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    Entries in Technology (247)


    Hating a workplace tech product is pretty common. But do you hate it enough to switch?

    This week I'm out at Cornerstone Convergence, which is talent management techology provider Cornerstone OnDemand's annual customer event. Cornerstone puts on one of the HR Tech industry's best (and most fun) events each year and it is one event I am sure to make time for each year. Aside, ask me about last year's Poison concert at Convergence - it was amazingly fun. 

    One of the data points that always comes up at these kind of events is customer retention rate, i.e., the percentage of customers that upon initial contract expiration, (typically after three years), decide to actually renew their contracts with the technology solution provider. At the Cornerstone event they mentioned a pretty high retention/renewal rate, somewhere north of 90%, (I can't remember the actual number and it doesn't really matter for the purposes of this post anyway).

    And Cornerstone is not the only HR Tech solution provider that is able to boast such lofty customer retention rates, I would guess that every single time I have heard a vendor, any vendor, talk about customer retention rates their numbers are similar - they claim their existing customer renew at a rate of 90% or better.  And since I have neither a reason to doubt any of the individual reports of extremely high customer retention rates, nor the existence of some kind of industry-wide handshake agreement where every vendor reports 90% and higher retention rates, let's assume that in fact this is the case, and that most customers do in fact, renew their software contracts at these levels.

    So what does that mean, or stated differently, why is a 90%+ retention rate important for the HR/Talent leader? I can think of three reasons, (although three will be easier to remember, so let's stick with that number for now).

    1. If you're actually in the market, (or soon will be), for a new ATS, LMS, HRIS, or any other kind of software that ends in an 'S', you'd better choose wisely, since these extremely high retention rates tell us that most likely you will be in a relationship with this new technology for quite some time. Take a little bit longer in your up front process, engage more folks in the technology evaluations, heck, maybe even earmark some more budget for bringing in some outside experts to help you navigate the selection process. Even in the modern age of SaaS technology, most enterprise software decisions tend to stay with us for a long, long time.

    2. We consistently underestimate people's aversion to change, even when presented with better alternatives. It has been estimated that in some applicaitions that a replacement technology has to be demonstrated as providing 9 times more value and utility than the existing solution in order for most folks to be willing to make a change. We don't like changing things as mundane as toothpaste brands or where we order coffee in the morning, and most of your workforce probably doesn't want you to change their workplace tools all that often, even if the 'new' ones are better. It's just too much hassle for the average, busy worker and manager to learn some new learning or recruiting or compensation tool. Said differently, they may not really like the tools they have now, but at least they know how to use them. 

    3. The ability to consistently deliver on promised future product development promises probably needs to be ranked higher on any HR technology software selection criteria your organization uses when evaluating competing technologies. This is the classic 'It's on the roadmap' stuff that you will hear often in the sales cycle or even after you become a customer. One of the most important challenges for providers is to balance the need for new product and feature development with their simultaneous need to support customers, fix bugs, and stabilize existing applications. How the provider can live up to promised future capabilities, particularly ones that are critical for your organization, becomes more and more important the longer the customer/provider relationship lasts.

    So take all that for what you think it's worth, I predict either if you agree or disagree, 90% or you (or more), will be back tomorrow for the next installment of this nonsense....


    A different view of 'Top' talent, namely that it is mostly a myth

    Caught this piece, The programming talent myth', over the weekend and if you are in the technology space at all (as a techie yourself, someone who has to attract and recruit tech talent, or simply just someone who is concerned/interested with the 'state' of technology today (particularly when it comes to issues of diversity and inclusion)), then you should carve out 15 or so minutes today or soon and give the piece a read.

    It is essentially a summary of a recent keynote speech at a developer's event called PyCon given by Jacob Kaplan-Moss, a well-known contributor to the programming language Django and the director of security at Heroku.

    In the speech Kaplan-Ross took square aim at the concept of 'Top' technical talent, (although I would argue his logic would apply to other disciplines as well), and how the dangerous myth of the 'Rock Star' programmer and the terrible programmer (with nothing really in between these extremes), is detrimental on all kinds of levels. It drives people out of technical careers and studies - if you are not a 'Rock Star' you might as well not even bother. It continues to foster and support less-than-healthy norms and lifestyles - 'Rock Star' programmers work 80+ hours a week and don't think of anything other than programming. And finally, it feeds in to what can easily develop into that 'Bro culture' that is common in many smaller startups and tech companies.

