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Businesses IT

Big Data Knows When You Are About To Quit Your Job 185

HughPickens.com writes Quentin Hardy reports at the NYT that a leading maker of cloud-based software for running corporate human resources and financial operations has announced new products that provide the kind of data analysis that Netflix uses to recommend movies, LinkedIn has to suggest people you might know, or Facebook needs to put a likely ad in front of you. One version of the software, called Insight Applications, predicts which high-performing employees are likely to leave a company in the next year; it then offers possible actions (more money, new job) that might make them stay. In another instance, expense reporting software can predict which employee populations are most likely to exceed their budgets. "We've applied machine learning to affect consumer tastes," says Mohammad Sabah, director of data science at Workday. "Putting it to career choices, to pay and employment, have a huge upside if we do it right." Already, Sabah says, "we're surprised how accurately we can predict someone will leave a job." The goal is to predict future business outcomes to take advantage of opportunities and cut risk levels. One future product may be the ability to predict who will and won't make their sales quotas, and suggest who should be hired to improve the outcome. "Making an employee happy, improving the efficiency of a company these are hard problems that affect corporations."
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Big Data Knows When You Are About To Quit Your Job

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  • by Anonymous Coward on Friday November 07, 2014 @03:18AM (#48332235)

    When managers and supervisors know you're probably going to quit, it's a different story from "I hear he's gotten an offer from other companies". Data like this gets trusted implicitly, and if you weren't planning to leave this year, your new and improved toxic environment will make damn sure of it.

    More likely though this software will be used to maximize everyone's ability to treat low level employees like machines.

    • Maybe, maybe not. (Score:5, Interesting)

      by khasim ( 1285 ) <brandioch.conner@gmail.com> on Friday November 07, 2014 @05:30AM (#48332563)

      I'm guessing that their "algorithm" is more like:

      X% change jobs after 1 year.
      Y% change jobs after 2 years.
      Z% change jobs after 3 years.
      etc.

      In my experience, people tend to change jobs because of something happening at their current job (or a personal/family situation change). And that's not something that can be predicted with any degree of accuracy.

      • by Cederic ( 9623 ) on Friday November 07, 2014 @06:41AM (#48332775) Journal

        So you don't think that a combination of factors such as where you live, how much you get paid, relative market rates, current job market conditions, your recent payrises, your recent year end appraisal scores, where your partner works, your age, your time since last promotion or anything else the company has or can easily gain access to would be an indicator of how likely you are to leave?

        Remind me not to ask you for data driven insights.

        • by nabsltd ( 1313397 ) on Friday November 07, 2014 @08:55AM (#48333291)

          So you don't think that a combination of factors such as where you live, how much you get paid, relative market rates, current job market conditions, your recent payrises, your recent year end appraisal scores, where your partner works, your age, your time since last promotion or anything else the company has or can easily gain access to would be an indicator of how likely you are to leave?

          Not for some jobs. In a lot of the tech world, the algorithm would be pretty much exactly as the GP listed, at least for talented people who are desired by employers.

          And, what does the company do when "big data" says somebody is or isn't going to leave in the next year? If they use just that metric, the will find out that a lot of people who they thought weren't going to leave end up gone..."we don't need to give him that big of a raise...the computer says he won't leave anyway". Or, "hey, we better find a cheaper replacement for this guy, because he's leaving in the next year" will be a lot more likely than giving the guy what it takes to keep him.

          Then, too, there's a lot of employees who won't ever leave their existing job because they can't do any better anywhere else. Sadly, many of those people are the ones that you might want to encourage to leave.

          • In a lot of the tech world, the algorithm would be pretty much exactly as the GP listed, at least for talented people who are desired by employers.

            Ah yes, we're all precious snowflakes, nothing like those sheeple out there.

            Then, too, there's a lot of employees who won't ever leave their existing job because they can't do any better anywhere else. Sadly, many of those people are the ones that you might want to encourage to leave.

            Yes, let me guess, they're only in work because of evil government interference in the free market of employment which makes it impossible to ever fire someone. Since the whole world is some sort of communist paradise for workers nowadays.

            Please.

          • by Cederic ( 9623 )

            Not for some jobs

            Bullshit. The weightings on each factor may shift according to role, education, profession, etc, but that's why this sort of analysis isn't done in an Excel spreadsheet by the part time temp.

            a lot more likely than giving the guy what it takes to keep him

            I'm not sure I'd agree with 'a lot more likely', but yes, HR could use this information in a very negative way.

