• The Digital Soul, Part IV

    Business is the voluntary exchange among free adults of goods and services.  We’ve typically made a distinction between goods and services having a physical form or impact and those for which the good or service is not material, or can not be touched.  It is the difference between a truck, a chair, or a razor on one hand, and insurance, trademarks, stocks (and lists of stock prices) on the other.

    With the coming of the Information Age, more goods have been released from their physical form and exist only as information: music has lost the LP, books the paper, games the physical board.  Human behavior has also been productized in the Information Age – no longer do we need to fill out the form and mail it in for more information, show up at Ladies Night to meet the opposite gender, or pick up the phone and “call now” because operators are standing by.  In what could only be a dream-come-true for the behavioral economists of our era, the information-seeking, intention-displaying, inference-driving, interaction-enabling of human behavior have exploded in scale since losing the requirements of physical actions by users (other than, it should be noted, the movement of keys on a keyboard or the mouse on a mouse pad, we have not entered into a world of pure telepathy… yet.)

    Students of business want to analyze the behaviors of present businesses and study the history of past ones in order to understand the “why” of the development of businesses.

    When students of business talk about McDonald’s being a real estate business, enabled by the automobile, that happens to sell food at their physical locations, we are talking about root causes and the underlying nature of the business, rather than what they appear to be on the surface: in this case, a fast way to get burgers and fries.

    To understand what business the various successful business models of the Internet are truly in, we need to better understand their nature and the nature of transformation in our time.

    The development of new technologies leads to the development of new businesses.  The rise of the railroad, the telegraph, the steel mills, brought about, and were brought into being by, the Industrial Revolution.   That revolution overturned the conception of what goods we could produce and at what scale.  It also separated the production of goods into several component hierarchies – raw materials, energy, distribution, capital goods, consumer durables, consumer packaged goods – that were novel at the time of their creation and changed considerably the understanding of the farmer receiving his Sears Roebuck catalog out in the plains of Nebraska of what was meant by “goods”. It was no longer possible to think of them all as being the same kind of thing.

    On a similar model, the Information Age reinvents the intangible.

    But rather than a revolution, I think this transformation is a reflection. We have reconstructed and re-imagined our societies in bits — sometimes quite literally, as in Second Life – even as Facebook maps our relationships with friends & family, 1 in 6 marriages now start online, my Kindle books don’t “exist”, and there is a thriving market for swords, potions and gold that exists only in the cyberspace World of Warcraft.

    We are reflecting our world through the means of digital bits, and we are also able to reflect upon ourselves: who we are, what we are doing, what we like, which things give us pleasure or who we want to create communities with.  The discoveries enabled by Netflix, Amazon, Pandora or Hunch teach us more about who we are.

    We’ve been happy to refer to these as online, or internet, or web-enabled businesses, but the time has arrived to understand and define them better, because they have different characteristics.

    Are dating sites, Netflix, a program that teaches chess, Google, prediction markets, Kindle books, Kiva, iTunes, GoDaddy, virtual currencies, job sites, and Pandora all in the same intangibles goods business?  If not, what are they?

    Is a dating site a matchmaking service? A content site?  A seller of intangible goods?  A subscription business?  Those in the online dating industry can tell you: yes and no.

    And as a practitioner in an online information business, I can tell you that this lumping of all online businesses into one undifferentiated framework leads to a worse, rather than a better understanding of our businesses.  Even thought we acknowledge the topical differences between dating and movies and books and music and jobs, this lack of a conceptual framework confuses the analogies we can use to understand our businesses, undermines the selection of the right metrics to drive the business, and turns management in the Information Age into a series of happy accidents rather than deliberate planning.

    In my post on the IIII hierarchy, I broke out an Information Age business framework:

    - Access
    - Information
    - Intention
    - Inference
    - Interaction
    - Time-space
    - Trials & diversions

    Each of these layers represents a human need in making economic decisions:

    - We need to be able to consume the information in human-understandable form.
    - We take information in with our senses – we read, watch, listen.
    - We make decisions based on that information to the best of our rational ability.
    - By our actions, we also enable experts in that area, whether human or machine, to be able to suggest other information that will be of interest to us.
    - From the above comprehension, decisions, and implications, we have desires to interact with people or products.
    - We make decisions to do so at a particular time or place, whether online or offline, with others or alone.
    - From which comes the ability of businesses to entice or induce us to try out new things.

