You Can Plan For Terrorism, Analytics Will Help

www.turner.com
 
The bombings at the Boston Marathon remind us once again that we live in a dangerous world, becoming more so with each passing year.  While it’s impossible to know exactly when terrorism will strike, it is possible to plan for when it does happen, and reports out of Boston indicate that the major hospitals and emergency responders have done their homework.  Someone made quick calculations regarding the number of casualties and injuries, and they were apportioned among the major hospitals with emergency trauma units so no single facility was overloaded.  Ambulances were loaded and directed to at least three major trauma units, roughly equal numbers of victims arriving at each.

 

The emergency units were staffed, supplied and ready to go when the ambulances began to arrive from the scene of the bombing.  Victims received immediate care, supplementing what the first responders had been able to do, thereby saving lives that might otherwise have been lost.  Many of the victims were in critical condition, but thanks to such prompt and effective care, many of them have gone on to survive.
All of this; having the right training and equipment for the first responders, through having the right personnel and equipment at the emergency rooms; represents a carefully analyzed and planned system for dealing with such events.  Those who were responsible for the analytics and planning necessary to make it all happen so effectively should get their share of congratulations, as well.  Let us hope facilities in other areas of the country have taken note and done their analytical planning as well.
–Warren B. Causey

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The World Is Complex; Advanced Analytics Can Simplify

www.globalgiants.com
Remember high school or college research projects?  Remember trying to find, and then pouring over, thick tomes that might or might not have the specific information you were looking for?  Remember the frustration of realizing that you probably didn’t have all the necessary information when you sat down to write your paper?

 

Those frustrations haven’t gone away, but they have been eased a bit with the convenience of the Internet, and advanced analytics hold even more promise.  Combine the tools and you have a powerful method of discerning truth in what seems an extremely complex world.  Currently, advanced analytics are used primarily by large private companies and governmental organizations to increase profitability and transparency; however, they also have possibilities for individuals needing to research or track virtually anything.  And as prices for business intelligence dashboards come down, it isn’t hard to imagine advanced analytics becoming more mainstream among the general public.
This is not to say that you’ll be able to use advanced analytics to research virtually anything from home or your dorm room in the near future.  However, it isn’t hard to imagine such a scenario over the next 20 years or so.  Of course then, with “one version of the truth” all those trying to convince you of “their way” may have more difficulties, which is not necessarily a bad thing.  Manufacturers, retail companies and high-tech firms and of course government and quasi-government agencies will be first, but they will be blazing trails more of us can follow.
–Warren B. Causey 

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Analytics For The Entrepreneur

www.entrepreneurshipforum.org
There are eternal optimists who start small businesses all the time—even in a generally down economy.  In many cases, preliminary research includes, “Well, that looks like a good place for a store,” or, “I know how to do a specific skill, why not start my own business”.
There was a day when that type of research was all you needed, or at least was what sufficed for many successes and even more failures.  Today, however, between the Internet, myriads of data sources and advanced analytics/business intelligence, there are many more ways to research and help promote success, even in small businesses.
Organizations such as the Chamber of Commerce, and a myriad of other federal and state agencies and organizations, track business development and results and monitor America’s progress.  If you know a lot about certain things or have specific skills, you still can learn more by digging into the data now generally available.  Advanced analytics and business intelligence doesn’t have to be just the purview of large organizations.  If you want to go into business—which basically is what America is about, or has been in the past—do your research up front.  Experience is a very hard teacher, it’s better to have a good look at what you’re getting into.
 
(Warren B. Causey)

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Even Churches Using Analytics In The Cloud

 
 
The United Methodist Church, of which I happen to be a part-time local pastor, had recently started a new cloud-based analytics system about two years ago.  Each week, each United Methodist church is required to file what are called “Vital Signs” in an Internet-based reporting and analytical system.
The weekly reports include things like attendance, giving, the number of small-group meetings held, age-group activities and a host of other indicators of the health of an individual congregation.  Then, all of these data are compiled and comparisons can be made on progress, or lack thereof, tracked by church, district, conference and the denomination at large.
The system allows individual pastors, or others at the local-congregation level, to go on-line and not only see tracking over time of their individual church, but also see how that congregation compares with others of its similar size, location and demographics.  The fact that the system is entirely open gives individual church members a view of their efforts in comparison with others in similar situations.  Most pastors and members like the system, though it does require a small amount of time each week to enter data.  However, that process has been made quite easy and most find the analysis returned well worth the effort.
–Warren B. Causey

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Dispatch and scheduling can be improved with analytics

www.embarksafety.com
 
Utilities usually maintain large fleets of service vehicles, most of which need to have up-to-date maintenance logs and are used by a different crew each day.  During routine times, these vehicles and their crews are out and about replacing or updating various facilities (poles, connectors, transformers, etc.).  During storm-caused outages, they are repairing things in a hurry to get the power back on for their customers.
Dispatch and scheduling of these vehicles and crews is a complex process that once was done—especially during outages—by individuals shuffling outage calls around tables in a conference room.  Today, they are more likely to be dispatched by computer-aided systems.
However, despite the advances of the last 20 years or so, balancing available crews with immediate needs is still a complex issue one that lends itself to advanced analytics and business intelligence.  If all the various systems which utilities operate; including SCADA, GIS, customer information, facilities databases; were thoroughly integrated through advanced analytics, a lot of decision-making could be automated, thus speeding the process and relieving strain on employees/executives.  It’s past time to bring advanced analytics the operations side of utilities.
(Warren B. Causey)

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Cisco Presents Our Internet of Everything Future

www.information-age.com
We have a new flavor of Internet of Things (IoT). Cisco just endorsed its $14 trillion vision for flowerpot sensors connected over a global network.
 
