[HN Gopher] Goodhart's Law
___________________________________________________________________
Goodhart's Law
Author : rfreytag
Score : 132 points
Date : 2021-09-17 13:42 UTC (9 hours ago)
(HTM) web link (en.wikipedia.org)
(TXT) w3m dump (en.wikipedia.org)
| [deleted]
| baron_harkonnen wrote:
| I once mentioned Goodhart's Law to a data scientist at a company
| and they immediately rejected it based on the unironic assertion
| that
|
| "that would mean that KPIs shouldn't be the sole measure of our
| performance that that doesn't make sense!"
|
| My experience in the field has been that an astounding number of
| products have been destroyed and users harmed by failing to heed
| Goodhart's Law.
| dang wrote:
| Is Goodhart's Law a sort of upper bound on the usefulness of
| data for decision-making in general?
| baron_harkonnen wrote:
| Rather than implying a limit to the usefulness of data, I
| find it speaks more to the folly of substituting data for
| critical thinking.
|
| You can reduce a fever by treating the underlying infection,
| soaking in ice water, or taking acetaminophen. No good doctor
| would judge a patient's health solely because a single
| metric, namely body temperature, was able to be moved into
| acceptable ranges. That doesn't mean temperature isn't
| extremely valuable data, and essential to decision making,
| but that it cannot be a substitute for understanding and
| solving the real problem.
|
| I once knew of a SaaS company that had perpetually growing
| MRR (Monthly Recurring Revenue), great right? Except, churn
| was also growing. An increase in MRR was achieved by
| upselling a perpetually shrinking group of core customers.
| The core KPI of this company was MRR, and, unsurprisingly,
| this company does not exist anymore. Again, here is a case
| where we can see all that other data (churn, upselling) is
| very useful, as is the KPI. But the key to success or failure
| here is whether or not you want to really expend the effort
| to understand the problem or just chase a KPI.
|
| KPIs are seductive because they make managing team's
| performance seem much easier: just get this number higher and
| you're doing good, get it lower and you're doing bad. But
| that's like playing a game of chess where each piece is
| controlled by a different person, and that person is judged
| solely on how many times they can get the king in check.
| cratermoon wrote:
| > No good doctor would judge a patient's health solely
| because a single metric, namely body temperature
|
| That's a good example because as Strathern's formulation
| notes, the problem lies in make the metric the target. It
| would be folly to think that reducing a patient's body
| temperature to the normal range is sufficient for curing
| illness. GE's Jack Welch famously focused solely on the
| stock performance as a measure of success. It worked, by
| that measure GE was wildly successful. By almost any other
| measure Welch destroyed GE
| https://www.bnnbloomberg.ca/jack-welch-inflicted-great-
| damag...
| some_furry wrote:
| I wonder if measuring managers' understanding of Goodhart's Law
| would result in better management.
|
| /s
| dhosek wrote:
| Are you sure it was unironic? Because I sure can't imagine
| anyone saying that unironically.
| marcosdumay wrote:
| I've heard plenty of "what else do I have to work with?",
| that has about the same meaning.
| rhizome wrote:
| The politician's syllogism comes to mind: "Something must
| be done, this is something, so we must do this."
|
| https://en.wikipedia.org/wiki/Politician%27s_syllogism
| gipp wrote:
| That at least acknowledges that it's an unsatisfactory
| situation, OP's conversation didn't even have that level of
| awareness.
| dboreham wrote:
| Presumably someone, somewhere, thinks KPIs are a good idea.
|
| Edit: but that person is unlikely to be subject to KPIs
| themselves.
| AnimalMuppet wrote:
| Re your edit: Not necessarily. They may be a winner under
| the KPI regime, and may feel that they are less likely to
| be so under a saner regime.
|
| For example, if I'm a manager that can make my people hit
| their KPIs, and _my_ KPIs are about getting my people to
| hit theirs, then I 'm subject to KPIs, _and I like it_. It
| 's easier than making my people succeed at what really
| matters, and it makes me look good.