            That doesn't negate the value of the information, it impacts whether you can realise that value.

        • So you don't think that a combination of factors such as where you live, how much you get paid, relative market rates, current job market conditions, your recent payrises, your recent year end appraisal scores, where your partner works, your age, your time since last promotion or anything else the company has or can easily gain access to would be an indicator of how likely you are to leave?

          I have never left a position for any of the reasons you listed. I have only left when the situation had deteriorated to the point where I couldn't stand being there another day. A toxic work environment, poor employee morale, job off-shoring, incompetent management, not promoting from within, not staffing appropriately/overwork, lack of professional growth, etc. are why I've left. By all of the metrics you listed I should have been happy.

          If a company needs to use a computer algorithm to judge an emplo

      • I'm guessing that their "algorithm" is more like:

        X% change jobs after 1 year.
        Y% change jobs after 2 years.
        Z% change jobs after 3 years.
        etc.

        In my experience, people tend to change jobs because of something happening at their current job (or a personal/family situation change). And that's not something that can be predicted with any degree of accuracy.

        It's hard to predict a single person with any degree of accuracy. It's easy to place a group of people at high risk.

        Take whatever you know about someone...

        And weigh that against how many times you put the words "tired," "traffic," "supervisor," and "human resources" in your posts.
        And weigh that against what your posting frequency during working hours.
        And weigh that against what Google Now knows about when you drive to work, and how early you leave every day.
        And weigh that against how long you linger betwee

    • by Lumpy ( 12016 ) on Friday November 07, 2014 @06:30AM (#48332745) Homepage

      If your work knows you are about to leave, it's because you were broadcasting it. Every time I left a company I broadsided them.

      Boss: "I though you were happy here"
      Me:"I have asked for a raise 3 times, you said no"
      Boss: " but we are paying you market rate"
      Me: "I'm getting 30% more with XYZ corp, so it seems you are not"
      Boss: " You know there is more to life than money"
      Me: " Yup, but I can not do any of that with the incredibly low pay you are giving me here"

    • No. They will use their metrics based on performance appraisals and the like.
      Of course, Performance Appraisals are just to document the bonus you get or don't get.
      They would just better data mine browsing habits at work and correlate that with skills and market pull for these.
    • by BarbaraHudson ( 3785311 ) <barbara.jane.hud ... minus physicist> on Friday November 07, 2014 @07:40AM (#48332953) Journal
      When anyone talks about "Putting it to career choices, to pay and employment, have a huge upside if we do it right" wrt people's pay, it's more like "they won't quit even if you tell them they're going to have to take a cut in pay" than "offering a raise to keep them happy." Anyone who thinks it won't be sold as a cost reduction method is a fool.
    • I can make it simple. If a company uses Big Data to analyze my behavior I will quit within a year. 100% prediction accuracy. See Big Data works.

      I also consider manipulating the impressions Big Data gathers on me to be a fun and engaging hobby.

  • by MRe_nl ( 306212 ) on Friday November 07, 2014 @03:18AM (#48332239)

    I never quit, I just go bankrupt ; ).

  • by Nyder ( 754090 ) on Friday November 07, 2014 @03:19AM (#48332243) Journal

    So now we can let machines do the hiring, firing, promoting & fluffing of employees.

    Nothing will go wrong with this.

    • by Thanshin ( 1188877 ) on Friday November 07, 2014 @04:23AM (#48332393)

      Well, if we're replacing all resources for machines, we will have machines hiring, firing, promoting and fluffing other machines.

      On a thinly related topic, I still struggle with the concept of automation of work creating poverty instead of wealth. Imagine an alien being coming to Earth and saying
      "We decided to make contact because you finally achieved the milestone of eliminating the need to work."
      To which the humanity replies:
      "Yep, we're all jobless, poor and hungry now."

      • by ultranova ( 717540 ) on Friday November 07, 2014 @08:52AM (#48333275)

        On a thinly related topic, I still struggle with the concept of automation of work creating poverty instead of wealth.

        It's because our economic system originates from before Industrial Revolution, and was designed to get everyone to "bust their ass" working. It was designed to maximize production in a situation where labour was the limiting factor, and breaks down spectacularly when raw materials (including energy) are.

