The best job in America has a median salary of over $116,000

This is great article from Samantha Cooney  at Mashable.com on 20 January 2016. Data analysis has never been more popular and this post gives an overview of what jobs are hot!

bh 2016/03/22

The best job in America comes with a handsome six figure salary — and has plenty of job openings.

The job: Data scientist.

It came out on top of job search site Glassdoor’s its annual list of the Best Jobs in America, which was released late on Tuesday night. The survey ranked the careers by a job score between 1 and 5 (with 5 being the best) based on earning potential, career opportunities, and the number of job openings in that field.

Link to the entire article is below:

http://mashable.com/2016/01/20/the-best-jobs-in-america-2016/?utm_cid=mash-com-fb-main-link#C5tNoAlHlkqf

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If You Want People to Hear You, Stop Talking Like a Statistician

This is a great post by Eston Martz via the Minitab blog. I love this quote:

… unless we’re speaking to a room full of other statisticians, we should stop talking like statisticians.

http://blog.minitab.com/blog/understanding-statistics/talking-the-statistical-talk-with-those-who-don%E2%80%99t-walk-the-statistical-walk

How Technology is Improving the Environment

This is an outstanding article from Jesse H. Ausubel, Director of the Program for the Human Environment at The Rockefeller University, about some of the positive aspects of technology’s impact on our world. Here is a teaser from the article:

“US Geological Survey data through 2010 shows that water use has now declined below the level of 1970, while production of corn, for example, has tripled 

Thanks to Russ Roberts (twitter handle econtalker) at EconTalk.org for featuring Jesse Ausubel in the 8-24-2015 podcast titled: Jesse Ausubel on Agriculture, Technology, and the Return of Nature

Link to the original article: http://thebreakthrough.org/index.php/journal/issue-5/the-return-of-nature

How Technology Liberates the Environment

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Despite predictions of runaway ecological destruction, beginning in the 1970s, Americans began to consume less and tread more lightly on the planet. Over the past several decades, through technological innovation, Americans now grow more food on less acres, eat more sources of meat that are less land-intrusive, and used water more efficiently so that water use is lower than in 1970. The result: lands that were once used for farms and logging operations are now returning as forests and grasslands, along with wildlife, such as the return of humpback whales off the shores of New York City (pictured above). As Jesse Ausubel elucidates in a new essay for Breakthrough Journal, as humans depend less on nature for the well-being, the more nature they have returned. Photo Credit: Artie Raslich / Getty Images.

Spring 2015 | Jesse H. Ausubel

Atlanta Braves 2014 Preview: Aging Trajectories

While this post does not fall into what I would traditionally call ‘lean’ thinking, it does point out great ways to use statistics to interpret the world. Plus, Jay went to UGA for grad school… and as a former Bulldog myself, I felt duty bound to “Like” and “Reblog” this great post about the baseball team I’ve been following since 1966.

Living In The Sprawl

Atlanta Braves Home Run Leaders The home run rate (home runs divided by at bats) of the top 12 home run hitters in Braves history.

Being a consumer of sabermetric analysis, a member of a fantasybaseballkeeper league, and a die hard Braves fan, the age of players is extremely important. You want youth with enough production that it makes sense to take the 23-year-old over the 30-year-old veteran.

When the Braves signed five of their young stars this off season to long-term deals, the team got their best players at below-market value for their most productive years, the mid-20s. They didn’t attempt to re-sign free agent Brian McCann, probably the second best offensive catcher the last five years (and the captain of the Baseball Police), who is 30. These moves show their fans and baseball that the front office actually knows what they’re doing and recognizes that you can’t build a…

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UCF Beating Baylor was NOT an Upset

The University of Central Florida beat Baylor University in the 2014 Fiesta Bowl. SB Nation declared this victory, “the biggest BCS bowl upset ever”.  I watched the game, and from the opening kickoff, it was clear that these two teams were equally matched. I love sports, and I especially enjoy American Football. 