But unlike other IoT evangelists GE and Intel, Cisco wants to connect more than just things. The reigning champ of networking gear calls their recipe the “Internet of Everything,” which integrates people, process, data and, of course, things into a web of connectivity. These networked connections, according to Cisco, turn “information into actions that create new capabilities, richer experiences, and unprecedented economic opportunity for businesses, individuals, and countries.”

If it’s terrestrial, it should compute. If it computes, it should be connected to the Internet.
 
Per Cisco’s thinking, none of this will happen without cloud computing and big data. Or Cisco’s knack for building IP-based platforms with jumbo scale.
 
So we’re going to connect physical objects together whether they like it or not, or need to be connected or not. Even Cisco recognizes new privacy models and security capabilities must be created to make an Internet of Everything (IoE) economy go. But where do we get $14 trillion connecting people with their pets and plants, or industrial robots to their plant workers?
 
Primary drivers of IoE:
  •       Asset productivity and cost reductions
  •       Employee productivity
  •       Supply-chain and logistics efficiency
  •       Innovation
  •       Customer Experience

Cisco based its calculations and analysis on 21 use cases, including one for smart factories, or factory automation. And Cisco says the manufacturing industry has the most money at stake (27 percent). Overall, the United States will see the biggest share of the IoE economy (32 percent).
IoE looks good for manufacturers. Cisco pegged smart factories as a favored use case.
 
The IoE assumes machines will be both easier to program and more adaptable. In addition, connections to the cloud for analytics will better integrate capital, labor and technology.
 
Other smart factory IoE superlatives:
  •       Allow greater customization and smaller runs
  •       Improve product quality through better sensors
  •       Reduce waste from materials and energy

But do we buy it? Can we really get rich and happy by connecting the unconnected?
 
Let’s start with today’s $70 trillion world GDP. Then accept Cisco’s claims we have exactly $14.4 trillion of IoE at stake over the next 10 years. And, Cisco claims 99.4 percent of physical objects destined for the IoE are now unconnected.
 
The numbers are intoxicating.
 
In fact, these are the kind of numbers that cause an entrepreneur’s heart to flutter and an electrical engineer’s head to shake. And the kind of blue-sky research that generates more questions than answers.
 
A dose of hyperbole tailored for futurists and shareholders, maybe. But we measure and hack, hack and measure. That’s what we do. Cisco is, at least, painting the broad brushstrokes of the next decade. And the real winners won’t be the ones making the 50-cent flowerpot sensors.
(Rory Crump)
 

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How Big Data Saved Intel $100 Million

www.tradearabia.com
 
It should be no surprise that Intel is profiting from big data; heavy in R & D through good times and bad, the Santa Clara chip giant has discovered three ways to reduce manufacturing costs by leveraging unused data. Over the past two years Intel has parlayed over a dozen data-driven projects into improvements in speed, quality and security.
 
In fact, Intel is weaving analytics into its many layers. Beyond manufacturing, the company is using predictive analytics to boost its reseller network with faster, tighter market data. No doubt Intel is a big data believer, maybe even downright giddy over future plans for measuring and analyzing more areas of their business.

Intel’s data ecosystem
Analytics are contagious at Intel. With designers and manufacturing sold on the benefits, projects are popping up throughout the company. It’s worth checking out Intel’s video series on big data to get a lesson on building an analytics culture.
 
As more manufacturers begin to experiment with big data, Intel makes a great test lab for great minds and fat wallets. But think about Intel’s matrix of a supply chain, the sheer number of end users they touch, and, of course, the urgency tied to a chipmaker’s roadmap. Also consider the opportunities hidden in all that data which Intel produces and how they could analyze it.
 
So the resources and test dummies are in great supply at Intel, but so are the numbers. Meaning the big numbers Intel has saved using predictive analytics to carve better silicon – $100 million in costs savings across the company. Ron Kasabian, Intel’s general manager of big data solutions, shared his company’s manufacturing successes in this article with InformationWeek.
 
Speed
At Intel, speed and quality have become intertwined. Intel does a quality check on every chip it produces. “We run a huge number of complicated tests on every single chip that comes through the manufacturing process,” Kasabian told InformationWeek.
 
Intel wants to find bugs, fix them, and squeeze time in the process. Intel squeezes time by analyzing historical data logged during manufacturing and cutting down on the thousands of tests required to produce a perfect chip. These tests drill down to the wafer level and focus on specific chips that need more, or less, testing.
 
According to Intel, predictive analytics saved $3 million in manufacturing costs in 2012. Small change to them, but the reported savings covered just one line of Intel Core processors.
 
Quality
“We’re talking about five terabytes an hour.” Did that get your attention?
Actually, per Kasabian, we’re talking five terabytes of data generated by a highly automated manufacturing line at Intel. So Intel’s goal is to detect failures within true big data volumes. In practice, information is pulled from log files and test machines, and then analyzed to reveal any hiccups. Specifically, Intel looks for deviations from normal tolerances along a manufacturing process. Analytics deliver data stealth enough to identify specific steps needing a fix.
 
Security
To build a security platform, Intel took its own distribution of Hadoop software last year for a test drive. The result processes 200 billion server events and can flag security threats inside of 30 minutes.
 
Kasabian talks of network intrusion devices (NIDs) that check packets across Intel’s network. Thousands of NIDs feed data into Hadoop. Hadoop captures and classifies the data in preparation for massive parallel processing (MPP). In the end, Intel is hunting anomalies which they are capable of spotting throughout its server network. The entire security system was built and deployed last summer.
 
Kasabian said 2012 included about 14 big data projects for Intel worth over $100 million in cost savings or avoidance. Even better, Kasabian claims Intel has just scratched the surface of what predictive analytics can accomplish in such a capital-intensive business. 
 
(Rory Crump)

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