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jerryking : noise   20

How Spotify’s algorithms are ruining music
May 2, 2019 | Financial Times | Michael Hann.

(1) FINAL DAYS OF EMI, By Eamonn Forde, Omnibus, RRP£20, 320 pages
(2) SPOTIFY TEARDOWN, By Maria Eriksson, Rasmus Fleischer, Anna Johansson, Pelle Snickars and Patrick Vonderau, The MIT Press, RRP£14.99, 288 pages
(3) WAYS OF HEARING, By Damon Krukowski, The MIT Press, RRP£14.99, 136 pages

In April, the IFPI — the global body of the recording industry — released its latest annual Global Music Report. For the fourth consecutive year, revenues were up, to a total of $19.1bn, from a low of $14.3bn in 2014. Nearly half those revenues came from music streaming, driven by a 33 per cent rise in paid subscriptions to services such as Spotify, Apple Music and Tidal...... It is worth remembering that 20 years ago, the IFPI reported global music revenues of $38.6bn. Today’s “booming” recording industry is less than half the size it was at the turn of the century.....The nadir for the recording industry coincided with the first shoots of its regrowth. ....In August 2007, the British record company EMI — the fourth of the majors, alongside Universal, Sony and Warner — was bought by private equity firm Terra Firma (Guy Hands, the fund’s founder and chairman) for $4.7bn; a year later, a Swedish company called Spotify took its music streaming service public. The former was, perhaps, the last gasp of the old way of doing things — less than four years after buying EMI, Terra Firma was unable to meet its debts, and ceded control of the company to its main lender, Citigroup. Before 2011 was out, the process of breaking up EMI had begun...EMI’s demise was foreshadowed before Hands arrived, with a blaze of hubris in the early 2000s. Forde, a longtime observer and chronicler of the music business recounts the “disastrous and expensive” signings of that era......Handspreached the need to use data when signing artists, not just the “golden ears” of talent scouts; data are now a key part of the talent-spotting process.

* to qualify as having been listened to on Spotify, a song has to have been played for 30 seconds.
* hit songs have become increasingly predictable, offering up all their pleasures in the opening half-minute. Their makers dare not risk scaring off listeners.
* for all the money that the streaming services have generated for the music industry, very little of it flows back to any musicians except the select few who dominate the streaming statistics,

.......On Spotify, music consumption has been reorganised around “behaviours, feelings and moods” channelled through curated playlists and motivational messages......The data Spotify collects enable the industry to work out who its market is, where it lives, what else they like, how often they listen to music — almost anything, really. It’s the greatest assemblage of information about music listeners in history, and it has profoundly altered the industry: it has made Spotify music’s kingmaker......when an artist travels abroad to promote a new album, the meeting with the local Spotify office is more important than the TV appearances or the newspaper interviews. ...Spotify enables artists to plan their band’s set lists so they can play the most popular song in any given city.............So what? What does it matter if one model of music distribution has been replaced by another.....It matters because Spotify has profoundly changed the listener’s relationship with music....Older musicians often wax about how, when you had to buy your own music as a kid, you listened to it until you liked it, because you wouldn’t be able to afford a new album for another month. Now you simply skip to the next one, and probably don’t give it your full attention. Without ownership, there’s no incentive to study...........Faced with the impossibly wide choice of Spotify, it becomes easier to return to old favourites — easier than when flicking through your vinyl or CDs, because the act of looking through your own music makes things you had not thought of in years leap out at you. Spotify actually makes people into more conservative listeners, a process aided by its algorithms, which steer you towards music similar to your most frequent listening.....The theme of Krukowski’s book is that the changes in the way the music industry works have been about controlling and eliminating excess noise. That’s in a literal sense and in a metaphorical one, too. Streaming has stripped music of context, pared it back to being just about the song and the moment....but noise is the context of life. Without noise, the signal becomes meaningless......The world of the old EMI was one of both signal and noise; where myths and legends could be created: The Beatles! Queen! The Beach Boys! Pink Floyd! It was never all about the signal. The world of Spotify is one of signal only, and if you don’t appreciate that signal within the first 30 seconds of the song...all may be lost
abundance  algorithms  Apple_Music  books  book_reviews  business_models  curation  cultural_transmission  data  decontextualization  EMI  gatekeepers  Guy_Hands  hits  indoctrination  iTunes  legacy_artists  music  music_catalogues  music_labels  music_industry  music_publishing  noise  piracy  platforms  playlists  royalties  ruination  securitization  signals  songs  Spotify  streaming  subscriptions  talent  talent_scouting  talent_spotting  Terra_Firma  Tidal  transformational 
may 2019 by jerryking
What You Need to Know to Pick an IPO
April 7, 2019 | WSJ | By Andy Kessler.
Dig up dirt on the competition and board members, and buy to hold long-term.......How do you know which IPOs to buy? No, not to trade—you’d never get it right. Lyft priced at $72, traded at $85 on its first day, then closed at $78, only to fall to $67 on its second day. It’s now $74. I’m talking about buying and holding for a few years. Yes I know, how quaint.

