Must See HDTV (January 4th - 8th)

While we're disappointed about some of the instant-classic bowl games we missed including in the listings during our extended New Year's break, we figure also skipping over the premieres of Work It and The Biggest Loser evens things out. Check below for the highlights remaining this week, followed after the break by our weekly listings of what to look out for in TV, Blu-ray and videogames.

Portlandia
If you're looking for a comedy that's a bit different, check out IFC's satirical take on hipster culture, although you'll probably need a subscription to the New Yorker as well as bookmarks for Pitchfork and Hype Machine to get the jokes. It stars and is written by Fred Armisen and Carrie Brownstein, whose characters travel through a slightly more absurd caricature of Portland, Oregon than the one that really exists, although it does star the real city mayor as the assistant to the mayor. It's a niche show, but if you get it, you'll get it. Check out a clip of what happens when the characters decide to watch just one episode of Battlestar Galactica embedded after the break.
(January 6th, IFC, 10PM)

Saturday Night Live
While SNL can be hit or miss, we're always intrigued when the host isn't just another actor, and this week the show features Charles Barkley. This could either be fantastic or turrible (c) Barkley, but we've just got to see it either way. Kelly Clarkson will also be in attendance, this information may or may not be relevant to your interests.
(January 7th, NBC, 11:30PM)

The Firm
With a plot that begins ten years after the events of the movie that starred Tom Cruise as lawyer Mitch McDeere, The Firm revisits John Grisham's most popular character as he and his family leave the witness protection program to start a new life. Of course, things just can't be so simple, and it appears he has stumbled on yet another law firm with a secret to hide. The new show premieres on NBC Sunday night, check out a preview trailer after the break.
(January 8th, NBC, 9PM)

Continue reading Must See HDTV (January 4th - 8th)

Must See HDTV (January 4th - 8th) originally appeared on Engadget on Wed, 04 Jan 2012 16:51:00 EDT. Please see our terms for use of feeds.

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from Engadget http://www.engadget.com/2012/01/04/must-see-hdtv-january-4th-8th/

Reports of 50" Apple Television in Jonathan Ive's Lab as Talk Heightens Ahead of CES

USA Today takes a look at the effect rumors of an Apple television set are having on expectations for next week's Consumer Electronics Show in Las Vegas, with the industry's existing players working hard to avoid to being caught flat-footed by Apple as mobile phone manufacturers in many cases were by the iPhone.

While rumors have pegged the Apple television set as offering Siri-powered voice recognition and control, the new report offers a few other tidbits of information on the project including claims that the company is working to launch models of at least 42 inches and that a 50-inch model is currently in the works in the its design studio.

Apple is said to be looking at a 42-inch or larger LCD TV with built-in Wi-Fi. Inside the locked-down studio of Jonathan Ive, senior vice president of industrial design at Apple, there's a slick 50-inch TV, according to the source who worked at Apple.
Early reports had claimed that Apple was looking at TVs in the 40-55" range, but a recent report from Digitimes claimed that suppliers were preparing components for smaller 32" and 37" models.

USA Today's report also summarizes some of the other expectations for an Apple television set, including Siri, an iOS-compatible processor supporting apps, AirPlay, and iCloud. But Apple reportedly continues to struggle with how to bring content to the new television set as it attempts to break free of the traditional cable TV model.

But a major roadblock for Apple along the way has been securing content needed to make an iTV succeed. The problems Apple is having securing content deals were described in an interview with a person who worked in the Apple TV group and verified by two television industry sources. All declined to be identified because of the confidential nature of the talks.

They say Apple has been unable to cut deals that would let it offer first-tier TV network programs for an à la carte iTunes TV service. That's seen as a key element to launching a revolutionary iTV.

