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    CHART OF THE DAY: What does it take for content to get noticed?

    Really interesting piece, (with accompanying chart that I will re-share below), on the GigaOM site on how social and online sharing is now truly the way readers (and potential customer and job candidates) discover content.

    The gist of the article was to point out that while they might like to think they are not in the same business as Buzzfeed, even more 'respected' publishers like the New York Times have to compete with the Buzzfeeds of the online world using modern metrics that describe success in online content creation - namely social shares (Twitter, LinkedIn, Facebook, etc.).

    Check out the chart below, (Email and RSS subscribers may need to click through), then some FREE commentary from me after the data:

    1. It is pretty obvious that for these big publishers, the bar for labeling a piece of content a 'social' success is really pretty high - at least 2K shares. Think about what you and your company might be sharing on social networks from your corporate blog or posting your open jobs on LinkedIn or Twitter. Two thousand shares of piece of content is a ton of shares, yet by the standards of the modern web, that barely starts to get you noticed. Less than 100 social shares leaves your content essentially 'unseen'.

    2. Unless, of course, it is 'seen' by the exact, right people. And that means most of us (me too, just look at the number of RTs of this post for example), have to really understand how to determine, classify, target, and attempt to engage a specific target market of interest in order to have success. There is almost no way any of us 'normals' are ever going to approach mass social virality like the masters of the modern web (Buzzfeed, HuffPo) can. If you post a job on Twitter and it is not RT'ed does it even exist?

    3. For the HR Tech spin on things, if you have employed a social sharing strategy for your jobs and employer brand building content, but you are not utilizing one of the several HR tech tools on the market that provide the capability to track, analyze, and help you determine actual results (clicks, shares, applicants, hires), for your jobs content, then you probably need to consider that investment in 2015. Since the easy and most common measure of success on the social web, absolute number of 'shares', is almost always going to leave you in the 'unnoticed' bucket, you need to find a way to 'prove' your social strategy is actually working. And the only way to do that is to better understand what happens to those lonely tweets after you send them out into the big, scary, social web.

    Happy Tuesday. Hope this post breaks out of the 'unnoticed' category.


    What Will Happen if we Move the Company: The Limits of Data

    Some years back in a prior career (and life) I was running HR technology for a mid-size organization that at the time had maybe 5,000 employees scattered across the country with the largest number located on site at the suburban HQ campus (where I was also located). The HQ was typical of thousands of similar corporate office parks - in an upscale area, close to plenty of shops and services, about one mile from the expressway, and nearby to many desirable towns in which most of the employees lived. In short, it was a perfectly fine place to work close to many perfectly fine places to live.

    But since in modern business things can never stay in place for very long, a new wrinkle was introduced to the organization and its people - the looming likelihood of a corporate relocation from the suburban, grassy office park to a new corporate HQ to be constructed downtown, in the center of the city. The proposed new HQ building would be about 15 miles from the existing HQ, consolidate several locations in the area into one, and come with some amount of state/local tax incentives making the investment seem attractive to company leaders. Additionally, the building would be owned vs. leased, allowing the company to purpose-design the facility according to our specific needs, which, (in theory), would increase overall efficiency and improve productivity. So a win-win all around, right?

    Well as could be expected once news of the potential corporate HQ relocation made the rounds across the employee population, complaints, criticism, and even open discussions of 'time to start looking for a different job' conversations began. Many employees were not at all happy about the possible increase in their commuting time, the need to drive into the 'scary' center city location each day, the lack of easy shopping and other service options nearby, and overall, the change that was being foisted upon them.

    So while we in HR knew (or at least we thought we knew), there would be some HR/talent repercussions if indeed the corporate HQ was relocated, we were kind of at a loss to quantify or predict what these repercussions would be. The best we were able to do, (beyond conversations with some managers about what their teams were saying), was to generate some data about the net change in commuting distance for employees, using a simple and open-source Google maps based tool.

    With that data we were able to show that (as expected), some employees would be adversely impacted in terms of commuting distance and some would actually benefit from the HQ move. But that was about as far as we got with our 'data'.

    What we didn't really dive into (and we could have even with our crude set of technology), was break down these impacts by organization, by function, by 'top' performer level, by 'who is going to be impossible to replace if they leave' criteria.

    What we couldn't do with this data was estimate just how much attrition was indeed likely to occur if the move was executed. We really needed to have an idea, (beyond casual conversations and rumor), who and from what areas we might find ourselves under real pressure due to possible resignations. 