The trick is to read the prospectus. What are you, crazy? That’s a couple hundred pages. Well, not the whole thing. But remember, where the stock trades on its first day is noise....... So understanding long-term prospects are critical. Here are a few shortcuts.

(1) First, glance at the underwriters along the bottom of the cover. On the top line are the banks putting their reputation on the line. If the one on the far left is Goldman Sachs , Morgan Stanley or JPMorgan , you’re probably OK.
(2) open the management section and study the directors. Forget the venture capitalists or strategic partners with board seats—they have their own agendas. Non-employee directors are the ones who are supposed to be representing you, the public investor. And their value depends on their experience.
(3) OK, now figure out what the company does. You can watch the roadshow video, look at prospectus pictures, and skim the offering’s Business section. Now ignore most of that. Underwriters are often terrible at positioning companies to the market.......when positioning companies, only three things matter: a monster market; an unfair competitive advantage like patents, algorithms or a network effect; and a business model to leverage that advantage. Look for those. If you can’t find them, pass. Commodities crumble........read the Management’s Discussion and Analysis. Companies are forced to give detailed descriptions of each of their sectors and products or services. Then flip back and forth to the Financials, looking at the items on the income statement and matching them up with the operations being discussed. Figure out what the company might look like in five years. And use my “10x” rule: Lyft is worth $25 billion—can they make $2.5 billion after-tax someday? Finally there’s the Risk section, which is mostly boilerplate but can contain good dirt on competition.
(4) Put the prospectus away and save it as a souvenir. Try to figure out the real story of the company. Do some digging.
(5) My final advice: Never, ever put in a market order for shares on the first day of an IPO.
10x  advice  algorithms  Andy_Kessler  boards_&_directors_&_governance  business_models  competitive_advantage  deception  due_diligence  howto  IPOs  large_markets  long-term  Lyft  network_effects  noise  patents  positioning  prospectuses  risks  stock_picking  think_threes  Uber  underwriting  unfair_advantages 
april 2019 by jerryking
How do hedge funds learn new industries quickly? - Quora
Quickly' is very subjective and remember funds(hedge,mutual,pension,etc) do not need to know everything about a industry only to understand the drivers of what moves the stock. That is a massive difference between how a student approaches learning and a analyst, analysts aren't trying to know everything only what can make them money.

Exceptional People
They are used to covering certain sectors some may come from the sell side and covered maybe 15-30 stocks or the buy side and covered 40-60 stocks. Regardless of where they came from they are used to tracking and getting alot of information very efficiently. They are also willing to put in long hours and read/study anything that is needed. After a while(if they don't burn out) they become masters are managing huge information bandwidth.

Tools/Data
For accounting and raw data there are plenty of tools. Bloomberg is quite widely used and with a few commands/clicks you can have a excel sheet with all the data you can want about a companies financials.

Sell side
If you have a large enough fund and relationships on the sell side then they'll do all they can to get you up to speed very quickly. The sell side will have a team of analysts covering a industry/sector your intrested in and if your a good client then they'll spend time and teach you want you want to know.