With so many rumors pointing towards Apple's work on television sets, it's not surprising that company co-founder Steve Wozniak also believes that an effort is underway.
"I do expect Apple to make an attempt," says Apple co-founder Steve Wozniak, "since I expect the living room to remain a center for family entertainment, and that touches on all areas of consumer products that Apple is already making."
Even as Apple's plans remain under wraps and the subject of considerable rumors and speculation, it is clear that competitors are taking note of where the company is likely to go with its project, with today's report citing executives from Samsung, LG, and Microsoft all acknowledging the threat.
"We do not discount what they are going to do in the space — they are going to come on strong," says [Microsoft general manager of content acquisition and strategy Ross] Honey.


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Focus on Product, Not Fundraising

Not a week goes by where I meet with an entrepreneur that has an all to familiar problem — “I can’t raise seed money”.  Even in this environment where it seems like everyone is pulling in $10′s of millions of funding, there are still alot of companies that are having a hard time raising seed capital.  The next statement that I often hear, is “I’ve been so focused on fund raising over the past XX months, I haven’t spent  much time on  product/customer acquisition/etc.”  When I hear this,  it always concerns me.

The reality is, they’re not listening to the market and instead of spending time on what really matters — they’ve spent their time chasing every lead, introduction, and possible funding source — with little to show (except frustration and exhaustion).  Hopefully you have a great team with really relevant experiences, and  there are a few entrepreneurs that can raise money based on reputation alone, but chances are — pretty slim.   So what’s my advice?  It’s simple really:

  • Stop spending all of your time on fundraising.
  • Listen to the feedback — silence is deafening.
  • Focus your time and energy on building a disruptive and compelling product & start to get data to show validation.
  • Great product and some traction, the funding will come to you.

What should traction look like?  It doesn’t have to be 6 months of data, or millions of users.  It should be directional (IE: does the slope of the line head the right way with a 3 or 4 key data points).  Your goal is to have a thesis (not all of the answers), start to understand whats working and what’s not, and what levers you need to pull to make the business head in the right direction……yup, it’s all about reducing risk!  A few key data points I’d think about (and I always ask about!) and be able to show data against: (Note: not all are always applicable)

  • User acquisition rate and source (can you acquire users and are you buying them, or are they organic?)
  • Of those users, what is the daily/weekly/monthly actives (registered users alone, is totally uninteresting w/o this data)
  • Unit economics and conversion of free to paid users? (can you build layers of services on top of a freemium model?)
  • What’s the cost of acquisition?  LTV of a customer?  (ideally you’l show cost going down, value going up)

You shouldn’t expect to have mountains of data, but the more data you can provide — the better.   What creates compelling data? Great product!!  If you’re struggling to fund raise —Focus on a building a compelling & disruptive product, the fundraising will complete itself.

Editor’s note: Gus is part of BostInno’s insider network. This post first appeared on his personal blog.

from BostInno http://bostinno.com/2012/01/05/focus-on-product-not-fundraising/

‘Portlandia’ Gets a Second Screen With IFC Sync


IFC is teaming up with ClipSync to provide a live second-screen experience to accompany the season two of the cult comedy, Portlandia.

Dubbed IFC Sync, the platform will give users a social experience that takes place in real-time while the show airs on IFC.

Users log in to ifc.com via Facebook and chat in real-time with Facebook friends, answer trivia questions and unlock extra content during the half-hour show.

IFC Sync will debut alongside the second season premiere of Portlandia on Friday, Jan. 6 and 10p.m. ET/PT. For the first episode, show creators and stars Fred Armisen and Carrie Brownstein will be chatting with fans live and answering questions about the show.

IFC Sync is powered by ClipSync, a company that adds second screen and social experiences to video content. ClipSync has worked with IFC‘s sister network, Sundance Channel for some of its second screen endeavors, including Girls Who Like Boys Who Like Boys.

ClipSync tells us that what separates their second screen experience from competing offerings is that it is designed for use on multiple devices. Most second-screen apps are for tablets. ClipSync’s technology is designed to work in a web browser and can be used on laptops, tablets and mobile phones.