    Over the course of the next several posts, I’ll assert that online businesses are not just one undifferentiated mass, but rather that they should be categorized according to the nature of the economic behavior they are enabling or supporting.

    It is worth noting that in the 20th century, the newspaper was able to stretch across all of these layers – from providing the physical platform that gave the industry its name, to advertisements, to announcements, to coupons, and so on: the newspapers were the information appliance tool of that century.

    As new technologies grow strong, we’ll see businesses shrinking back from trying to own more than one of these layers.  That is not to say we won’t see legacy businesses that stretch across two or more of these layers (the Wall Street Journal as an excellent example) but these vestigial exceptions will grow increasingly rare and idiosyncratic, like Japanese holdouts from World War II or the Medieval German spoken in Southern Pennsylvania.

    In discussing each layer in the Information Age hierarchy, I’ll discuss what they must, can, could and mustn’t, do.  See you tomorrow!

  • Congratulations to this week’s most active recruiters on the Career Graph

    We have thousands of recruiters using MyPipeline each week to communicate with TheLadders’ 4.5mm members.  Here are the cleverest and most effective recruiters using TheLadders this week:

    So what’s going on here?  For recruiters, MyPipeline is a phenomenal way to get your message out:

    1. You invite who you want to see your jobs from our 4.5 mm subscribers
    2. Build a warm pipeline of competitive candidates from companies in your industry.
    3. You send your Hiring Alerts (for free) to your followers anytime — we take care of sending it to their inboxes.
    4. The highest read rate (43%) in the industry means the best social referrals for your job.
    5. It’s the largest Passive Network on the planet.

    Read more

  • Eisenmann’s Treasure Chest

    If you’re an entrepreneur, you couldn’t possibly do better than to go to Tom Eisenmann’s blog Platforms and Networks, cancel the rest of your day, lock the door, and r-e-a-d.

    The top two posts, which should take you one day each to read, are:

    Launching Tech Ventures, readings

    and

    Compilation of the Web’s Best Advice for Entrepreneurs.

    These are two big meaty treasure lockers full of the best of the best — you should thank Prof. Eisenmann for curating for you and saving you untold wandering hours.

    These excellent collections of great blogs make me feel appropriately sheepish about my own entries in the “entrepreneur’s story” category:

    How can I tell if I am failing at my entrepreneurial venture or start-up?

    How to raise angel money with the ’send’ button: TheLadders’ $635,000 angel round

    OK, you can go now.

  • Why should I pay for your TV and radio?

    As one of “those Americans” that does not own a television, and I wonder why MoveOn members want me to pay for their TV and radio.

    I prefer reading books and visiting museums. I also like Yankees games and live music on the Lower East Side of Manhattan.  I think I should have to pay my own way to enjoy the cultural objects and institutions that I enjoy.  I think you should too.

    So my question for the TV imperialists out there is: why should I pay for your TV and radio? Why won’t you leave me alone with my books? It seems like a a rather rude imposition of your desires onto my wallet.

  • Why don’t referral bonus systems work?

    One of my favorite, and also the least successful, ideas in online recruiting has been the referral bonus system.

    Almost 50% of hires are referrals (65% according to CareerXroads’ recent 10th Annual Sources of Hires Report). This was true a century ago, it’s true today, and it will probably be true a century from now. “Word-of-mouth” advertising, implied endorsement, and the resulting social pressure to perform in the workplace and not let your peers down, all combine to make referrals a very effective means for staffing any company.

    While most companies have an internal system for handling employee and internal referrals, the thinking goes, wouldn’t it be so much more powerful to tap into the broader networks of contacts that we all have and reward them when we hire somebody?

    As a result, entrepreneurs in the internet recruiting marketplace periodically strike upon the idea of building a third-party referral marketplace – a way to reward anybody who suggests a new employee to a company with a big payment, thereby encouraging lots of effective referrals.

    The reason the idea is so attractive is that by putting $5,000 or $10,000 bounty on the table for a hire, it is imagined that an army of referrers will be put to work on the hiring company’s behalf. And as the company only pays when it hires, the thinking continues, there’s no cost and no risk to them.

    When I first came across the idea, I, too, was a big fan. I imagined it would work really well in cases where a third party had very good knowledge of the capabilities of a group of potential employees – say, for example, a grad student TA in computer science, or a Meetup organizer of brand marketing experts. She could make referrals to a number of companies of her students / members and make a tidy sum when the magic happened and a connection was made.