    And finally, we had no real idea what remedial actions we might consider to try and stave off the voluntary and regrettable separations (the level of which we didn't really know).

    We basically looked at our extremely limited data set and said, 'That's interesting. What do we do with it?'

    Why re-tell this old story? Because someone recently asked me what was the difference between data, analytics, and 2015's hot topic, predictive analytics. And when I was trying to come up with a clever answer, (and I never really did), I thought of this story of the corporate relocation.

    We had lots of data - the locations of the current campus and the proposed new HQ. We also had the addresses of all the employees. We had all of their 'HR' data - titles, tenure, salary, department, performance rating, etc.

    We kind of took a stab at some analytics - which groups would be impacted the most, what that might mean for certain important areas, etc. But we didn't really produce much insight from the data.

    But we had nothing in terms of predictive analytics - we really had no idea what was actually going to happen with attrition and performance if the HQ was moved, and we definitely had no ideas or insights as to what to do about any of that. And really that was always going to be really hard to get at - how could we truly predict individual's decisions based on a set of data and an external influence that had never happened before in our company, and consequently any 'predictions' we made could not have been vetted at all against experience or history?

    So that's my story about data, analytics, and predictive analytics and is just one simple example from the field on why this stuff is going to be hard to implement, at least for a little while longer.


    CHART OF THE DAY: Is today a good day?

    Is today a good day? A bad day? Or just a typical, run-of-the-mill kind of day? 

    Maybe it is still too early to tell.

    But the answer someone is likely to give to the 'Is today a good day?' question could be highly dependent in which country you live. Take a look at today's CHART OF THE DAY, courtesy of the fine people over at Pew and taken from their Spring 2014 Global Attitudes survey, and of course some FREE commentary from me after the chart.

    It may seem odd or counter-intuitive, but many of those in the poorer countries surveyed were more likely than those in richer nations to say that the day, and this is just a randomly selected day, was a good one.

    When looking at this question by national income, there is a slightly negative correlation between respondents reporting that the day is a good one and their country's per capita GDP. The USA being the major outlier on this measure. The USA has the highest GDP per capita among the countries surveyed by Pew and these American respondents were more likely to rate a day as particularly good than people in other rich nations. But across the board in almost all the surveyed countries, the most common response to this question is that the day was just “typical.”

    Kind of interesting, even if it is hard to know what, if anything to make of it. On the one hand it is noteworthy that with the exception of the USA, the relative wealth (as expressed in per capita GDP), doesn't seem to predict general happiness, (or at least contentedness). But the fact that across the world most people's are just 'meh', seems more interesting.

    Think about your typical day. Today even. 

    Good, bad, or 'meh'. 

    How about yesterday? The day before?

    When was your last really, really good day?

    I hope it is today.

    Happy Wednesday.


    REPRISE: Whose Labor Market is it Anyway?

    Note: The blog is taking some well-deserved rest for the Holidays (that is code for I am pretty much out of decent ideas, and I doubt most folks are spending their holidays reading blogs anyway), and will be re-running some of best, or at least most interesting posts from 2014. Maybe you missed these the first time around or maybe you didn't really miss them, but either way they are presented for your consideration. Thanks to everyone who stopped by in 2014!

    The below post first ran back in July as a part of the CHART OF THE DAY series and was a great example (in convenient chart form) on a subject I hit quite a few times in 2014 - the tightening labor market and its impacts and talent and work. Long story short: In 2014 the candidates strengthened their control of the market and HR/Talent pros can't ignore that fact any longer.

    Happy 2015.


    Whose Labor Market is it Anyway?

    There is a simple answer to that question, really. 

    The candidates run the current labor market, at least for large, (and growing) swath of managerial, professional, and technical roles. 

    Check out this week's Chart of the Day, a look at how recruiters see the labor market - candidate driven or employer driven,  courtesy of the MRI Network's latest recruiter sentiment study, (as always, some pithy commentary from me after the chart)

    Wow - pretty simple and clear to see how at least this group of surveyed MRI Network recruiters have seen the labor market shift pretty dramatically in just two and a half years.

    From late 2011, when the sentiment was that that the power and leverage in recruiting was about an even split between candidate and employer, to one where now these recruiters see about a 4x advantage for the candidates, this shift will have some pretty profound implications for many HR/talent pros.

    Quite simply, offers to candidates with desirable, in-demand skill sets are going to have to get sweeter, and they are going to have to happen faster. Digging in to the MRI data you see that the primary reason candidates can't be closed is that they have accepted a different job offer. Sure, there are plenty of factors at play here, but the lesson is that just like in the market for desirable real estate in New York or San Francisco, the market for top candidates is likely to be super-competitive, with candidates holding signifcant leverage and multiple offers.

