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Featured Story

How Technology Is Destroying Jobs

• By David Rotman on June 12, 2013

• 752 comments

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MIT Technology Review Magazine
July/August 2013
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Why It Matters

Economic theory and government policy will have to be rethought if technology is indeed destroying jobs faster than it is creating new ones.

Given his calm and reasoned academic demeanor, it is easy to miss just how provocative Erik Brynjolfsson’s contention really is. ­Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator and coauthor Andrew McAfee have been arguing for the last year and a half that impressive advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years. Even more ominous for workers, the MIT academics foresee dismal prospects for many types of jobs as these powerful new technologies are increasingly adopted not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine.

That robots, automation, and software can replace people might seem obvious to anyone who’s worked in automotive manufacturing or as a travel agent. But Brynjolfsson and McAfee’s claim is more troubling and controversial. They believe that rapid technological change has been destroying jobs faster than it is creating them, contributing to the stagnation of median income and the growth of inequality in the United States. And, they suspect, something similar is happening in other technologically advanced countries.
Perhaps the most damning piece of evidence, according to Brynjolfsson, is a chart that only an economist could love. In economics, productivity—the amount of economic value created for a given unit of input, such as an hour of labor—is a crucial indicator of growth and wealth creation. It is a measure of progress. On the chart Brynjolfsson likes to show, separate lines represent productivity and total employment in the United States. For years after World War II, the two lines closely tracked each other, with increases in jobs corresponding to increases in productivity. The pattern is clear: as businesses generated more value from their workers, the country as a whole became richer, which fueled more economic activity and created even more jobs. Then, beginning in 2000, the lines diverge; productivity continues to rise robustly, but employment suddenly wilts. By 2011, a significant gap appears between the two lines, showing economic growth with no parallel increase in job creation. Brynjolfsson and McAfee call it the “great decoupling.” And Brynjolfsson says he is confident that technology is behind both the healthy growth in productivity and the weak growth in jobs.
It’s a startling assertion because it threatens the faith that many economists place in technological progress. Brynjolfsson and McAfee still believe that technology boosts productivity and makes societies wealthier, but they think that it can also have a dark side: technological progress is eliminating the need for many types of jobs and leaving the typical worker worse off than before. ­Brynjolfsson can point to a second chart indicating that median income is failing to rise even as the gross domestic product soars. “It’s the great paradox of our era,” he says. “Productivity is at record levels, innovation has never been faster, and yet at the same time, we have a falling median income and we have fewer jobs. People are falling behind because technology is advancing so fast and our skills and organizations aren’t keeping up.”
Brynjolfsson and McAfee are not Luddites. Indeed, they are sometimes accused of being too optimistic about the extent and speed of recent digital advances. Brynjolfsson says they began writing Race Against the Machine, the 2011 book in which they laid out much of their argument, because they wanted to explain the economic benefits of these new technologies (Brynjolfsson spent much of the 1990s sniffing out evidence that information technology was boosting rates of productivity). But it became clear to them that the same technologies making many jobs safer, easier, and more productive were also reducing the demand for many types of human workers.

Anecdotal evidence that digital technologies threaten jobs is, of course, everywhere. Robots and advanced automation have been common in many types of manufacturing for decades. In the United States and China, the world’s manufacturing powerhouses, fewer people work in manufacturing today than in 1997, thanks at least in part to automation. Modern automotive plants, many of which were transformed by industrial robotics in the 1980s, routinely use machines that autonomously weld and paint body parts—tasks that were once handled by humans. Most recently, industrial robots like Rethink Robotics’ Baxter (see “The Blue-Collar Robot,” May/June 2013), more flexible and far cheaper than their predecessors, have been introduced to perform simple jobs for small manufacturers in a variety of sectors. The website of a Silicon Valley startup called Industrial Perception features a video of the robot it has designed for use in warehouses picking up and throwing boxes like a bored elephant. And such sensations as Google’s driverless car suggest what automation might be able to accomplish someday soon.
A less dramatic change, but one with a potentially far larger impact on employment, is taking place in clerical work and professional services. Technologies like the Web, artificial intelligence, big data, and improved analytics—all made possible by the ever increasing availability of cheap computing power and storage capacity—are automating many routine tasks. Countless traditional white-collar jobs, such as many in the post office and in customer service, have disappeared. W. Brian Arthur, a visiting researcher at the Xerox Palo Alto Research Center’s intelligence systems lab and a former economics professor at Stanford University, calls it the “autonomous economy.” It’s far more subtle than the idea of robots and automation doing human jobs, he says: it involves “digital processes talking to other digital processes and creating new processes,” enabling us to do many things with fewer people and making yet other human jobs obsolete.
It is this onslaught of digital processes, says Arthur, that primarily explains how productivity has grown without a significant increase in human labor. And, he says, “digital versions of human intelligence” are increasingly replacing even those jobs once thought to require people. “It will change every profession in ways we have barely seen yet,” he warns.
McAfee, associate director of the MIT Center for Digital Business at the Sloan School of Management, speaks rapidly and with a certain awe as he describes advances such as Google’s driverless car. Still, despite his obvious enthusiasm for the technologies, he doesn’t see the recently vanished jobs coming back. The pressure on employment and the resulting inequality will only get worse, he suggests, as digital technologies—fueled with “enough computing power, data, and geeks”—continue their exponential advances over the next several decades. “I would like to be wrong,” he says, “but when all these science-fiction technologies are deployed, what will we need all the people for?”
New Economy?
But are these new technologies really responsible for a decade of lackluster job growth? Many labor economists say the data are, at best, far from conclusive. Several other plausible explanations, including events related to global trade and the financial crises of the early and late 2000s, could account for the relative slowness of job creation since the turn of the century. “No one really knows,” says Richard Freeman, a labor economist at Harvard University. That’s because it’s very difficult to “extricate” the effects of technology from other macroeconomic effects, he says. But he’s skeptical that technology would change a wide range of business sectors fast enough to explain recent job numbers.

Employment trends have polarized the workforce and hollowed out the middle class.

David Autor, an economist at MIT who has extensively studied the connections between jobs and technology, also doubts that technology could account for such an abrupt change in total employment. “There was a great sag in employment beginning in 2000. Something did change,” he says. “But no one knows the cause.” Moreover, he doubts that productivity has, in fact, risen robustly in the United States in the past decade (economists can disagree about that statistic because there are different ways of measuring and weighing economic inputs and outputs). If he’s right, it raises the possibility that poor job growth could be simply a result of a sluggish economy. The sudden slowdown in job creation “is a big puzzle,” he says, “but there’s not a lot of evidence it’s linked to computers.”
To be sure, Autor says, computer technologies are changing the types of jobs available, and those changes “are not always for the good.” At least since the 1980s, he says, computers have increasingly taken over such tasks as bookkeeping, clerical work, and repetitive production jobs in manufacturing—all of which typically provided middle-class pay. At the same time, higher-paying jobs requiring creativity and problem-solving skills, often aided by computers, have proliferated. So have low-skill jobs: demand has increased for restaurant workers, janitors, home health aides, and others doing service work that is nearly impossible to automate. The result, says Autor, has been a “polarization” of the workforce and a “hollowing out” of the middle class—something that has been happening in numerous industrialized countries for the last several decades. But “that is very different from saying technology is affecting the total number of jobs,” he adds. “Jobs can change a lot without there being huge changes in employment rates.”
What’s more, even if today’s digital technologies are holding down job creation, history suggests that it is most likely a temporary, albeit painful, shock; as workers adjust their skills and entrepreneurs create opportunities based on the new technologies, the number of jobs will rebound. That, at least, has always been the pattern. The question, then, is whether today’s computing technologies will be different, creating long-term involuntary unemployment.
At least since the Industrial Revolution began in the 1700s, improvements in technology have changed the nature of work and destroyed some types of jobs in the process. In 1900, 41 percent of Americans worked in agriculture; by 2000, it was only 2 percent. Likewise, the proportion of Americans employed in manufacturing has dropped from 30 percent in the post–World War II years to around 10 percent today—partly because of increasing automation, especially during the 1980s.