    Alas, it doesn’t work this way in practice.

    A typical recruiter can make 24 placements in a year. This number ranges from one to ten dozen, depending on the level of effort, difficulty of the position, frequency of the position, etc., but let’s use 24 for now.

    That means a typical placement requires 2 weeks full-time work – sourcing candidates, calling them, qualifying them, setting up appointments with the hiring manager, doing follow up debriefings, negotiating offers, and closing. All of those activities really add up.

    Providing the name of a potential hire is useful, but represents just a fraction of the overall workload. So from a company’s standpoint, the correct referral bonus to offer for a name is far lower than $5,000. Further, managing these suggestions, which would vary in quality across referrers, would take time and money on the company’s part.

    From the referrer’s standpoint, the small number of times a placement occurs from this type of recommendation system – perhaps 1 in 1,000, means that, on average, the typical referrer will earn zero dollars for his efforts, thereby making word-of-mouth work against the system.

    So while it’s a brilliant idea that always sounds good on paper, and has been implemented by some of the smartest people to enter the online recruiting business, the economics of the third-party referral system make it a business model that does not work.

  • Let my people go!

    Jewish holidays are getting the best treatment on the web these past 12 months. I wonder why the breakthrough?

    I particularly love how the quantity of live frogs ordered from Amazon goes up to 50,000,000, “the people who bought this also bought” side-joke, and what happens to the Egyptian First-Born Son Club. All in all, wry, dry and witty. A great Passover sendup!

    Via AllThingsD

  • The Digital Soul, Part III: Insights that are queer but true

    thousandbirds

    ‘Never index your own book,’ she stated.

    A duprass, Bokonon tells us, is a valuable instrument for gaining and developing, in the privacy of an interminable love affair, insights that are queer but true.  The Mintons’ cunning exploration of indexes was surely a case in point.  A duprass, Bokonon tells us, is also a sweetly conceited establishment. The Mintons’ establishment was no exception.

    Some time later, Ambassador Minton and I met in the aisle of the airplane, away from his wife, and he showed that it was important to him that I respect what his wife could find out from indexes.

    “You know why Castle will never marry the girl, even though he loves her, even though she loves him, even though they grew up together?” he whispered.

    “No, sir, I don’t.”

    “Because he’s a homosexual,” whispered Minton.  “She can tell that from an index, too.”

    -       Kurt Vonnegut, Cat’s Cradle

    If you want to figure out if your first date will sleep with you tonight, what would you ask them? What would be the single, best, statistically significant question you could ask to determine his or her licentiousness?  The web’s got the answer for you:

    “Do you like the taste of beer?”

    A positive answer to this question indicated a 60% greater likelihood to “be okay with sleeping someone they’ve just met,” on OKCupid.com, one of the largest dating sites on the web. Among the 50,000 other questions reviewed, this one’s promiscuity predictive power is unrivaled.

    In the IIII hierarchy, this is an inference, and a remarkably important one for all of us — not just the two hormonally-inflicted junior brand managers wasting their afternoons away on the opposite ends of a dating site — because of what it means for what we can know about people and how we can know it.

    In the novel Cat’s Cradle, quoted above, a duprass is “a valuable instrument for gaining and developing… insights that are queer but true. “

    In Kurt Vonnegut’s telling, the beauty of the duprass is their spontaneous generation of striking insights – unexpected glimpses through an open window into the human being.

    Adapting the word to express its output, let’s term a duprass any insight that is “queer but true”.  While Vonnegut was able to write his duprasses into his novel, we’ll have to understand how the web manufactures them.

    I suppose that if you seek “queer but true”, you could reverse engineer it such that you find all things true first, then discard the obvious, rote, standard, expected, boring or tiresome observations to remain with the queer.

    Queer, in this case, must mean that correlation is not enough; we’ll need to find those truths that surprise, tease and titillate, those that are not ready accessible via logic.

    For a start, let’s consider the production of answers.

    Me personally, I’ve always liked surveys and have filled them out whenever I could.  Receiving them in the mail, submitting them after a hotel stay, pleasantly scratching out the bubbles on a guest satisfaction quiz, tickled me.  I remember the little thrill that would go through my bones when I’d read through the disqualifier notices – you must not be an employee of the client or the agency or work in any marketing or advertising company – and conclude for the hundredth time in a row that they didn’t apply to me – I was eligible to participate!

