Decision MediaWorks

The Fox News Deck and You

Shepp revealed it. You gawked. You laughed. Buzz Feed roasted it.

“It” of course, is the Fox News Desk. An Apple store on steroids filled with either large iPads or tiny people that feels like a Saturday Night Live spoof. Laugh now but I’ve got a Fox News Alert for you. Your future workplace will look alot like the Fox News Deck.

Increasingly, “knowledge workers” spend their time sifting through multiple streams of information in order to arrive at decisions or solve problems.  If you are reading this at work, you likely have your phone on the desk receiving text messages,  Outlook open on your desktop for emails and scheduling, Twitter open in your browser and at least one productivity application like excel or word (you know, to do “real work”).

Your desk is essentially a mini war room where you run command and control of your working life.  An everyday triage of real time information demanding real time response that defines the modern workplace.  A workplace that really is not so different from a busy news desk.

Laugh at the 56 inch touch screens but remember, critics said the iPad was “just a big iPhone” when it launched.  As it turned out of course, the larger iPad provided a superior browsing and work experience to the iPhone. Today, touch is the prefered user interface technology from iPhones to airplane controls.

In an environment where information is being flung at us rapid fire it only makes sense that we should be able to field these bursts of information with both hands.  Once fielded, why should we have to tediously click, drag, attach, copy and paste files? Isn’t it just easier to fling documents across our screen and onto a co-worker’s screen or onto a large screen that can be seen by everyone?

But why so large a screen? The same reason so many workers now prefer to use multiple monitors for their desktop computers. Allowing the eye to survey as much area as possible is simply the quickest way to scan large amounts of information. More screen space allows for the display of more information and therefore eliminates inefficient scrolling and switching between applications.

Sitting at a desk, squinting and hunched over a laptop is a profoundly unnatural and uncomfortable way to work.  The easel arrangement puts our hands and body in an ergonomically friendly position.  This is the same reason we prefer to use our IPads not flat on the table but canted upward slightly in our direction.

Unfortunately, the ability of technology to deliver real time information has greatly exceeded our brain’s ability to process and prioritize.  The Fox News Deck looks comical to us because it is the epitome of our information overload ad absurdum. The tweets, videos and wire stories flood the Fox News Deck at a rate that makes the young “Information Specialists” (See yellow arrow in picture) look like Lucy on the assembly line.

Luckily, the next big thing in workplace technology will be the integration of voice, gesture and artificial intelligence into our everyday activities (think the computer in StarTrek).  In the next five years, your devices will filter and prioritize incoming data for you by automatically learning from your workplace behaviors (check out Google Now).

Gmail will sift through your emails to determine what needs your attention now, what can wait and draft a suggested response.  Excel will respond to natural language commands to “find the average of Column D” or  “Tell me what accounts are the best performing?” Your phone will read your heart rate and body temperature to determine your stress level and text your spouse a heads up that you’ve had a tough day.

This leaves us with one big question. When does the real work get done?

If the work flow paradigm de jur is information triage then when do we do “surgery?”  Amid all this modern bustle, how does the careful, detailed and important work actually get done?

The answer, very likely, is  the same way we get “real work” done today. At home late at a night, red-eyed and hunched over a laptop on our kitchen table.

As always, if you like our content please share us and sign up for the email list on the sidebar.

8 Big Data Terms Every Policymaker Should Know

In the last few years, a long-brewing technology trend has begun to bubble up into the policy-making process at all levels of government. That trend is called “Big Data”, and industry experts expect policymakers will be dealing with the questions it raises over the next decade.

Big Data offers the potential to drastically increase our quality of life (self driving car) but is also raises questions about privacy and security (NSA snooping). The response of policymakers to the questions raised by Big Data technology will have an impact on every American business, from Google to Publix, and every American citizen, from high school students to cancer patients.

The six terms below are a primer on the lingo used in the Big Data discussion.

Data Science: An emerging field that combines statistics, computer science and business analysis to gain insight from data. Google’s chief economist has called data science the sexiest job of the next decade. Florida Poly will offer degrees in data science when it opens next year.

Big Data: A term that describes data sets of massive volume that change rapidly and come from a wide variety of sources. Big data sets are so big that they cannot be maintained on a traditional database and require new methods to process and search. Big data has applications ranging from the self-driving car to decoding the human genome.

Data Mining (Undirected Discovery)*: The methods used to explore big data sets for patterns, trends and relationships between data. A data mining project seeks to find the most compelling relationships in the data as a whole. Organizations use the insights extracted from these data mining activities to improve business functions, discover new trends, or explain the causes behind certain happenings in the business.