| hpoe wrote:
| To push against this point I prefer KPIs, or something
| objective that I can be measured against, now that doesn't
| mean I like bad KPIs but the fact of the matter is there
| are always going to be KPIs the only question is how
| explicit or implicit they are.
|
| When KPIs are explicit everyone knows what they are and can
| modify their behavior to optimize for their KPIs when all
| measurement goes away the new KPI is the arbitrary one held
| in the decision makers head, and now instead of it being an
| explicit bar that can be objectively used to make decisions
| the entire system falls apart into politics and emphasizing
| appearances over work because the only thing that matters
| with implicit KPIs are what everyone else thinks of you,
| which is much easier to manipulate than the amount of cash
| you brought in.
| cs702 wrote:
| The same phenomenon has many different names. From the OP:
|
| > See also:
|
| > Campbell's law - "The more any quantitative social indicator is
| used for social decision-making, the more subject it will be to
| corruption pressures"
| https://en.wikipedia.org/wiki/Campbell%27s_law
|
| > Cobra effect - when incentives designed to solve a problem end
| up rewarding people for making it worse
| https://en.wikipedia.org/wiki/Cobra_effect
|
| > Gaming the system
| https://en.wikipedia.org/wiki/Gaming_the_system
|
| > Lucas critique - it is naive to try to predict the effects of a
| change in economic policy entirely on the basis of relationships
| observed in historical data
| https://en.wikipedia.org/wiki/Lucas_critique
|
| > McNamara fallacy - involves making a decision based solely on
| quantitative observations (or metrics) and ignoring all others
| https://en.wikipedia.org/wiki/McNamara_fallacy
|
| > Overfitting https://en.wikipedia.org/wiki/Overfitting
|
| > Reflexivity (social theory)
| https://en.wikipedia.org/wiki/Reflexivity_(social_theory)
|
| > Reification (fallacy)
| https://en.wikipedia.org/wiki/Reification_(fallacy)
|
| > San Francisco Declaration on Research Assessment - 2012
| manifesto against using the journal impact factor to assess a
| scientist's work
| https://en.wikipedia.org/wiki/San_Francisco_Declaration_on_R...
|
| > Volkswagen emissions scandal - 2010s diesel emissions scandal
| involving Volkswagen
| https://en.wikipedia.org/wiki/Volkswagen_emissions_scandal
|
| Source: https://en.wikipedia.org/wiki/Goodhart%27s_law#See_also
| Beldin wrote:
| Inspired by a scandalous fraud case in scientific publishing, i
| wrote a paper applying Goodhart's Law to scientific publishing
| ("A Much-needed Security Perspective on Publication Metrics",
| published at the Security Protocols Workshop 2017). That was a
| really fun paper to write! Basically, how can you systematically
| start cheating at publishing - and how could you catch that?
|
| The most fun was challenging the audience - security researchers
| all - to think even more outside the box than usual for them.
|
| I'm still (slowly) forging ahead on ideas spawned by this paper.
| Bringing the ideas of catching crooks to reality was not as
| straightforward as hoped. Then again, when has any project ever
| gone as planned?
| MattGaiser wrote:
| The ignoring of this law in software development is referred to
| as Scrum.
| azhenley wrote:
| I wrote a blog post a few months ago about Goodhart's Law in my
| life, titled "Gamification, life, and the pursuit of a gold
| badge".
|
| https://web.eecs.utk.edu/~azh/blog/gamification.html
|
| The Tyranny of Metrics is a good book that covers real-world
| cases of metrics gone wrong.
| paulpauper wrote:
| This is why efforts at raising school test scores have not
| improved actual achievement
| wyager wrote:
| And why sending everyone to college hasn't achieved anything
| good.
| dnautics wrote:
| This is why efforts at alleviating poverty have not improved
| actual poverty...
| umvi wrote:
| Poverty is a special case though because it's relative. You
| could be a millionaire with a yacht on earth but be below the
| poverty line if the middle and upper classes live in space
| stations or on other planets with higher standards of living.
|
| An impoverished person in the US is rich compared to an
| impoverished person in India or Africa.