Reduce noise/Very focused:
Great analysts are masters are reducing the amount of noise that comes there way. They filter emails and calls like crazy so there are less distractions. If your ideas don't make them money they will ignore you(regardless of how smart you are). If they are really good they won't even open your emails if you have not proven you add value to them.
hedge_funds  ideas  discernment  filtering  learning_curves  noise  signals  Quora  new_industries  sell_side 
november 2018 by jerryking
Getting smarter, knowing less
March 16, 2018 | FT | by Robert Armstrong.

The point is that for me, and perhaps most people, the main barrier to being smart is not what we do not know. It is the masses of things we know and mistakenly believe to be relevant.

My wife and I have been thinking about the next stage of our kids’ education. Being central-casting middle-class professional types, we hired an educational consultant to talk us through a range of state schools. She provided briefings about each school, crammed with facts about test scores, teacher turnover, class sizes, and so on.

Feeling slightly dizzy, I asked which bits I should pay attention to. She responded — with glorious honesty for someone being paid by the hour — that there was only one piece of information that really mattered: how many students are late or absent on a regular basis. If a school is the kind of place where almost everybody shows up and shows up on time, then it is the kind of place where kids and teachers can achieve a lot together. The rest is noise.

That comment made me smarter, not because it was a surprising revelation but because it allowed me to clear a lot of junk out of my head — and avoid putting a lot more junk into it. What we all need is the cognitive equivalent of decluttering guru Marie Kondo, who can help us to go into our own heads and throw out all the beliefs that have outlived their usefulness.
decluttering  problem_framing  signals  noise  information_overload  questions  smart_people  incisiveness  education  schools  pretense_of_knowledge  pay_attention  what_really_matters  work_smarter 
march 2018 by jerryking
With 125 Ph.D.s in 15 Countries, a Quant ‘Alpha Factory’ Hunts for Investing Edge - WSJ
By BRADLEY HOPE
Updated April 6, 2017

The firm is part of the forefront of a new quantitative renaissance in investing, where the ability to make sense of billions of bits of data in real time is more sought after than old-school financial analysis.

“Brilliance is very equally distributed across the world, but opportunity is not,” said Mr. Tulchinsky, a 50-year-old Belarusian. “We provide the opportunity.”

To do this, WorldQuant developed a model where it employs hundreds of scientists, including 125 Ph.D.s, around the world and hundreds more part-time workers to scour the noise of the economy and markets for hidden patterns. This is the heart of the firm. Mr. Tulchinsky calls it the “Alpha Factory.”....Quantitative hedge funds have been around for decades but they are becoming dominant players in the markets for their ability to parse massive data sets and trade rapidly. Amid huge outflows, traditional hedge funds are bringing aboard chief data scientists and trying to mimic quant techniques to keep up, fund executives say.

Some critics of quants believe their strategies are overhyped and are highly susceptible to finding false patterns in the noise of data. David Leinweber, a data scientist, famously found that the data set with the highest correlation with the S&P 500 over a 10-year period in the 1990s was butter production in Bangladesh.
quantitative  Wall_Street  PhDs  alpha  investors  slight_edge  massive_data_sets  signals  noise  data_scientists  real-time  algorithms  patterns  sense-making  quants  unevenly_distributed  WorldQuant 
april 2017 by jerryking
How to avert catastrophe
January 21, 2017 | FT | Simon Kuper.

an argument: people make bad judgments and terrible predictions. It’s a timely point. The risk of some kind of catastrophe — armed conflict, natural disaster, and/or democratic collapse — appears to have risen. The incoming US president has talked about first use of nuclear weapons, and seems happy to let Russia invade nearby countries. Most other big states are led by militant nationalists. Meanwhile, the polar ice caps are melting fast. How can we fallible humans avert catastrophe?