        Total demand = (demand of labour of previous timestep) * (fraction of GDP paid as wages) + min((fraction of GDP paid as profits), constant)

        Demand of labour = (avg((total demand), (total demand of previous timestep)) / productivity

        As long as productivity stays low, production is limited by workforce, and economy tends towards full employment. If productivity increases faster than wages, as has happened, you eventually hit a situation where total wages of all workers can no longer create enough demand to buy the entire supply. Market prices fall, and companies need to invest on increasing efficiency rather than increasing production to keep their profits up. Since a physical product will always require a certain amount of raw materials, eventually they reach the point where the only thing they can cut is workforce. This causes demand to fall (you can only spend money you have), and thus the economy enters a stall.

        This is also why stimulus isn't working: investment now goes to cutting workforce - and thus demand - further, not expanding production. The only way to actually fix the economy would be to increase the buying power of Joe Average. This, in practice, means drastically increasing wages and unemployment benefit, in other words, to move income from the rich to the poor. That seems unlikely to happen, especially under a Republican government, so I guess we're seeing the twilight of capitalism.

        Of course, it's also possible to keep demand up and economy working by giving credit with reckless abandon and hope you can keep juggling an ever more complex web of financial instruments to obfuscate that. But who would be stupid enough to risk the fate of their country - and their own golden goose, and possibly the entire Western civilization - for that, rather than just ensure people are paid enough?

        • by stdarg ( 456557 )

          I think that's a really interesting take on things, but I disagree that it means the twilight of capitalism. It sounds more like the end of long work weeks. We'll still need a way to choose economic winners and losers, a way to vote that product A fills our needs at a given price better than product B. That's true even if 100% of the population is on welfare and robots do all the work.

          I also think it's a mistake to leave out the service economy. There may well come a time when human labor is entirely worthl

          • I think that's a really interesting take on things, but I disagree that it means the twilight of capitalism. It sounds more like the end of long work weeks.

            If you get a shorter workweek with the same pay, it's an effective pay rise (which I recommended). If you don't, how will that help? Same total wages = same total demand.

            We'll still need a way to choose economic winners and losers, a way to vote that product A fills our needs at a given price better than product B.

            Of course we need an economic system.

    • by Lumpy ( 12016 )

      wait there is fluffing?

      Dammit I am in the wrong business, I get no fluffing.

    • This was covered in Manna (http://marshallbrain.com/manna1.htm).

      The story is about how a burger chain installed software to "manage" employees by telling them to wear a headset and follow the commands given to them. Although not named as such, Manna was a realtime ERP system that managed employees in the most efficient way at any given point in time. The counter a bit slow? Reassign those employees to cleaning the restaurant, rest rooms, kitchen, whatever. Getting busy? More people on the cash registers

    • It might be an improvement in some ways; the machine doesn't have an ego and thus doesn't do stupid things out of an irrational need for retaliation.

  • by Roodvlees ( 2742853 ) on Friday November 07, 2014 @03:21AM (#48332247)
    "Putting it to career choices, to pay and employment, have a huge upside if we do it right."

    Yea especially the "if we do it right" part. Because if you do it wrong it could have very damaging personal consequences. Machine learning by definition generalizes across the population, so if you don't behave like others have before you, you are screwed. Especially in the USA where employers have very little power this will be used against people and cause serious career damage.
    • I don't think "upside" for the employees is particularly what they had in mind. (Actually, it can't be, because employees don't have the data to populate this sort of model - only the employer does).

      Harm to employees also doesn't require them to do anything wrong, if by that you mean "incorrect." If the algorithm notices that you're a caregiver for your aging mother, and you have 3 kids in high school, and your wife has a state-issued licensed for her job, you're certainly not going anywhere no matter

  • by DNS-and-BIND ( 461968 ) on Friday November 07, 2014 @03:27AM (#48332265) Homepage

    All this software does is make predictions based on averages. It explicitly does not recognize outliers. This is the road to tyranny. It looks great, and offers us much better efficiency than before. We use it to get things done, there is no time lost with needless discussions. If it's wrong 10% of the time, then so what! We consider 90% to be acceptable.