    Here is a little piece from the talk:

    Programmers like to think they work in a field that is logical and analytical, but the truth is that there is no way to even talk about programming ability in a systematic way. When humans don't have any data, they make up stories, but those stories are simplistic and stereotyped. So, we say that people "suck at programming" or that they "rock at programming", without leaving any room for those in between. Everyone is either an amazing programmer or "a worthless use of a seat".

    But that would mean that programming skill is somehow distributed on a U-shaped curve. Most people are at one end or the other, which doesn't make much sense. Presumably, people learn throughout their careers, so how would they go from absolutely terrible to wonderful without traversing the middle ground? Since there are only two narratives possible, that is why most people would place him in the "amazing programmer" bucket. He is associated with Django, which makes the crappy programmer label unlikely, so people naturally choose the other.

    But, if you could measure programming ability somehow, its curve would look like the normal distribution. Most people are average at most things.

    It makes sense if you think of programming as not some mystical endeavor that somehow one is innately born with the talent for or is not. If you see programming and other technical occupations as just ones consisting of a set of skills and capabilities that can be learned over time, (like just about every other skill), then the idea of programming talent and programmers existing on a more normal distribution curve seems the most likely outcome.

    One last quote from the piece:

    The tech industry is rife with sexism, racism, homophobia, and discrimination. It is a multi-faceted problem, and there isn't a single cause, but the talent myth is part of the problem. In our industry, we recast the talent myth as "the myth of the brilliant asshole", he said. This is the "10x programmer" who is so good at his job that people have to work with him even though his behavior is toxic. In reality, given the normal distribution, it's likely that these people aren't actually exceptional, but even if you grant that they are, how many developers does a 10x programmer have to drive away before it is a wash?

    How much does the 'Rock Star' mentality and assumption play in to toxic workplaces, less inclusive workforces, and unfulfilled 'Good, but not a Rock Star' people?

    It is a really interesting piece, and Kaplan-Ross' speech is also on YouTube here, and I recommend checking it out.


    HRE Column: On the HR and Marketing Connection

    Here is my semi-frequent reminder and pointer for blog readers that I also write a monthly column at Human Resource Executive Online called Inside HR Tech that can be found here.

    I kind of liked this month's column, (I suppose I like all of them, after all I wrote them), but felt like sharing this one on the blog because it touches upon what has been in the past a pretty popular topic with readers here - the connections and synergies between HR and Marketing.

    Here is a piece from the HRE Column, HR and the Marketing Mind-set:

    There are four important stages that marketers should traverse when building relationships with customers and potential customers. I think these stages can also be highly relevant and applicable to HR leaders, and they can also be supported by HR technologies and thought of as one way to help guide and organize your thinking if your goal is to “think more like a marketer.” Here are the four stages and some ideas of how they might fit into an HR leader’s program:

    1. Collect and Analyze Data

    While marketing has embraced data, data analysis and using data to make investment decisions for quite some time, it is only more recently that HR leaders and organizations have joined their marketing colleagues in this mind-set. But, since HR has embraced data at least conceptually, it is probably time to think about data more strategically—much like marketers do.

    A big part of the Oracle marketing presentation was not just about how collecting data itself is the goal, but about what the data empowers you to do once it’s been collected. More specifically, the marketing technologies that enable increased understanding of customers and prospects for the purposes of targeted communication and messaging suggests HR leaders consider similar segmentation and targeting with their own outreach efforts.

    Unique and more specific messaging that “fits” your audience more specifically is much more likely to get noticed, read and acted upon. Think about how your next “All Employees” email blast can be segmented and made more individually meaningful for the people in your organization, based on some defining criteria or past behavior that makes sense....

    Read the rest over at HRE Online.

    Good stuff, right? Humor me...

    If you liked the piece you can sign up over at HRE to get the Inside HR Tech Column emailed to you each month. There is no cost to subscribe, in fact, I may even come over and wash your car or cut the grass for you if you do sign up for the monthly email.

    Have a great weekend and Happy Mother's Day to all the Moms out there!


    Revealing Complexity

    Probably the most significant barrier to user adoption of new workplace technology is that users don't see the personal benefit of adopting these technologies. This is the classic 'What's in it for me?' conundrum. While that subject is important and worthy of exploration, I won't be hitting that specific problem today. Instead, let's talk about what is likely the second-most important barrier to employee adoption of workplace technology, namely, that most enterprise technologies have provided (relatively) poor user experience and/or are just too complex for them to use intuitively.