• You can’t know which catastrophe will happen, but expect that any day some catastrophe could. In Tversky’s words: “Surprises are expected.” Better to worry than die blasé. Mobilise politically to forestall catastrophe.
• Don’t presume that future catastrophes will repeat the forms of past catastrophes. However, we need to expand our imaginations. The next catastrophe may take an unprecedented form.
• Don’t follow the noise. Some catastrophes unfold silently: climate change, or people dying after they lose their jobs or their health insurance. (The financial crisis was associated with about 260,000 extra deaths from cancer in developed countries alone, estimated a study in The Lancet.)
• Ignore banalities. We now need to stretch and bore ourselves with important stuff.
• Strengthen democratic institutions.
• Strengthen the boring, neglected bits of the state that can either prevent or cause catastrophe. [See Why boring government matters November 1, 2018 | | Financial Times | Brooke Masters.
The Fifth Risk: Undoing Democracy, by Michael Lewis, Allen Lane, RRP£20, 219 pages. pinboard tag " sovereign-risk" ]
• Listen to older people who have experienced catastrophes. [jk....wisdom]
• Be conservative. [jk...be conservative, be discerning, be picky, be selective, say "no"]
Simon_Kuper  catastrophes  Nassim_Taleb  black_swan  tips  surprises  imagination  noise  silence  conservatism  natural_calamities  threats  unglamorous  democratic_institutions  slowly_moving  elder_wisdom  apocalypses  disasters  disaster_preparedness  emergencies  boring  disaster_myopia  financial_crises  imperceptible_threats 
january 2017 by jerryking
6 Ways Pretend Investors Differ From the Real Ones
NOV. 21, 2016 | The New York Times | By CARL RICHARDS.

* Have a long term plan
* Don't react to every single event that happens in the short term. Financial pornography is not 'actionable information' on which to make a decision about.
* Make changes to my investments based on what happens in my own life. If my goals change or there is a fundamental change in my financial situation, then I should consider an alteration.
* Real investors know that it takes a long time for a tree to grow, and it will not help to dig it up to see if the roots are still there. The same rule applies to investments. And because watching things get big slowly is not very exciting, real investors tend not to talk about that tree all that much.
* Real investors understand the difference between the global economy and their personal economy (aka micro economy) and choose to focus on the latter.
* Focus on the things I can control, like saving a bit more next year, keeping my investment costs low, not paying fees unless it’s necessary and managing my behavior by not buying high and selling again when prices are low.
howto  investors  advice  personal_finance  beyond_one's_control  habits  microeconomics  personal_economy  actionable_information  long-term  span_of_control  financial_pornography  patience  noise  discretion  global_economy 
november 2016 by jerryking
A field guide to lies : critical thinking in the information age : Levitin, Daniel J., author. : Book, Regular Print Book : Toronto Public Library
Year/Format: 2016, Book , 304 pages

It's becoming harder to separate the wheat from the digital chaff. How do we distinguish misinformation, pseudo-facts, distortions and outright lies from reliable information? In A Field Guide to Lies, neuroscientist Daniel Levitin outlines the many pitfalls of the information age and provides the means to spot and avoid them. Levitin groups his field guide into two categories--statistical infomation and faulty arguments--ultimately showing how science is the bedrock of critical thinking. It is easy to lie with stats and graphs as few people "take the time to look under the hood and see how they work." And, just because there's a number on something, doesn't mean that the number was arrived at properly. Logic can help to evaluate whether or not a chain of reasoning is valid. And "infoliteracy" teaches us that not all sources of information are equal, and that biases can distort data. Faced with a world too eager to flood us with information, the best response is to be prepared. A Field Guide to Lies helps us avoid learning a lot of things that aren't true.
books  nonfiction  critical_thinking  infoliteracy  biases  lying  information_overload  TPL  Daniel_Levitin  engaged_citizenry  signals  noise  information_sources 
september 2016 by jerryking
Intelligence Start-Up Goes Behind Enemy Lines to Get Ahead of Hackers - The New York Times
By NICOLE PERLROTH SEPT. 13, 2015

iSight Partners, a company that provides intelligence about threats to computer security in much the same way military scouts provide intelligence about enemy troops....For the last eight years, iSight has been quietly assembling what may be the largest private team of experts in a nascent business called threat intelligence. Of the company’s 311 employees, 243 are so-called cyberintelligence professionals, a statistic that executives there say would rank iSight, if it were a government-run cyberintelligence agency, among the 10 largest in the world, though that statistic is impossible to verify given the secretive nature of these operations.