    And then, people start altering their behavior because they know they're being watched. Articles start appearing about how to conform to the mandarins' idea of a model citizen. Viewing these articles is, of course, a black mark against you. And on and on it goes, led by society's best shouting the battle cry, "it's for your own good!"

    • Goodhart's Law (Score:3, Insightful)

      by Anonymous Coward

      When a measure becomes a target, it ceases to be a good measure.

      So, yeah, as soon as people figure out what it is that is being measured, expect them to alter their behavior to make that measure useless.

    • by gsslay ( 807818 ) on Friday November 07, 2014 @04:50AM (#48332461)

      So the headline should be;

      Big Data guess quite well when the average employee may quit a job, on average, usually.

      But that doesn't make as good a click-bait.

    • And on and on it goes, led by society's best shouting the battle cry, "it's for your own good!"

      Really? Because to me, the battle cry sounds a lot more like "if you don't submit to everything corporations want, you're a communist, and go by the way of Soviet Russia!"

      A system that's built on competition self-destructs because it no longer has credible competition. Oh the irony.

  • by TrollstonButterbeans ( 2914995 ) on Friday November 07, 2014 @03:38AM (#48332289)
    A: Top performers usually leave because they are top performers.

    Know the sun will rise does not give one a means to prevent it. Nor death or taxes or progress. It has never been hard to predict top performers leaving.

    B: Sabah says, "we're surprised how accurately we can predict someone will leave a job." Never, ever buy prediction software from a place that is surprised with the result. Quality prediction is the result of hard work and statistical analysis, results should almost NEVER come as a surprise to anyone working in the field statistics or data-modelling. This is one field where "surprise" is a sign of incompetence.
    • But there's currently only a finite number of people who can properly devise data models and interpret statistical data. There will always be a limit to how "reliable" derived information can be.

    • by Anonymous Coward on Friday November 07, 2014 @05:01AM (#48332507)

      Their algorithm is pretty obvious just looking at their screenshot.

      Analysis dimensions of significance:
      1. Number of roles in the company: people with more roles are likely less assertive about what their job responsibilities should be and have less self confidence to refuse unwanted assignments. They are eager to please suggesting engagement in the company culture and optimism about future outcomes. Most importantly: they cannot simply go across the street to any old business because the niche they fill internal to the company seems to be a complex balance of complementary skills. While this makes them difficult to replace, it also limits the transferability of their skills to other employers. The longer they have allowed themselves to stagnate in this "devops" type jack of all trades role: the more difficult a departure will be. Their salary increases will not keep pace with their peers who do job-hop but by the time they notice they will already be a captive cog in the machine. Their replacement cost is likely manageable simply because the skills they posses are likely to be easily learned on the job, and their mastery of them is probably far down the tail end of diminishing returns, where the majority of the expertise "value-added" can be quickly gained through field promotions.

      2. Tenure: They can treat all employees as an equal flight risk according to this dimension. They have a probability distribution for leaving the company after X years. The first 2-3 years they are a flight risk, but people who last longer than that probably have risk adverse personalities or have gotten comfortable.

      3. Market Demand: This dimensions is based on job title. Data sources such as Craigslist job listings per month or BLS "growth statistics" are used to give a weighting factor based on the employees job title.

      4. "How underpaid are they?": This dimension isn't explicitly shown on the website but it's obvious they would take consideration of the nice data on Salary.com or Glassdoor to figure out how appropriate an employees salary is. Below market rate salary translates to high risk of departure obviously.

      5. "Time between promotions/pay-raises": This metric might as well be called "internal politics popularity contest metric" because it's simply a course granularity measurement for how appreciated or validated they feel. If they haven't gotten a promotion or pay raise recently: they are more likely to be thinking about moving on to greener pastures. Duh.

      6. "Performance": I suspect this is actually a "feeder" data source for "Market Demand" as much as it is a measurement of which employees should be a priority to retain. That's the unwritten subtext to this entire thing though -> They talk about retaining the top performers but the side effect of this will be investing less money on retaining low performing employees. Their goal is going to be to keep the top performers out of the red, and keep the company at a nice uniform "yellow" with nobody dwelling in the "overcompensated-green-land".

      Gaming the system then becomes obvious: find out what metrics are being used to drive this sterilized spin on "Rank and Yank" and then get even more catty and political to abuse your coworkers in to leaving your little office-"Survivor island". You make your metrics better(relatively speaking) by undermining the performance ranking of those around you via neglecting teamwork related activities that help your coworkers be successful at their activities in favor of self-aggrandizing individual promotion.