    Prior to the Web, surveys were conducted differently.  I remember in 1994 being called to do a 1-hour interview about my subscription to Fortune Magazine, and meeting with the researcher at the McDonald’s in Sorrento Valley, San Diego.

    I enjoyed it immensely, though I was a little let down at the payoff : Do I get to see the results? May I weigh in on the conclusions? Can I help explicate the answers, Dear Fortune? All for naught.

    The cost, frequency and serendipity of surveying was low; a manual process, without cross referencing, conducted in person, could only be so productive.  And perhaps not all Americans were as eager to participate as I.

    So what happens when the average person increases their output of recorded answers from one per year…

    …to dozens per month…

    …to hundreds per day?

    Photos by etgeek via creative commons.

    From the single starling, you can’t predict the beauty of the flock, suddenly appearing and flashing shapes and colorations…

    …the queerly mesmerizing truth of the flock in flight; its duprass.  The emergent behavior of the internet is to reveal us to be fascinating.

    Hunch.com, the pioneer in the inferences business the way Google was the pioneer in the intentions business, packages duprasses for us.  What can we surmise from these Hunch correlations?:

    South Americans are more likely than North Americans to dream of being underwater or being able to fly; North Americans are more likely than South Americans to dream of being chased or attacked.

    Cookie Monster fans believe in life after death and consider themselves “foodies”.

    Bacon double cheeseburgers lovers are more likely than haters to be able to do 10 pull-ups.

    And before I respond “tsk tsk” to your cry that “these are just silly games; parlor tricks for people who still have parlors”, may I point you to that section of “Innovator’s Dilemma” which presents prior exemplars of market entrants becoming market revolutionaries through low-utility innovation?

    I was a political science undergrad, and I’d been fascinated by Thomas Sowell’s A Conflict of Visions, a brilliant tour de force that uses inductive reasoning to draw the lines between the political ideologies and show how their many different answers stem from the same underlying differences in conception of human nature and possibility.  It is a supreme example of what the human Expert can do: forty years of study from a leading political philosopher results in a book of penetrating insights.

    Compare this with the work of a cheeky dating site run by flippant 20-somethings, who have discovered that the question most likely to indicate whether you are conservative or liberal is:

    Do you prefer the people in your life to be simple or complex?

    Or, for good measure, who determined that answering the question “Is my date religious?” could best be achieved by asking the question:

    Do spelling and grammar mistakes annoy you?

    Far from being parlor tricks, the portent of these inferences is the destruction of the social sciences – the belief that we can understand human behavior and explain it through our rational faculties — and the rise of something far more powerful, fast, and compelling: the Inference Machine.

    If a taste for hops predicts hopping in the sack, if grammatalogical correctness tops theology in predicting religiosity, if a simple question tells us more than four decades of complex study, we face an epistemological paradigm shift in our understanding of humans in the 21st century.

    Each survey, each poll, each choice online creates more answers.  When we have thousands, when we have millions, when we have billions of answers to these questions each day, what will they tell us about ourselves?  And what questions will the answers give us?

    And who knows? When we’ve answered the questions, connected the dots, and drawn the lines between faith and fact…

    Photo by Mrs. LH via creative commons.

    …will our conclusions bind us more tightly together?

  • The Digital Soul, Part II: Google Pro

    Why doesn’t Google sell a Google “Pro” version to all you addicts out there?  A paid version that indexes more webpages, provides faster results, gives you more search filters and less web spam than the “Basic” version?  With a billion users globally, wouldn’t it make sense to give the best features and functionalities to those most willing to pay for it?  To understand that question, we’ll need to understand something about the nature of web businesses, users, scale, and monetization.

    Pre-internet information technology businesses correlated to the DIKW hierarchy: data – information – knowledge – wisdom.   In the 20th century, IT businesses provided the hardware to store, the tools to gather, the software to visualize and report, and the consulting services to understand, the inputs and outputs of human experience.  The atom, the core irreducible mote, underlying the DIKW hierarchy is the stimulus outside of ourselves which we perceive with our senses, thus creating data capable of being recorded.

    The web enables, and therefore requires, a very different structure.  With the rise of the web we see businesses based around a different atom, a different mote: that of human behavior. Without our recognizing it, the global communications and technology network that has been our obsession for the past two decades has changed from being about things, to being about people.