ISight analysts spend their days digging around the underground web, piecing together hackers’ intentions, targets and techniques to provide their clients with information like warnings of imminent attacks and the latest tools and techniques being used to break into computer networks.

The company’s focus is what John P. Watters, iSight’s chief executive, calls “left of boom,” which is military jargon for the moment before an explosive device detonates.... iSight's services fill a critical gap in the battle to get ahead of threats. Most security companies, like FireEye, Symantec, Palo Alto Networks and Intel’s security unit, focus on blocking or detecting intrusions as they occur or responding to attacks after the fact.

ISight goes straight to the enemy. Its analysts — many of them fluent in Russian, Mandarin, Portuguese or 21 other languages — infiltrate the underground, where they watch criminals putting their schemes together and selling their tools.

The analysts’ reports help clients — including 280 government agencies, as well as banks and credit-card, health care, retail and oil and gas companies — prioritize the most imminent and possibly destructive threats.

Security experts say the need for such intelligence has never been greater....the last thing an executive in charge of network security needs is more alerts, he said: “They don’t have time. They need human, actionable threat intelligence.”
cyber_security  security_&_intelligence  dark_web  hackers  intelligence_analysts  iSight  Symantec  threats  humint  spycraft  pre-emption  actionable_information  noise  threat_intelligence  left_of_the_boom  infiltration 
september 2015 by jerryking
A 25-Question Twitter Quiz to Predict Retweets - NYTimes.com
JULY 1, 2014 | NYT | Sendhil Mullainathan.

how “smart” algorithms are created from big data: Large data sets with known correct answers serve as a training bed and then new data serves as a test bed — not too differently from how we might learn what our co-workers find funny....one of the miracles of big data: Algorithms find information in unexpected places, uncovering “signal” in places we thought contained only “noise.”... the Achilles’ heel of prediction algorithms--being good at prediction often does not mean being better at creation. (1) One barrier is the oldest of statistical problems: Correlation is not causation.(2) an inherent paradox lies in predicting what is interesting. Rarity and novelty often contribute to interestingness — or at the least to drawing attention. But once an algorithm finds those things that draw attention and starts exploiting them, their value erodes. (3) Finally, and perhaps most perversely, some of the most predictive variables are circular....The new big-data tools, amazing as they are, are not magic. Like every great invention before them — whether antibiotics, electricity or even the computer itself — they have boundaries in which they excel and beyond which they can do little.
predictive_analytics  massive_data_sets  limitations  algorithms  Twitter  analytics  data  data_driven  Albert_Gore  Achilles’_heel  boundary_conditions  noise  signals  paradoxes  correlations  causality  counterintuitive  training_beds  test_beds  rarity  novelty  interestingness  hard_to_find 
july 2014 by jerryking
World’s largest asset manager rails against companies’ short-term thinking - The Globe and Mail
BOYD ERMAN
The Globe and Mail
Published Friday, May. 23 2014,

...Mr. Fink is worried that the great tide of economic growth is not rising as quickly as it could be because of persistent and pernicious short-term thinking. Everyone from Main Street to Wall Street to Pennsylvania Avenue is too focused on near-term waves to pay attention to what the overall water level is doing.