    While enterprise technology companies have talked about, and some have actually delivered, better, more compelling, more consumer-like technology user experiences, even the most modern, best-designed applications eventually run into a common problem in that enterprise tools often require LOTS of data be input into them.

    It could be a new sales prospect being recorded in a CRM, a new supplier that needs to be set up in Procurement, or even a relatively simple matter of entering a new hire in the HRIS, all of these use cases while impacting disparate systems and organizational departments, have much more in common than we usually think. Each of these transactions requires (usually), a whole bunch of data fields to be populated with a whole bunch of data. And even in 2015, for many organizations the bulk of these myriad data elements have to be manually typed into the respective system form fields the old fashioned way - manually.

    And so since the makers of CRM and Supply Chain and HR technologies understand this reality, and like to be able to sell to customers the things they need to run their business operations, even the most modern, slick, mobile responsive, and really amazing looking enterprise solutions often and still have these kind of busy, kind of ugly, kind of tired looking data input forms in order to support these kinds of transactions. And while we might be tempted to look at these kinds of forms, (and the processes that make these 37 field data input forms necessary), as relics from an older, less awesome age, they still have a place in most organizations and in most modern technology solutions.

    Not every interaction with an enterprise technology can (or should) be reduced to a graphic or chart on a tablet, or a glanceable notification on your new Apple Watch. Sometimes, the hard and necessary work of getting relevant data (and lots of it) about customers, vendors, and employees into the enterprise tools that organizations rely upon is, still, kind of boring, kind of repetitive, and even kind of monotonous.

    But that is entirely ok, and should not be considered some kind of an indictment of the technology solution provider that has not figured out a way to make inputting 32 fields about a customer into some kind of a gorgeous 'swipe left' and 'swipe right' kind of user experience.  

    User Experience and what is good User Experience is highly variable and highly personal. And what usually constitutes great User Experience for the sales exec who wants to look at the Q3 funnel on her tablet is much, much different than what makes up great UX for a payroll entry clerk. We can't confuse them with each other.

    The best designed enterprise systems, of course, support both UX's and both kinds of users. The key is, I think, to have the system only reveal its fundamental complexity, and the form with 37 input fields, only to those people who really need them, and care about them, and help them see the 'What's in it for me?' as well as treating them and their role with respect.


    VIDEO: The project is called 'Replacing humans with robots'

    Directing you to a super-interesting short (about 5 minutes or so) video produced by the New York Times as the first installment of a series they call 'Robotica'. In the video, we see more about the growth, challenges, and worker impact of the surge in adoption of industrial robots in Chinese manufacturing. Take a few minutes to watch the piece, (embedded below, Email and RSS subscribers will have to click through), and then some comments from me after the clip.

    Really interesting stuff I think, and for me, very instructive as in 5 minutes it hits many of the big picture issues associated with the increasing automation of work and the impacts this will have on human workers.

    1. At least in this Chinese province, the goals of this program are extremely clear - 'Replacing human workers with robots.' While the motivations for this stated goal might be specific to this region, I think it would be foolish to think that this phenomenon and executive attitude isn't much more common, and not just in China. CEOs everywhere are going to be intrigued and in pursuit of what increased automation promises - lower costs, increased consistency and quality, and a predictable labor supply.

    2. The video does a nice job of showing the likely mixed or divergent impact of increased automation on the front-line workers that are usually most effected. While one (hand-picked by the factory leaders) employee waxes happily about how the robots are making his job easier and happier, another talks frankly about his (and other's) inability to easily transition from manual, repetitive work that is replaced by robot workers, to higher value added or creative and 'human' work. Whether in China or in Indianapolis, no low skilled worker can suddenly become a high-skilled or creative worker overnight. 

    3. The video alludes to the potential, one day, for robots to actually manufacture the robots themselves, even if that is not yet happening today. This notion, that automated technologies will largely build more of themselves is one of the key differences from modern, robotic-type automation than in previous technological breakthroughs. Henry Ford's Model A didn't drive itself, (or build itself). Telephones didn't make calls for you. Personal computers needed LOTS of people entering data into them in order to get anything useful back out from them. But robots building more robots to replace more people? That sounds a little scary.

    I will sign off here, take a look at the video if you can spare a few minutes today and let me know what you think in the comments below. Or have your robot assistant watch it for you.

    Have a great week!