New York City Bans Pre-Employment Testing for Marijuana

New York City Bans Pre-Employment Testing for Marijuana

In April, the New York City Council passed a bill that would prohibit employers from requiring candidates to undergo testing for marijuana as a condition of employment, becoming one of the first jurisdictions to grant employment-specific protections to marijuana users. Mayor Bill de Blasio, who expressed support for the bill, did not sign or veto it within 30 days of its passage, so it became law on May 10 and will come into effect a year from that date, according to Seyfarth Shaw’s marijuana law blog.

The new law includes exemptions for certain safety-sensitive occupations, including law enforcement, construction, medical and child care, and jobs requiring a commercial driver’s license. It also does not apply to federal and state employees or contractors, nor does it override federal regulations governing transportation workers such as truck drivers and pilots. Employees can still be subjected to marijuana testing if they appear intoxicated at work.

New York State legalized marijuana for medicinal use in 2014; recreational use of the drug remains illegal, but the state legislature is considering a legalization bill, which governor Andrew Cuomo has said he intends to pass and sign in this legislative session. In New York City, De Blasio supports legalization, while the NYPD announced last year that it would stop arresting most people caught smoking marijuana in public. Given that this pledge was central to Cuomo’s re-election campaign platform in 2018, it is likely that New York will soon join the growing number of US jurisdictions where recreational marijuana is legal, including Alaska, California, Colorado, Maine, Massachusetts, Michigan, Nevada, Oregon, Vermont, and Washington state, as well as Washington, DC.

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April Jobs Report Shows Lowest US Unemployment in 50 Years

April Jobs Report Shows Lowest US Unemployment in 50 Years

The latest jobs numbers from the US Department of Labor, released on Friday, show that the US economy continues to create jobs at a robust pace despite historically low levels of unemployment. According to the April report from the Bureau of Labor Statistics, 263,000 jobs were created last month, overshooting analysts’ predictions in the range of 185,000-190,000. The unemployment rate fell to 3.6 percent, a level not seen in the US since December 1969.

Wages also rose, albeit more modestly than economists would expect to see in such a tight labor market: Average hourly earnings were up 0.2 percent month-to-month for a 3.2 percent increase over the last 12 months. While this was nearly the best year-over-year growth figure since the end of the Great Recession in 2009, it doesn’t make up for years of stagnation, while inflation wiped out a significant portion of those gains, Vox highlighted in its coverage of the jobs report:

The latest pay data suggests that workers and labor unions will continue to strike to force businesses to boost wages. Slow income growth has been the weakest part of the US economy in its recovery from the Great Recession. Wages have barely kept up with the cost of living, even as the unemployment rate dropped and the economy expanded. April’s 6-cent average hourly wage hike suggests more of the same, despite a surprising 10-cent jump in February.

Over the past year, the cost of food and housing has gone up, so paychecks have had to stretch further. But because of recent falling gas prices, the annual inflation rate has fallen to 1.9 percent, compared to a high of 2.4 percent in 2018 (based on the Consumer Price Index). So when you take inflation into account, workers’ real wages only grew about 1.3 percent within the past year.

There are also reasons to hesitate before celebrating the decline in the unemployment rate, the New York Times pointed out, noting that “the factors behind it aren’t as hopeful as the headline number itself”:

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We’re Already Living in the Future of Talent Analytics

We’re Already Living in the Future of Talent Analytics

Recently at the Harvard Business Review, management professor Thomas H. Davenport asserted that HR “is right up there with the most analytical functions in business—and even a bit ahead of a quantitatively-oriented function like finance.” Davenport backs this claim with findings from a global survey of senior managers, directors, and VPs at large companies by Oracle, on which he collaborated. The survey found that many HR leaders are well-versed in using data and predictive analytics to make talent management decisions:

  • 51% of HR respondents said that they could perform predictive or prescriptive analytics, whereas only 37% of Finance respondents could undertake these more advanced forms of analytics.
  • 89% agreed or agreed strongly that “My HR function is highly skilled at using data to determine future workforce plans currently (e.g. talent needed),” and only 1% disagreed.
  • 94% agreed that “We are able to predict the likelihood of turnover in critical roles with a high degree of confidence currently.”
  • 94% also agreed that, “We have accurate, real-time insight into our employees’ career development goals currently.”
  • When asked “Which of the following analytics are you using?” “artificial intelligence” received the highest response, with 31%. When asked for further detail on how respondents were using AI, the most common responses were “identifying at-risk talent through attrition modeling,” “predicting high-performing recruits,” and “sourcing best-fit candidates with resume analysis.”
  • These findings suggest that the analytics transformation in HR is farther along than you might have thought, with the caveat that the survey respondents were from companies with $100 million in revenue or more, and are thus more likely to have the capacity to deploy new techniques and technologies that may be out of reach for smaller organizations. It should come as no surprise that more and more companies are adopting AI and analytics into their HR functions; what’s new in this survey data is that HR functions are becoming increasingly confident in the maturity and capability of their analytics programs.

    In terms of where companies are deploying talent analytics, Oracle’s findings track with what we have seen elsewhere: The lowest-hanging fruit is in predicting turnover, while there’s also a lot of promise in AI-powered recruiting, predicting performance, and career pathing. The focus on attrition makes sense, as employees who quit often time that decision to leave around predictable life and career events and drop lots of hints about their plans beforehand.

    If you can use data to detect these warning signs and head off unwanted departures, that can save your organization considerable amounts of money. IBM CEO Ginni Rometty made headlines earlier this month when she told attendees at CNBC’s @Work Talent + HR Summit that IBM’s AI technology was able to predict which workers were planning to quit with 95 percent accuracy:

    IBM HR has a patent for its “predictive attrition program” which was developed with Watson to predict employee flight risk and prescribe actions for managers to engage employees. Rometty would not explain “the secret sauce” that allowed the AI to work so effectively in identifying workers about to jump (officially, IBM said the predictions are now in the 95 percent accuracy “range”). Rometty would only say that its success comes through analyzing many data points.

