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    Entries in labor (57)


    CHART OF THE DAY: Trends in Labor Force Participation

    It's been ages since I broke off a CHART OF THE DAY post and even longer since I talked about the Labor Force Participation Rate, so let's remedy both of these situations in one shot.

    Courtesy of your pals at the Federal Reserve Bank of Atlanta, have a look at a recently published chart on participation, this one broken down by gender. As always, some insightful comments from me after the data:

    Let's break down the data a little, and see if we might (Shock!) learn something. Some observations...

    1.  Male labor force participation has been on a long and steady decline for ages. In fact, males, as a group, have been less and less inclined to participate in the labor market since at least World War II.

    2. The female participation rate increased from about 43 percent in 1970 to a peak of 60 percent in the late 1990s, from which it has remained relatively flat over the last 15 - 20 years.

    3. But despite the economic recession of 2007 - 2008 ending, the data show that between 2010 and 2013, participation declined even more steeply for both men and women. Average female participation in 2014 was 57 percent—the lowest level since 1988—and male participation was down to a record low of 69 percent.

    What should we think about when considering this data? After all, participation is influenced by numerous factors like workforce age, prospects, disability rates, desire to continue schooling, etc.

    Let's look at what the Atlanta Fed thinks is the near-term direction for Labor Force Participation:

    "As a guide, the Bureau of Labor Statistics projects that the factors pulling down the labor force participation rate will outweigh those pushing it up, and that by 2022, labor force participation will be 61.6 percent, 1.4 points below its level at the end of 2014."

    The trends and the predicted continuation of these trends suggest a labor market that is even tighter than we are experiencing currently. It seems also likely that the kinds of jobs that will be hardest to fill are not the ones that will be easily filled by simply coaxing more people back into the labor force. 

    If anything, a declining participation rate makes even seemingly 'easy' to fill jobs that much harder to fill.

    Long story short, this data suggests that filling all kinds of jobs is just going to get tougher. It's probably a good time to be a recruiter though.

    A good recruiter I mean.


    CHART OF THE DAY: How large is the 'gig' economy?

    In my 'What HR should and should not be talking about in 2016' piece from early January I had the 'gig' economy listed as one topics that we collectively needed to stop talking and thinking so much about this year. By way of refresher (mostly for me), here is what I said in January about the 'gig' economy:

    "The 'Gig' Economy - Here's the thing about the rise in importance of the so-called 'Gig Economy', it is quite possible that its growth as a percentage of the labor force has been generally exaggerated possibly due to the oversized coverage that the largest Gig company, Uber, has received over the years. According to this Wall St. Journal piece from last July:

    Far from turning into a nation of gig workers, Americans are becoming slightly less likely to be self-employed, and less prone to hold multiple jobs. Official government data shows around 95% of those who report having jobs are accounted for on the formal payroll of U.S. employers, little changed from a decade ago.

    If Uber and its ilk were fundamentally undermining the relationship workers have with employers, that shift would be showing up in at least some of the key economic indicators. Hundreds of thousands of Americans, or even a few million, may have dabbled in the gig economy, but in the context of the 157 million-strong U.S. labor force, the trend remains marginal.

    It is possible that since there are likely more 'Gig' workers in coastal 'elite' cities like New York and San Francisco, and folks in these cities dominate the conversations in the media, that it just feels like the Gig economy is fast becoming the dominant form of work. But the data just doesn't reflect that, at least not yet. And it likely will not in 2016 or in 2018 or maybe even in 2020. So for now, it makes sense to think about your labor force composition, sure, (just like it always has), but massive, fundamental changes in that mix of labor is not typically top of mind for most organizations."

    So that was my take in January and two months later I have not really seen much if anything to make me think any differently about how important/influential the 'gig' economy really is to the vast majority of workers, organizations, and HR leaders. Today's CHART OF THE DAY courtesy of the JPMorgan Chase research folks seems to back that conclusion up.

    Taken from a three-year study of over 1 million JPMorgan Chase customers, the survey titled 'Paychecks, Paydays, and the Online Platform Economy' attempted (among other things) to get a better understanding over a three-year period just how important the 'gig' economy was/is in terms of worker participation levels and contribution to overall individual income. The entire report is interesting, but the chart I want to share is below, on the overall participation rates in 'gig' work. Here is the data, and the as you demand, some FREE comments from me:

    Apologies if some of the figures on the charts are a little tough to read, so I will just repeat the headline numbers - in Sept. 2015 the final month of the study, about 1% of individuals earned income from the 'gig' economy. In the second chart we see that in the 3-years of data up to Sept 2015, that about 4% of individuals had at any time earned income from the 'gig' economy.