IFC is jumping into the second screen concept with Portlandia because of the social nature of the show and its audience. If you haven’t seen the show, it’s a mix of Little Britain, Tim and Eric Awesome Show (as well as Tom Goes to the Mayor) and Mr. Show, but with self-important Portland hipsters.

Are you a fan of Portlandia? Will you tune in online alongside the show? Let us know in the comments.

More About: ClipSync, ifc, IFC Sync, Portlandia, second screen, social tv

For more Entertainment coverage:

from Mashable! http://mashable.com/2012/01/04/portlandia-ifc-sync/?utm_source=feedburner&utm...

Did Twitter Predict the Iowa Caucus Better Than Pundits?


In the closest Iowa caucus the nation has ever witnessed, former Massachusetts Governor Mitt Romney edged out former Pennsylvania Senator Rick Santorum by only 8 votes. That’s not 8% of votes, it’s just 8 actual votes. No pundit could have predicted such a neck-and-neck finish.

But did Twitter see it coming?

Yesterday, we shared the results of our Twitter sentiment analysis, conducted by Globalpoint. Their weighted metric combined candidate tweet volume with the sentiment surrounding each candidate.

Information from Twitter matched up with pre-Iowa polling data from NBC/Marist, with one glaring difference: On Twitter, Rick Santorum was on fire.

National Poll vs. Twitter (Iowa Caucus)

Here are the results of the Iowa Caucus:

No, Twitter could not have predicted that Iowa would been won by a minivan’s worth of caucus-goers. But it did a much better job of anticipating Santorum’s excellent performance than the national polls accomplished.

Michael Urban, President of Globalpoint, said that many polls showed Santorum moving to the top tier of candidates, but didn’t have numbers even close to the 25% he gained in Iowa last night.

“Twitter is indeed a leading indicator of public opinion, but it leads polling data and elections by about two weeks,” Urban said. ”It’s important to view our results through that lens. [NBC Chief White House Corespondent] Chuck Todd noted this morning that if the Iowa caucus was held next week, Santorum would likely have won by seven points. We agree.”

Mashable will continue to examine Twitter’s efficacy in predicting electoral results throughout 2012. Have you noticed any trends or patterns in how Twitter can predict election results? Let us know in the comments below.

Image courtesy of iStockphoto, DSGpro

More About: 2012 presidential campaign, Iowa caucuses, republicans, trending, Twitter

from Mashable! http://mashable.com/2012/01/04/twitter-predict-iowa-caucus/?utm_source=feedbu...

Comcast, Disney TV deal opens up access on multiple screens, tightens VOD strings

A renewal of the carriage agreement between Disney and Comcast has extended the cable company's "TV Everywhere" model, allowing it to offer customers access to "70 services" including all the ABC, Disney and ESPN channels you can name on their TVs, computers and mobile devices. Comcast's blog post notes this access extends both in and outside of the home, a major sticking point for most of the live TV streaming apps offered by cable and satellite companies (with the obvious exception of Dish Network and its Sling integration) so far. Other news mentioned in the press release (included after the break) is that the ABC video on-demand access on Comcast's cable boxes is fast-forward disabled -- no ad skipping. Other than the existing WatchESPN which Comcast customers will now have access to, there are also WatchDisneyChannel, WatchDisneyXD and WatchDisneyJunior services on the way, a part of disney's own multiscreen initiative called TV+. One other note is that for the first time the deal covers retransmission fees for ABC-owned local stations, which used to be free. There's no word on exactly how much money is changing hands as a result, but we'll probably be able to look at our cable bills in the future and see the effect -- hopefully being able to pull in the latest Grey's Anatomy episodes on the go is worth it.

Continue reading Comcast, Disney TV deal opens up access on multiple screens, tightens VOD strings

Comcast, Disney TV deal opens up access on multiple screens, tightens VOD strings originally appeared on Engadget on Wed, 04 Jan 2012 14:50:00 EDT. Please see our terms for use of feeds.

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from Engadget http://www.engadget.com/2012/01/04/comcast-disney-tv-deal-opens-up-access-on-...

