exhaust_data   12

The résumé is dead: your next click might determine your next job | Guardian Sustainable Business
16 February 2017 | | The Guardian| Tim Dunlop.

The traditional CV and interview are being abandoned as firms use new forms of data aggregation to find employees. This new field of recruitment, dubbed workforce science, is based on the idea that the data individuals create while doing things online can be harvested and interpreted and to provide a better idea of a person’s suitability than traditional methods.

Whereas in the past employers might have been impressed with the school you went to, practitioners of workforce science are encouraging them to prioritise other criteria. A New York Times article on the topic noted: “Today, every email, instant message, phone call, line of written code and mouse-click leaves a digital signal. These patterns can now be inexpensively collected and mined for insights into how people work and communicate, potentially opening doors to more efficiency and innovation within companies.”

Organisations including Knack and TalentBin are providing companies with information that, they claim, better matches people to jobs. Peter Kazanjy, the chief executive of TalentBin, explained to Business Insider Magazine: “Résumés are actually curious constructs now because, for the most part, work and our work product is fundamentally digital. Sometimes you don’t even need [résumés]. The reality of what somebody is and what they do … is already resident on their hard drive or their Evernote or their box.net account or their Dropbox cloud.”
LinkedIn  résumés  Knack  TalentBin  Managing_Your_Career  job_search  exhaust_data  digitalization  recruitment  workforce_science 
february 2017 by jerryking
Wall Street’s Insatiable Lust: Data, Data, Data
By BRADLEY HOPE
Updated Sept. 12, 2016

One of his best strategies is to attend the most seemingly mundane gatherings, such as the Association for Healthcare Resource & Materials Management conference in San Diego last year, and the National Industrial Transportation League event in New Orleans.

“I walk the floor, try to talk to companies and get a sense within an industry of who collects data that could provide a unique insight into that industry,” he said.....Data hunters scour the business world for companies that have data useful for predicting the stock prices of other companies. For instance, a company that processes transactions at stores could have market-moving information on how certain products or brands are selling or a company that provides software to hospitals could give insights into how specific medical devices are being used......A host of startups also are trying to make it easier for funds without high-powered data-science staffers to get the same insights. One, called Quandl Inc., based in Toronto, offers a platform that includes traditional market data alongside several “alternative” data....
data  conferences  Wall_Street  hedge_funds  investors  unconventional  exhaust_data  sentiment_analysis  quants  private_equity  insights  Quandl  mundane  data_hunting  market_moving  unglamorous 
september 2016 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
Pulling More Meaning from Big Data
August 2013 | Retail Leader | By Ed Avis

"A.G. Lafley [Procter & Gamble's CEO] spoke of the two moments of truth," says John Ross, president of Inmar Analytics based in Winston-Salem, N.C. "The first occurs when a consumer buys a product, and the second when they use it. Much of the data today is about orchestrating and understanding those two moments. But two additional moments of truth are emerging to bookend Lafley's. One occurs when a consumer is planning to make a purchase. The other happens following use, when the consumer talks about his or her experience with the product. All of these activities leave a 'data wake' that describes how the consumer is moving down the path to purchase." (jk: going to assume that data wake = exhaust data).

Like most consumer packaged goods companies, Procter & Gamble relies on data to determine what consumers are looking for. "Consumer insight is at the core of our business model. We approach every brand we make by asking the question, 'What do people really need and want from this product? What does this mean to their lives?' Let me be clear – this is not casual observation. We employ teams of behavioral scientists, researchers, psychologists, even anthropologists to uncover true insight based on intensive research and exploration," said Marc Pritchard, P&G's global marketing and brand building officer, speaking at the Association of National Advertisers' 2012 Annual Conference....Most firms haven't advanced beyond localized analytics and don't fully capitalize on the existing data they have at hand – such as POS data, loyalty club data and social media traffic – according to a 2012 Deloitte study for the Grocery Manufacturers Association.
massive_data_sets  Sobeys  grocery  supermarkets  Safeway  P&G  A.G._Lafley  Kroger  point-of-sale  loyalty_management  customer_insights  insights  CPG  exhaust_data  psychologists  psychology  anthropologists  anthropology  ethnography  behavioural_science  hiring-a-product-to-do-a-specific-job  data  information_sources  moments  moments_of_truth 
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. 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  Bank_of_England  data  data_driven  value_creation  JCK  exhaust_data  commercialization  monetization  valuations  Wal-Mart  windfalls 
march 2013 by jerryking
Data Is the World
Aug 1, 2005 | Inc.com | Michael S. Hopkins.

