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Data-Powered Forecasting

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The results of the recent presidential election in the USA came as a surpise to some.  Most of the pundits and forecasters on the Republican side had predicted a victory for their candidate, while those on the Democratic side were quite certain theirs would win.  A “Pundarts” graphic at the Slate.com website illustrates the relative success of these two groups in predicting the final outcome.

Right in the bullseye was Nate Silver, blogger for the New York Times, now hailed as the “golden boy of electoral statistics.”  He was spot-on this year, as he was four years ago.  No wonder that sales of his book The Signal and the Noise: Why So Many Predictions Fail-but Some Don’t jumped some 850% the day after the election.

According to Silver, in spite of how important forecasting is to our daily lives, we are remarkably poor at it.  Those who are most successful tend to be more modest, less ideological, and to rely on empirical evidence.  The key is to be able to successfully sift through a sea of noise to detect the signal.  Much of that noise can be internal, coming from the pundits themselves in the form of personality traits, subconsious biases, and pride in being an expert.

One arrow hits the target, the rest miss.While we don’t have much control over the human nature of forecasters, real-time cloud computing opens new possibilities for gathering empirical evidence.  Those currently using real-time systems already understand the value of real-time data.  Connecting to the cloud provides more depth and reach for these systems, as hard data and empirical evidence become more readily available, and up-to-the-second.  The growing availability of data, broad-based and timely, is moving us out of the realm of supposition into higher levels of certainty.

Take Nate Silver’s own success, for example.  He didn’t conjure up an imaginary all-knowing genie, or shake a Magic 8 Ball.  He certainly didn’t try to advance his own “expert” opinion.  He simply looked at the average of a number of polls.  He worked with the hard facts, considered historical precedence, and made reasonable guesses with a stated level of probability.  In addition to these, he was willing and able to adapt to rapidly changing conditions.

If you read his blog entries and other reports, you will see that as the polls changed over time, Silver changed his predictions as quickly as possible.  He was recalculating up until the day of the election, and even during the hours that the returns were coming in he was posting updates to his blog.

All successful forecasting, be it for the weather, the stock market, or business planning, ultimately relies on hard data.  In our ever-accelerating world we are becoming increasingly aware of the need for timeliness of that data.  The more recent the data, the better the forecast.  And in our growing interconnectedness, we are discovering the value of having full access to that data anywhere, any time.

The availability and speed of the incoming data are constantly increasing.  Where will all of this end up?  Will the past, present, and future eventually get compressed into real time, making data spontaneously available everywhere?  Are we ready to consider the possibility of going beyond the guesswork of forecasting, to realize a new reality, the certainty of now?

Not quite yet.  We’ll take up that topic soon.

Cloud Economics 1: A Vision

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For the past few months we’ve been looking at the technical side of real-time cloud computing.  We’ve touched on some of the requirements for supporting real-time data communications on the cloud, looked at how SCADA and embedded systems might benefit from accessing the cloud, and even considered how the term “real time” may be best applied to cloud computing.

Going forward, I thought it might be a good idea to switch gears a bit, and take a deeper look at the business and economic side of cloud computing, and see how the latest thinking about cloud economics may or may not apply to real-time applications.

A new book, Cloudonomics, by Joe Weinman, Senior Vice President of Cloud Services and Strategy at Telx, gives a profound yet accessible overview of the business value of cloud computing—in other words, cloud economics.  Among other things, the book’s cover blurb says, “Weinman drills down past the hype and hysteria, the myths and misconceptions, to uncover the fundamental principles underlying how the cloud works, how it’s used, and how it will evolve in a business context.”

With the vision of a mathematician, Weinman strips away the non-essential features of the cloud and breaks it down into its basic elements and principles.  At that level, he can demonstrate how “cloudy” ideas and concepts have been used for centuries.  For example, he shows the similarities between cloud computing and the transportation and lodging infrastructure of ancient Rome, complete with multi-protocol wide-area networks, pay-per-use resources, value-added services, regulatory agencies, security tokens, branding, advertising, and more.Coins for the cloud.

Weinman uses lots of real-world examples to show how we find cloud concepts in every facet of life, such as hotels, taxicabs, and movie theaters.  At the same time, he introduces some simple mathematical theories and models that sometimes uphold and sometimes contradict much of the conventional wisdom that has grown up around cloud computing.

Through it all, he strives to adhere to three goals: 1) present a multidisciplinary view from a number of fields of economics, mathematics, natural sciences, and system dynamics; 2) plant seeds of ideas in areas related to cloud computing, which may be cultivated and developed by others; and 3) take an evergreen approach, where the concepts are so fundamental and universal that they will serve to inspire research and application in business for many years to come.

Although I haven’t read it exhaustively, I’ve not yet seen much mention of the application or value or real-time systems in the cloud.  This is not surprising, as this topic is still on the distant horizon for many leaders of thought.  Or, it could be that what applies to cloud computing in general also applies to real-time cloud computing.

This raises an interesting question: Is there any significant difference between the economics of the more familiar cloud systems of business and consumer applications, and the less-well-known real-time cloud systems for industrial and embedded applications?  We know there are some unique technical requirements.  Is there a fundamentally different business model for real-time cloud?

In the weeks to come we’ll take a look at some of the ideas presented by Weinman in Cloudonomics, and see how they may or may not apply to the special case of real-time cloud computing.

Getting to Ten in Ten

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The other day I saw a video and presentation called Ten in Ten – Ten Technology Trends that Will Change the World in Ten Years by Dave Evans, the Chief Futurist at Cisco.  Standing in a unique position to view in detail what some of us only hear about in bits and pieces, Dave lays out a mind-reeling mural of the future.  The video is almost a year old now, and it may well take us the nine remaining years to ponder and digest its implications.