Can You Help Local Businesses Convert Social Media to Sales? The City of Boston Wants to Give You a $10K Grant

The City of Boston is looking for help from your startup, and they are ready to pay for it.

Most local companies are using Facebook and Twitter to engage their communities. Some of these, like Boloco, are wizards at the trade and require no external help. But plenty of others are having a tough time measuring results and ensuring a positive impact given the timely nature of social media. Boston based StartupBLVD is here to change that. They have recently teamed up with the City of Boston’s Office of Business Development (“OBD”) to help local businesses convert social media in to sales.

The Challenge, which is currently looking for local startups, will give you a $10k grant, visibility via City-sponsored press and events and a partnership with Boston Main Streets, which serves over 3,500 local businesses.

I spoke with StartupBLVD founder Enrique Shadah to get a little more insight into what the ideal candidates are. “We want a startup that of course has a product that currently works, but more importantly a startup that needs the city of Boston. In partnering with the city we are really trying to engage more startups in helping solve community issues.”

The best part of this program is that there can be multiple winners. “We are looking for startups that want to have a direct impact in their local community and don’t want to limit it to just one winner,” replied Shadah.

I am told that this is the first of many similar challenges that we can expect from StartupBLVD. StartupBLVD itself is in its earliest of stages and is aiming to be the “monster.com for companies.” “We want to help your company find opportunities, and there is no better place to look than local right now,” added Shadah.

This challenge is a great opportunity for an early stage startup to beta test or even soft launch a product with actual companies here in Boston. And with a $10k grant, you will be able to extend your runway well past the program.

Applications close on January 31st, sign up today.

from BostInno http://bostinno.com/2012/01/03/can-you-help-local-businesses-convert-social-m...

Top 5 VC Mentors and Early-Stage Investors in Boston [Study]

Over the last 3 months, numerous entrepreneurs building early-stage startups or applying for the TechStars Boston 2012 program, and a few who are new to Boston have reached out to me to get my feedback on the Boston VC community.

Most of their questions have revolved around 3 areas -

1.  Who are the “best” VC Partners?
2.  Who are the “best” Principals / Associates, who actually provide value and are not just gate keepers?
3.  Who are the “best” micro-VCs?

More often than not, when an entrepreneur asks me about the “best” this or that, I get the sense that she is asking me about who is likely to invest in her early stage startup. I try really hard to give an unbiased opinion on the VC ecosystem in Boston, derived from a combination of my personal experience and anecdotes from other early-stage entrepreneurs.

Furthermore, apart from talking about how different Boston VCs invest in early-stage companies, I also try to impress on the entrepreneur that some of the VCs are truly generous with their time, advice and introductions through their network; i.e. – they make an amazing effort to be great mentors!

To get a better sense of the Boston VC ecosystem, I created a 4-question survey to get a wider range of feedback on 4 questions -

  1. Which Boston VC (Partner) is the best mentor?
  2. Which Boston VC (non-Partner) is the best mentor?
  3. Which Boston Micro-VC (Partner) is the best mentor?
  4. Which Boston VC is most likely to invest in an early-stage startup?

I sent the survey to founders from the TechStars Boston 2009, 2010 and 2011 classes, and asked friends in the Boston early-stage startup ecosystem to Tweet out the URL between January 1st and January 3rd of 2012.

Here are the results from 100 responses to the survey:

1.  Which Boston VC (Partner) is the best mentor?

Winner:  Antonio Rodriguez (with 19% of the vote)

Note:  There were 17 VCs who had 1 vote each, and I’ve filed them in the “Other” category

2. Which Boston VC (non-Partner) is the best mentor?

Winner: Richard Dale (with 23% of the vote)

Note: There were 6 Principals / Associates who had 1 vote each, and I’ve filed them in the “Other” category

3. Which Boston Micro-VC is the best mentor?

Winner: Katie Rae (with 21% of the vote)

Note: There were 5 Micro-VCs who had 1 vote each, and I’ve filed them in the “Other” category. Also, 3 people answered “None” for this question.