| nicodds wrote:
| It is like quantum mechanics: the measurement process produces a
| perturbation of the physical system
| rpdillon wrote:
| A closely-related effect I often cite is the McNamara fallacy[0],
| which is essentially about the tendency to focus on aspects of a
| system that are easily measurable, often at the expense of
| aspects that are not. I see it as one of the weaknesses of the
| data-driven decision-making movement, since many interpret "data"
| to mean "numbers". I think this fallacy can partly explain why
| Goodhart's Law holds: it's the non-measurable (or difficult-to-
| measure) aspects that suffer most when a metric becomes a target,
| since measurable aspects could be (and often are) integrated into
| the target metric.
|
| [0]: https://en.wikipedia.org/wiki/McNamara_fallacy
| serverholic wrote:
| Another problem is that overly focusing on metrics means that
| people with good instincts are brought down to the same level
| as those with poor instincts.
|
| As long as metrics are increasing someone can write shit code
| and design a bloated product.
| burnafter182 wrote:
| As it's told by Mandelbrot, the January effect was identified.
| Rather quickly it was exploited to the point where it no longer
| existed because the market exerted pressures to counteract it
| in the process of exploiting it.
|
| "Consider three cases. First, suppose a clever chart-reader
| thinks he has spotted a pattern in the old price records--say,
| every January, stock prices tend to rise. Can he get rich on
| that information, by buying in December and selling in January?
| Answer: No. If the market is big and efficient then others will
| spot the trend, too, or at least spot his trading on it. Soon,
| as more traders anticipate the January rally, more people are
| buying in December--and then, to beat the trend for a December
| rally, in November. Eventually, the whole phenomenon is spread
| out over so many months that it ceases to be noticeable. The
| trend has vanished, killed by its very discovery. In fact, in
| 1976 some economists spotted just such a pattern of regular
| January rallies in the stocks of small companies. Many
| investors close their losing positions towards the end of the
| year so they can book the loss as a tax deduction--and the
| market rebounds when they reinvest early in the new tax year.
| The effect is most pronounced on small stocks, which are more
| sensitive to small money movements. Alas, before you rush out
| to trade on this trend, you should know that its discovery
| seems to have killed it. After all the academic hoopla over it,
| it no longer shows up as clearly in price charts."
|
| -Benoit Mandelbrot, The Misbehavior of Markets
|
| https://en.wikipedia.org/wiki/January_effect
| Stratoscope wrote:
| This reminds me so much of a Christmas present hack my sister
| and I invented when we were kids. We used to open all our
| presents on Christmas morning.
|
| Then we begged "Can't we open a couple of presents on
| Christmas Eve?" So we got to open a few that night.
|
| Next year was "Well, how about Christmas Eve Morning? Maybe
| just one or two?"
|
| And the next year was "The 23rd is practically Christmas Eve,
| isn't it? It's just a few hours apart. Can't we open all our
| presents on the evening of the 23rd?" And we did!
|
| We didn't push it past that: we were already so happy that we
| got our presents a day and a half before all our friends!
| kbelder wrote:
| "First get rich; then, publish".
|
| If that's not a law, it should at least be a rule-of-thumb.
| miki123211 wrote:
| As far as I'm aware, this is why markets are considered a
| second-order chaotic system. In those systems, measurements
| of how the system performs can actually influence what
| happens next. This is in contrast to first order systems,
| i.e. the weather, which are hard to simulate, but the results
| of the simulations don't affect their accuracy.
| rossdavidh wrote:
| In the context of manufacturing, W.E.Deming said something
| similar: "that which gets measured, gets improved". His
| conclusion from this was a little different than McNamara's,
| though. Since you will inevitably want to track your progress,
| make sure you track as many things as possible, because
| anything which is not tracked will get sacrificed to that which
| is. Up to a point, it's true.
|
| One issue is that some things, like vulnerability to supply
| chain disruptions, are intrinsically harder to track because
| they are based on rare occurrences. Thus, they will tend to get
| sacrificed in favor of measures which are more frequent,
| leading to an emphasis on short-term strategies.