While such changes can be painful for workers whose skills no longer match the needs of employers, Lawrence Katz, a Harvard economist, says that no historical pattern shows these shifts leading to a net decrease in jobs over an extended period. Katz has done extensive research on how technological advances have affected jobs over the last few centuries—describing, for example, how highly skilled artisans in the mid-19th century were displaced by lower-skilled workers in factories. While it can take decades for workers to acquire the expertise needed for new types of employment, he says, “we never have run out of jobs. There is no long-term trend of eliminating work for people. Over the long term, employment rates are fairly stable. People have always been able to create new jobs. People come up with new things to do.”
Still, Katz doesn’t dismiss the notion that there is something different about today’s digital technologies—something that could affect an even broader range of work. The question, he says, is whether economic history will serve as a useful guide. Will the job disruptions caused by technology be temporary as the workforce adapts, or will we see a science-fiction scenario in which automated processes and robots with superhuman skills take over a broad swath of human tasks? Though Katz expects the historical pattern to hold, it is “genuinely a question,” he says. “If technology disrupts enough, who knows what will happen?”
Dr. Watson
To get some insight into Katz’s question, it is worth looking at how today’s most advanced technologies are being deployed in industry. Though these technologies have undoubtedly taken over some human jobs, finding evidence of workers being displaced by machines on a large scale is not all that easy. One reason it is difficult to pinpoint the net impact on jobs is that automation is often used to make human workers more efficient, not necessarily to replace them. Rising productivity means businesses can do the same work with fewer employees, but it can also enable the businesses to expand production with their existing workers, and even to enter new markets.
Take the bright-orange Kiva robot, a boon to fledgling e-commerce companies. Created and sold by Kiva Systems, a startup that was founded in 2002 and bought by Amazon for $775 million in 2012, the robots are designed to scurry across large warehouses, fetching racks of ordered goods and delivering the products to humans who package the orders. In Kiva’s large demonstration warehouse and assembly facility at its headquarters outside Boston, fleets of robots move about with seemingly endless energy: some newly assembled machines perform tests to prove they’re ready to be shipped to customers around the world, while others wait to demonstrate to a visitor how they can almost instantly respond to an electronic order and bring the desired product to a worker’s station.
A warehouse equipped with Kiva robots can handle up to four times as many orders as a similar unautomated warehouse, where workers might spend as much as 70 percent of their time walking about to retrieve goods. (Coincidentally or not, Amazon bought Kiva soon after a press report revealed that workers at one of the retailer’s giant warehouses often walked more than 10 miles a day.)
Despite the labor-saving potential of the robots, Mick Mountz, Kiva’s founder and CEO, says he doubts the machines have put many people out of work or will do so in the future. For one thing, he says, most of Kiva’s customers are e-commerce retailers, some of them growing so rapidly they can’t hire people fast enough. By making distribution operations cheaper and more efficient, the robotic technology has helped many of these retailers survive and even expand. Before founding Kiva, Mountz worked at Webvan, an online grocery delivery company that was one of the 1990s dot-com era’s most infamous flameouts. He likes to show the numbers demonstrating that Webvan was doomed from the start; a $100 order cost the company $120 to ship. Mountz’s point is clear: something as mundane as the cost of materials handling can consign a new business to an early death. Automation can solve that problem.

Meanwhile, Kiva itself is hiring. Orange balloons—the same color as the robots—hover over multiple cubicles in its sprawling office, signaling that the occupants arrived within the last month. Most of these new employees are software engineers: while the robots are the company’s poster boys, its lesser-known innovations lie in the complex algorithms that guide the robots’ movements and determine where in the warehouse products are stored. These algorithms help make the system adaptable. It can learn, for example, that a certain product is seldom ordered, so it should be stored in a remote area.
Though advances like these suggest how some aspects of work could be subject to automation, they also illustrate that humans still excel at certain tasks—for example, packaging various items together. Many of the traditional problems in robotics—such as how to teach a machine to recognize an object as, say, a chair—remain largely intractable and are especially difficult to solve when the robots are free to move about a relatively unstructured environment like a factory or office.
Techniques using vast amounts of computational power have gone a long way toward helping robots understand their surroundings, but John Leonard, a professor of engineering at MIT and a member of its Computer Science and Artificial Intelligence Laboratory (CSAIL), says many familiar difficulties remain. “Part of me sees accelerating progress; the other part of me sees the same old problems,” he says. “I see how hard it is to do anything with robots. The big challenge is uncertainty.” In other words, people are still far better at dealing with changes in their environment and reacting to unexpected events.
For that reason, Leonard says, it is easier to see how robots could work with humans than on their own in many applications. “People and robots working together can happen much more quickly than robots simply replacing humans,” he says. “That’s not going to happen in my lifetime at a massive scale. The semiautonomous taxi will still have a driver.”
One of the friendlier, more flexible robots meant to work with humans is Rethink’s Baxter. The creation of Rodney Brooks, the company’s founder, Baxter needs minimal training to perform simple tasks like picking up objects and moving them to a box. It’s meant for use in relatively small manufacturing facilities where conventional industrial robots would cost too much and pose too much danger to workers. The idea, says Brooks, is to have the robots take care of dull, repetitive jobs that no one wants to do.
It’s hard not to instantly like Baxter, in part because it seems so eager to please. The “eyebrows” on its display rise quizzically when it’s puzzled; its arms submissively and gently retreat when bumped. Asked about the claim that such advanced industrial robots could eliminate jobs, Brooks answers simply that he doesn’t see it that way. Robots, he says, can be to factory workers as electric drills are to construction workers: “It makes them more productive and efficient, but it doesn’t take jobs.”
The machines created at Kiva and Rethink have been cleverly designed and built to work with people, taking over the tasks that the humans often don’t want to do or aren’t especially good at. They are specifically designed to enhance these workers’ productivity. And it’s hard to see how even these increasingly sophisticated robots will replace humans in most manufacturing and industrial jobs anytime soon. But clerical and some professional jobs could be more vulnerable. That’s because the marriage of artificial intelligence and big data is beginning to give machines a more humanlike ability to reason and to solve many new types of problems.

Even if the economy is only going through a transition, it is an extremely painful one for many.