4. Which Boston VC is most likely to invest in an early-stage startup?

Winner: Atlas Venture (with 27% of the vote)

Note: There were 3 VCs who had 1 vote each, and I’ve filed them in the “Other” category. Also, 18 people answered “None” for this question, which I find very insightful and telling.

So there you have it. Now, go get these great VCs and Micro VCs to be your mentors, and then convince them to invest in your company. Good luck!

Notes:  

  1. I focussed this survey on VCs and Micro-VCs.  The Angel Investors in Boston are an integral part of the early-stage startup ecosystem, and require a separate post.  That’s for another day.
  2. Atlas Venture (Jeff Fagnan, Fred Destin and Dustin Dolginow), Boston Seed (Nicole Stata), TechStars (Katie Rae and Reed Sturtevant) and Apricot Capital (Jennifer Lum) are all investors in Kinvey.  But I only get 1 vote. :)

Editor’s Note: Sravish is part of BostInno’s insider network. This post first appeared on his personal blog.

from BostInno http://bostinno.com/2012/01/03/top-5-vc-mentors-and-early-stage-investors-in-...

The feedback economy

Military strategist John Boyd spent a lot of time understanding how to win battles. Building on his experience as a fighter pilot, he broke down the process of observing and reacting into something called an Observe, Orient, Decide, and Act (OODA) loop. Combat, he realized, consisted of observing your circumstances, orienting yourself to your enemy's way of thinking and your environment, deciding on a course of action, and then acting on it.

OODA chart
The Observe, Orient, Decide, and Act (OODA) loop. Click to enlarge.

The most important part of this loop isn't included in the OODA acronym, however. It's the fact that it's a loop. The results of earlier actions feed back into later, hopefully wiser, ones. Over time, the fighter "gets inside" their opponent's loop, outsmarting and outmaneuvering them. The system learns.

Boyd's genius was to realize that winning requires two things: being able to collect and analyze information better, and being able to act on that information faster, incorporating what's learned into the next iteration. Today, what Boyd learned in a cockpit applies to nearly everything we do.

Data-obese, digital-fast

In our always-on lives we're flooded with cheap, abundant information. We need to capture and analyze it well, separating digital wheat from digital chaff, identifying meaningful undercurrents while ignoring meaningless social flotsam. Clay Johnson argues that we need to go on an information diet, and makes a good case for conscious consumption. In an era of information obesity, we need to eat better. There's a reason they call it a feed, after all.

It's not just an overabundance of data that makes Boyd's insights vital. In the last 20 years, much of human interaction has shifted from atoms to bits. When interactions become digital, they become instantaneous, interactive, and easily copied. It's as easy to tell the world as to tell a friend, and a day's shopping is reduced to a few clicks.

The move from atoms to bits reduces the coefficient of friction of entire industries to zero. Teenagers shun e-mail as too slow, opting for instant messages. The digitization of our world means that trips around the OODA loop happen faster than ever, and continue to accelerate.

We're drowning in data. Bits are faster than atoms. Our jungle-surplus wetware can't keep up. At least, not without Boyd's help. In a society where every person, tethered to their smartphone, is both a sensor and an end node, we need better ways to observe and orient, whether we're at home or at work, solving the world's problems or planning a play date. And we need to be constantly deciding, acting, and experimenting, feeding what we learn back into future behavior.

We're entering a feedback economy.

The big data supply chain

Consider how a company collects, analyzes, and acts on data.

The big data supply chain
The big data supply chain. Click to enlarge.

Let's look at these components in order.

Data collection

The first step in a data supply chain is to get the data in the first place.

Information comes in from a variety of sources, both public and private. We're a promiscuous society online, and with the advent of low-cost data marketplaces, it's possible to get nearly any nugget of data relatively affordably. From social network sentiment, to weather reports, to economic indicators, public information is grist for the big data mill. Alongside this, we have organization-specific data such as retail traffic, call center volumes, product recalls, or customer loyalty indicators.