Blogs, polls, the story of the moment – that is what drives peoples’ thinking, he says. That means investment decisions and political moves are based on what’s happening now, and not long-term goals. The economy will bear the cost of this short-term obsession, and so will investors, Mr. Fink warns. He would like to see big changes in everything from accounting to corporate governance to government spending priorities, to reset the focus on more distant horizons....“We need executives in business to start focusing on what is right in the long run,” ...“Societies are having a hard time, politically and economically, adjusting to the immediacy of information: The 24/7 news cycle, blogs, the instantaneous information. It’s very hard. This is one of the things where we are developing a crisis.”...Mr. Fink is particularly frustrated with the lionization of activist investors in the media. Think Bill Ackman, Carl Icahn and others who push for changes that will lead to an immediate runup in the stock price,....Similarly, he is critical of accounting rules that push insurance companies to invest in shorter-term assets, rather than long-term projects such as infrastructure. “Everything is leading toward an underinvestment in infrastructure and an underinvestment in capital expenditures.”...In 1999, the company went public. It has grown incredibly fast ever since. It manages money for everyone from retail investors to pension plans. During the financial crisis, the U.S. Treasury hired BlackRock to run assets in the Troubled Asset Relief Program, and the Bank of Greece hired the company to help fix the country’s banking system. (Model for WaudWare?)
BlackRock  Laurence_Fink  asset_management  long-term  Boyd_Erman  Wall_Street  delayed_gratification  thinking  strategic_thinking  Communicating_&_Connecting  CEOs  money_management  shareholder_activism  immediacy  insurance  infrastructure  CAPEX  short-term  short-term_thinking  financial_pornography  pension_funds  underinvestments  noise  pay_attention 
may 2014 by jerryking
Busy and Busier
Oct 24 2012 | The Atlantic | James Fallows.

a lot of people are feeling overwhelmed is because people are not in true survival or crisis mode as often as they have been in much of our history. The interesting thing about crisis is that it actually produces a type of serenity. Why? Because in a crisis, people have to integrate all kinds of information that’s potentially relevant, they have to make decisions quickly, they have to then trust their intuitive judgment calls in the moment. They have to act. They’re constantly course-correcting based on data that’s coming up, and they’re very focused on some outcome, usually live—you know, survive. Don’t burn up. Don’t die.

But as soon as you’re not in a crisis, all the rest of the world floods into your psyche. Now you’re worried about taxes and tires and “I’m getting a cold” and “My printer just crapped out.” Now that flood is coming across in electronic form, and it is 24/7.....The thing about nature is, it’s information rich, but the meaningful things in nature are relatively few—berries, bears and snakes, thunderstorms, maybe poison oak. There are only a few things in nature that force me to change behavior or make a decision. The problem with e-mail is that it’s not just information; it’s the need for potential action. It’s the berries and snakes and bears, but they’re embedded, and you don’t know what’s in each one....Things on your mind need to be externalized—captured in some system that you trust. You capture things that are potentially meaningful; you clarify what those things mean to you; and you need maps of all that, so you can see it from a larger perspective. With better technology, I’d like a set of maps—maps of my maps. Then I could say, “Okay, which map do I want to work on right now? Do I want to work on my family map, because I’ve got family members coming over for dinner?” Then you can drill down into “Oh, my niece is coming. She likes this food, her favorite color is pink, her dog is named …” Then you can back off and say, “That’s enough of that map. What’s the next map I want to see?” Or: “I’d just like to read some poetry right now.”
busy_work  course_correction  crisis  David_Allen  GTD  human_psyche  information_overload  James_Fallows  living_in_the_moment  mapping  metacognition  metadata  metaphysical  monotasking  productivity  nature  noise  overwhelmed  sense-making  signals  stress_response 
november 2013 by jerryking
Think markets raise capital? Think again.
March 25, 2013 | G&M | John Kay as told to Brian Milner

On the glut of information available to investors:

“We need to dispose of the idea that more information is better and eliminate informa...
economists  information_overload  investment_custodians  relevance  middlemen  dysfunction  money_management  asset_management  capital_markets  noise  incentives  conflicts_of_interest 
march 2013 by jerryking
Big Data should inspire humility, not hype
Mar. 04 2013| The Globe and Mail |Konrad Yakabuski.

" mathematical models have their limits.