| CalChris wrote:
| Actually, Deming said much the opposite: It
| is wrong to suppose that if you can't measure it, you can't
| manage it - a costly myth.
|
| p. 26 of The New Economics for Industry, Government,
| Education
|
| It wasn't Drucker either.
|
| https://medium.com/centre-for-public-impact/what-gets-
| measur...
|
| This whole mindless _must measure, must measure_ mentality
| has been criticized since the 50s. Measurement is a tool.
| There are many tools.
| rossdavidh wrote:
| In my experience, if it isn't measured, then it is assumed
| that the policy (whatever it is) is working. If you don't
| measure, you can't be surprised by "wow, it didn't work
| like we thought". Therefore, mistakes don't get recognized
| or corrected. There are many tools, but measurement is one
| of the only ones that brings unexpected bad news to the
| user, and that is invaluable.
| mumblemumble wrote:
| I would argue that it's worthwhile to measure as much as
| you can, insofar as it facilitates orderly decisionmaking
| processes.
|
| The problem is that people tend to think that all
| measurement is necessarily quantitative. I think that this
| might be a version of the streetlight effect? Quantitative
| measurements tend to be much easier to collect and analyze
| than qualitative measurements. Oftentimes you can let it
| all run on autopilot, whereas doing good qualitative work
| always requires concentration, effort, and expertise.
| mhink wrote:
| > One issue is that some things, like vulnerability to supply
| chain disruptions, are intrinsically harder to track because
| they are based on rare occurrences. Thus, they will tend to
| get sacrificed in favor of measures which are more frequent,
| leading to an emphasis on short-term strategies.
|
| I suppose this is part of why "chaos engineering" has gained
| popularity- introducing artificial disruptions at a known
| rate makes it easier to quantify the impact of otherwise-
| unusual events.
| rossdavidh wrote:
| Ooh, good point! Another example is auditing, where you
| substitute regular, frequent disruptions (being audited is
| disruptive to normal operations) for infrequent, less
| predictable, bigger disruptions.
| cryptica wrote:
| To make matters worse, it's also a vicious cycle. For example,
| if everyone is focused only on specific kinds of data and
| ignores observable reality, the trend in the data will become
| self-fulfilling until a point when the perceived inconsistency
| between the data and observable reality has grown so large that
| it becomes impossible to ignore.
|
| To understand what the big problems are today, you just have to
| think about the kinds of data which people in government (and
| the public) haven't been thinking about or aiming for. For
| example: Happiness, honesty, altruism, sanity... These are not
| measured and not targeted so they got completely crushed.
|
| In the past, large, powerful religious groups would target
| these characteristics but nowadays, society is more secular so
| these aspects of our lives have suffered significantly.
| serverholic wrote:
| That's one of the thing Andrew Yang talks about. GDP isn't
| the only thing that matters, nor is it the best metric.
| miki123211 wrote:
| I believe this effect greatly contributes to why government IT
| systems are so bad.
|
| When you're writing a procurement contract, it's relatively
| easy to describe what the requested system must do, but almost
| impossible to enforce a great UI design, as great UI design
| isn't objectively measurable.
|
| As a contractor, you're optimizing for minimum money spent, so
| if good design is not required, good design gets sacrificed
| first.
|
| One solution to this specific problem would be to conduct user
| surveys on how pleasant the system is to use, requiring a
| specific score before the contract is deemed completed.
|
| This trend manifests more generally in bigger organizations.
| Smaller orgs let people judge things subjectively, so all
| possible aspects are taken into account, making those things
| relatively good; this is why startups succeed. In a bigger org,
| there are often objective judgement measures to prevent the
| influence of personal biases, politics or even bribes. However,
| those measures poorly reflect how good the thing in question
| actually is. This is why a big corp might produce worse
| software, even when competing against a small and underfunded
| startup.
|
| As an example, Apple exempted the first iPhone crew from most
| internal company procedures, creating a quasi-startup inside
| Apple. Steve Jobs always had the final say, and his opinions
| were based on what he thought personally, not on how many
| points in a requirements specification were satisfied. I
| believe this was one of the reasons for the iPhone's success.