    • Comment removed based on user account deletion
  • Algorithm (Score:5, Funny)

    by Alicat1194 ( 970019 ) on Friday November 07, 2014 @04:05AM (#48332343)
    I take it the algorithm looks something like this:

    If EMPLOYEE WEBSURFING equals EMPLOYMENT WEBSITE then output "Employee is thinking of leaving" else output "All good, nothing to see here"?
    • It looks like that would probably be as reliable as what they do use, but cheaper to implement.
    • by chrish ( 4714 )

      Another easy way would be to mine their LinkedIn (or other job sites) profile... mine says I've never stayed at a job as long as five years. Presumably the employer already knows how long you've been working for them.

  • by Anonymous Coward on Friday November 07, 2014 @04:15AM (#48332367)

    if (subjective.IsActiveOnLinkedInLastThirtyDays()){ThinkingOfLeaving = true};

  • by ctrl-alt-canc ( 977108 ) on Friday November 07, 2014 @04:25AM (#48332399)
    ...I think that we should study the algorithm, and adopt behaviours that can deliver us more money from our employer :-)
  • by sasquatch989 ( 2663479 ) on Friday November 07, 2014 @04:37AM (#48332435)

    I have a degree from a Top 25 school.
    I have maxed out my annual merit raise, annual bonus, and have received 2 small performance bonuses.
    My performance reviews are near perfect.
    I make slightly less than median for my title and location, mostly because my peers have a few more years experience than I do.
    I work for an employer that is widely known and respected in the industry that I work.

    For the past 6 months:
    I've been vocal about my displeasure for the working environment.
    I've posted publicly viewable resumes on all the big hiring boards.
    I've added dozens of recruiters to my LinkedIn connections.
    I've been on numerous call screens and interviews.
    I've been so brazen as to upload resumes and cruise job listings FROM MY WORKSTATION

    Today I turned in my 2 week notice.
    I've not once heard from HR or a manager about my career path.
    Management is split between angry and befuddled about this.

    Big Data seems legit

    • by Aqualung812 ( 959532 ) on Friday November 07, 2014 @05:54AM (#48332629)

      I've been a top performer at several companies. I before leaving each of them, I discussed my issues with a manager more than once, which were usually pay + one other issue.
      In each time before I left, neither were addressed.
      In each time after I left, management was either "shocked" or angry, and made attempts to keep me. I flatly refuse to accept offers after I have accepted a job elsewhere, I should be taken at my word and not forced to demonstrate that I am leaving to be taken seriously.
      I have no idea why any company would waste money on this. Either they care, and they'll know when someone is leaving without software, or they don't care, and the software will be ignored as well.

      • Re: (Score:3, Funny)

        Yeah, the program will probably just generate another daily email blast to management/HR that will get lost or ignored

      • I've done the same thing to Comcast/Uverse/WideOpenWest lots of times for the last ten years. They never take me seriously until I call for the disconnect! TOO LATE! The new service is installed. Damn I am happy to have three providers!
    • by Lumpy ( 12016 ) on Friday November 07, 2014 @06:37AM (#48332759) Homepage

      "I make slightly less than median for my title and location, mostly because my peers have a few more years experience than I do."

      Stop accepting this bullshit line when you hear it. If you regularly out perform your peers that have more experience, then you get more pay than those slackers.

      I really hate it when people buy that bullshit line when managers trot it out.

      Also, giving you a 10-20% raise is NOTHING to the company. And honestly it's almost nothing to you when you look at your paycheck. Yet they act like you are asking hem to cut off their legs when you demand to be fairly compensated for your work.

      Understand that Paying you an additional $10,000 a year is absolutely nothing to a stable and healthy company. Now understand why no company deserves any loyalty from an employee.

      • by MobyDisk ( 75490 )

        I'm not sure how you came to your conclusions, but they certainly aren't universally true.

        If you regularly out perform your peers that have more experience, then you get more pay than those slackers.