In the tony northern suburbs of New York City, IBM Research is pushing super-smart computing into the realms of such professions as medicine, finance, and customer service. IBM’s efforts have resulted in Watson, a computer system best known for beating human champions on the game show Jeopardy! in 2011. That version of Watson now sits in a corner of a large data center at the research facility in Yorktown Heights, marked with a glowing plaque commemorating its glory days. Meanwhile, researchers there are already testing new generations of Watson in medicine, where the technology could help physicians diagnose diseases like cancer, evaluate patients, and prescribe treatments.
IBM likes to call it cognitive computing. Essentially, Watson uses artificial-­intelligence techniques, advanced natural-language processing and analytics, and massive amounts of data drawn from sources specific to a given application (in the case of health care, that means medical journals, textbooks, and information collected from the physicians or hospitals using the system). Thanks to these innovative techniques and huge amounts of computing power, it can quickly come up with “advice”—for example, the most recent and relevant information to guide a doctor’s diagnosis and treatment decisions.
Despite the system’s remarkable ability to make sense of all that data, it’s still early days for Dr. Watson. While it has rudimentary abilities to “learn” from specific patterns and evaluate different possibilities, it is far from having the type of judgment and intuition a physician often needs. But IBM has also announced it will begin selling Watson’s services to customer-support call centers, which rarely require human judgment that’s quite so sophisticated. IBM says companies will rent an updated version of Watson for use as a “customer service agent” that responds to questions from consumers; it has already signed on several banks. Automation is nothing new in call centers, of course, but Watson’s improved capacity for natural-language processing and its ability to tap into a large amount of data suggest that this system could speak plainly with callers, offering them specific advice on even technical and complex questions. It’s easy to see it replacing many human holdouts in its new field.
Digital Losers
The contention that automation and digital technologies are partly responsible for today’s lack of jobs has obviously touched a raw nerve for many worried about their own employment. But this is only one consequence of what ­Brynjolfsson and McAfee see as a broader trend. The rapid acceleration of technological progress, they say, has greatly widened the gap between economic winners and losers—the income inequalities that many economists have worried about for decades. Digital technologies tend to favor “superstars,” they point out. For example, someone who creates a computer program to automate tax preparation might earn millions or billions of dollars while eliminating the need for countless accountants.
New technologies are “encroaching into human skills in a way that is completely unprecedented,” McAfee says, and many middle-class jobs are right in the bull’s-eye; even relatively high-skill work in education, medicine, and law is affected. “The middle seems to be going away,” he adds. “The top and bottom are clearly getting farther apart.” While technology might be only one factor, says McAfee, it has been an “underappreciated” one, and it is likely to become increasingly significant.

Not everyone agrees with Brynjolfsson and McAfee’s conclusions—particularly the contention that the impact of recent technological change could be different from anything seen before. But it’s hard to ignore their warning that technology is widening the income gap between the tech-savvy and everyone else. And even if the economy is only going through a transition similar to those it’s endured before, it is an extremely painful one for many workers, and that will have to be addressed somehow. Harvard’s Katz has shown that the United States prospered in the early 1900s in part because secondary education became accessible to many people at a time when employment in agriculture was drying up. The result, at least through the 1980s, was an increase in educated workers who found jobs in the industrial sectors, boosting incomes and reducing inequality. Katz’s lesson: painful long-term consequences for the labor force do not follow inevitably from technological changes.
Brynjolfsson himself says he’s not ready to conclude that economic progress and employment have diverged for good. “I don’t know whether we can recover, but I hope we can,” he says. But that, he suggests, will depend on recognizing the problem and taking steps such as investing more in the training and education of workers.
“We were lucky and steadily rising productivity raised all boats for much of the 20th century,” he says. “Many people, especially economists, jumped to the conclusion that was just the way the world worked. I used to say that if we took care of productivity, everything else would take care of itself; it was the single most important economic statistic. But that’s no longer true.” He adds, “It’s one of the dirty secrets of economics: technology progress does grow the economy and create wealth, but there is no economic law that says everyone will benefit.” In other words, in the race against the machine, some are likely to win while many others lose.

752 comments. Share your thoughts »

Credits: Noma Bar (Illustration); Data from Bureau of Labor Statistics (Productivity, Output, GDP Per Capita); International Federation of Robotics; CIA World Factbook (GDP by Sector), Bureau of Labor Statistics (Job Growth, Manufacturing Employment); D. Autor and D. Dorn, U.S. Census, American Community Survey, and Department of Labor (Change in Employment and Wages by Skill, Routine Jobs)

Tagged: Computing, Biomedicine, Business, Communications, Energy, Web, robotics, AI, economy, jobs, automation, middle class

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Dear Avinash: Your Digital Marketing + Analytics Challenges Answered.

Dear Avinash: Your Digital Marketing + Analytics Challenges Answered
By Avinash Kaushik
Every once in a while I take a pause and answer your questions, your burning questions (!), about digital marketing and analytics.
I'd requested you to submit questions on my Facebook or Google+ pages and am always delighted at the wide range of challenges you share.
For some answers, What is Avinash's typical day like? Hour-by-hour report please. :)?, you'll have to wait for my biography (thanks for asking Simo Ahava!). I'll answer a selection of other questions in this post.
We will cover questions in four areas: business/strategy challenges, analytics/technical challenges, career/self-development questions and rampant speculation.
Many of these questions have multiple possible answers, I invite you to participate in the discussion by adding your own answers via comments.
Let's do this!
^ Business/Strategy Challenges
Glenn Walker

Hi, I have recently started working with more enterprise clients, its been fun but there are a lot of new challenges. I am having issues prioritizing 1) recommending fixing on site issues affecting real traffic levels versus 2) correcting significant configuration issues in Analytics measuring current site traffic. Both are large scale issues requiring buy in from execs and multiple departments.
I need to pick my spots and decide where to assign resources first. Grow traffic first, with even with bad measurement I can find positive ROI areas for growth or invest time getting Analytics in order first for more objective decision making? How do you think about making reconsiderations for a scenario like this??

Strategy one…
Prioritize by where you will make money for your client quickly. Even the worst analytics configuration in the world will most likely allow you to measure cart and checkout abandonment rate. If you can fix that, more revenue will immediately flow into your client's bottom-line. They will show affection towards you. Bank it. Next, it should be easy to measure bounce rates for landing pages (you would have to have zero code on the site not to be able to do this). Find campaigns where they are spending most money, lower the bounce rate and reduce acquisition cost. Earn more affection.
When you feel you have enough, use it to buy time/money to go fix the configuration problems.
The mistake we make is that we obsess about every big, small and insignificant analytics implementation challenge and try to fix it because we want 99.95% comfort with data quality. Six years go by. Nothing changes for the business. We wonder why data people are not loved. :)
Don't make that silly mistake.
Strategy two…
Book two hours with the senior most company leaders who will talk to you, and create the Digital Marketing and Measurement Model .

If you have the DMMM, you have your priorities clearly laid out.
If there is anything you can measure, even with your broken analytics implementation, do that first. Add value to the business. Then prioritize fixes to the analytics implementation based on what your DMMM indicates is important to measure.
Strategy three…
Leverage the Digital Analytics Ladder for Magnificent Success to help you prioritize where to focus next.

Identify where your company is currently, what the next optimal step is in the ladder and give it all your attention in terms of data analysis or analytics code fixes.
Three different strategies to help you figure out what you should do next, even with a horrible analytics implementation. What they have in common is they encourage you to extract whatever value from the data you can first, prove your worth to the business, and then focus on analytics code fixing.
Stephen Cornelius

How do you come up with compelling analytics KPIs if there isn't a simple relationship between online activity and profit, for example when you sell online content via a traditional offline annual subscription sales process??

I'm afraid there isn't enough context in your question to answer it specifically. There can be so many different answers based on your specific scenario.
But if you would like a quick collection of tips: Multichannel Analytics- Tracking Online Impact Of Offline Campaigns The enabler of tying offline activity to online is ensuring you have a weak or strong primary key. The post provides more detail.
I believe these two posts with a collection of some of my favorite metrics will inspire you: 1.Best Metrics For Digital Marketing: Rock Your Own And Rent Strategies 2.Best Web Metrics / KPIs for a Small, Medium or Large Sized Business.
Joseph Boisseaux

Why is it so incredibly difficult to make people understand that last click attribution model is just idiot? That seems so trivial common sense that I am wondering if France is not in a parallel dimension.

