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jerryking : monetization   16

Apple’s drive for world auto dominance spooks the industry - The Globe and Mail
GREG KEENAN, BRIAN MILNER AND OMAR EL AKKAD
The Globe and Mail
Published Friday, Mar. 20 2015,

Apple’s big advantage over traditional car makers is simple, yet hard to overcome, and it lies in the cloud.

The cloud consists of remote servers that store vast amounts of data and run applications, giving everyone on the planet with a connected device access to unlimited computing power essentially for free. It is also revolutionizing the way companies do business by instantly providing them with vast amounts of customer data. And it means Apple would not need to acquire car manufacturing capacity or build assembly and distribution networks in order to create chaos in the club.

It’s an advantage few traditional manufacturers, including auto makers, fully grasp, let alone have the ability to exploit.....“Apple thinks from the cloud out,” says Mr. McInerney, who would definitely line up for an Apple vehicle. At least then, he says, he would be assured of a better communications interface than the clunky one in his new upscale German model.

“If you’re an Apple or a Google, it allows you to use the same power to manage your supply chain that you use to manage your customers,” he says.

“That’s a revolution in thinking that allows you to identify all the cash-wait states [where money sits idle] and to collect a stunning amount of customer information in real time. Put the two together and you’re turning that information into cash at an accelerated rate. Car companies don’t think like that.”
automotive_industry  automobile  Apple  batteries  autonomous_vehicles  cloud_computing  connected_devices  layer_mastery  digital_first  data_coordination  incumbents  monetization  cash  customer_data  idle_funds  SMAC_stack  connected_cars 
march 2015 by jerryking
The Big Mystery: What’s Big Data Really Worth? - The CFO Report - WSJ
October 13, 2014 | WSJ | By VIPAL MONGA.

“Data is worthless if you don’t know how to use it to make money,” said Laura Martin, an analyst with Needham & Co. Information on individual users loses value over time as they move or their tastes change, she added. That makes data a perishable commodity and more difficult to value at any given moment.
massive_data_sets  valuations  data  Kroger  monetization  Nestlé  P&G  Nielsen  perishables  commodities  shifting_tastes 
october 2014 by jerryking
Deloitte: Companies Engage in ‘Hidden Market for Data Monetization’ - The CIO Report - WSJ
January 23, 2014 | WSJ | By Michael Hickins.

Companies are engaging in “a hidden market for data monetization,” and are starting to “trade data among themselves for mutual benefit,” according to John Lucker, Deloitte LLP’s market leader for advanced analytics and modeling. The question they still haven’t wrestled to the ground is how much is too much data, and when does trading data cause consumers to revolt.
data  monetization  exhaust_data  privacy  data_marketplaces  CIOs  hidden  latent 
february 2014 by jerryking
Making dollars and sense of the open data economy - O'Reilly Radar
by Alex Howard | @digiphile | +Alex Howard | Comment | December 11, 2012.

Any post-mortems that picked up on the broad challenges, problems. difficulties of monetizing open-data?
monetization  open_data  commercialization 
january 2014 by jerryking
Accessing Open Data via APIs: Never Mind the App, Is There a Market for That?
Mark Boyd, September 4th, 2013

But is the market ready to monetize? In Big Data: A Revolution That Will Transform How We Live, Work, and Think, authors Viktor Mayer-Schönberger and Kenneth Cukier argue that at present, those with “the most value in the big data value chain” are those businesses and entrepreneurs with an innovative mindset attuned to the potential of big and open data. While still in its nascence, “the ideas and the skills seem to hold the greatest worth”, they say. However, they expect:

“…eventually most value will be in the data itself. This is because we’ll be able to do more with the information, and also because the data holders will better appreciate the potential value of the asset they possess. As a result, they’ll probably hold it more tightly than ever, and charge outsiders a high price for access.”
data_scientists  open_data  massive_data_sets  entrepreneurship  start_ups  InfoChimps  Junar  mindsets  commercialization  monetization 
january 2014 by jerryking
Open data: Is there a business case? | ZDNet
By David Meyer for Communication Breakdown | September 18, 2012
open_data  monetization 
december 2013 by jerryking
Monetizing open data
September 21, 2012| Strata| by Jenn Webb

One of the big questions on everyone’s mind at this year’s Open Knowledge Festival in Helsinki, according to a report by David Meyer at ZDNet, is: Where’s the money in open data?