        Some places don't give significant merit raises. Instead, they give bonuses or long-term-incentives that vest. That means that if you have been there for 5 years, and someone else has been there for 30 years, they might make more money than you do even if you perform better. This might depend on your location and vocation. What is the difference in profit between a top performer and a low performer? That is really

        • Re: (Score:3, Interesting)

          by Anonymous Coward

          LinkedIn has $5,312 revenue per employee. That's revenue, not profit. So giving a $10,000 raise to an employee means that employee puts the company in the negative.

          If they had a revenue of $5k per employee they'd be bankrupt. They've got a profit of about that. From http://investors.linkedin.com/financials-statements.cfm the revenue in 2013 was about $1.5 billion, profit about $27 million. From http://press.linkedin.com/about they have about 6,000 employes. So profit of about $4,500 per head, revenue about $250,000

    • by Agares ( 1890982 )
      I had a similar experience at my last job a few years back. When I left they called me the next day asking me if I would come back and they were very surprised I even quit. Of course I didn't go back since where I work pays more and is a pretty good place to work.
  • by Anonymous Coward on Friday November 07, 2014 @04:39AM (#48332439)

    Why can't you just talk to the people that work at a company? They might just tell you what you want to know.

    Here are some of the problems that affect corporations.
    -Indirect Communication
    -Gossip
    -Immaturity

    If employees happiness and company efficiency are really important than why do you need the cloud and some software?

  • by ciaran2014 ( 3815793 ) on Friday November 07, 2014 @06:19AM (#48332701) Homepage

    For PR reasons, the sellers of this system pretend it's about highlighting certain employees to get raises, but HR meetings are much more often about the problem of cutting costs than about the problem of how to give out more raises, so it's easy to see how this will really be used.

    When a company wants to cut its workforce, they will use this software to find which low- or medium-productivity employees are most likely to leave and then make some policy change they know will frustrate those employees so that some of them quit and the company doesn't have to pay any severance packages etc. This will generally lower employees' quality of life, but the company doesn't care because those employees were leaving anyway.

    • by Cederic ( 9623 )

      You say that like it's a bad thing. It is, but not for the reasons you think.

      When it comes to reducing headcount that's going to happen anyway, and you will lose good people whether you like it or not.

      The trick is to incentivise low performers to leave without damaging the work environment for retained staff, and without reducing your ability to attract 'talent'.

      That's actually very hard, without using financial incentives. Most large corporations I know of use financial incentives to encourage certain indi

    • by tomhath ( 637240 )
      That strategy will probably backfire. It's very difficult to frustrate low productivity workers enough to make them leave without also pissing off high performers. And the high performers are the ones who can most easily find another job. Think about what your workforce will be when that happens.
  • Why have public relationships? Public internet relationships are a fad of fake, self-destructive behavior, like the way women dressed in the 1950's.

    All of the LinkedIn requests I've ever received have been attempts to pretend that a relationship exists that is more meaningful than in reality.

    Sometimes a large percentage of people do crazy things. Don't follow them. I have friends, customers, and business contacts who sometimes read and reply to only the first paragraph of an email, and don't read the
  • but hey... it is easy to get brag posts of my erstwhile "friends" vacations - so why not.

  • >it then offers possible actions (more money, new job) Most companies would just preemptively fire the employee. Out of spite...? Something like that...
  • http://www.youtube.com/watch?v... [youtube.com]
    "This lively RSA Animate, adapted from Dan Pink's talk at the RSA, illustrates the hidden truths behind what really motivates us at home and in the workplace."

    Full lecture here: http://www.thersa.org/events/v... [thersa.org]

    Don't need a fancy algorithm to tell you that. Fix the cultural setting in a company and retention fixes itself...

    • by Shados ( 741919 )

      That will fix high turnover issues. But sooner or later, people will leave. They need change every now and then.

      But since an employee that has been around a while is potentially more productive by a factor (because they already have so much domain expertise, which is often several times more important than any technical ability), delaying that by an additional year or two can provide a LOT of value...

      ie: on the east coast, numbers I've seen show that the average software engineer will stay somewhere 2 years

      • As the video suggests, "incentives" don't really make much of a difference to motivation. However, you make some good points about value to a company of an experienced employee (whether motivated much or not), and it is true, if you want to hang onto mostly unmotivated employees a little longer, then incentives may help keep them from being unmotivated elsewhere. And it is true that a lot can get done by a lot of unmotivated employees -- just not stuff that is generally that creative or innovative. But that

  • I just recently took a new job after 10 years with the same company, and the only two reasons I did was because they were offering me 40% more money than I was making before, and the opportunity to spread out into a new field and away from what was getting stale.