This does drive me bananas! In this day and age using last-click attribution to measure digital success is spectacularly dumb. Genuinely awful.
Who is to blame?
First, I blame the analytics vendors. Vast majority of Adobe Analytics / Google Analytics remain last-click based. (Yes, yes, yes, with GA you can dive into Multi-Channel Funnels reports to move beyond last-click.) Many other tools remain 100% last-click based. If they won't take this seriously, how will they users ever see the light?
Second, I blame you and myself and all other analysts. Even when we have free solutions like MCF in GA with free attribution modeling tools, we don't really use them. Yes it does take a small mental shift, but if, the smart ones (!!), won't make the shift how can we blame anyone else? Are all your reports and presentations beyond last click?
Finally, and only lastly, I blame the management teams. They still tend to think of digital as a fulfillment channel. They have still not embraced the strategy for optimizing for marketing portfolios and still obsess about optimizing silos (they learned this from their TV, Print etc. strategies). They are actively losing money and actively creating upset customers. But they don't realize the cost. I blame their entrenched thinking.
Oh, and nothing is weird about France. Pretty much every company here is using last-click (at least until I visit them :)).
If you would like to move beyond the stupidity, sorry, of last-click:

Strategic advice: Multi-Channel Attribution: Definitions, Models and a Reality Check
Tactical advice: Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models.

Justin Dux

Tag Management. What you need to know before you choose third party tool.

First, if you are going to touch the code on your site make sure you get a tag management tool right now. Analytics implementations are getting numerous (tools) and more complicated with every passing data. Get a tag management tool. It will speed up code changes, it will improve the quality of your tagging, angels will sing songs in your praise.
How should you choose one? I'll share the same advice with you I'd shared about choosing a web analytics tool in Sept 2006… Get the nicest free tag management tool you can find. The Google Tag Manager is a good one, you don't need to use Google Analytics to use it. Deploy it. Enjoy it. Revel in its glory. At some point you'll bump into a small issue. Note down the limitation. If it is not a deal-breaker, keep using the tool, keep benefiting from it. Then you'll find something else. Make a note of that one.
At some point, three years from now, because you'll evolve your sophistication, you'll have five limitations and now it has reached a big problem point for your company. You now have your "what do you need to know before your choose a third party tool" list. You will make the smartest possible decision for your company because your selection will be based on your experience with a free tool that you actually used rather than reading competitive FUD literature, and you found actual problems you could not live without.
You're welcome.
^ Technical Analytics Challenges
Mehdi Oudjida

What would be the future of Adwords marketers with not provided searched query ?
- Their reflex would be to expand the number of bought keywords as work around (manual long train work) to try to understand the performance using directly bought keywords?
- It would drive a part of ads to cheaper bids (for the beginning) of long train keywords ?
- Adwords min bulk quotas to be displayed need to be reduced by Google to follow this responsive behavior ??

There might be some confusion here.
What has actually happened is that Google team has announced that they are removing the query from the referrer on ad clicks by users who use secure (SSL) search on Google.com. So analytics packages et. al. won't have access to this data.
But you as the advertiser will still see the data in the Search Terms report inside your Adwords account. You will be able to measure performance of your bids just as you did in the past.
For automated reporting you can also use the AdWords API Search Query Performance Report or the AdWords Scripts Report service.
There is a small bummer here for sure. I like to analyze my AdWords keyword performance using custom reports , especially using dimensions like Matched Search Query, inside Google Analytics and in context of other campaigns I'm running.

I can't do this anymore and I'm sad about that. But, I'm adapting to the new reality and playing with available options.
Isak Easa

What is a way to analyze Not provided data in GA, its increasing day by, can you suggest how to analyze brand vs non brand out of it?

You are in luck!
Ok, only partially. But, here's an extremely detailed posts that looks at five different data sources to help you make the best of keyword data that is available in other places to optimize your SEO (or even PPC) strategies: Search: Not Provided: What Remains, Keyword Data Options, the Future.
The post covers what is still there in your analytics tools, competitive intelligence tools, Google Webmaster tools, AdWords Keyword tool, and SEO tools.

And you can definitely do brand vs non-brand analysis using these options. It is not perfect, but it is also very far from insufficient.
Alexander Velinov

My question may be a trivial, but… Do I need campaign tagging with utm parameters for Google Analytics in order to receive more valuable information in multi channel funnel reporting and what exactly valuable information may I achieve ? Let use the question in general way.
I know that it depends of business, goals, measurement plan, resources and so on… But i talk in general. Btw our business is lead generation website and we have a lot of campaigns in different channels. Till now (I am in company from month) we use internal link tracking system which works only in user session, and do not use cookies so i think that we don't have exact information for real business decisions. Thanks in advice.

Let's unpack what is going on here.
Most of the time the way Google Analytics (or WebTrends or whomever) knows where someone came from is by parsing the information in the URL. If someone comes from a link, that information gets provided to Analytics, you can see where the visitor came from. If there is nothing in the referring string, that visit is marked as Direct.
If you are deliberately sending traffic, say via a campaign or an activity you are undertaking, it is best to pass that in the referral string. That way Analytics knows it was your handiwork to send that traffic. It will put that data in Campaigns section of the Acquisition report.
Here's an example. I post on twitter, http://goo.gl/W6P01k, the link brings you back to my website, and you'll see this url:
http://www.kaushik.net/avinash/best-web-metrics-digital-marketing-own-rent-strategies/?utm_source=social-media&utm_medium=twitterfbgp&utm_campaign=aktw
The URL parameters help GA put the data in the right place and classify it as a campaign. Like so…

I can now see the value of my social media campaigns clearly, and segment them by Twitter, LinkedIn, Google+ and then lastly Facebook (Oh, I love you Twitter, I love you so much!).
So a very long way of saying that if you do anything to generate traffic, always use campaign tracking parameters. Always. Typically this will apply to Paid Search, Affiliates, Email Marketing, Social Media, and Display campaigns.
If you have a lot of them, aggregate them up. In my case above I can see individual campaigns or just create and advanced segment for social-media.
Fruition Internet Marketing

Do you have any metrics to measure the effectiveness of offline campaigns (Print/TV/Radio)??

You have three options at your disposal, depending on how hard you want to work / how accurate of an answer you want (and remember, you don't always need the most accurate answer – it is very smart to do, even back of the napkin, cost benefit analysis).
I'd outlined the simplest possible option in a post on how I measured the impact of one of our radio campaigns on our digital existence and profits. Here it is: Excellent Analytics Tip #12: Unsuspected Correlations Are Sweet!

The graph above is the end result, fascinating results. Please read the blog post for all the details.
Your second option is to ensure that you invest in various techniques that allow you to create a primary key to tie your offline campaign data with online behavior and outcomes. More details are in my post on tracking online impact of offline campaigns .
Finally, the hardest option, and the one that is most rewarding and perhaps even the most accurate, is to measure effectiveness of offline campaigns by leveraging controlled experiments .

My example in the post is about measuring the value of catalog and email campaigns, but the technique you would follow would be the same. For additional inspiration seek our media-mix modeling techniques.
Measuring multi-channel campaigns and outcomes takes some effort, but if you are willing you can totally do it.
Martin Penner

Why is Google Analytics telling me that the average time-on-page for my homepage is 16 minutes? It can't possibly be true?