The legality of collection is perhaps more restrictive than getting the data in the first place. Some data is heavily regulated — HIPAA governs healthcare, while PCI restricts financial transactions. In other cases, the act of combining data may be illegal because it generates personally identifiable information (PII). For example, courts have ruled differently on whether IP addresses aren't PII, and the California Supreme Court ruled that zip codes are. Navigating these regulations imposes some serious constraints on what can be collected and how it can be combined.

The era of ubiquitous computing means that everyone is a potential source of data, too. A modern smartphone can sense light, sound, motion, location, nearby networks and devices, and more, making it a perfect data collector. As consumers opt into loyalty programs and install applications, they become sensors that can feed the data supply chain.

In big data, the collection is often challenging because of the sheer volume of information, or the speed with which it arrives, both of which demand new approaches and architectures.

Ingesting and cleaning

Once the data is collected, it must be ingested. In traditional business intelligence (BI) parlance, this is known as Extract, Transform, and Load (ETL): the act of putting the right information into the correct tables of a database schema and manipulating certain fields to make them easier to work with.

One of the distinguishing characteristics of big data, however, is that the data is often unstructured. That means we don't know the inherent schema of the information before we start to analyze it. We may still transform the information — replacing an IP address with the name of a city, for example, or anonymizing certain fields with a one-way hash function — but we may hold onto the original data and only define its structure as we analyze it.

Hardware

The information we've ingested needs to be analyzed by people and machines. That means hardware, in the form of computing, storage, and networks. Big data doesn't change this, but it does change how it's used. Virtualization, for example, allows operators to spin up many machines temporarily, then destroy them once the processing is over.

Cloud computing is also a boon to big data. Paying by consumption destroys the barriers to entry that would prohibit many organizations from playing with large datasets, because there's no up-front investment. In many ways, big data gives clouds something to do.

Platforms

Where big data is new is in the platforms and frameworks we create to crunch large amounts of information quickly. One way to speed up data analysis is to break the data into chunks that can be analyzed in parallel. Another is to build a pipeline of processing steps, each optimized for a particular task.

Big data is often about fast results, rather than simply crunching a large amount of information. That's important for two reasons:

  1. Much of the big data work going on today is related to user interfaces and the web. Suggesting what books someone will enjoy, or delivering search results, or finding the best flight, requires an answer in the time it takes a page to load. The only way to accomplish this is to spread out the task, which is one of the reasons why Google has nearly a million servers.
  2. We analyze unstructured data iteratively. As we first explore a dataset, we don't know which dimensions matter. What if we segment by age? Filter by country? Sort by purchase price? Split the results by gender? This kind of "what if" analysis is exploratory in nature, and analysts are only as productive as their ability to explore freely. Big data may be big. But if it's not fast, it's unintelligible.

Much of the hype around big data companies today is a result of the retooling of enterprise BI. For decades, companies have relied on structured relational databases and data warehouses — many of them can't handle the exploration, lack of structure, speed, and massive sizes of big data applications.

Machine learning

One way to think about big data is that it's "more data than you can go through by hand." For much of the data we want to analyze today, we need a machine's help.

Part of that help happens at ingestion. For example, natural language processing tries to read unstructured text and deduce what it means: Was this Twitter user happy or sad? Is this call center recording good, or was the customer angry?

Machine learning is important elsewhere in the data supply chain. When we analyze information, we're trying to find signal within the noise, to discern patterns. Humans can't find signal well by themselves. Just as astronomers use algorithms to scan the night's sky for signals, then verify any promising anomalies themselves, so to can data analysts use machines to find interesting dimensions, groupings, or patterns within the data. Machines can work at a lower signal-to-noise ratio than people.

Human exploration

While machine learning is an important tool to the data analyst, there's no substitute for human eyes and ears. Displaying the data in human-readable form is hard work, stretching the limits of multi-dimensional visualization. While most analysts work with spreadsheets or simple query languages today, that's changing.