    How's "Big Data" gonna find that one?

  • Comment removed based on user account deletion
  • by organgtool ( 966989 ) on Friday November 07, 2014 @10:33AM (#48333901)
    The real use of this software is so that companies can monitor the likelihood of a departure of their critical employees as they slowly cut benefits and stagnate wages across the board.
  • by Sir_Eptishous ( 873977 ) on Friday November 07, 2014 @10:53AM (#48334061)
    I'm always disappointed and not surprised by the points taken by debaters here on slashdot.
    It's the same f*CK1ng thing every time...Black and White - either/or - up or down.

    There is really no such thing as:
    "I'm going to volunteer EVERYTHING and firehose my datasets everywhere..."
    VS
    "I live in a cave in the Yukon with a picture of the unibomber on the wall"

    Give me a break people, WE ALL to varying degrees share things, whether with financial, government or online entities.
    We've been doing it for years, just like here on slashdot.

    I really get sick of the "Oh, you want privacy, what's wrong with you? Why aren't you posting to FB every ten minutes like "normal" people"
    VS
    "I change my route to work every other day, only pay for food with gold bullion and hack my neighbors wifi to connect to Tor" etc;

    We can pretty much assume that groups like the NSA, with their vast resources and ability to pretty much data mine whatever they want, have the goods on most Americans, and have the nefarious ability to blackmail anyone they want. Why else would they datamine? Their mandate about terrorism is really just a facade for the concentration of power through knowledge.

    With that being said, I sure as f*ck don't give out my info readily to Target, FB, Wal-Mart, or the vast array of businesses trying to datamine the f*ck out of every peon they sell a widget to.

    It's bad enough knowing the NSA is doing that already.
  • by nitehawk214 ( 222219 ) on Friday November 07, 2014 @10:57AM (#48334089)

    "Making an employee happy, improving the efficiency of a company these are hard problems that affect corporations"

    Bullshit. This will be used to preemptively fire employees, and deny them unemployment claims based on "they were going to quit anyhow."

    The worst part is that it is a fact of life for companies. Happy or not, people quit jobs. Sometimes its out of everyone's hands. Sometimes a person does not want to quit, but due to economics there is no upward mobility for the employee, forcing them to seek another job. Having proper succession plans and not alienating past employees is the key here. The companies gain nothing by being dicks here, but shitty managers will try to screw over outgoing employees, even when the company policy is to do nothing.

    My favorite is the promise of "lots lots more money" when I put in my notice. Hey, if you wanted me to stick around, you should have either paid me more before i was quitting, or at least treated me like a human being. Both would be better, but lets not be unrealistic.

    Alex Papadimoulis at The Daily WTF summed it up nicely in an article about having alumni [thedailywtf.com] instead of ex-employees. Perfectly succinct analysis from someone that has been in the industry. And the mentality change it would take will never happen in a company bigger than a few dozen people.

  • by PPH ( 736903 ) on Friday November 07, 2014 @11:12AM (#48334231)

    Create a few fake Facebook or LinkedIn profiles. Make yourself a few lucrative job offers and your present employer will pour cash on you.

    Back in the old days, I used to ask for the afternoon off every once in a while and then show up for work that day in a nice suit. Everybody figured it was for a job interview and I got another raise.

  • It knows when you are sleeping
    It knows when you're awake
    It knows when you've been bad or good,
    So be good for goodness sake...

    Therefore, Big Data is Santa Claus.
    I wouldn't have guessed; but the clues were there all along. He's a communist, which explains the red suit and giving away stuff that kids should be earning; but it still doesn't explain the flying reindeer. We're working on it though. We'll get back to you...

  • The most likely application of this software is not to maximize the retention of top performers. Rather they will seek to minimize the amount of benefits paid for a given level of quit risk for the employee population. In other words, how much can we squeeze them without them doing anything about it? Not that this is new, but now they'll be able to do it more efficiently! Ahh, progress, how much we love thee.
  • This is a company trying to sell their product.

    This needs to be independently evaluated. This big data shit is almost always some sort of logical optical illusion. Something that looks some way from the right angle but when actually examined is just smoke and mirrors.

    I trust this not at all until they get it evaluated.

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