    Even more compellingly, it has changed from being constituted of data on the nature of things, to data generated by the nature of people.


    The web hierarchy is:

    Information – Intentions – Inferences – Interaction

    If the pre-internet IT hierarchy is composed of bits that correlate to atoms, the web IT hierarchy is composed of behaviors that represent users:

    -  Users seek information on the internet, thereby

    -  Developing and revealing their intentions, thereby

    -  Enabling inferences that are valuable and non-intuitive, thereby

    -  Allowing for interactions or communities of which the user was previously unaware

    This last step, the provision of discovery to users, has been an obvious, productive, and compelling application of the web since at least the founding of Firefly in 1995. (If you roll that way, here is Suck’s awesome 1995 review of the launch.)

    Seeking information

    We use Google to seek information, which in Google’s case is composed of requests that let us know who the Yankees play next Tuesday, how much butter to put in the cookies, where to eat in Luang Prabang, or the molecular weight of tryptophan.  We use other sites to seek other types of information – on jobs, on stocks, the definitions of words.  In either case, in each act of information-seeking we do not just learn about the information, but reveal something about ourselves.

    Revealing intentions

    John Battelle defined Google as a database of intentions: “The Database of Intentions is simply this: The aggregate results of every search ever entered, every result list ever tendered, and every path taken as a result.”

    Beyond the search engines, users generate data about their actions at ecommerce sites, in dating applications, in the job search, in fact, every click, search, form, survey, poll, and mouse-over tells us something more about the user and their intentions.  What they think they are doing tells us something about what they think, but also tells us a great deal more.

    Enabling inferences

    Intentions may or may not represent the conscious understanding of the user – for anybody who’s sat through usability labs and heard the subject say “I don’t know why I clicked, just seemed like that’s where I should go”, you know what I mean.

    Based on their apparent intentions and expressed preferences, web businesses can make inferences about users.

    As I am writing this, I’m listening to my Pandora Station named “Smog” after the band I seeded it with.  Looking through the resultant list of songs to which I’ve given the “thumbs up” I see seven new bands that I’ve discovered in the past two weeks that I’d never heard of before and of whom I am now tremendously fond.

    Surprising, non-trivial, productive inferences may not be unique to the web, but surprising, non-trivial, productive inferences at scale, are.

    Allowing interaction and community

    And those surprising inferences will create a user with the desire to act: to buy music, or join a discussion, or purchase an appliance, or go to a concert, or attend a Meetup.  The things we can teach users about themselves allow them to participate in a broader set of activities, and understand the context of why they are doing so.  It is not just generating behavior, or trial, it is generating self-enlightened behavior that is the most compelling aspect of this web hierarchy.

    The IIII business hierarchy

    The DIKW hierarchy had a corresponding business hierarchy: hardware for storing, tools for collecting, software for analyzing, and consulting for understanding.  Each successive step in the hierarchy uses the bits provided by the prior step as the raw material from which it creates value.

    Similarly, the IIII hierarchy has a corresponding web business hierarchy, as shown in bold below.  And where the DIKW hierarchy passes bits from one level to the next, the IIII hierarchy passes user behavior from one level of the hierarchy to the next.

    If access is your product, information is your revenue

    If information is your product, intentions are your revenue.

    If intentions are your product, inferences are your revenue.

    If inferences are your product, interaction / community is your monetization.

    If interaction / community is your product, time-space is your monetization.

    If time-space is your product, trial is your monetization.

    (In italics are the pre- and post-web-hierarchy business models, representing 20th century informations services business on one hand, and online-enabled offline businesses such as Meetup and Groupon on the other, respectively. I will discuss these in another post.)

    Because each level of the hierarchy generates the “raw material” for the next level, web business have the interesting characteristic that you cannot monetize your core product – that is, the part of your product that generates user behavior, engagement, and attention for your site or app in the first place.   For any particular product or service, one level in the hierarchy must be unfettered, cost-free, and generate as much user behavior as possible, in order for the company to monetize it effectively at the next level of the hierarchy. (In another post, I’ll discuss the scale – the perhaps surprisingly massive scale – of behavior required to generate monetization.)

