Hard Data v Gut Feel

  • Comments posted to this topic are about the item Hard Data v Gut Feel

  • Your touching on something interesting there. I partly compare my ways and methods to those of scientists other people in different roles like a salesman or boss often act more like an artist. While we all can have visions, those that comes from science often has a real base to be built upon with facts supporting it.

  • Good article. Something I read once that has stuck with me is "the plural of anecdote is not data" - I find myself reminding myself of that quite regularly (see signature line!)


    RedLlewy
    "The Plural of Anecdote is not Data"

  • I will avoid getting into anything partisan here, but it would be really nice to have some politicians that are prepared to use evidence based policy, as opposed to the current system where the policy is decided by lobbying and generally corrupt and opaque means, and then 'evidence' gathered to support that policy.

    I know, I'm a hopeless dreamer.

  • call.copse (7/10/2012)


    ... it would be really nice to have some politicians that are prepared to use evidence based policy, as opposed to ... where the policy is decided by lobbying ....

    The evidence is the amount of money they get :w00t:

    "Figures don't lie, Liars figure" is an old saying, but in truth figures do lie. Sample enough data and you can find data to support about anything. I don't think the debate should be between "gut feel" and data. I think it should be about ethical decisions. I think the focus should be on being truthful, not truthful in what I want you to know, but truthful in what is known.

    Did somebody mention something about dreaming. :Whistling:

    <><
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  • Gut Feel is a baby boomer approach. The old "establishment" managers and politicians just need to retire...:)

  • Data analysis is its own science, with its own complexities, and very, very few people are educated and trained in it, and most of those are in the Intelligence field. Stats is just a very small piece of it.

    - Gus "GSquared", RSVP, OODA, MAP, NMVP, FAQ, SAT, SQL, DNA, RNA, UOI, IOU, AM, PM, AD, BC, BCE, USA, UN, CF, ROFL, LOL, ETC
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  • This is not all that simple. In well travelled areas, where data is complete and understood, data should be a priority.

    But data is often incomplete, often wrong. Excessive reliance on data can also tend to keep one on the tried and true and missing the chance at true innovation. You can extrapolate on the past for only so long (RIM) but a really good excutive must be willing to take a risk and throw in a wild card. The famous Pontiac GTO (not the 200* version, you younger guys) was a classic example of breaking all the rules (including company directives) and it changed the automotive landscape. In fact marketing success has often been crippled by people who went by test group data ('new Coke' anyone?) not realizing that merely the fact of organizing a test group distorts the results.

    ...

    -- FORTRAN manual for Xerox Computers --

  • thadeushuck (7/10/2012)


    Gut Feel is a baby boomer approach. The old "establishment" managers and politicians just need to retire...:)

    I see the :), but this thinking by "every" younger generation causes them/us to repeat mistakes made by the older generation. Technology just allows us to do it quicker. 😛 The trick is to see the bad old and the bad new before you use it and make a different choice.

    <><
    Livin' down on the cube farm. Left, left, then a right.

  • thadeushuck (7/10/2012)


    Gut Feel is a baby boomer approach. The old "establishment" managers and politicians just need to retire...:)

    I'll assume by the smiley at the end that this was meant sarcastically/facetiously.

    I'm Gen-X, and plenty of my generation works almost exclusively on "gut instinct". Same for boomers. Same for Gen-Y, millennials, and "greatest generation". It's a human trait.

    But don't mistake "gut instinct" for "not based on data". It may not be based on data from a computer system, but it's based on data as analyzed by instincts built over billions of years, and on knowledge based on a lifetime of experience, education, etc. (The "lifetime" in question may be longer for some than for others, is the primary difference between generations here.) In other words, it can be just as GIGO as data from a computer system, it's just the imput and output methods for the garbage that are different, but it's still data, and still being analyzed by very complex algorithms.

    - Gus "GSquared", RSVP, OODA, MAP, NMVP, FAQ, SAT, SQL, DNA, RNA, UOI, IOU, AM, PM, AD, BC, BCE, USA, UN, CF, ROFL, LOL, ETC
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    "Nobody knows the age of the human race, but everyone agrees it's old enough to know better." - Anon

  • If you can show that there is data to support a decision, it is more likely to be well received than one based on the experience, instinct, or hunches of any person.

    I agree with that statement. Even though experience should have significant import, it's the numbers that matter - or so it seems.

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  • SQLRNNR (7/10/2012)


    If you can show that there is data to support a decision, it is more likely to be well received than one based on the experience, instinct, or hunches of any person.

    I agree with that statement. Even though experience should have significant import, it's the numbers that matter - or so it seems.

    But experience can tell you when to trust the numbers, and how much weight to give them.

    ...