The Great Recession should have made that clear. The forecasters and risk managers who relied on supposedly foolproof algorithms all failed to see the crash coming. The historical economic data they fed into their computers did not go back far enough. Their models were not built to account for rare events. Yet, policy makers bought their rosy forecasts hook, line and sinker.

You might think that Nate Silver, the whiz-kid statistician who correctly predicted the winner of the 2012 U.S. presidential election in all 50 states, would be Big Data’s biggest apologist. Instead, he warns against putting our faith in the predictive power of machines.

“Our predictions may be more prone to failure in the era of Big Data,” The New York Times blogger writes in his recent book, The Signal and the Noise. “As there is an exponential increase in the amount of available information, there is likewise an exponential increase in the number of hypotheses to investigate … [But] most of the data is just noise, as most of the universe is filled with empty space.”

Perhaps the biggest risk we run in the era of Big Data is confusing correlation with causation – or rather, being duped by so-called “data scientists” who tell us one thing leads to another. The old admonition about “lies, damn lies and statistics” is more appropriate than ever."
massive_data_sets  data_driven  McKinsey  skepticism  contrarians  data_scientists  Konrad_Yakabuski  modelling  Nate_Silver  humility  risks  books  correlations  causality  algorithms  infoliteracy  noise  signals  hype 
march 2013 by jerryking
Surprise business result? Explore whether it is a hidden opportunity
June 18, 2007 | G&M pg. B8 | George Stalk Jr.

What does it take to capitalize on anomalies systematically?

For starters, you need to have metrics and information systems that are sufficiently refined to identify anomalies in the first place. Knowing the average margins and market share isn’t enough; look at the entire range of outcomes—across customers, geographies, products, and the like. This allows you to surface out-of-the-ordinary results for closer inspection.

The next step is to separate wheat from chaff: those anomalies that signal a potential business opportunity from those that are merely one-time events. The key is to examine the pattern of unusual performance over time. The customer who consistently buys high volumes or the market that outperforms the average year after year are, by definition, not random. Is there an underlying cause that can be identified and then replicated elsewhere?

Finally, you need to understand the precise mechanisms that animate the anomalies you identify. Why is the unusual pattern of performance happening? What specific features of the product or the local environment or the customer experience are bringing it about? Don’t accept the usual first-order explanations. It’s not enough to know that a particular customer has been loyal for years; find out precisely why.

It’s up to senior management to create the forum for asking why and to persist until the question is answered with genuine insight.
metrics  George_Stalk_Jr.  BCG  anomalies  growth  opportunities  customer_insights  surprises  systematic_approaches  quizzes  ratios  pattern_recognition  insights  questions  first-order  second-order  OPMA  Waudware  curiosity  new_businesses  one-time_events  signals  noise  overlooked_opportunities  latent  hidden  averages  information_systems  assessments_&_evaluations  randomness  5_W’s 
january 2013 by jerryking
The Rhino Principle
01.30.06 | Forbes.com | Paul Johnson
We can choose to lead quiet lives and get through them without achieving much. But if we want to do the big thing, if we hope to leave a record that will be admired and remembered, we must learn to distinguish between the peripheral and the essential. Then, having clearly established our central objective, we must charge at it again and again until the goal is achieved.

That is what the rhinoceros does. It may not be a model animal in most ways. But it does one thing very well. And that one thing we can learn: Charge!
historians  gtd  indispensable  worthiness  signals  noise  discernment  judgment  thinking_big 
june 2012 by jerryking
Trader Hits Jackpot in Oil, As Commodity Boom Roars On - WSJ.com
February 28, 2008| WSJ | By ANN DAVIS.
Mr. Hall Bet Early On Market Shift; Buoying Citigroup.

Profiles Andrew J. Hall, an enigmatic British-born trader who, in 2003, anticipated an important shift in the way the world valued oil -- and bet big....Mr. Hall's bet -- that long-term and short-term energy prices would soon abandon their historical relationship with one another -- looked like a long shot when he made it....Around 2003, Mr. Hall became convinced big structural changes were looming in the oil markets. For more than a decade, oil had ranged from $10 to $30 a barrel. But growth in demand was starting to outstrip growth in supply. And the once-sleepy economies of China and India were starting to compete for that fuel.