    And it is thus precisely because the user behavior on one level of the IIII hierarchy is the raw material for the monetization on the next level of the hierarchy that Google cannot have a “Google Pro” version.  And it is precisely because the web is composed of human behavior that a new hierarchy is required to explain it.

  • The Digital Soul, Part I

    “Ordinary riches can be stolen, real riches cannot. In your soul are infinitely precious things that cannot be taken from you.” – Oscar Wilde

    What if I told you I was willing to pay you $1.81 if you tell me about your bulimia?  Or at the other end of the spectrum, $1.05 to tell me about your gout?  How about $1.93 in your pocket if you’ll admit to me that you and your spouse need marital counseling?

    Or $10.11 that your house doesn’t have a security system, $7.16 that you’ve finally given up on paying off your student loans, and $9.24 if you’ll ‘fess up to your coke problem?

    $130.34 if you’re afraid you might have asbestos-related mesothelioma?

    Or $31.06 if you think you need a DUI attorney? (But only $29.03 if you need a DUI lawyer?)

    Or, and I know this might seem chintzy, $0.72 if you think your husband might be gay?

    Would you do it?

    If I pulled out my checkbook or a stack of bills and the correct change, would you agree to tell me truthfully?

    No?

    Well, maybe it’s just because we don’t know each other that well yet…  perhaps this would work better if you asked your friends?

    Let’s try it.  Click here to send an e-mail to all of your contacts with the subject line “I’ll pay you $9.37 if you admit to your drinking problem.”

    How many takers do I have?  Are you up for it?

    Now what if I took this thought experiment a step further and proposed to you a business where the model is, in fact, that I am going to ask you to tell me all of these things… for free…  because you’ll want to.

    And then I’ll plan on selling that information to a bunch of people you don’t know for the cash.

    If you’re gout-stricken, I get a buck and change, almost $2 if you and the Mrs. are at it again. Your being a cokehead nets me a Hamilton.  I get three times as much if you’ve had a run-in with the law at a nighttime checkpoint. And if you’ve been sucking on asbestos for the past decade, I get a crisp Benjamin plus plus.

    Are you ready to invest in my venture? I think it’s got real potential.

    I’m naming it “Google”… perhaps you’ve heard of it?

    ——————————————-

    How did we become these people?  Telling such personal things to machines? Sharing what we wouldn’t share with colleagues or classmates or co-religionists or competitors?

    Sharing, in fact, our gravest and riskiest confidences with an unforgetting, uncorruptable, unerring, and utterly amoral machine?

    Forever, our secrets will be hidden there; they were not stolen, we gave them away willingly.  How did we become those people?

    The internet wasn’t supposed to turn out like this.

    While it can be conceived, in the words of one late befuddled Senator, as a “series of tubes” through which passes the world’s information, to be strictly precise the internet wasn’t conceived of at all.  It was, rather, the logically inevitable but unplanned, outgrowth of the invention of packet-switching.  Eliminating the single point of failure germinated a thousand, a billion, a trillion, points on the graph.

    The World Wide Web was to be the nodes on the graph.

    As Tim Berners-Lee shared early on: “The WWW world consists of documents, and links… [It] is a way to link and access information of various kinds as a web of nodes in which the user can browse at will. It provides a single user-interface to large classes of information (reports, notes, data-bases, computer documentation and on-line help).”

    The World Wide Web was about information – large classes of information – and information technology and information scientists were here to assist with its management.  The excitement you feel in reading Berners-Lee’s original proposal, his proselytizing emails, and his usenet posts come from the sense of a man on the brink of enabling a great discovery: the discovery of where we already are.

    By creating access to the world’s research, its thought, and its insight, Berners-Lee imagined minds all over the planet downloading, consuming, sharing more and better information than they ever had before.

    The information, the beauty, was in the nodes, not between them.

    Today, when there are 1,112,000 DUI arrests in the United States annually and 1,620,000 Google U.S. searches on the phrase “DUI attorney” over the past twelve months, do you have any doubt that the majority of the former shared their predicament with the latter?

    And all of the examples of payouts above come from searches conducted this morning on Google’s Adsense tools, which estimate how much each click will cost an advertiser in response to keywords such as “alcohol abuse”, or “bulimia”, or “mesothelioma.”

    Today the information, the beauty, the shock and surprise, come from between nodes: their interaction, their aggregation, their implications.