    So 1% of JPM's surveyed customers were active on Uber, AirBnb, EBay ,and the like in Sept 2015 and 4% of people overall at some time earned some income from working (or selling things), on one of these platforms.

    While both figures represent significant growth in the reporting period, both were growing from incredibly small starting points. The truth is that the vast majority of people are not participating in these platforms and the ones that are, (another major section of the survey data), are using it as a supplement to more 'regular' forms of income, i.e. 'normal' jobs. Said differently, the chances are the only Uber drivers you have ever met are the ones that have driven you somewhere.

    To get back to my original point from January, while we read lots and lots about the 'gig' economy, its actual impact and influence on most worker's lives is not all that significant, at least not yet. If you are at all interested in this kind of data, I encourage you to check out the full JPMorgan Chase study here.


    CHART OF THE DAY: Is it a good time to find a quality job?

    Guess what? CHART OF THE DAY is back for another year of stats, data, and information about work, labor markets, demographics, basketball, and Tom Cruise movies. 

    For new blog readers, here is a quick reminder of how CHART OF THE DAY works. First, I find what I think is an interesting chart, graph, Venn diagram, or my favorite an exploding Pie chart that helps visualize some data set I find intriguing. I re-publish the chart here with a link back to the original source. Last, I toss out 2 or 3 thoughts on the data's significance or relevance for those of us in the HR, talent, technology, workplace spaces.

    Got it? Okay, here goes...

    For 2016's first submission courtesy of Business Insider and Gallup, a look at what American's think about the question "Is it a good time or a bad time to find a quality job?"

    Some quick thoughts about the data:

    1. Gallup has been asking this question in their surveys since 2001, and the latest data from 2015 that shows the percentage of Americans that feel it is a good time to find a quality job sits at 42%, which is just a shade under the series' all-time high of 43% from 2007. Said a little differently, since 2001, according to this survey American's attitudes about the job market conditions have NEVER been more optimistic.

    2. Gallup didn't specifically survey people 'actively' looking for work, so we can assume the increased confidence in the labor market is a reflection of the broader population's attitudes. That means just about everyone is feeling if not good, at least relatively better about labor market conditions. Which translates to the likelihood of increased turnover, even for those employees that you thought were 'safe', i.e., not likely to seek opportunities elsewhere. Will 2016 be the year that more people seek greener grass elsewhere? Maybe so.

    3. The recent HR technology trend towards developing 'predictive' models for providing insights into things like attrition and retention can provide tools that can possibly help HR leaders in this area. But the key question I would ask my HR technology provider of such predictive tools is the extent to which, if at all, these tools take into account these external trends in worker attitudes. Does the tool adapt to reflect the macro-trends and environmental conditions that exist and impact organizations? Or will your 'predictive' tool really act like more of a 'reactive' tool, failing to adapt quickly enough to changing market conditions? Good questions to ask. 

    Ok that's it, I'm out.

    Happy Tuesday! 


    Work and the next wave of industry transformation

    I like reading stuff from McKinsey and the other Tier 1 management consultancies out there like BCG, Bain, Booz Allen and the like. Sure, sometimes they are a little behind trend, try to place names (and the ensuing trademarked models and frameworks) on general business conditions or trends, and can be accused of being kind of a relic of the 80s and 90s, and out of touch with the modern age of technology and business.

    But they still do, reliably, churn out some snappy graphics that make for interesting blog fodder, so that is probably why I still love them. 

    Case in point, from our pals at McKinsey the below graphic that they call the 'Industry 4.0 Digital Compass', which "consists of eight basic value drivers and 26 practical Industry 4.0 levers. Cross-functional discussions that will help companies find the levers that are best suited to solve their particular problems." These are the big trends that are impacting manufacturing, (and really all kinds of industries), like digital technologies, the internet of things, the increased use of business intelligence tools, and advances in robotics and other forms of automation, and some ideas of how these trends will be applied in business.