Why did the pundits consider UCF’s victory an upset?

#1: Experts discounted UCF’s 2013 accomplishments based on their schedule.

UCF plays in the American Athletic Conference, not in a ‘power conference’ like the SEC or the PAC 12. They don’t even play in a former power conference like the Big 10 or Big 12.

#2: UCF does not have a rich and storied football tradition.

According to wikipedia,  the University of Central Florida opened in 1968 as Florida Technological University, with the mission of providing personnel to support the growing U.S. space program at the Kennedy Space Center, which is located only 35 miles (56 km) to the east. 

#3: Groupthink

(or, “nobody else is saying that UCF has a chance to beat Baylor, so I’m not going to the first on on the UCF bandwagon”)

Groupthink is the practice of thinking or making decisions as a group in a way that discourages creativity or individual responsibility. American football comentators fall into two categories: jocks and journalists. There are two subcategories of jocks, the players, and the coaches. Some, like the legendary Mike Ditka, were renowned as coaches and players. But when it comes to football expertise, there is a rigid hierarchy, jocks hold the trump card in every argument, coaches trump the journalists, and nearly to a man, everyone in this arena believes the ‘stats guy’ is a subhuman parasite who is hell bent on wrecking the noble game. Despite the popularity of Moneyball, and the success of the baseball teams using its principles, we continued to be fooled by what we see. Some people are willing to look past what they see to the facts. One of those people is Josh Friemel.    

Josh Friemel Nailed IT… with FACTS on 12/31/2013!

I had never read Josh Friemel’s work until today, but I am impressed with his “pre-game” analysis of the Baylor vs. University of Central Florida Fiesta Bowl game. Josh writes for the Dallas Morning News’ sports blog… and in his December 31, 2013 post titled, What’s up with UCF? Five things Baylor fans should know about the Knights, he lays out a convincing case for UCF. He talks about their strong defense, how their offense is balanced, the passing prowess of UCF quarterback Blake Bortles and about the Knights’ lone loss to the University of South Carolina. He backs up each assertion with facts. 

But he still predicted that Baylor would win easily…

Baylor Wins!

Given time to reflect on the things Baylor fans needed to know about UCF must have lessened his zeal for the Knights since at lunchtime on New Year’s Day, Josh posted, Prediction: UCF can’t handle Baylor’s speed, Bears easily win first ever BCS bowl. Please don’t think I’m being hard on Josh. He was the ONLY person I could find in who had published anything remotely positive related to the UCF Knight team’s chance to beat Baylor.

What can we learn?

Guard Against Groupthink.

In this case, former players and coaches spout opinions as if they are facts, and poo poo anyone who disagrees. In Howard Cosell’s book “I Never Played the Game” he helped popularize the term “jockocracy” and he talked openly about announcing jobs being given to former atheletes who had not earned them. Ironically, Cosell was replaced for the 1985 World Series broadcast by former St. Louis Cardinal Tim McCarver. <I’ll refrain from opining on Mr. McCarver’s journalistic chops in this post.>

Learn About “Confirmation Bias”

Confirmation bias (also called confirmatory bias or myside bias) is the tendency of people to favor information that confirms their beliefs. This is a difficult problem to deal with, since most of us are unaware of our biases, or worse, we are convinced that our biases are facts.

Decisive: How to Make Better Choices in Life and Work

I strongly recommend Chip and Dan Heath’s book, Decisive: How to Make Better Choices in Life and Work. It’s a great look at how we make decisions and how we can improve as individuals and as organizations.