Use your data. "Companies aren't taking advantage of the data they generate, Levitt says. "Often, data generated for one purpose is useful for another. Freakonomics describes the case of an entrepreneur selling bagels in corporate offices who kept meticulous records to track profits and loss—data that eventually yielded insights about white-collar crime and the effects of office size on honesty.
Ask different questions. The abortion-crime link revealed itself when Levitt thought to stop asking what made crime fall and try asking why it had risen so much in the first place. That led him to justice system practices in the 1960s, which led him to a statistical understanding of which individuals were likeliest to commit crimes, and ultimately to the question of why a large segment of that population seemed to have vanished.
Don't mistake correlation for causality. Innovative policing and a drop in crime happened simultaneously, but data proved the one didn't cause the other. (Be mindful of the feudal king who, having learned disease was greatest in regions with the most doctors, figured that reducing doctors would reduce disease.)
Question conventional wisdom. An idea that is both easy to understand and a source of comfort (such as the credit quickly given to innovative policing for cutting crime) should be especially suspect.
Respect the complexity of incentives. "You can't imagine, says Levitt, "all the ways humans will connive to beat a system.
Employ data against cheating. Just as companies don't sufficiently capitalize on the data they have access to, they aren't exploiting what Levitt calls "opportunities to think about fraud or theft in their businesses.
causality  correlations  data  data_driven  Freakonomics  incentives  exhaust_data  gaming_the_system  massive_data_sets  social_data  skepticism  questions  '60s  justice_system  cheating  conventional_wisdom  bank_shots  metadata  Steven_Levitt  insights  white-collar_crime  think_differently 
january 2013 by jerryking
International: Mining the urban data
Nov 21st 2012 | The Economist | Ludwig Siegele: deputy international editor, The Economist from The World In 2013 print edition
cities  urban  data  smartphones  smart_cities  London  Singapore  sensors  mit  SENSEable  exhaust_data  optimization  real-time 
january 2013 by jerryking
Why Big Data is the new competitive advantage
July / August 2012 | Ivey Business Journal | by Tim McGuire, James Manyika, and Michael Chui
competitive_advantage  McKinsey  massive_data_sets  exhaust_data 
july 2012 by jerryking
Enterprise RSS: Harvard Biz Review on CorpBlogging
November 03, 2004 | Harvard Biz Review on CorpBlogging | Allen Engelhardt.

Paul Kedrosky offers three practical steps your company should take to begin exploring syndication and some pointers to tools:

"First, make sure the executive team understands syndication and its implications.
Next, make sure your IT people keep syndication top of mind as the refine your systems and infrastructure. You are soon going to be a de facto broadcaster, and your technology infrastructure must be able to support that role.
Finally, think about what information you could feed. Consider what event data you generate, who would want it, and how you could benefit by syndicating it. Ask yourself, why not? "
syndications  data  HBR  Paul_Kedrosky  exhaust_data 
june 2012 by jerryking
Feeding Time
June 2004 | HBR | Paul Kedrosky

Every time eBay lists a new book, FedEx touches a package, or Procter & Gamble changes a price, the act generates data. But most of that information isn’t easily accessible, despite its immediate value to someone, somewhere. That’s about to change. Soon, any data-generating act, no matter how trivial it may seem, will be released over the Internet in real time to anyone who wants to know about it. This isn’t wide-eyed speculation. It’s already happening, and it will change how companies and their customers do business.

These broadcasts take the form of syndication feeds: customized information streams instantaneously distributed over the Internet.
HBR  Paul_Kedrosky  data  syndications  exhaust_data 
june 2012 by jerryking

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