

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Today I recommend you take a moment and read The Economist's special report on managing information. It's brilliant. I've kept a copy at my desk for reference.

One of the first practical aides it provided me was directing my attention to ManyEyes, a site run by IBM. Some great places to start here are the Visualization types page and the visualizations themselves. Some are just beautiful, while others simply show incredible information in an easily understood way.

The key lessen to those who do manage information is how we present what we have. Information is abundant and as the chart below demonstrates, it's only going to be more abundant. However, is it easily understood by everyone? Certainly not without synthesis. But even then, are you excluding individuals by the method you've chosen to present information (i.e. in raw numbers)? If you work in the non-profit industry, do you think there may be a higher responsibility to ensure those who do not have business or finance backgrounds, do not have an eye for data, or just aren't 'numbers people' feel included? It could make a big difference to everyone's success.