Creve Maples, an early advocate of better computer interaction, designs systems that take dozens of independent, data sources and displays them in navigable 3D environments, complete with sound and other cues. Maples' studies show that when we feed an analyst data in this way, they can often find answers in minutes instead of months.

This kind of interactivity requires the speed and parallelism explained above, as well as new interfaces and multi-sensory environments that allow an analyst to work alongside the machine, immersed in the data.

Storage

Big data takes a lot of storage. In addition to the actual information in its raw form, there's the transformed information; the virtual machines used to crunch it; the schemas and tables resulting from analysis; and the many formats that legacy tools require so they can work alongside new technology. Often, storage is a combination of cloud and on-premise storage, using traditional flat-file and relational databases alongside more recent, post-SQL storage systems.

During and after analysis, the big data supply chain needs a warehouse. Comparing year-on-year progress or changes over time means we have to keep copies of everything, along with the algorithms and queries with which we analyzed it.

Sharing and acting

All of this analysis isn't much good if we can't act on it. As with collection, this isn't simply a technical matter — it involves legislation, organizational politics, and a willingness to experiment. The data might be shared openly with the world, or closely guarded.

The best companies tie big data results into everything from hiring and firing decisions, to strategic planning, to market positioning. While it's easy to buy into big data technology, it's far harder to shift an organization's culture. In many ways, big data adoption isn't a hardware retirement issue, it's an employee retirement one.

We've seen similar resistance to change each time there's a big change in information technology. Mainframes, client-server computing, packet-based networks, and the web all had their detractors. A NASA study into the failure of Ada, the first object-oriented language, concluded that proponents had over-promised, and there was a lack of a supporting ecosystem to help the new language flourish. Big data, and its close cousin, cloud computing, are likely to encounter similar obstacles.

A big data mindset is one of experimentation, of taking measured risks and assessing their impact quickly. It's similar to the Lean Startup movement, which advocates fast, iterative learning and tight links to customers. But while a small startup can be lean because it's nascent and close to its market, a big organization needs big data and an OODA loop to react well and iterate fast.

The big data supply chain is the organizational OODA loop. It's the big business answer to the lean startup.

Measuring and collecting feedback

Just as John Boyd's OODA loop is mostly about the loop, so big data is mostly about feedback. Simply analyzing information isn't particularly useful. To work, the organization has to choose a course of action from the results, then observe what happens and use that information to collect new data or analyze things in a different way. It's a process of continuous optimization that affects every facet of a business.

Replacing everything with data

Software is eating the world. Verticals like publishing, music, real estate and banking once had strong barriers to entry. Now they've been entirely disrupted by the elimination of middlemen. The last film projector rolled off the line in 2011: movies are now digital from camera to projector. The Post Office stumbles because nobody writes letters, even as Federal Express becomes the planet's supply chain.

Companies that get themselves on a feedback footing will dominate their industries, building better things faster for less money. Those that don't are already the walking dead, and will soon be little more than case studies and colorful anecdotes. Big data, new interfaces, and ubiquitous computing are tectonic shifts in the way we live and work.

A feedback economy

Big data, continuous optimization, and replacing everything with data pave the way for something far larger, and far more important, than simple business efficiency. They usher in a new era for humanity, with all its warts and glory. They herald the arrival of the feedback economy.

The efficiencies and optimizations that come from constant, iterative feedback will soon become the norm for businesses and governments. We're moving beyond an information economy. Information on its own isn't an advantage, anyway. Instead, this is the era of the feedback economy, and Boyd is, in many ways, the first feedback economist.

Strata 2012 — The 2012 Strata Conference, being held Feb. 28-March 1 in Santa Clara, Calif., will offer three full days of hands-on data training and information-rich sessions. Strata brings together the people, tools, and technologies you need to make data work.

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from O'Reilly Radar - Insight, analysis, and research about emerging technologies. http://radar.oreilly.com/2012/01/the-feedback-economy.html?utm_source=feedbur...