Two things to remember.
All web analytics tools by default don't measure time on page for a bounced visit. So if many people come to your site and leave instantly from your home page then their time in the system is N/A (not available). Of the sessions where time is measured (because a click was made on a link that goes into your site), it is entirely possible that for a good percentage of people they land on your site, go do something else, for whatever reason, later see the tab open and make a click and go deeper into your site causing a higher time period to be recorded for your site. They can't leave the tab/page open for a lot time, after 29 minutes of inactivity the visitor session is terminated. There could be other such reasons causing your high home page time on page.
Check if you have a high bounce rate, if so you don't need a lot of people to exhibit weird behavior for your time on page metric to get messed up.
Bonus reading: Standard Metrics Revisited: #4 : Time on Page & Time on Site
Denis Pinsky

In recent years an increasing percentage of traffic is being labeled as 'Direct', for the most part I know why this is happening, but is analytics industry working on something that will provide more accurate 'Channel' attribution??

Here is a comprehensive guide to look over: Excellent Analytics Tip #18: Make Love To Your Direct Traffic The post shares six reasons why traffic is imprecisely classified as Direct.
I do think the analytics industry is all it can to classify your traffic as cleanly as possible. There are other shadier ways to solve this problem, they will break privacy laws and breach user trust and so I'm glad no legitimate analytics solution is doing anything like that.
Recently the single biggest reason for a spike in Direct traffic is the massive increase in use of mobile applications by all of us. A huge chunk of social media consumption is via dedicated mobile apps. And I don't think you need me to share with you the number of mobile apps, and numbers on mobile app adoption. Mobile apps don't pass a referrer, the visitor gets classified as Direct.
So, for every single campaign you execute, very link you share via social media, and every single action you might undertake on mobile, make sure you are using campaign tracking parameters .

All the traffic you generate will now be classified correctly. The ones others generate might not be, but there is not much you can do about it.
If you want to go one more step further and really ensure all things at your end of the responsibility spectrum are covered, check that you have your analytics code implemented completely and correctly.
Bernardo Contopoulos

My current challenge: I want to measure how much the increase in usage of my subscription-based online content is caused by an increase in new subscriptions, and how much is caused by efforts we make to stimulate older subscribers to use more our content (ongoing training, phone calls…)?
As far as I’m concerned, I’m dead on the unique visitors metric (or news vs. returning), as it seems more and more people/companies clean or block third-party cookies.
Short version: how can I measure the results of our efforts in client acquisition and retention distinctively, if I cannot totally rely on unique/new vs. returning visitor data?

You are right, you cannot rely on new and returning visitors/users.
This is a little bit of a complex problem, so you are indeed better off working with an authorized consultant who can evaluate your unique circumstances are help you implement the right solution very quickly. Here's a list: www.bit.ly/gaac You can also try to "figure out out" :), but I'm afraid if you don't have the technical chops (and that is ok) it will simply take you too long.
All that said there are two solutions that might work.
You can use custom variables, with scope set to Visitor or User, to anonymously identify people who have received your new subscriptions and measure increased content consumption by those people. You can also of course use this strategy to differentiate between new and old subscriptions. Oh, and if you want to analyze behavior of new subscribers from a specific time period, say everyone in Jan 2016, you can use the spiffy cohort analysis option in advanced segmentation . Truly sexy stuff.
Another more advanced strategy might be to leverage the User ID option with the new Universal Analytics roll-out by the team at Google. This will allow you to do some pretty spiffy things related to tracking people and do so across devices (which my above recommendation will not do).
Bonus: User ID implementation guide .
Dan Chow

What is the best way to avoid sample data in segments and views in GA? (without upgrading to GA premium :))

Use standard reports. They are not sampled (unless you apply filters of some kind or advanced segmentation on top of the report and other such things).
Sampling kicks in most frequently when you are looking at the data across a very large time period and use my favorite Google Analytics features like Custom Reporting and Advanced Segmentation.
Also please remember that while the default sampling is applied at 250k, you can change this (look at the top right of any given report) to anywhere from 1k to 500k.
For a more detailed and specific answer: How sampling works in Google Analytics

With sampling what GA is trying to do is not have you wait for five hours to get a perfect answer, or have your query time out, both of which happen commonly in other tools for large datasets. It is very quickly trying to five you a good enough answer. It uses very advanced strategies to ensure it is a good enough answer.
Sometimes that is simply not sufficient. Either our peers don't know how to use sampled data, or have a psychological barrier to overcome. In those cases, please use the techniques outlined above or pay for the Premium version.
Bonus: Web Analytics Data Sampling 411
^ Career / Self-Development Questions.
Kaja Sousek

How to not get frustrated if you are responsible in corporation for digital marketing, but you are the almost only one there, because digital dept. is nonexistent and you get to your Hippo two times per year to discuss digital things?
On the surface it may looks like that everything is running smoothly as you care about website, run campaigns, do reports & analyses, but you know all the time that your company did not buy "big picture" yet.

It does not seem like your company takes digital marketing seriously. If they did, you would see the HiPPO more than twice a year. Even if you were not the most important person on the digital side of your business.
So with that as a background, what do you do?
If you have enough influence (and you can have that even without a big title), then try to take charge of as much of the digital effort as you can and prove to them that by being serious you can win big. Pick the area with the most amount of revenue or cost, use data and digital savvy to improve revenue even more or reduce cost a lot. That will attract attention.
If you have very little influence, try to pick a small area. Say, email marketing. Rock it. Prove how well it can work. Perhaps the right light will shine on your effort and your management team will take you seriously, and then the digital business.
If you have no influence, keep doing the best you can but get your resume ready and find another job. This is not always an option, you might be in a geographic location where this in not an option at all. But if it is an option, in this type of a scenario without any influence for the sake of your personal passion and ambition you are better off some place else where you can add value and achieve professional success.

Webbing Yourway

Do you believe that a person who focused on the technical in and out of the analytical tools, had a job that did nothing but implementation and training users how to use the tool, is at a disadvantage to those those that only use the tools to drive insight / reporting but cannot tell you how the tools work?
If yes, why do you think this is the case and do you think it is fair??

It is one of those cases were we have to define what disadvantage really means.
If you consider disadvantage to be having a limit on how high your salary can be and how high your influence on the business side can be then yes, I do believe that having a job that is only focused on implementation is a disadvantage.
But if you are at your happiest doing a job that is technically challenging and allows you to solve difficult data collection and data processing challenges, then it is not a disadvantage. You are doing what makes you happy. Is there anything more important?
As to why I consider it to be a disadvantage (with the above mentioned definition)… Analysis is an incredibly difficult challenge not because it is hard to use the tools, it is hard because you have to be comfortable with ambiguity, you have to deeply understand business strategy, you can't just stop at data puking rather you have to identify actions to take (which means big network of people relationships and business savvy) and compute impact and then recommend things that will work (or you are out of a job). These jobs also mean, for better and for worse, more interfacing with senior management and influencing them (in your technical job you won't as much, even as your job is important), and that does matter a lot.
So, those jobs will pay more, will allow you to drive more change than a job that is simply implementation and tools training.
For more on this, and salary structures and job promotion options, please see this post: Analytics Career Advice: Job Titles, Salaries, Technical & Business Roles.
Kara Martens

What is the best way to start really learning Google Analytics, beyond the basics? Certification? Specific reading materials? or just old-fashioned hands-on training??

If you simply want to learn how to use Google Analytics, your very first stop is the Google Analytics Academy, learn all the material in the Digital Analytics Fundamentals course and proceed to take your Google Analytics Individual Qualification (IQ) test.
I do believe that tools training can take your career forward, but less far than you might desire. You want to actually get good at analytics. The business of analysis. Transforming data into insights. And all that good stuff.
In that case seek books, blog posts, certifications that teach you how to think about analysis. This blog is a good start, :), but there are others. I link to some in the right navigation. You are welcome to consider my book Web Analytics 2.0 (which is not tool centric).