Ville Peltola, IBM’s innovation chief in Finland, told Meyer the situation is becoming frustrating, that he doesn’t understand why it’s so hard to properly open up data, or even just some of it. “You could have bronze, silver and gold APIs, where more data costs more,” Peltola said to Meyer. “It’s like a drug dealer. Maybe you have to solve this chicken-and-egg problem by giving samples of raw data.”

Meyer points out the real issue inherent in what Peltola is saying: “that large amounts of data are very valuable, and the companies that create them tend not to know how to realise the greatest value from them.” Peltola had an interesting idea to address this: “What if you have an internal start-up in your company tasked only with monetising your data?”

Chris Taggart, co-founder of OpenCorporates, made a more competitive argument for opening up your company’s data: it “exposes your competitors’ internal contradictions” and might inspire disruption, he told Meyer — “Most big, fat secure companies don’t have the confidence to disrupt themselves,” he said.
open_data  monetization  massive_data_sets  problems  challenges  intrapreneurship  chicken-and-egg  commercialization  APIs  disruption  complacency  contradictions 
december 2013 by jerryking
The Financial Bonanza of Big Data
March 7, 2013 | WSJ | By KENNETH CUKIER AND VIKTOR MAYER-SCHÖNBERGER:
Vast troves of information are manipulated and monetized, yet companies have a hard time assigning value to it...The value of information captured today is increasingly in the myriad secondary uses to which it is put—not just the primary purpose for which it was collected.[True, but this secondary or exhaust data has to be placed in the right context in order to maximize value]. In the past, shopkeepers kept a record of all transactions so that they could tally the sums at the end of the day. The sales data were used to understand sales. Only more recently have retailers parsed those records to look for business trends...With big data, information is more potent, and it can be applied to areas unconnected with what it initially represented. Health officials could use Google's history of search queries—for things like cough syrup or sneezes—to track the spread of the seasonal flu in the United States. The Bank of England has used Google searches as a leading indicator for housing prices in the United Kingdom. Other central banks have studied search queries as a gauge for changes in unemployment.

Companies world-wide are starting to understand that no matter what industry they are in, data is among their most precious assets. Harnessed cleverly, the data can unleash new forms of economic value.
massive_data_sets  Amazon  books  Google  branding  Facebook  Wal-Mart  Bank_of_England  data  data_driven  value_creation  JCK  exhaust_data  commercialization  monetization  valuations  windfalls  alternative_data  economic_data  tacit_data  interpretation  contextual  sense-making  tacit_knowledge 
march 2013 by jerryking
Monetize, Monetize, Monetize: Startups need to make money fast. - WSJ.com
February 6, 2013, 9:32 p.m. ET

Monetize, Monetize, Monetize

By DAVID WEIDNER
Like this columnist
commercialization  monetization  start_ups 
february 2013 by jerryking
With Smartphone Deals, Patents Become a New Asset Class - NYTimes.com
September 24, 2012, 1:21 pm4 Comments
With Smartphone Deals, Patents Become a New Asset Class
By STEVE LOHR

patents have become a new asset class.

Traditionally, patents sat on corporate shelves and were occasionally used as bargaining chips in cross-licensing deals with competitors. But that began to change in the 1990s, when technology companies like Texas Instruments and I.B.M. started to regard their patent portfolios as sources of revenue, licensing their intellectual property for fees.

Today, companies routinely buy and sell patents, mostly in deals that draw little attention, for millions of dollars instead of billions. The question, experts say, is how big the market will become.

“Patents are a tricky asset to trade,” said Josh Lerner, an economist at the Harvard Business School. “But there is clearly a huge amount of value in intellectual property. And I think what we’re seeing is the beginning of a lot more monetization and trading of intellectual property rights.”

A sizable specialist industry has developed to build the marketplace for trading ideas. The players include patent aggregators like Intellectual Ventures and RPX, patent brokers like Ocean Tomo and ICAP, hedge funds, investment banks and law firms.
smartphones  patents  intellectual_property  law_firms  asset_classes  Steve_Lohr  valuations  Ocean_Tomo  markets  monetization  portfolio_management  cross-licensing 
september 2012 by jerryking
New Rules for Bringing Innovations to Market
March 2004 | HBR | Bhaskar Chakravorti.