| cratermoon wrote:
| > government IT systems
|
| This is not limited to governments. Although it's a common
| naive bias to assert that governments are worse and less
| efficient than private industry, what is really happening is
| that government budgets and projects are open to the public,
| done in the open. For every failed Healthcare.gov, there are
| dozens of private industry failures that don't make the news
| because the operations are not subject to the public
| disclosure rules.
| ghaff wrote:
| It's a genuinely hard problem because the quantifiable output
| metrics are easy to measure and an individual often does have
| some level of direct control over them. So we convince
| ourselves that they're a reasonable proxy for something we care
| about but aren't sure how to measure and that we have control
| systems in place, whether management or individual
| responsibility, that largely prevent e.g. quality being thrown
| away in pursuit of quantity.
|
| And we're often not entirely wrong if we do pick reasonable
| proxies and have reasonable control systems in place. Because
| throwing up our hands and saying metrics are useless is usually
| not the answer either.
| serverholic wrote:
| The better option is to put someone in charge with a vision.
| However that is risky.
| TeMPOraL wrote:
| A flavor of this problem is what could be called "diffusion
| of responsibility", for a lack of better term. An individual
| who defined the measure and then optimizes for it will
| quickly figure out when their measure stops being a good
| proxy. But in organizations there usually isn't a single
| person who both understands what the measures are proxying,
| and has the power to remove a metric once it is used up, or
| get people to stop overfitting it.
| Jtsummers wrote:
| Another thing I've observed is when you have two measures
| that operate at different time scales. Both may even be
| valid measures, but the one measured (and responded to)
| more often has a stronger impact, and can negatively impact
| the less frequently measured metric when there's a conflict
| between them.
|
| A particular instance for this has been (to keep it simple)
| quantity (speed) and quality in production environments
| (factories and the like). Daily throughput measures paired
| with less frequent quality measures. The desire is to keep
| throughput high, and quality ends up suffering as a result.
| By integrating quality measures into the process you make
| the two measures compete on more equal footing, forcing a
| balance. At least one factory I worked in (well, adjacent
| to, I was in the software portion not the assembly line)
| massively reduced their quality problems by integrating
| quality checks between each station. This contrasted with
| the prior years where throughput, being measured and
| reacted to daily, drove them to make things so fast that
| they had piles of rework at the end. Integrating the
| quality measures between stations slowed them down, but
| their rework numbers turned into a rounding error (over a
| decade ago so I've forgotten the exact numbers, but they
| went from having items needing rework nearly every day to
| maybe one or two a month). As a result their real
| (deliverable to customers) production increased and their
| cost per unit dropped.
| AceyMan wrote:
| I see this as the root cause of the recently announced
| class action suit against LADWP over their implementation
| of tiered electricity pricing.
|
| The tiers (kwh rates) are in hunks of the a day measured
| in hours.
|
| But the _reporting_ is only available to the consumer in
| the form of a monthly bill, so by the time you discover
| you were eating pixies in the Peak Cost hours the heat
| wave is over and your bill is already through the roof.
|
| (Any local SoCal residents please feel free to pick my
| analysis apart, but that was my first take when I heard
| about the legal action.)