The names of the trends give a glimpse of what we can expect: The Zettaflood, The Next Dimension, The Power of Power, and more.  Reading through the list (see below), it occurred to me that the first five of these trends all have something in common–they all point in some way to the value of real-time cloud computing:

1. The Internet of Things is Already Here
Electronic devices, sensors, and all kinds of everyday objects with RFID tags connected to the Internet now outnumber people who are connected by 2 to 1.  By 2020 there will be more than 6 connected devices per person.  Real-time data from these devices and sensors flowing through the cloud can serve as a world-wide nervous system.

2. The Zettaflood Is Coming  
Human efforts, combined with an avalanche of incoming data from all of these devices will soon produce zettabytes of information.  One zettabyte = 1 trillion terabytes, or 1021 bytes.  Much of this information will be needed instantaneously, and discarded as quickly, making real-time access that much more important.

3. Wisdom of the Cloud
Cisco’s Cloud CTO, Lew Tucker said, “By 2020 one-third of all data will live in, or pass through, the cloud.”  The expression “pass through” the cloud should not go unnoticed here.  We expect to see distribution of data in real time via the cloud becoming commonplace within the next ten years.

4. The Next Net
The continuing trend towards higher-speed, higher-reliability networking can only enhance today’s technologies for cloud-enabled real-time data connectivity, making them even more robust and reliable than they are today.

5. The World Is Flat and So Is Your Technology     
As concerned citizens in Japan were able to tweet out earthquake reports several minutes ahead of the US Geologial Survey, Evans predicts that we can expect the convergence of broadband, smart phones, and Internet TV to reach a point where everyone becomes a reporter.  He says, “You’ll be broadcasting to people’s televisions, in their homes, in real time.”

Exactly how these trends might shape our world in the coming ten years remains to be seen.  In 2021 we’ll be able to sift through the archives and dig up the presentation—if it hasn’t gotten completely lost in the zettaflood or been made inaccessible by ever-more-efficient data storage hardware—and see if these predictions came true.  Meanwhile, to start moving in that direction, we’ll keep our focus on real-time applications for cloud computing.

Trends Implications
1. The Internet of Things is Already Here Things used as data sources
2. The Zettaflood Is Coming are contributing staggering amounts of information,
3. Wisdom of the Cloud increasingly available on the cloud
4. The Next Net over a high-speed network,
5. The World Is Flat and So Is Your Technology moving from near time to real time
6. The Power of Power and enabled by low power consumption,
7. It’s All About You which can enhance our lives through innovations like brain-machine interfaces,
8. The Next Dimension products on demand,
9. Another Family Tree advanced robotics,
10. You…Only Better and a high-tech leap in the evolution of the species.
Source: Ten in Ten on CiscoLive, July 12, 2011

Predictions for the Cloud for 2012

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Every month the IBM cloudchat invites a deluge of tweets about a topic related to cloud computing.  A few weeks ago they asked for predictions for the cloud for 2012.  The replies from the all-star panel of Dr. Srini Chari, Judith Hurwitz, and Amy Wohl, as well as many others around the world came thick and fast—hundreds of tweets raining in during the hour-long session.

During the storm it was almost impossible to read, much less to ponder implications.  But I’ve had a few days now to digest the content a bit, and thought I’d share a few of these predictions, along with how they might apply to real-time cloud computing.  Here are some of the answers to the question:  Looking ahead into 2012, what predictions do you have for the industry?

Broad acceptance
Tweets like, “The cloud debate is over, it’s how do I get there now!“, “customers are no longer asking if cloud but when cloud,” and “Cloud is here to stay, evolution after distributed computing. No turning back,” make it clear that everyone was on the same page.  The common wisdom is that cloud computing will become widely accepted.  In fact, Judith Hurwitz went so far as to say, “companies that have ignored the cloud model might not figure out how to remain competitive,” and Srini Chari added, “no IT system except top secret installations can exist in isolation.”

Growth
As you might expect, it was widely agreed that cloud computing will continue to grow.  Predictions included increased private cloud adoption, significant growth in hybrid cloud, and further adoption by small and medium-sized businesses.  This tweet from Tina Williams at IBM sums it up: “Everything as a service.”

Implications
There is significant expectation that widespread acceptance and growth will lead to a greater number of cloud applications in both the business and consumer markets.  A number of tweets mentioned more mobile apps.  Amy Wohl pointed out that “Consumer applications will continue to push business applications to keep up.”  Another implication for general lifestyle change is that more and more people will be working and collaborating across the Internet.

Challenges
A variety of challenges were mentioned, ranging from technical issues like data latency to business concerns like pricing.  Among these, you could sense an awareness of a need for expanding our vision.  “In 2012 people will finally realize that cloud is ‘not your parents IT infrastructure’ – new approaches for better outcomes,” tweeted Angel Luis Diaz, of IBM.

What about real-time cloud computing?
All of these predictions have strong implications for real-time cloud computing in 2012.  Widespread acceptance and growth of the cloud means that people working with industrial and embedded systems may start looking for cloud-based solutions.  We expect that with increased implementation of real-time industrial applications in the cloud, consumer apps using real-time data won’t be that far behind.  In fact, they may lead the pack.  Either way, any kind of real-time cloud system, industrial or consumer, will depend on an infrastructure that is neither your parents’ IT infrastructure, nor an industrial SCADA system, nor even what we typically see for cloud computing.  Real-time cloud computing will certainly require “a new approach for better outcomes.”