Fullpower built the lab about a decade ago to capture data from sleep patterns. Of course, test subjects don’t typically snooze deeply with wires glued to their skulls, chests, legs, and arms. But almost everyone manages to at least nod off for a while, and the data that subjects generate are valuable and often surprising. “What we found early on is that sometimes you sleep less and feel more refreshed,” Kahn says. “It’s because you woke up in the light part of the sleep cycle.” The insight led him to develop a sleep-cycle alarm that could determine the best time to alert a person within a certain window. “Sometimes it’s better to get up at 10 of seven than at seven,” he says.
Orbital Insight Inc. founder Crawford says he wants to create the “macroscope” that will alter the world as microscopes did centuries ago.
The Palo Alto, California, company uses advanced image processing and algorithms to track national and global trends. One product estimates sales at 60 U.S. retail and restaurant chains. Others generate a global poverty map and predict illegal deforestation by watching for road construction and other signs of logging.
Customers include hedge funds, banks, government agencies, nonprofit organizations and Fortune 500 companies — “anyone who needs to understand the world at scale to make decisions,” said Crawford, who led the team that created the daily activity planners for NASA’s Mars rovers.
These images are a composite of oil storage facilities around the globe. Crude is stored in massive tanks whose capacity can be estimated from the shadows they cast. How much is stored can be gauged from the shadows on the interior lids, which move up and down based on the amount of oil in the tank.
“From tracking tweets and social media engagement during matches; to reporting on the weather and fans in attendance at the All England Club; to the on-court numbers like serve-speed and distance covered, IBM technologies covers all aspects of the game to help to bring the digits of tennis to life at Wimbledon 2015.
For the third Grand Slam of the 2015 season, SI.com has once again partnered with IBM to bring readers data-driven infographics and visualizations that help fully tell each storyline at Wimbledon.”
Want to work at a hedge fund or in private equity? Your employer might want to know how you measure up in terms of Cattell’s 16 personality factors, the Hogan Personality Inventory’s seven scales or the Caliper Profile’s more than 22 traits–tests that can take anywhere from 20 minutes to several hours, according to some frustrated job seekers. Interested in becoming a nurse? You might face questions from the Prophecy Behavioral Personality Assessment or Pegged Software, a startup founded by a former White House economist that administers tests to 3 million job applicants in health care annually. One of the most popular tests, Gallup’s StrengthsFinder, is now used by 457 of the Fortune 500 companies as a way to communicate with workers, according to the Wall Street Journal.
Some employers are now monitoring workers’ temperaments in real time–including the world’s largest hedge fund, where employees can track their individual stats on a personalized digital “baseball card.” Experts in the fast-growing “people analytics” industry believe it won’t be long before algorithms regularly sift through Facebook and Twitter postings to glean and analyze additional data.
“To make the numbers, Knight figured that managers would need to deliver 15% annual returns on all new business and capital outlays.
Today the network planning group of 70 analysts oversees this process from cubicles on the 11th floor of Union Pacific’s office tower in Omaha. The “smart guys” are anything but wonks. Many are managers from the field who spend a year or two in the department and blend excellent math skills with rail yard know-how. A case in point is Danny Torres, who spent most of his career working in repair facilities and depots, and now runs a network of 10 terminals in Iowa. “We work with a financial model that says, How much profit will adding this siding or extra track add? Will it slow or increase efficiency in other parts of the network? When it’s all taken together, will the total return reach 15%?”
Knight also built a second financial function that might be called “green, yellow, red.” In each of the big operating businesses—coal, industrial products, chemicals, and so on—Knight installed financial managers to evaluate new business. They enter the proposed pricing on all new contracts, as well as the extra costs in fuel, manpower, and everything else the business will require, into an online operating system that projects the rate of return. If the number is well over 15%, the system flashes green. If it’s on the margin, the signal is yellow. “If it’s red,” says Knight, “and it’s the best pricing we can offer, we let it go.””
I am reviewing Dr. Hasso Plattner and Bernd Leukert’s new book. I am doing it more to make sure I get a 360 degree perspective for my SAP Nation sequel.
Not surprisingly, there is not much new on S/4HANA, recent as that is. In fact, that portion reads more like a marketing brochure. They don’t use the word “simple” much but there is plenty of promise of “non-disruption”. There is insufficient focus on migration or destination economics other than it should be lighter in data, ergo TCO should go down.
What is nice, and the reason it qualifies for New Florence is the “Big Data”/HANA use cases profiled – medical research insights, fraud detection, omni-channel retail at Burberrys, margin management at Conagra, hurricane damage prediction for insurers and consumer sentiment analysis among them. I wish they had profiled these 3-4-5 years ago, when they would have stood out much more in the Analytics category of this blog where other products/vendors have been showcasing similar examples. Again, in the use cases, there is little focus on what it cost these customers.
Another nice touch – a spiritual foreword by Clayton Christensen, “Mr. Disruption” which plays to the S/4 message of simplification through removal of aggregates
“I am a religious person, and I regularly think about whether God is pleased with my life. In one of these ponderings recently, I had an important insight: God does not need accountants in Heaven. Because we have finite minds, we need to aggregate data into bigger numbers to have a sense for what is going on around us. For example, I can’t keep track of all of the specific invoices we have sent to our customers, So thank goodness, we have an accountant who can count up all these into a single number which we call “sales.” … I realized, however, that because God has an infinite mind, he doesn’t need to aggregate above the level of individuals in order to have a perfect understanding of what is going on in the world. And this implies that when he measures my life, he will only discuss with me what I have done to help other people — because he doesn’t aggregate above the level of the individual.”
Finally, a production note: Amazon has not had the book available for weeks now. Springer, the publisher, still does not have the eBook version out, and as of last week was not shipping the print version to the US (that may have changed). I had to escalate within Springer to get a copy. Hopefully, readers will have an easier time.
I would certainly recommend reading the use cases. At $79.99 the print version is priced more for a college course, but if it is released on the Amazon Kindle, it would certainly be a good one to borrow from their online library.
Crouch is the CEO of Mark43, a New York City–based startup that claims it has developed a better system for getting police records–currently a patchwork of isolated paper and digital files–into a single searchable body in the cloud. The software can display relevant information that’s as readable as the feeds on LinkedIn or Twitter. Crouch says this new way of visualizing suspects’ data–sketching out a web of phone calls or following a gang’s movements across a map, for example–could help investigators identify key players in a crime ring or exonerate the usual suspects much faster.
Each digital wind farm begins life as a digital twin, a cloud-based computer model of a wind farm at a specific location. The model allows engineers to pick from as many as 20 different turbine configurations – from pole height, to rotor diameter and turbine output - for each pad at the wind farm and design its most efficient real-world doppelganger. “Right now, wind turbines come in given sizes, like T-shirts,” says Ganesh Bell, chief digital office at GE Power & Water. “But the new modular designs allows us to build turbines that are tailor-made for each pad.”
But that’s only half of the story. Just like Apple’s Siri and other machine learning technologies, the digital twin will keep crunching data coming from the wind farm and providing suggestions for making operations even more efficient, based on the software’s insights. Longtin says that operators will be even able to use data to control noise. “If there is a house near the wind farm, we will be able to change the rotor speed depending on the wind direction to stay below the noise threshold,” he says.