In terms of certification, I'm biased but I do recommend the Web Analytics Master Certification program at Market Motive (my start-up) that focuses on the art and science of analysis (and not reporting or a particular tool).
This blog post shares other practical tips, books and certification options: Web Analytics Career Guide: From Zero To Hero In Five Steps!
Josh Thomas

Thanks for everything you're doing for the community. As a B2B marketer looking to get more heavily involved in web analytics, I'm looking for a place to start – specifically your books.
As a beginner, should I plan to start with the slightly older An Hour a Day, or is that information already in or updated within your second book Web Analytics 2.0? ?

Hello Josh. I recommend skipping Web Analytics: An Hour A Day and just jumping to Web Analytics 2.0 (chapter 5 specifically provides advice on B2B and non-ecommerce websites).
Please also see the post above titled Zero to Hero, I believe you'll find it to be of value. And please see the Unmissable Articles listed on the bottom right of this post.
^ Rampant Speculation
Suzanne van Tienen

To what extent do you personally believe unique user (cross-device) and persona based analytics will succeed – and stick??

Let's get this out of the way: The world already lives in a multi-device, multi-channel world. It is silly, even today, to pretend otherwise. Your current, today, right this very moment, digital analysis should be based on person-based analysis.
Not people-based, a euphemism I use to refer to small groups of "persons" where you can't identify any one person. Person-based, where you can track a person and their behavior across devices and channels. Digital first. Digital and real-world in the near future.
How likely is this?
See my reply above to Joseph Boisseaux where he, rightly, complains about all of still being stuck with last-click attribution. And switching away from that is actually really easy, and businesses still refuse.
So person-based analysis will take a long time. Initially it will just be technical challenges (it is really hard to implement a unique user_id tied to one person, no matter easy analytics tools say it is). Then there will be challenges related to privacy and government rules (unclear at the moment, and if they become clear what their impact might be).
Does this mean you should not try?
No. You are making wrong decisions already by not focusing on person-based analysis. Every little step you take away from visit-based analysis makes you less wrong every day. And that is totally worth shooting for!
Let's end on that note of optimism.
As I'd mentioned at the start of this post, each question above could have a slightly different answer. I would love to have you jump in and help the folks who asked the above questions benefit from your experience and wisdom. Please share your insights via comments below.
Thank you. Merci. Arigato.

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"We empower people and businesses to realize their potential"

Craig Bailey
20 de febrero de 2013

    "We empower people and businesses to realize their potential"
    The most interesting part of this interview with Steve Ballmer is his answers to the following two questions from Jason Pontin:
    “ I understand Google’s vision for the future of computing....

"We empower people and businesses to realize their potential"

The most interesting part of this interview with Steve Ballmer is his answers to the following two questions from Jason Pontin:

    I understand Google’s vision for the future of computing. I know what Apple stands for. I used to understand what Microsoft stood for. I no longer know. What’s your vision for the company?

    This question quintessentially is a question of altitude. So, in this context tell me what Google and Apple stand for, and I’ll give you the equivalent.

    Google stands for indexing the world’s information in a useful fashion. That’s their claim to planetary utility. Steve Jobs said Apple made insanely great devices for consumers. That altitude.

    At that level of altitude, I’ll give you the slogan, and then I’ll sort of put just a little meat on it. We empower people and businesses to realize their potential. And to expand, I would simply say we’re about defining the future of productivity, entertainment, and communication. In the new world, software is going to have to come in kind of an integrated form—or at least a well-designed form that includes cloud services and devices.

Ballmer says “we’re about defining the future of productivity, entertainment, and communication”. I think that’s a good goal, but I don’t think Microsoft are really understanding the needs of the user. Windows 8 for example, has been a productivity killer for me and many others. 

What are Your Goals for the Next 30 Days? & You Can't Do Everything First.

Greetings!

Three key ingredients to a successful business include having a focus, prioritizing what is important and taking action. Without these, you will keep spinning your wheels. This month's newsletter discusses how to achieve greater success by focusing on the action steps required to take your business from where it is now to where you want it to be in the future.

Speaking of priorities, November is a great month for an annual goals review. We take a look back at the objectives that were set for 2012 and see what worked, what didn't and why. From there, we shift our focus to the overall organizational and personal goals for 2013.

Warmest wishes for a wonderful holiday season!
Best,

Diane

Diane Yochelson Peak Impact, LLC diane@peakimpact.us www.peakimpact.us 301-525-5516

What are Your Goals for the Next 30 Days? Today's small business owner often wears a number of different hats. How many of you act as the CEO, the general manager, the accountant, the salesperson, the computer technician, the secretary, the receptionist, etc.? Sound familiar? Many entrepreneurs try to chase too many targets at once and end up overwhelmed rather than focusing on their business. They spend all their energy carrying out daily tasks leaving little time for the most important part of their day - their own business! To avoid this, spend some time focusing on your business and decide which strategies will be most helpful in developing your own marketing plan. In order to grow and succeed in your business, you first need to have a crystal clear idea of what you want to do and where you want to go. In other words, have you defined your objectives? And more importantly, have you put them in writing?            Writing your objectives on a weekly basis and being very specific in each area of your business can give you the opportunity to create strategic alliances with other entrepreneurs, triple your database, increase your revenue, and maybe even leave time for writing that book you've always talked about. You can make your big dreams a reality! When you write your objectives on a weekly or monthly basis, it makes you actually work on them and act faster. If you are not specific and just say, "I will have money, or I will have more clients," then yes, these things will come, but the question is "when"? You don't have any deadline to accomplish them by! But, if you decide that by December 30th you will have 6 new clients, you will then do something in order to get those clients, instead of praying or waiting to see if this will happen. At a recent networking event, I asked some of the participants, "What are your goals for the next 30 days?" Some answered without hesitation, while others had to think about it. And one person responded, "Thanks for reminding me that I need to work on my goals, I had actually forgotten about it." I found that the best way to incorporate time for your objectives and marketing plan is to set up an appointment with yourself. And whatever happens, even if there is a client emergency, never cancel this appointment. It is critical that once a month or once a week you schedule an hour or two working on your business, focusing on: strategies to get more clients, new products or services to offer, special campaigns to make more sales and writing articles for your newsletter, newspapers, or ezine directories to promote your business. The more links you get, the more traffic you will receive on your website. Do you have a newsletter? This is the easiest and cheapest way to communicate on a regular basis with your clients and prospects in order to promote and grow your business. This can be another objective for the next 30 days. Take the time to plan strategies that will help grow your business. Consider yourself as your most important client. Do for yourself what you do for your clients. Your business needs all your attention, all your energy, and all your dedication. Your future and your success depend upon it (back to top)