Analytics (Directed Discovery)*: Closely related to data mining, however the primary difference is that analytics tend to focus on improving a single business area or answering a specific question. Example: determining what key factors drive sales of a certain product.

Predictive Analytics: Using data to build a mathematical model that forecasts a future event. Example: an airline using data about certain parts to predict when they may be about to fail.

Business Intelligence (BI): A collection of key data sets of known significance to a business or organization. These key data sets are often formatted into charts, graphs and gauges on a “dashboard” for easy reference by decision makers.

Datatization: The increasing trend of everyday activities being digitized and recorded through sensors and WiFi internet connections. It is estimated that more data was created in the last two years than in all of preceding human history. The smart phone is the primary agent of datatization in everyday life.

*There is debate in the data science regarding the exact meanings of the terms “data mining” and “analytics.” Some even suggest ditching the term data mining completely because of its negative connotation. 

Click image to see a larger versionThe Real World of Big DataThe Real World of Big Data via Wikibon Infographics

Florida’s Football Stadiums: By The Numbers

Each Saturday statewide, nearly one half million college football fans fill stadium seats at a host of stadium venues, ranging from Raymond James Stadium to Doak Campbell Stadium.

That lead us to wonder which team claims the largest share of this market by stadium size?

Obviously, the answer to this question is biased towards the school with the largest stadium capacity. And that turned out to be the answer. The Florida Gators have the largest market share of filled seats in the state of Florida. With a stadium capacity of 88,548, Ben Hill Griffin Stadium gives the Gators an advantage over each team. They have a share of 27.65% of filled seats. Second place, no surprise, went to Florida State, having 23.86%.

But when investigating this question, another one arose.

Which team fills the largest portion of their seats? Who comes closest to selling out every game. Again, the Gators win this contest. This is rather surprising given the recent run of success the Seminoles have enjoyed. The Seminoles have filled an average of 91.86% of Doak Campbell Stadium’s seats in 2012. The Gators were ahead, having filled an average of 98.93% of their house last year. Not to knock the Seminoles, though. Given the size of their house, 92% is still great.

The chart below is sized by the portion college football seats statewide held by each stadium and shaded for overall stadium capacity. The chart is interactive, if you like it, please share it.

You Are Not A Savvy College Football Fan Until You Know This

Quick Note: After posting we found a data set that included the 2012-13 season and draft stats. When we updated with these numbers, FSU made a leap to a .55 Pearson’s r. Essentially, FSU was an outlier until last season. 

During the initial round of college football games last weekend, all three of Florida’s major programs won their season openers. As I was in the midst of devouring a salsa-covered chip, a friend announced, in sage-like fashion, that the Gators will “clean up” when the next NFL draft comes around.

Around here we question assumptions with data, and that got me to thinking… I began to wonder…

1) Does a team’s success have an effect on the draft prospects of its players?

2) Are some teams better at converting talented players (draft picks) into wins?

So, I brewed some coffee and dove into the data. I entered the number of draft picks for the Gators, Seminoles and Hurricanes each year in the last ten years and the number of wins in the previous season. I then calculated the Pearson’s r over those years for each team. The Pearson’s r is a convenient little statistical tool that tells us the strength of a relationship between two variables (in this case the number of players drafted and the number of wins). The Pearson’s r may be either positive or negative but will always fall between 0 and 1. In short, the smaller the number, the weaker relationship and the larger the number, the stronger the relationship.

What I found was nothing short of bizarre.

Over the last ten years, the Gators had a moderately strong relationship between wins and draft recruits. The Florida Pearson’s r is .52. The Miami Hurricanes aren’t much different, with a Pearson’s r of .57. This means that when these two teams perform better on the field, their players benefit by having better luck in the NFL draft. But the shocker is Florida State. Their Pearson’s r is .06. This is extremely weak and more or less non-existent. You can see the Pearson’s r comparisons in the graph below.

This lack of a relationship is baffling and means that if the Seminoles perform well, their seniors and juniors are no more likely to be drafted than if the team collapses into a pile of sweat and loses.

For a moment, I suspected this could be explained by the Seminoles’ reputation, so I decided to perform the same calculation on two other historically well performing football teams, the Alabama Crimson Tide and the Notre Dame Fighting Irish. This didn’t clear up anything. The Tide had a very strong relationship, with a Pearson’s r of .63. The Fighting Irish had a Pearson’s r of .41. So, the players benefit more from better seasons.

You can check all the data in the interactive table below. If you learned something interesting here today, please share it with your friends.