| cratermoon wrote:
| Also https://en.wikipedia.org/wiki/Campbell%27s_law
| dang wrote:
| Past related threads. In this case a few of the 1-or-2 comment
| threads have particularly good posts:
|
| _Goodhart 's Law_ -
| https://news.ycombinator.com/item?id=26839177 - April 2021 (2
| comments)
|
| _Goodhart's Law Rules the Modern World. Here Are Nine Examples_
| - https://news.ycombinator.com/item?id=26604130 - March 2021 (3
| comments)
|
| _Goodhart 's Law and how systems are shaped by the metrics you
| chase_ - https://news.ycombinator.com/item?id=23762526 - July
| 2020 (58 comments)
|
| _When Goodharting Is Optimal_ -
| https://news.ycombinator.com/item?id=22054359 - Jan 2020 (3
| comments)
|
| _Goodhart's Law: Are Academic Metrics Being Gamed?_ -
| https://news.ycombinator.com/item?id=21065507 - Sept 2019 (27
| comments)
|
| _Goodhart's Law: Are Academic Metrics Being Gamed?_ -
| https://news.ycombinator.com/item?id=20076485 - June 2019 (2
| comments)
|
| _When targets and metrics are bad for business_ -
| https://news.ycombinator.com/item?id=19135694 - Feb 2019 (6
| comments)
|
| _Goodhart 's Law: When a measure becomes a target, it ceases to
| be a good measure_ -
| https://news.ycombinator.com/item?id=17320640 - June 2018 (134
| comments)
|
| _Goodhart 's Law_ -
| https://news.ycombinator.com/item?id=10075780 - Aug 2015 (1
| comment)
|
| _Goodhart 's law_ - https://news.ycombinator.com/item?id=1368745
| - May 2010 (1 comment)
| rfreytag wrote:
| Earlier posts here (134 comments):
| https://news.ycombinator.com/item?id=17320640
|
| and here (58 comments):
| https://news.ycombinator.com/item?id=23762526
|
| Also NPR's Planet Money (audio) also covered this interviewing
| Goodhart himself:
| https://www.npr.org/sections/money/2018/11/19/669395064/epis...
| lisper wrote:
| It is possible to turn this effect to your advantage. I wrote a
| spam filter that takes advantage of signals that would be easy
| for spammers to spoof (like the list-id header), but no one
| spoofs them because no one but me uses this approach to spam
| filtering. So, ironically, if more people used my spam filter, it
| would probably stop working as well as it does now.
| paulorlando wrote:
| Good that this topic gets some attention. I see Goodhart's Law
| again and again in metrics. I wrote about this a while back,
| including why we use the misleading name.
| https://unintendedconsequenc.es/new-morality-of-attainment-g...
| bedhead wrote:
| I do investment stuff for a living and this was one of the
| single-most important things I ever learned.
| pikwip wrote:
| Here's a interesting paper I found that attempts to categorize
| the mechanisms by which Goodhart's Law operates in the real
| world. The variants are separated into Causal and Non-causal
| mechanisms.
|
| https://arxiv.org/abs/1803.04585
| derbOac wrote:
| Thanks for posting that. I was going to say -- it's interesting
| to think about the reasons why Goodhart's Law might hold if it
| does.
|
| I've always assumed the problem is that the metric is always
| influenced by other, nontarget variables that become more
| causally important when the metric becomes a proxy target. So,
| for example, "gaming the metric" becomes important (in a
| percent variance sense) after the metric becomes a target. I
| think the paper's adversarial scenario is closest to this
| maybe.
|
| They discuss some other factors that seem more relevant to
| individual cases at any moment in time than an explanation for
| why a metric's utility might decline over time. In that sense
| the paper seems to be more about Goodheart-like phenomena in
| general.
|
| It would be interesting to demonstrate Goodheart's law
| conclusively with real data in some domains.
| vagab0nd wrote:
| Here's another interesting one that's somewhat related:
|
| https://en.wikipedia.org/wiki/Decline_effect
| rfreytag wrote:
| Could be...yes.
|
| "Decline effect" could also be mostly due to the
| https://en.wikipedia.org/wiki/Replication_crisis
|
| Goodhart's Law starts out as effective and the social system it
| purports to measure adapts (some might say 'distorts'), till
| the measure not longer serves its original purpose.
| brightball wrote:
| One of the most important lessons to promote.
| gftsantana wrote:
| My first job was at the anti-fraud department at a telecom
| company in the early 00s. Our job was basically to determine
| whether a new landline or mobile contract was fraudulent or not.
| Some requests would be flagged by an automated piece of software
| that was basically a black box to most employees, myself
| included. We would basically look at the documents sent by the
| clients and, sometimes, ask a few questions via phone.
