With the start of a rather warm, dry summer here in Wisconsin, we’ve decided to take the plunge (literally) and purchase a new above ground pool. We seem to outgrow these things every few years and I’ve become intrigued with the idea that we just keep buying larger and large cylinders of water. After some exhaustive research (which mostly involved looking through a lot of old photographs and estimating pool sizes), I present you with a timeline of our family’s pool history. The bubbles represent surface area and allow for relative size comparison.
Pool History (1997-2012)
Bubble Size = Pool Size
It is interesting to see that — with the exception of a few strays — we seem to buy a new pool every three years. It is also interesting to see the exponential growth in water volume that began about the time my daughter was born (when my son was four). If we keep up that pace, our next pool will be over 10,000 cubic feet — about the size of two 18-wheelers full of water.
The Wall Street Journal recently published a table of income and unemployment data that presented pay and employment rates for various college majors. The original study by Georgetown University’s Center on Education and the Workforce contained enough additional details that I thought it might be worth trying to incorporate the information into a Tableau visualization.
After a little data massaging, I created charts for both the high-level fields of study and the more detailed individual majors. Each level contains unemployment rates, income levels, and popularity of major measured by number of enrollees.
One of the first things you notice is that, despite frequent claims to the contrary, college graduates with a degree in Education have the lowest median earnings overall. The Education field also has the narrowest range of income and includes four of the ten majors with the lowest median earnings. On the plus side, fifteen of the sixteen Education majors have (or had at the time of the study) unemployment rates below 5.5% — the weighted average rate of unemployment for all majors in the study.
Graduates with an Engineering degree have the highest median earnings overall and a relatively low unemployment rate compared to other disciplines. In addition, seven of the ten majors with the highest median earnings were found in Engineering.
Other majors with good earnings potential included the usual suspects (Computers & Mathematics, Health, and Business) while the best employment prospects were found in Education, Health, Physical Sciences, and Agriculture & Natural Resources.
As for individual majors, the winners in my completely fictitious categories are as follows:
Most Popular - Business Management & Administration takes this category with nearly 2.8 million grads holding this degree. The next two majors in line (also in the Business field) weren’t even close — trailing by over a million people.
Best Prospects – Actuarial Science beat out four other fully-employed competitors by coming in with a median income of over $80K.
Worst Prospects – Clinical Psychology tops this category with an estimated unemployment rate of nearly 20%. Yikes! I also noticed that a number of other majors in the Psychology field had unemployment rates above 10%, which means that intra-discipline career changes for people with this major would be difficult.
Most Deceptive – The “winner” here is Architecture, an outlier with the lowest median earnings and the highest unemployment rate of all of the Engineering majors. For this category, I wanted a relatively popular major with an uncommonly high unemployment rate … the kind of major that churns out grads and then strands them in the unemployment line. An educational Judas, if you will. (Full disclosure: I have an Architecture degree, but I can’t say I wasn’t warned.)
Hidden Gem – I’m going to call this one a tie between Petroleum Engineering and Pharmacy Pharmaceutical Sciences & Administration. Petroleum Engineering has a slight edge on median earnings ($127K vs. $105K) but the Pharma major has a lower overall unemployment rate (3.2% vs. 4.4%). You probably can’t go wrong with either one but keep on eye on the horizon … Petroleum Engineering is notoriously dependent on the boom/bust cycles of the oil and gas industry while workers in the pharmaceutical industry are facing major changes as companies try to adjust to globalization and increasing costs of product development.
One of the biggest barriers to introducing new concepts to people is that they often have old, preconceived notions about those concepts that are just close enough to the truth to cause confusion. For example, my company recently started a sales program that establishes performance incentives by “vertical” — one of those vague business terms that could mean just about anything to anybody. Tracking such an ambiguous concept can cause a lot of angst when someone’s paycheck is on the line so it fell to me to come up with some ideas to help clarify the definition.
The first problem I needed to address was the fact that most people already thought they knew what vertical meant. When you try and find a definition online, you’ll usually come across terms like “vertical industry” or “vertical market” which both refer to groups of companies that serve specific, related industries (i.e. a niche market). In contrast, a “horizontal market” refers to companies that meet more general business needs.
The differences between these two definitions are pretty subtle and, as a result, most people tend to associate the term vertical with almost any industry, departmental function or even groups of occupations. In our business, we need to keep such categories distinct so I decided to create a matrix that placed our two main areas of focus — jobs and industries — on two separate axes. This would provide a simple visual cue to the differences during future discussions and presentations. The basic distinctions are:
Industry (based on the NAICS standard) applies to a company or client.
Occupation (based on the SOC standard) applies to a person or individual.
Unfortunately, a standard table would still present the information in columns and rows — leaving the vague association with “vertical” unresolved. To address this, I decided to take a cue from a common Scandinavian holiday decoration and rotate the table 45 degrees. This eliminates all vertical and horizontal lines in the diagram and forces the observer to abandon the concept altogether. In the diagrams, the industry information appears in the orange axis, while the occupation appears in the blue axis.
Once this basic structure is established, unique industry/occupation combinations can be “mapped” to demonstrate situations that are familiar to the audience. These examples help reinforce the concepts while emphasizing the difference between the two categories. It can be particularly helpful explaining examples where industries and occupations share some elements in their names (i.e. health services vs. healthcare practitioners).
I was looking at an online timeline development application from xTimelines but I couldn’t get the embedding feature to work on this site. A quick search for similar tools led me to my alma mater, of all places, where they had done a nice evaluation of alternative timeline applications.
I also liked the Timeglider application but I thought the navigation was a little less intuitive. One interesting facet of this tool is that the company has teemed up with the New York Times to create an online application that generates a timeline of headlines for any search string. This is a powerful concept that takes advantage of the NYT data API … something I’ll have to explore further.