To place his bet, he focused on what was then a stagnant corner of the commodities world: The extremely long-term market in which traders buy and sell oil to be delivered years in the future.

Futures are contracts to buy or sell a product later on, at a price agreed upon today. Back in 2003, oil for future delivery was considerably cheaper than oil in the "spot," or current, market. For instance, a barrel of oil for delivery in 2005 was as much as 20% cheaper than spot oil....A key to Mr. Hall's success, says a friend, Thomas Coleman, a Louisiana oil-storage executive and fellow art collector, is an ability to block out the noise of the crowd. When Mr. Hall "locks in on an idea, he'll take it to the extreme," Mr. Coleman says.
Citigroup  Phibro  traders  oil_industry  hedge_funds  big_bets  commodities  collectors  pattern_recognition  structural_change  extremities  commodities_supercycle  ratios  noise  turbocharge  extremes 
june 2012 by jerryking
A First Draft of History? - WSJ.com
March 12, 2005 | WSJ | By BRET STEPHENS

The cliché is that journalism is the first draft of history. Yet a historian searching for clues about the origins of many of the great stories of recent decades--the collapse of the Soviet empire; the rise of Osama bin Laden; the declining American crime rate; the economic eclipse of Japan and Germany--would find most contemporary journalism useless. Perhaps a story here or there might, in retrospect, seem illuminating. But chances are it would have been nearly invisible at the time of publication: eight column inches, page A12.

The problem is not that journalists can't get their facts straight: They can and usually do. Nor is it that the facts are obscure: Often, the most essential facts are also the most obvious ones. The problem is that journalists have a difficult time distinguishing significant facts--facts with consequences--from insignificant ones. That, in turn, comes from not thinking very hard about just which stories are most worth telling....As for the media, it shouldn't be too difficult to do better. Look for the countervailing data. Broaden your list of sources. Beware of exoticizing your subject:
Bret_Stephens  journalism  journalists  critical_thinking  history  signals  noise  frictions  pain_points  worthiness  countervailing  storytelling  seminal_moments  wide-framing  discernment  origin_story  historians  consequential  clichés  worthwhile_problems 
may 2012 by jerryking
Contrary Rules for Business Success
Jun. 24, 2009 | The Globe & Mail | by Harvey Schachter.
Reviews The Moneymakers, by Anne-Marie Fink, Crown Business, 310
pages, $32. Fink gets paid to separate the wheat from the chaff in the
corporate world or, to put it in business terms, separate the
moneymakers from the destroyers of shareholder value. Fink is an equity
analyst with J.P. Morgan Asset Management, she has billions of dollars
resting on her assessment of companies and their management.
equity_research  investment_research  books  rules_of_the_game  book_reviews  Harvey_Schachter  slight_edge  signals  noise  value_creation  value_destruction  shareholder_value  JPMorgan_Chase 
february 2010 by jerryking
Mining for Gold - WSJ.com
Interview with Deutsche Bank Asset Management CIO, Sean Kelly.
Details how the firm sorts through the clutter of information to gain an
edge.

THE WALL STREET JOURNAL: How is information technology strategically important for Deutsche Asset Management?

MR. KELLEY: In finance there is a concept called "alpha," which means that you make returns beyond the market as a whole. It's really what asset managers get paid for. For us technology is a sizable factor for creating alpha.

"There's a lot of information but also a lot of noise. You have to figure out algorithms to crawl through [all] this automatically, taking out 95% of the noise and finding signals that indicate the emotions of the market. That's the thing: The information doesn't have to be correct -- it just has to be dominant. A person doesn't have to be right. It just has to be that everyone thinks that way. So if you can figure out ways to get to that information and act on it before the market has a chance to correct itself, it gives you an added edge."
alpha  Deutsche_Bank  data_mining  slight_edge  information_overload  competingonanalytics  CIOs  sorting  noise  signals  informational_advantages 
january 2009 by jerryking

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