    Emergence is the occurrence of novel properties in the whole which are not present in the components, and are unpredictable from the knowledge of those parts.  There is nothing about ice crystals that tell us what snowflakes will look like.  There is nothing in the raindrop that can describe the hurricane.  Studying the grain of sand will not yield knowledge of the dune, nor will knowing the bird teach you about the flock.

    In every case, it is the interaction between the “nodes”, whether they be water droplets, birds, ice crystals… or keyboards, that leads to the surprise of scale.

    What, then, we can ask ourselves, is the emergent behavior of the internet?

  • Your $100,000 order with Amazon has been placed.

    ** From my weekly newsletter to TheLadders.com subscribers **

    I’ve been on the road these past few weeks, meeting with our customers Microsoft, Lucas Group, Starbucks, and many others. What I’m hearing from them is what you would expect during the turnaround year of a recession: budgets have stopped being cut, HR staff is stretched thin, and the conversations are all about the hundreds or thousands of employees that these companies need to add in the coming year.

    I was particularly enchanted with my friends at Amazon — I’ve been visiting their campus for the better part of the decade, and this year the buzz is as strong as I’ve ever felt it. And, no, I don’t think it’s just Seattle’s awesome coffee culture that’s got them buzzing.

    So I thought I’d ask them a few questions on landing your $100,000+ job order with Amazon this Monday morning…

    Susan Harker, Amazon’s Director of Global Talent Acquisition, was kind enough to spend some time answering my questions on Amazon’s hiring philosophy, innovation, and what it’s like to build at the company with a smile on, and in, every box!

    MC: Amazon has pledged to be “Earth’s most customer-centric company.” Does that affect hiring decisions even for jobs that aren’t traditionally customer facing? If so, how?

    SH: Being customer-centric is the cornerstone of Amazon’s business, and our teams work hard every day to innovate on behalf of our customers. It doesn’t matter which area of the business you’re in. We always start with the customer and work backwards, and this touches every part of the hiring and employee experience. Every position in the company impacts our customers, and Amazonians work hard to build solutions in every area of our business.

    MC: I’ve heard that the interview process at Amazon can be long and exacting. What can a senior candidate expect from first interview to offer?

    SH: One of Amazon’s leadership principles is hiring and developing the best. Through our interview process, candidates talk about their skills and experience and ask questions through phone and in-person interviews. As well as understanding our candidates’ backgrounds in depth, we ask our candidates to get hands-on in interviews, which may mean coding on a whiteboard in real-time or solving a business problem. This is what it’s like to work at Amazon — senior level Amazonians provide vision and direction, but can also roll up their sleeves.

    MC: What are some of the hottest skill sets in demand at Amazon today?

    SH: At Amazon, we’re looking for analytical and critical thinkers with great judgment who can both think big and roll up their sleeves to solve hard problems on behalf of our customers. A spirit of innovation is part of our DNA at Amazon, and we’re looking for leaders who can drive innovation in their area and enjoy solving hard problems. While technical skills are important, we really value these more intangible traits.

    MC: I enjoyed your 2008 video series showing the working life of Amazon employees (http://www.youtube.com/user/InsideAmazon). How do you assess cultural fit at Amazon?

    SH: Our company motto is ‘work hard, have fun and make history’. There’s no particular formula for assessing cultural fit, just as there is no formula for a typical Amazonian — we look for smart candidates that are great problem solvers, have a bias for action, and can get the job done. We also have a set of Leadership Principles, which include thinking long-term, innovating, and thinking big, that define successful leadership traits at Amazon. We look for people to join Amazon who embody these principles.

    MC: What would you like a former employee to say first about Amazon if someone asked about working there?

    SH: Employees at Amazon have an opportunity to make an impact and solve hard problems on behalf of our customers. It’s a place where builders can build and anyone can drive great innovation for customers. It’s a place where employees are super engaged and passionate about creating a great customer experience.

    MC: For our 4 million professionals thinking about their next great job, what’s the first thing you’d want a prospective employee to know about a career at Amazon?

    SH: Amazonians are builders. We work together every day to innovate on behalf of our customers, and we’re looking for people who want to join us in building solutions in every area of our business. We have tough and interesting problems to solve in all areas of the business, and it’s an environment that values and recognizes builders.

    MC: Thanks for your time, Susan!

    …Well, folks, that’s the straight scoop direct from the folks who brought us the Kindle, Mechanical Turk, and Earth’s Largest Bookstore.

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