    One more nugget from the data - candidates accepting counter-offers to remain with their current employer are rising. Whether or not it makes sense to even make counter-offers is definitely subject to debate, but the fact that if you don't at least consider the practice for your in-demand talent, you are likely going to find yourself having to replace at least some of that talent sooner than you might have liked. 

    Looking back over this data, and the last few Charts of the Day I have posted and it continues to become more clear - job openings are up, employees are more willing to jump for a better opportunity, the competition for candidates is getting more fierce, and the strategy and tactics you were using as recently as 2011 probably are not going to work in labor markets where the best candidates have all the power.

    Have fun and be careful out there.


    REPRISE: The Analytics Takeover Won't Always Be Pretty

    Note: The blog is taking some well-deserved rest for the next few days (that is code for I am pretty much out of decent ideas, and I doubt most folks are spending their holidays reading blogs anyway), and will be re-running some of best, or at least most interesting posts from 2014. Maybe you missed these the first time around or maybe you didn't really miss them, but either way they are presented for your consideration. Thanks to everyone who stopped by in 2014!

    The below post first ran back in March and is a good example of a combination of themes that I love writing about on the blog: NBA basketball and talent management. In this piece I took a look at the trend developing in the modern NBA, where business and tech savvy (and new) team owners are valuing data and analytics skills and experience more than decades of actual basketball experience when making executive hires. As you would expect this change in hiring philosophy will have pretty significant implications for talent, and might just be indicative of bigger talent management challenges. 

    Happy Sunday!


    The Analytics Takeover Won't Always Be Pretty

    Seems like it has been some time since I dropped a solid 8 Man Rotation contribution here on the blog, so to remedy that, please first take a look at this recent piece on ESPN.com, 'Fears that stats trump hoops acumen', a look at the tensions that are building inside NBA front offices and among team executives.

    In case you didn't click over and read the piece, the gist is this: With the increased importance and weight that a new generation of NBA team owners are placing on data-driven decision making and analytical skills, that the traditional people that have been the talent pool for NBA team management and executive roles, (former NBA players), are under threat from a new kind of candidate - ones that have deep math, statistics, and data backgrounds and, importantly, not careers as actual basketball players.

    Check this excerpt from the ESPN piece to get a feel for how this change in talent management and sourcing strategies is being interpreted by long time (and anonymously quoted) NBA executives:

    Basketball guys who participated in the game through years of rigorous training and practice, decades of observation work through film and field participation work feel under-utilized and under-appreciated and are quite insulted because their PhDs in basketball have been downgraded," the former executive, who chose to remain anonymous, told ESPN NBA Insider Chris Broussard.

    One longtime executive, who also chose to remain anonymous, postulated that one reason why so many jobs are going to people with greater analytical backgrounds is because newer and younger owners may better identify with them.

    "Generally speaking, neither the [newer generation of] owners nor the analytic guys have basketball in their background," the longtime executive told Broussard. "This fact makes it easy for both parties to dismiss the importance of having experience in and knowledge of the game.

    The piece goes on to say that since many newer NBA owners have business and financial industry backgrounds, (and didn't inherit their teams as part of the 'family business'), that they would naturally look for their team executives to share the kinds of educational and work experience profiles of the business executives with which they are accustomed to working with, and have been successful with.

    The former players, typically, do not have these kinds of skills, they have spent just about all their adult lives (and most of their childhoods), actually playing basketball. A set of experiences, it is turning out, no longer seems to provide the best training or preparation for running or managing a basketball team. 

    But the more interesting point from all this, and the one that might have resonance beyond basketball, is the idea that the change in hiring philosophy is coming right from the top - from a new generation of team owners that have a different set of criteria upon which they are assessing and evaluating talent.

    Left to tradition, hiring and promotion decisions would have probably only slowly begun to modernize. But a new generation of owners/leaders in the NBA are changing the talent profile for the next generation of leaders.

    The same thing is likely to play out in your organization. Eventually, if it has not happened yet, you are going to go to a meeting with your new CHRO who didn't rise through the HR ranks and maybe is coming into the role from finance, operations, or manufacturing. In that meeting your 19 years of experience in employee relations might be a great asset to brag on. Or it might not be.

    And you might find out only when you are introduced to your new boss, who has spent her last 5 years crunching numbers and developing stats models.