Key Links

Josh_Friemel on twitter 

The American Athletic Conference Official site

University of Central Florida

Bob Hubbard, 1/3/2014

Know the Difference Between Your Data and Your Metrics?

from HBR.org Blog

http://blogs.hbr.org/2013/03/know-the-difference-between-yo/


Know the Difference Between Your Data and Your Metrics

by Jeff Bladt and Bob Filbin  |   11:00 AM March 4, 2013

580x215-0313-insightcenter-4How many views make a YouTube video a success? How about 1.5 million? That’s how many views a video our organization, DoSomething.org, posted in 2011 got. It featured some well-known YouTube celebrities, who asked young people to donate their used sports equipment to youth in need. It was twice as popular as any video Dosomething.org had posted to date. Success! Then came the data report: only eight viewers had signed up to donate equipment, and zero actually donated.

Zero donations. From 1.5 million views. Suddenly, it was clear that for DoSomething.org, views did not equal success. In terms of donations, the video was a complete failure.

What happened? We were concerned with the wrong metric. A metric contains a single type of data, e.g., video views or equipment donations. A successful organization can only measure so many things well and what it measures ties to its definition of success. For DoSomething.org, that’s social change. In the case above, success meant donations, not video views. As we learned, there is a difference between numbers and numbers that matter. This is what separates data from metrics.

You can’t pick your data, but you must pick your metrics.

Take baseball. Every team has the same definition of success — winning the World Series. This requires one main asset: good players. But what makes a player good? In baseball, teams used to answer this question with a handful of simple metrics like batting average and runs batted in (RBIs). Then came the statisticians (remember Moneyball?). New metrics provided teams with the ability to slice their data in new ways, find better ways of defining good players, and thus win more games.

Keep in mind that all metrics are proxies for what ultimately matters (in the case of baseball, a combination of championships and profitability), but some are better than others. The data of the game has never changed — there are still RBIs and batting averages; what has changed is how we look at the data. And those teams that slice the data in smarter ways are able to find good players that have been traditionally undervalued.

Organizations become their metrics.

Metrics are what you measure. And what you measure is what you manage to. In baseball, a critical question is how effective is a player when he steps up to the plate? One measure is hits. A better measure turns out to be the sabermetricOPS” — a combination of on-base percentage (which includes hits and walks) and total bases (slugging). Teams that look only at hitting suffer. Players on these teams walk less, with no offsetting gains in hits. In short, players play to the metrics their management values, even at the cost of the team.

The same happens in workplaces. Measure YouTube views? Your employees will strive for more and more views. Measure downloads of a product? You’ll get more of that. But if your actual goal is to boost sales or acquire members, better measures might be return-on-investment (ROI), on-site conversion, or retention. Do people who download the product keep using it, or share it with others? If not, all the downloads in the world won’t help your business.

In the business world, we talk about the difference between vanity metrics and meaningful metrics. Vanity metrics are like dandelions – they might look pretty, but to most of us, they’re weeds, using up resources, and doing nothing for your property value. Vanity metrics for your organization might include website visitors per month, Twitter followers, Facebook fans, and media impressions. Here’s the thing: if these numbers go up, it might drive up sales of your product. But can you prove it? If yes, great. Measure away. But if you can’t, they aren’t valuable.

Metrics are only valuable if you can manage to them.

Good metrics have three key attributes: their data are consistent, cheap, and quick to collect. A simple rule of thumb: if you can’t measure results within a week for free (and if you can’t replicate the process), then you’re prioritizing the wrong ones. There are exceptions, but they are rare. In baseball, the metrics an organization uses to measure a successful plate appearance will impact player strategy in the short term (do they draw more walks, prioritize home runs, etc.?) and personnel strategy in the mid and long terms. The data to make these decisions is readily available and continuously updated.

Organizations can’t control their data, but they do control what they care about. If our metric on the YouTube video had been views, we would have called it a huge success. In fact, we wrote it off as a massive failure. Does that mean no more videos? Not necessarily, but for now, we’ll be spending our resources elsewhere, collecting data on metrics that matter. Good data scientists know that analyzing the data is the easy part. The hard part is deciding what data matters.

Please join the conversation and check back for regular updates. Follow the Scaling Social Impact insight center on Twitter @ScalingSocial and give us feedback