You Can't Do Everything First Trying to decide which of 15 or 20 options to pursue can be frustrating, especially if all of them appear to be good choices. Let's take an example that we often see on the Internet. How many eBooks have you bought within the last six months? Of that number, how many of them tell you how to market or to make money online? If a book is any good, you'll be impressed; you'll say, "Yeah, I can do this." But then, after a few days, you'll read another really great sales letter, and feel that you really, really need the knowledge in this new offering. Then, you'll buy yet another eBook, and you'll again be impressed: "Yeah, I can REALLY do THIS." This cycle is being repeated over and over every day all around the Internet. This may have happened to you. I've done it. Lots of people have. So there you sit with perhaps dozens of books, all good, dozens or even hundreds of affiliate offerings, some excellent, and page after page of website ideas, all interesting. In fact, you've got so many options that you may not know what to do first. If all your options are good, then it doesn't really matter which one you choose first. Throw a dart if you have to, but move. Make a decision. Get yourself into motion. For many people, getting into motion means you'll be stepping into unfamiliar territory, doing things you've never done before. So what? At least it's interesting and exciting. But never terrifying! If you think starting your very first business is terrifying, you need to think again. Wrestling a grizzly bear is terrifying. Falling from an airplane without a parachute is terrifying. But starting a business? Nah ... that's not scary; it's just unfamiliar. And right there we have the main reason most people lock up when they face a long list of options. It's unfamiliar ground, so they think they don't know how to choose. Here's a strategy for taking the terror out of decision making. Take that long list of options. Perhaps there are 15 items on it, and you've never done any of them before. Once you've examined all the items on the list, do this: Decide if all the items are REALLY about equal. If there are any that clearly don't measure up, cross those off. You'll still be left with lots of choices. Let's say you're left with only 10 items on your list. Take out a new sheet of paper. Write item number one on it, the first item from your original list. Okay, that's it. That's your new list of options - just one item. We've already agreed that all the choices are more or less equal. So now you've got your action agenda. One item. No more indecision. Now just go do it. And those other 9 items? They'll be there waiting when you get done with the first task. See how easy decision-making can be? (back to top)

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Barcelona: HP Discover 2013 live coverage.

HP Discover 2013 live coverage: News, photos and analysis from Barcelona

BusinessFeatures09 Dec 2013 by Paul CooperPaulMCCooperpaul@itproportal.com

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HP Discover Barcelona has become one of the must-attend enterprise conferences of 2013, featuring hundreds of sessions covering the hottest topics in the IT industry today – big data, converged cloud, mobility, security, risk management and more.
With 10,000 attendees pouring into the Fira de Barcelona Conference Centre in Grand Via (the second largest conference centre in Europe), over 75 sponsors, 35 industry analysts and 500 sessions taking place over two-and-a-half days, this is definitely not one to miss.
As the hosts put it:
"HP Discover is your best opportunity in 2013 to learn how to put HP innovation to work for you. More than 7,000 IT executives, managers, architects, engineers, and solution experts from around the world will gather at HP Discover to explore technology developments, strategies, and best practices. Featuring hundreds of business and technical sessions, HP Discover will equip your organization to convert data into value, technology into solutions, and ideas into economic and social impact."
Be sure to check out the official agenda, as well as the full session and demo catalogue, available on the HP website.
To keep you up to date with the action, ITProPortal is bringing you live commentary, photos and analysis from Barcelona, as well as all the breaking news as it lands, so stick around.

• 10 December
• 18:35
  Stay tuned for tomorrow, as we've been told that there are some exciting developments in everyone's favourite: the cloud!
• 18:33
  We started the day with a bang, and we ended it with one - as a HP executive threw the new EliteBook onto the floor to demonstrate its toughness. We didn't actually get to see them turn it on afterwards, and it's not like HP can't afford to just break one... but it got everyone's attention nonetheless.
• 18:32
  Ooh, shiny!
  
• 17:23
  If this BIOS is attacked by malware, it repairs itself!
• 17:23
  BREAKING: HP self-healing BIOS announced. "We believe that no other competitor can achieve this, as it's hard-wired into the hardware."
• 17:21
  BREAKING: HP Business Desktop MIni released. All the power of a desktop in a processor that fits into the palm of your hand. Looks pretty impressive.
• 17:19
  BREAKING: HP Spectre 13 Pro laptop also announced. 13.3in screen. Slim and powerful, apparently. 
• 17:18
  BREAKING: HP EliteBook Folio 1040 announced. 15mm thin, built to withstand extreme shock, and tested to military standards of toughness.
• 14:40
  If you think the announcements are over, I have it on good authority that they are not! Apparently there are a whole slew of new products being announced tomorrow. You crazy, HP!
• 14:14
  Not to mention our breakdown of the Earth Insights project. Could big data analytics save the world? HP seems to think so.
• 14:13
  And don't forget to check out our interview with Tom Joyce, senior vice president of HP Converged Systems, where we talk to Tom about HP's advancements in converged systems, and what that could mean for enterprise and small businesses.
• 14:11
  So what do the new Converged Systems and Converged Storage releases mean for business? Find out here.
• 14:10
  Absolutely cracking keynote by Meg Whitman. Stick around for more updates as they come in.
• 14:09
  
• 14:06
  If you remember nothing else from Discover, remember this: "We are here to be the best technology company ever. So challenge us. bring us your goals, bring us your unsolvable problems. Let's build a better enterprise together."
• 14:05
  Whitman: "We know you're being drawing into disciplines that you're not familiar with. You're experiencing increasing pressure, too: time pressure, cost pressure, pressure to get things to work. But HP is there with you. Consider us as an asset in your organisation. We're happiest when you look like superman."
• 14:04
  You ever think: "I can't wait for the dawning golden age of IT, but right now I just want my Wi-Fi to work"?
  That's me right now.
• 14:03
  John Herbert, CIO of 2oth Century Fox joins Whitman on the stage.
  "What an incredible company," Whitman tells him. "What a legacy."
  Something tells me we're not meant to confine that verdict to 20th Century Fox?
• 14:03
  Weird and pointless montage of 20th Century Fox movies, from the Sound of Music to James Bond to Avatar. What are you claiming credit for, HP? Did they shoot Indiana Jones in the converged cloud?
• 14:02
  This is the infrastructure of HP, which they think  gives them the best vantage point to help you with yours. Look familiar to anyone?
  
• 14:00
  Hinshaw: "Our IT team was so astonished when we brought out moonshot, the 95 per ent reduction in space that it required that they actually come to me and said, 'we think we can go down from 6 to 4 data centres.' And certainly, we will never build another data centre again. That's the power of Moonshot."
• 14:00
  Now a talk from John Hinshaw is Executive Vice President of Technology & Operations at Hewlett-Packard.
• 13:59
  Whitman: "Photonics uses photons in light instead of electrons in copper wire. We have a solid road map to get 6TB per second over photonic networks. In that architecture, you can transfer 4 days of digital video in 1 second."
• 13:58
  "90 per cent of the energy used in computing is used moving data from the processor to storage and back again. We are quickly reaching the limits of what this architecture is capable of handling. We need a new architecture for the digital age."
• 13:56
  
  Whitman: "We have the cloud that companies can rely on. no other company has the sinews, no toher company has the experience in hardware, software and services. We make it, we back it, we service it."
• 13:25
  Whitman: "If the cloud were an independent country, it would be number 5 in the worldwide ranking of energy consumption. That's after, the US, Russia, China and India. Japan is number 6. To put it another way, the cloud uses five times the amount of energy as Spain. This is simply not sustainable. We have to make better use of the electricity we've got."
  
