Enter your email address:

Delivered by FeedBurner


E-mail Steve
This form does not yet contain any fields.
    Listen to internet radio with Steve Boese on Blog Talk Radio

    free counters

    Twitter Feed

    CHART OF THE DAY: There's Just 5 Million Open Jobs in the USA

    Here's your latest Chart of the Day, courtesy of my two favorite online data sources, the Bureau of Labor Statistics, (specifically the Job Openings and Labor Turnover Summary, or JOLTS report), and the FRED data analysis and visualization tool.

    First, the chart, then some FREE commentary from your humble scribe:

    1. First, the actual numbers - there were 5.028 million job openings in the US on the last business day of December 2014, the highest number since December 2001.

    2. The chart shows a pretty much straight up and to the right climb in job openings since early 2009, meaning talk of the recession and the labor market disruptions it caused are really seeming far, far behind us

    3. This increase in openings is driving organizations like Walmart to raise wages for many of its workers - for a wide range of industries, and geographies, (including previously 'low worker power' ones like retail), the balance of that power is shifting. 

    4. Average weekly earnings for Production and Non-farm employees are climbing as well, not as fast as jop openings, but certainly on the same trajectory.

    So what does this mean for you, Mr. or Ms. HR pro?

    Probably nothing new, or at least nothing you have not been hearing about and likely experiencing in the last 18 months or so. 

    Lots more noise in the system to get your company and your opportunities noticed in a much more crowded market of available jobs.

    Many fewer un- and under-employed individuals around that might not always been qualified for your openings, but at least were a source of steady candidate flow. At the depths of the recession, there were about 7 unemployed workers for every job opening. Today that ratio is less than 2/1.

    You, having a harder time coming up with explanations/excuses to your leadership and hiring managers who (traditionally) are much slower to accept these changes in the labor market and the ensuing power shifts. I recommend forwarding to them the Walmart story above, with a subject line that says 'See, even Walmart is having a hard time finding and keeping people'.

    Long story short, we entering year 6 of an extended recovery/tightening of the labor market. Talent is in shorter supply, opportunities are everywhere, the Dow and the S&P 500 are at record highs, and the people you need to find, attract, and retain are well, harder to find, attract, and retain.

    Have fun, it's a jungle out there.


    On trusting algorithms, even when they make mistakes

    Some really interesting research from the University of Pennsylvania on our (people's) tendency to lose faith and trust in data forecasting algorithms (or more generally, advanced forms of smart automation), more quickly than we lose faith in other human's capabilities (and our own capabilities), after observing even small errors from the algorithm, and even when seeing evidence that relative to human forecasters, the algorithms are still superior.

    From the abstract of Algorithm Aversion: People Erroneously Avoid Algorithms After Seeting Them Err:

    Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet, when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.

    Let's unpack that some. In the research conducted at Penn, the authors showed that even when given evidence of a statistical algorithm's overall superior performance at predicting a specific outcome (in the paper it was the likelihood of success of MBA program applicants that the humans and the algorithm attempted to predict), most people lost faith and trust in the algorithm, and reverted to their prior, inferior predictive abilities. And in the study, the participants were incentivized to pick the 'best' method of prediction: They were rewarded with a monetary bonus for making the right choice. 

    But still, and consistently, the human participants more quickly lost and faith and trust in the algorithm, even when logic suggested they should have selected it over their (and other people's) predictive abilities.

    Why is this a problem, this algorithm aversion?

    Because while algorithms are proving to be superior at prediction across a wide range of use cases and domains, people can be slow to adopt them. Essentially, whenever prediction errors are likely—as they are in virtually all forecasting tasks—people will be biased against algorithms, because people are more likely to abandon an algorithm than a human judge for making the same mistake.

    What might this mean for you in HR/Talent?

    As more HR and related processes, functions, and decisions become 'data-driven', it is likely that sometimes, the algorithms we adopt to help make decisions will make mistakes. 

    That 'pre-hire' assessment tool will tell you to hire someone who doesn't actually end up beign a good employee.

    The 'flight risk' formula will fail to flag an important executive as a risk before they suddenly quit, and head to a competitor.

    The statistical model will tell you to raise wages for a subset of workers but after you do, you won't see a corresponding rise in output.

    That kind of thing. And once these 'errors' become known, you and your leaders will likely want to stop trusting the data and the algorithms.

    What the Penn researchers are saying is that we have much less tolerance for the algorithm's mistakes than we do for our own mistakes. And maintaining that attitude in a world where the algorithms are only getting better, is, well, a mistake in itself.

    The study is here, and it is pretty interesting, I recommend it if you are interested in making your organization more data-driven.

    Happy Tuesday.


    US Time Zones, Ranked

    A long, long day of scheduling, re-scheduling, and conducting meetings with people all across the USA was the inspiration for the below, your definitive ranking of United States Time Zones:

    6. Mountain Time - Not needed, really. How many people do you know who reside in Mountain Time?Click for giant version

    5. Alaska Time - Reality TV would be a vast wasteland if not for Alaska. Plus, you can see Russia from there.

    4. Central Time - Sort of a middle-of-the-road, not making waves kind of time. Plain.

    3. Pacific Time - Has the annoying habit of showing Knicks home games at 4PM.

    2. Hawaiian-Aleutian Time - I have never actually used this time zone, but since it has Hawaii, it must be fantastic.

    1. Eastern Time - The only US time zone that really counts. Yes, I live in Eastern time, what of it?

    Have a great night, (or day if you are on Hawaiian-Aleutian Time).