The more networked a market is, the harder it is for an innovation to take hold, writes Bhaskar Chakravorti, who leads Monitor Group's practice on strategies for growth and managing uncertainty through the application of game theory. Chakravorti argues that executives need to rethink the way they bring innovations to market, specifically by orchestrating behavior change across the market, so that a large number of players adopt their offerings and believe they are better off for having done so. He outlines a four-part framework for doing just that: The innovator must reason back from a target endgame, implementing only those strategies that maximize its chances of getting to its goal. It must complement power players, positioning its innovation as an enhancement to their products or services. The innovator must offer coordinated switching incentives to three core groups: the players that add to the innovation's benefits, the players that act as channels to adopters and the adopters themselves. And it must preserve flexibility in case its initial strategy fails.

Chakravorti uses Adobe's introduction of its Acrobat software as an example of an innovator that took into account other players in the network--and succeeded because of it. As more content became available in Acrobat format, more readers were motivated to download the program," he observes. "The flexibility in Acrobat's product structure and the segmentation in the market allowed the pricing elasticity that resulted in the software's widespread adoption."
HBR  innovation  networks  network_effects  rules_of_the_game  commercialization  monetization  product_launches  howto  growth  managing_uncertainty  cloud_computing  endgame  Adobe  uncertainty  switching_costs  jump-start  platforms  orchestration  ecosystems  big_bang  behaviours  behavioral_change  frameworks  sharing_economy  customer_adoption  thinking_backwards  new_categories  early_adopters  distribution_channels  work-back_schedules 
july 2012 by jerryking
PeteSearch: How to turn data into money
October 20, 2010 by Pete Warden. The most important unsolved
question for Big Data startups is how to make money. Here's a hierarchy
showing the stages from raw data to cold, hard cash:
(1) Data. You have a bunch of files containing info. you've gathered,
way too much for any human to ever read. You know there's a lot of
useful stuff in there though, but you can talk until you're blue in the
face & the people with the checkbooks will keep them closed. The
data itself, no matter how unique, is low value, since it will take
somebody else a lot of effort to turn it into something they can use to
make $. (2) Charts. Take that massive deluge of data and turn it into
some summary tables & simple graphs. You want to give an unbiased
overview of the info., so the tables & graphs are quite detailed.
This makes a bit more sense to the potential end-users, they can at
least understand what it is you have, and start to imagine ways they
could use it. (3) Reports; (4) Recommendations.
analysis  commercialization  data  data_driven  data_marketplaces  data_scientists  entrepreneurship  hierarchies  ideas  InfoChimps  massive_data_sets  monetization  value_creation  visualization 
july 2011 by jerryking
A Future for Newspapers - WSJ.com
MAY 24, 2007 | Wall Street Journal | op-ed by ANDY KESSLER

Google, Microsoft and others dropped over $10 billion to buy online ad-delivery companies in the last few weeks alone.
Andy_Kessler  media  newspapers  op-ed  P2P  future  digital_media  business_models  monetization 
april 2009 by jerryking
Firms Seek Profit in Twitter's Chatter - WSJ.com
MARCH 25, 2009 | The Wall Street Journal | by JESSICA E.
VASCELLARO

Companies are experimenting with ways to profit from Twitter's
popularity by trialing various business models that incorporate parts of
the free messaging service.
advertising  social_media  twitter  monetization 
march 2009 by jerryking
Twitter VC Laughs at the Idea that Twitter Has No Business Model - NYTimes.com
March 1, 2009, NYT, By LIDIJA DAVIS of the blog, ReadWriteWeb. References to another blog, Innovation Economy.
twitter  growth  business_models  monetization 
march 2009 by jerryking
globeandmail.com - Taking ideas to market: an insider's view
Oct. 16, 2007 G&M article by Charles Finlay profiling Avanindra Utukuri, president and CTO of Nytric Ltd.
product_development  business_development  ideas  manufacturers  innovation  Nytric  monetization  commercialization 
january 2009 by jerryking

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