  Crazy!
• 13:25
  "You might not be used to the view from the bridge - but there is a storm coming. IT managers are being thrust into new areas of expertise, and new areas of technology that weren't part of the job description 10, 5, or even 2 years ago. But HP is here to help. You know this reality better than anyone else, because you live it every day."
• 13:20
  Whitman: "IT is no longer just about keeping the computers running. It can make the difference between whether your company will sink or swim in the world of business."
• 13:20
  "IT is now more important than ever. You're no longer down in the engine room - you're up on the bridge with the captain, scanning the horizon."
  If there's one thing that's sure to get applause at a tech conference, it's Star Trek analogies.
• 13:20
  "We believe we're at the next big shift in technology. We're ahead of the big shift in IT, because we know that it's really a shift in business. These shifts happen once every 5-10 years. I witnessed one of those shifts very clearly when I was at eBay. And when they happen, they change everything."
• 13:19
  
• 13:18
  Whitman: "What else do you want in a partner? You want someone who's here today, but is also going to be here tomorrow. And let me tell you - Hewlett Packard is here to stay."
  There's a steady gathering of applause.
• 13:17
  Whitman: "We're helping you make sense of the IT world of today, and we're helping to build the IT world of tomorrow - because we know most of you have one foot in both."
• 13:17
  Whitman: "I've come to Barcelona to show you how HP is helping its customers. I've personally met with over a thousand customers around the world, and everywhere I go, I heard one message - you want HP to win. You want us to continue to bring you solutions that help save your problems."
• 13:08
  HP CEO Meg Whitman on the stage!
• 13:08
  Packed hall!
• 13:06
  "We're creating a Mount Everest of new data every day."
  Is that the new way of measuring data?
• 13:03
  Attendants zipping down the aisles on electric unicycles. A conference full of surreal moments...
• 13:01
  Meg Whitman's keynote is about to start!
• 12:22
  Had some great conversations today, with Jonathan Dove of HP Enterprise services, about the Earth Insights project, as well as Chris Selland, vice president of Vertica, about big data. Stay posted for those interviews!
• 09:21
  BREAKING: HP announce HP Earth Insights, a collaboration with Conservation International to create an "early warning system" for species extinction. Could big data analytics save the world? 
• 08:54
  The laid-off workers are handing out leaflets outside, accusing HP management of "compromising the quality of HP products and technicians" by promoting a policy of staff reductions.
  
• 08:52
  Today's proceedings started with a bang, as groups of protesters gathered outside the Fira de Barcelona centre, letting off fire crackers, chanting, waving flags and playing what at least sounded like communist workers' tunes over a crackly tannoy. They're protesting against recent massive layoffs by HP, in which 28,000 workers have been cut from the workforce since 2012.
  
• 08:44
  And we're back, for day 2 of HP Discover in Barcelona.
• 16:36
  Just spoke to Tom Joyce about big data, SMBs and what the future holds for Converged Systems. Stick around for a full interview!
• 15:48
  Stay posted for a press briefing with Tom Joyce himself, Senior Vice President and GM, Converged Systems.
• 15:48
  Phew, a crazy hour and a half! Now we break out into talks.
• 15:48
  Scott: "we have extensive abilities to encrypt data at rest, and that's an increasing demand of our clients."
• 15:48
  Now for a quick Q&A.
  
  Joyce: "best of breed is different from market-leading. Leading the market is a heritage from what you did in the past, but best of breed is having the greatest capacity right now. "
• 15:47
  HINT: Major announcement hinted around flexible capacity service!
• 15:47
  BREAKING: HP StoreAll Archive released!
• 15:47
  How often have you heard these, eh?
  
• 15:46
  "StoreOnce Backup reduced our storage administration costs by 50% and backup window by 70%, so we could maintain around-the clock operation" - Thomas Poulsen CIO of EETIF
• 15:46
  BREAKING: HP announces HP StoreOnce Backup Family.
• 15:46
  Pronounce your T's man! Were you brought up by wolves?
• 15:45
  "If a customer lost 600TB of data with our competitors, the recovery time is up to 80 hours. That could cost you your entire business."
• 15:45
  "Over 90 per cent of all data ever collected by private companies was collected over the last two years."
  Also: the value of time for an average enterprise is around 250,000 Euros an hour. Crazy!
• 15:45
  Scott: "Changing nothing risks everything."
• 15:45
  
• 15:44
  Scott: "it's been a bad day for EMC and Cisco, and I'm about to make it a lot worse."
• 15:44
  Now on to David Scott, Senior Vice President and General Manager of Converged Systems.
• 15:44
  Joyce: "We're one company. We're HP. We have control over our whole production line. We can do this project at about 25 per cent lower than our competitors. And we have a much lower cost per VM."
• 15:44
  "Their utility payment model allows users to add scale and when it's needed."
• 15:43
  Joyce: "These converged systems can work about twice as fast as their competitors, while costing up to a quarter less."
• 15:43
  More rolling supercomputers.
• 15:43
  HP Converged Systems 700 and HP Converged Systems 300 announced - exciting times!
• 15:43
  Surreal moment as the new converged systems supercomputer edges out from behind a curtain with the two-strings Jaws theme playing.
  Joyce: "I don't know if you hear that, but if I was VCE I'd get out of the water."
• 15:43
  "Sharks are designed to complete their mission."
• 15:42
  
• 15:42
  HP reveals that it has been working on a super-secretive "project shark". Gummy sharks explained!
• 15:40
  "Setup mistakes are what happen when too many people are touching a project and adding customisations. Customers want to move past complex and custom and into standard and simple"
  "Customers want a truly simple virtualization machine."
• 15:40
  
• 15:38
  Joyce: "We've shipped more infrastructure for virtual machines than any other companies in the history of IT. We know what we're doing."
• 15:38
  Now Tom Joyce is coming on to speak to us, the Senior Vice President and GM, Converged Systems at Hewlett-Packard!
• 15:38
  "By our DNA, we are a partnering organisation. We work together with our partners to deliver great solutions for our customers."
• 15:38
  "We have a comprehensive set of services - more comprehensive than any other vendor in the marketplace."
  Is that true?
• 15:37
  
• 15:36
  "It's not just about better software and better hardware, it's about getting those services out there. It's about providing 24/7/365 pro-active support with our services."
• 15:35
  "The converged cloud is not simply a private cloud. It's inside the firewall as well as outside the firewall."
  "Our partners tell us 'you've got the best services, you've got the best services', but we want to see those brought into an integrated service."
• 14:45
  "We have a dream of converged infrastructure that is not just isolated, brittle silos of infrastructure."
• 14:38
  "Solutions aren't just about a software or hardware packages, or a services infrastructure. Solutions are about all three."
• 14:16
  HP: "We're asking the big questions - what if? and what now?"
• 14:12
  Pity about all the popcorn rustling.
• 14:11
  Very Apple-ish opening video. 
• 14:11
  Very Apple-ish opening video. 
• 14:10
  Popcorn and gummy-sharks? HP saying "sit back and enjoy the ride". And also aren't sharks cool?
  
• 13:55
  In little over an hour, we'l be hearing firsthand about all the breaking news to come out of HP Converged Systems.
• 13:53
  While you're waiting for the action to start, why not check out the official agenda, as well as the full session and demo catalogue, available on the HP website.
• 13:50
  From HP:
  "HP Discover is your best opportunity in 2013 to learn how to put HP innovation to work for you. More than 7,000 IT executives, managers, architects, engineers, and solution experts from around the world will gather at HP Discover to explore technology developments, strategies, and best practices. Featuring hundreds of business and technical sessions, HP Discover will equip your organization to convert data into value, technology into solutions, and ideas into economic and social impact."
• 13:49
  Over the next two and a half days, we'll be bringing you up-to-the-minute coverage of all the breaking HP news tipped to be released this year, plus photos and a breakdown of what this means for business, customers and IT managers.
  By the looks of it, last year's conference was quite a show!
  
• 13:43
  
• 13:39
  Welcome HP Discover in Fira Barcelona - the second largest conference centre in Europe. It's like ten aircraft hangers all in a row - pretty impressive!

Read more: http://www.itproportal.com/2013/12/09/hp-discover-2013-live-coverage-news-photos-and-analysis-barcelona/#ixzz2n8Mu0PF0