    -- FORTRAN manual for Xerox Computers --

  • jay-h (7/10/2012)


    SQLRNNR (7/10/2012)


    If you can show that there is data to support a decision, it is more likely to be well received than one based on the experience, instinct, or hunches of any person.

    I agree with that statement. Even though experience should have significant import, it's the numbers that matter - or so it seems.

    But experience can tell you when to trust the numbers, and how much weight to give them.

    As long as you look at the numbers. Too many people ignore them

  • The movie "Moneyball"* is about this same topic, except in the realm of professional baseball. Basically, Moneyball is about the application of Business Intelligence/Analytics to baseball.

    One interesting thing the movie showed is that it's not just using numbers which matters, but which numbers you are using that can be even more important. It's not like the "old school" managers and scouts weren't using numbers to evaluate players, but they were using metrics like RBIs and Batting Averages. The Oakland A's started using metrics like On-base Percentages and found they could better predict a player's future success with these kinds of numbers. And since these metrics were undervalued in general by pro baseball, the players who had good On-base Percentages, etc. were also undervalued.

    Their low budget for player salaries was what really drove the A's to have to find a way to compete with teams like the New York Yankees who could spend a bundle on players. Oakland had some amazing success using these new metrics, and the other teams were left scratching their heads about how the A's could do what they were doing with the kinds of players they had signed, at the salary levels they were able to pay.

    * Oh yeah... I think there was a book by the same name too. 🙂

  • Steve Jones - SSC Editor (7/10/2012)


    jay-h (7/10/2012)


    SQLRNNR (7/10/2012)


    If you can show that there is data to support a decision, it is more likely to be well received than one based on the experience, instinct, or hunches of any person.

    I agree with that statement. Even though experience should have significant import, it's the numbers that matter - or so it seems.

    But experience can tell you when to trust the numbers, and how much weight to give them.

    As long as you look at the numbers. Too many people ignore them

    At least partially because they are too often better off ignored.

    Weather forecasts for example. Studies have been done that show that flipping a coin is more accurate.

    Decades of weather forecasts were analyzed for the simple measure, "If the forecast said x-percent chance of rain tomorrow, how often did it actually rain the next day?" For example, if it said 10% chance of rain, and it rained 15% of the time on the following days, then it was incorrect by 50%. If it said 50% rain, and it rained 45% of the days, then it was off by 10%. And so on. This was then measured against flipping a coin, "heads it'll rain tomorrow, tails it won't". The coin-tosses had better overall accuracy.

    Huge, well-funded industries depend on weather forecasts. Aggriculture, shipping, energy, to name a few. The R&D dollars are there. Vast amounts of data are gathered by local weather stations, satelites, and so on. And the accuracy is still lower than a random guess when taken over any meaninful period of time.

    Hurricane-season "predictions" are modified repeatedly throughout the year, and still end up wrong by the end of the year more often than not.

    Moving out of the weather, take a look at the US CBO. The non-partisan Congressional Budget Office. Math and finance wizards with more PhDs than you can shake a stick at. They have all the access to vast amounts of information. And, so far as I can tell, they've never been right yet about anything. They crunch huge amounts of data, they use the most widely accepted and practiced algorithms, and they're consistently off by huge margins, even when they aren't being made to load the numbers a certain way for some political agenda.

    On the other hand, insurance actuary tables are amazingly accurate, but only on large systems of data. X-people will likely die of Y cause in Z time period, given large populations with known smoking, eating, etc., habits. (Smoking and income-level being the two biggest factors, if I remember correctly. Gender might be right up there, I'm not sure.) Can't predict the age-of-death of any given individual with any accuracy, but that's not what they're for.

    Horse racing is another one where real odds can actually be predicted. And, of course, poker and blackjack give the odds to the house or they wouldn't be played in Vegas.

    So, you have to know whether you're dealing with something simple like risk factors associated with smoking, or winning poker hands, or with anything that involves complex systems, like weather, or systems that are very poorly studied and often intentionally muddied, like money+politics.

    But in many of these systems, ignoring the "data" is quite likely the best option. After all, if a coin toss is more accurate, then the data is beyond being simply flawed, and is actually likely to increase your chances of error.

    Keep in mind, though, that all of what I just wrote is written by a serious data-junkie (me), and may be skewed by my prejudices on the subject. (On the other hand, I've accurately predicted every US presidential election since I started noticing them in the '80s. So maybe I'm slightly more accurate than a coin-toss. Who knows?)

    - Gus "GSquared", RSVP, OODA, MAP, NMVP, FAQ, SAT, SQL, DNA, RNA, UOI, IOU, AM, PM, AD, BC, BCE, USA, UN, CF, ROFL, LOL, ETC
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    "Nobody knows the age of the human race, but everyone agrees it's old enough to know better." - Anon

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