    WEBINAR: Six Ways to Make Your Recruiting/Talent Metrics More Strategic

    Your friends and mine over at Fistful of Talent are back with the 2015 debut of the often-imitated but never surpassed FOT Webinar - this one titled Six Ways to Make Your Recruiting/Talent Metrics More Strategic – And Make Managers Own Their New Hires - sponsored by Chequed.com, set for Thursday, February 26th at 2pm EST.

    Why should you take time out of a busy Thursday to hang out with the FOT crew for an hour?

    Let's face it---the recruiting metrics you use at your company are either non-existent or stale.  Sure, you tried to roll out the basics---time to hire, cost per hire---but all that did was put the focus on your HR/Recruiting function, not the people who actually make the final hiring decision.  Flash forward 12 months since the launch of those basic recruiting metrics, and you're bored... heck, everyone's bored.

    Not to fear! The FREE FOT webinar, Six Ways to Make Your Recruiting/Talent Metrics More Strategic – And Make Managers Own Their New Hires, was made to help (and to make you look like a superstar).

    What will the FOT gang cover?

    1. A review of the traditional talent selection/recruiting metrics.  We'll give you a rundown of those metrics like Time To Fill and Cost Per Hire, what the standard benchmarks are for each and then explain why only using these traditional metrics is a lost cause/suckers play.

    2. An explanation of the Holy Grail of reporting Recruiting Effectiveness and why it changes the conversation from "Did we fill the position?" to "Did we make the right hire and what happened once we filled the position?". We call this metric Hiring Manager Batting Average (HMBA for those of you that need an acronym), and it's the cleanest, most all-encompassing metric you can have to make your internal recruiting conversation strategic---not transactional---and actually make it tie in to your overall talent strategy, not just Talent Acquisition.

    3. How to change the dialog of organizational turnover from being an HR problem to being everyone's problem. Admit it, you report on turnover all the time. We'll show you how to link turnover to your selection process in a way that spreads the wealth related to turnover responsibility---and actually sets you up to be more consultative and less reactive related to employee churn.

    4. We'll give you 5 additional metrics to show how your recruiting/staffing process actually reduces risk of bad hires and prepares for future searches.  You need to get out of the trap of only reporting cost and time.  We've got the metrics to show you how to do that.

    Convinced yet?

    Things that are hard:  Riding a bike on a freeway. Getting your kids to eat peas. Getting managers to own the bad hires they make and be interested in getting better at selection.  Join for Six Ways to Make Your Recruiting/Talent Metrics More Strategic – And Make Managers Own Their New Hires on Thursday, February 26th at 2pm EST, and we'll show you how to create recruiting/talent metrics that get the attention of your organization.  You're on your own with the other two.



    PODCAST - #HRHappyHour 203 - The HR Happy Hour Oscars Preview

    HR Happy Hour 203 - The HR Happy Hour Oscars Preview

    Recorded Thursday February 19, 2015

    Hosts: Trish McFarlane, Steve Boese

    Listen to the show HERE

    I know what you are thinking - what in the hell are Steve and Trish thinking doing an Oscars preview show?

    I must admit, for a second I thought the same thing myself, but once we sort of 'found' the topic on the show, (the Oscars stuff starts in after about five minutes or so after Steve had to talk NBA trades for a few moments), we had a fantastic time talking movies, actors, and of course making some Oscars predictions.

    You can listen to the show here, or using the widget player below, (Email and RSS subscribers will need to click through, or go to the show direct link).

    Check Out Business Podcasts at Blog Talk Radio with Steve Boese Trish McFarlane on BlogTalkRadio


    Since Steve (admittedly), actually saw an amazingly low number of Oscar nominated movies and performances, we ended up having to get a little more creative in devising new ways to evaluate the contenders. Without giving away too much, let's just say the movie Mr. Mom plays a big role in the assessments, as well as which actor did a better job playing The Incredible Hulk. Luckily, Trish was much more prepared to talk movies and actors or else this could have been a disaster.

    This was a really fun show, I hope the HR Happy Hour fans that are also movie fans or just plan to watch the Oscars on Sunday night will enjoy the show. Once the show goes live, we will post it to the HR Happy Hour page on Facebook, (yes, we have one of those, I always forget to mention it), where we hope you will leave your Oscar predictions as well.

    As always, you can listen to the current and all the past shows from the archive on the show page here, on our HR Happy Hour website, and by subscribing to the show in podcast form on iTunes, or for Android devices using Stitcher Radio (or your favorite podcast app). Just search the iTunes store or your podcast app for 'HR Happy Hour' to add the show to your subscriptions.

    Enjoy the weekend, enjoy the Oscars, and if you are in the Easter half of the USA, please stay warm!