    Take a look at the chart, paying particular attention to the slice called 'Labor', as that is the section I want to dig into next:

    Remember, in this diagram, the items in the inner circle, ('Labor', 'Time to Market', 'Quality', etc.), represent 'value drivers' for the firm, i.e., things that can be exploited to make more profit.  The items on the outer ring represent 'levers' that the savvy CEO or CHRO can pull to unlock that value. Let's take a look at McKinsey's four 'Labor' levers for a second and see what, if anything, they might mean for work, workplaces, labor, and HR.

    1. Human - Robot Collaboration - For hundreds of years many management and leadership ideas centered around trying to find ways to get people to work better with each other and to more effectively collaborate. These efforts, largely, have had mixed results. After all, the other guy is either a buffoon, or is not motivated, or doesn't have the right skill, or is an egomaniac - #amirite? So instead of trying to 'fix' annoying people so that they will be able to collaborate better, the next phase of technological transformation will focus on making us work better with the robots. This is a noble idea, and likely spells trouble for many of us. While we will remain buffoons, unmotivated, unskilled, and egomaniacal, our robot co-workers will suffer none of these conditions. 

    2. Remote monitoring and control - Let's take this one very literally and assume this means increased digital monitoring of workers and workplaces, probably through advances and increased adoption of wearable technologies. These will gain traction in many industrial settings as even today wearable technologies from companies like Wearable Intelligence have created incredibly powerful and productivity, (and safety) enhancing applications for manufacturing and field workers. In fact, the McKinsey piece references a trial of a Virtual Reality technology by the company Knapp AG that allows workers to find, identify, and take stock levels of items all via the wearable VR headset. These are extremely interesting and exciting applications of wearable technology in the workplace and likely will ultimately become the lasting means of impact and significance for a wide range of Google Glass type devices.

    3. Digital performance management - McKinsey (probably) isn't referring to the simple practice of taking very traditional HR-led performance management processes and documents and automated same. Rather, this is probably a trend, in combination with number two above, to leverage sophisticated tools and technologies to actually measure and improve performance. A great example of this is from the world of sports, specifically how the teams in the NBA have adopted a technology called SportVU Player Tracking, which users a battery of digital video cameras to create a massive data set of player movements, ball movements, and individual and team outcomes of every play in a basketball game. This massive data set, and the ability and technology to make sense of it all, has allowed coaches to better prepare team strategy, team leaders to evaluate player performance fairly and objectively, and players to learn how to become more effective on court. These approaches have relevance beyond sports into areas like agriculture, construction, and more.  It is about using data to make people better and organizations more successful and it is coming.

    4. Automation of knowledge work - Now we are getting to something probably a little more near and dear to the minds and hearts of folks who are in HR. The first few trends, since this entire construct has a manufacturing/industrial context, are mostly focused on how technology can improve the work performance of front-line, field, assembly, and distribution workers. While many of these kinds of jobs can be augmented with tech, it is also true that the current limitations of robotic technology in particular make many of them still immune from complete automation. Robots for the most part still are not able to take on tasks that require highly variable movements, fine motor skills, and navigating safely in close, uneven, or unpredictable environments. But knowledge work has none of those physical barriers to automation. If the job primarily involves moving bits of information from one digital format to another, then the algorithms are probably not much farther behind than we think. 

    Taken together, and as a part of the macro-level look at the future of industrial transformation, these labor and workforce trends seem to fit and make sense. Technology will change work in many different and subtle ways, but the undercurrent of all of them speaks towards a future with much closer integration between people and technology - often at a physical level. We will wear technology at work, be tracked in more ways than before, and have to interact with more forms of technology, like robots, than we might be comfortable with.

    And the best, most forward-thinking HR professionals are thinking about and leading their organizations in these directions today. 


    CHART OF THE DAY: More open jobs today than since... well, since ever

    Not much to say about this data as I think it is more or less is self-explanatory.

    Courtesy of our friends at the Bureau of Labor Statistics and powered by the St. Louis Fed's awesome 'Fred' data service, take a look at the last 15 years or so of data on Total Job Openings in the US.

    A quick glance at the data tells us what we need to know: Job opening as of the end of April 2015 were about 5.4 million, and are at the greatest level in the history of this data set, surpassing the previous high mark in January 2001.

    There's lots and lots of opportunity out there. And I will bet lots of said opportunities are not the ones that like to hassle their opportunity holders about unfiled time sheets, and sick leave accruals, and bereavement leave, and having to 'check in' when they are out on vacation. 

    The labor market continues to get tighter. People have more options. And the organizations that are slow to realize this will probably, eventually regret their ignorance or arrogance.

    Have a great weekend!