|
| I was very young at the time, but I remember basically deriving
| Goodhart's law after a few months in the job. I don't remember
| clearly most of the things that led me to that conclusion, but I
| do remember the most extreme: at some point, management started
| requiring us to block clearly non-fraudulent phones because the
| directors decided to increase the blocked installations target.
| It would include even old contracts by good paying customers that
| happened to be flagged.
|
| I remember trying to talk to people about this, but the idea that
| trying to reach a target by any means necessary is usually not a
| good idea was incomprehensible to most people. Years later, I
| realized that others knew exactly what was going on; they just
| didn't care, and I was naive for not seeing that.
|
| It was a few years later when I learned about perverse
| incentives, Goodhart's law, the cobra effect, etc., and it
| allowed me to have more productive conversations with people
| about targets and incentives.
| cratermoon wrote:
| When I explain the concept to people I usually call it the
| Goodhart-Strathern principle, to recognize the generalization she
| contributed and acknowledge the author of the most-commonly
| quoted form of the law: "When a measure becomes a target, it
| ceases to be a good measure"
| colechristensen wrote:
| The only systems that escape goodhearts or similar laws are those
| that have either A) people who genuinely care about quality and
| have the judgment for it or B) systems where the mechanics of how
| the control variable effects the system are well understood.
| (i.e. no black boxes)
| leephillips wrote:
| I think the only way to apply a metric while avoiding the
| consequences of the Law is to keep the metric secret. As soon
| as the subjects are aware of the metric, they will try to
| optimize it, rather than the real performance that the metric
| is supposed to indicate.
|
| There is a close connection with security, say screening at
| airports. If you fail to keep your screening criteria secret,
| the terrorists will simply ensure that they do not match the
| criteria. One way to thwart this is through randomness. There
| is a long public debate between Sam Harris and Bruce Schneier
| where the latter tried in vain to explain this to the former,
| who insisted that it was a waste of resources to search little
| old ladies. If one of your metrics is "don't search little old
| ladies", the terrorists will discover this through time by
| observation. The next bomb will be carried by a little old
| lady.
| _greim_ wrote:
| What's the takeaway? How can statistics inform action, if such
| action invalidates those statistics?
| ItsMonkk wrote:
| You need to measure the KPIs.
|
| The reason we use metrics is because things have scaled out of
| control, and using a "real" judgment system is no longer
| possible. Not for everyone, anyway.
|
| Using hiring as an example, but this should work for nearly all
| metrics driven workloads. Hire a small subset of your staff
| using a real judgment system, hire most of your staff using
| metrics, then take a sample of those hired using metrics and
| take a real look at them compared against those hired using
| real judgments.
|
| If they are reasonably close, the KPIs are working. If they are
| alien to each-other, you need to either stop using KPIs or
| alter them significantly to fit with what the more effective
| people are doing.
| rhizome wrote:
| > _You need to measure the KPIs._
|
| What KPIs do you use when the statistics are being used to
| measure whether the KPIs are the right ones?
| cryptica wrote:
| The take away is that governments and large institutions which
| impact large numbers of people should never attempt to set
| quantifiable targets and should never attempt to meet
| quantifiable targets.
| Jtsummers wrote:
| That we can't stop thinking. It becomes too easy to stop using
| our own judgement when we have numbers to back up our
| decisions. We can point to he analysis and say, "Look, we've
| improved <metric>!". That itself becomes the justification for
| the actions taken, regardless of their actual sensibility.
|
| This is an area where discipline remains essential, and
| maintaining discipline is a constant battle.
| castlecrasher2 wrote:
| That statistics should inform action or measure of efficacy,
| but not drive it.
|
| A dev manager running on only numbers will inevitably get
| empty, meaningless values such as tickets resolved or lines of
| code written, while the polar opposite manager will run on
| intuition alone. I imagine most would agree neither type is
| generally effective and a balance should be struck, and
| Goodhart's Law means you should be aware of what's important,
| pay attention to it, but do not make it your sole focus. And
| for God's sake, don't make a public dashboard for it.
| starnger wrote:
| I could not help but relate it to Heisenberg uncertainty
| principle.
| thekhatribharat wrote:
| me too :)
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