    “It took time to convince company management it was accurate,” Rometty said, but the AI has so far saved IBM nearly $300 million in retention costs, she claimed.

    But predicting turnover with enough accuracy to add value may not require IBM-level AI capabilities. A new study from Peakon finds that employees begin showing clear signs of wanting to quit a full nine months before they pull the trigger on their resignation. A big-data study drawn from over 32 million employee survey responses in 125 countries, the Peakon report points to several key indicators of attrition that show up months in advance: declining engagement and loyalty, as well as dissatisfaction based on unchallenging work, an inability to discuss pay, an unsupportive manager, and the lack of a clear path to advancement in the organization.

    In a recent interview with David McCann at CFO, data scientist Jon Christiansen notes that it’s much easier to predict who will stay than who will leave, but highlights a few indicators that consistently point toward a greater likelihood that an employee will quit, such as whether the employee feels that their performance is evaluated fairly or that they have control over their workday. Other signs include an employee avoiding conflict, siloing themselves, focusing excessively on rewards over the common goal of the organization, and facing either too much or too little pressure at work.

    The advantage for a company like IBM, which continues to invest heavily in AI, is that it can delegate the detection of these patterns to an algorithm. Predicting quits was the first area the tech giant’s HR function focused on when deploying AI, IBM’s chief human resources officer Diane Gherson explained to Jena McGregor at the Washington Post:

    IBM had already been using algorithms and testing hypotheses about who would leave and why. Simple factors, such as the length of an employee’s commute, were helpful but only so telling. “You can’t possibly come up with every case,” Gherson said. “The value you get from AI is it doesn’t rely on hypotheses being developed in advance; it actually finds the patterns.”

    For instance, the system spotted one software engineer who hadn’t been promoted at the same rate as three female peers who all came from the same top university computer science program. The women had all been at IBM for four years but worked in different parts of the sprawling company. While her manager didn’t know she was comparing herself to these women, the engineer was all too aware her former classmates had been promoted and she hadn’t, Gherson said. After the risk was flagged, she was given more mentoring and stretch assignments, and she remains at IBM.

    IBM is also using its Watson AI for other talent-related purposes, such as learning and development or career pathing, Carrie Altieri, IBM’s vice president of communications for people and culture, noted in a recent interview with Riia O’Donnell at HR Dive:

    AI has been a driving force of innovation for IBM’s HR team. Cognitive talent alerts mine for patterns; it searches for employees who’ve been in a job longer than usual (which could signal flight risk) and can determine whether they need more training to move up. …

    AI also can personalize learning and development for each job role and lead the way in making learning a central aspect of a company’s culture. Altieri said that more than 45,000 learners are visiting IBM’s learning platform every day and 98% of employees access it each quarter. While the company requires 40 hours of learning per year, staff average around 50 hours, regardless of tenure. Learning is a huge part of the culture at IBM, she explained, and the new system gives managers the tools to have more intentional discussions with staff.

    And like other tech companies experimenting with these technologies, IBM is not only deploying its AI capabilities internally, but also selling them as a service to other organizations. Last November, the company announced the launch of IBM Talent & Transformation, a new business venture offering AI skills training in addition to services that “harness the power of AI personalization to guide employees in developing skills and pursuing opportunities to grow within the company.”

    Two Studies Suggest Incentives May Not Drive Participation in Wellness Programs

    Two Studies Suggest Incentives May Not Drive Participation in Wellness Programs

    A new study by researchers at the University of Chicago and Harvard, recently published in the Journal of the American Medical Association, sheds new light on the impact on increasingly popular workplace wellness programs on employees’ actual health outcomes. The effectiveness of these programs has not been extensively researched, as they are relatively new and rely on an evolving set of strategies and technologies, and studies so far have drawn mixed conclusions. The new research, Kaiser Health News senior correspondent Julie Appleby explains, had a more sophisticated design than many past studies in this area: The researchers randomly chose 20 BJ’s Wholesale Club outlets to offer a wellness program to all their employees, then compared their results with 140 other stores with no program, covering a total study group of almost 33,000 employees.

    Unfortunately, the researchers found no significant correlation between the introduction of the wellness program and a strong improvement in employee health:

    After 18 months, it turned out that yes, workers participating in the wellness programs self-reported healthier behavior, such as exercising more or managing their weight better than those not enrolled. But the efforts did not result in differences in health measures, such as improved blood sugar or glucose levels; how much employers spent on health care; or how often employees missed work, their job performance or how long they stuck around in their jobs.

    The BJ’s wellness program offered small incentives for participation: Employees could receive about $250 in small-dollar gift cards for taking courses on nutrition, exercise, and other wellness topics. Around 35 percent of eligible employees completed at least one course throughout the duration of the study. One wellness program vendor commented to KHN that the limited impact of the program may have come down to the incentives being too small:

    Jim Pshock, founder and CEO of Bravo Wellness, said the incentives offered to BJ’s workers might not have been large enough to spur the kinds of big changes needed to affect health outcomes. Amounts of “of less than $400 generally incentivize things people were going to do anyway. It’s simply too small to get them to do things they weren’t already excited about,” he said.

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    State and Local Minimum Wage Hikes Continue This Year Throughout the US

    State and Local Minimum Wage Hikes Continue This Year Throughout the US

    A consistent trend in the US business environment over the past three years has been a shift from federal to state and local governments as the main source of regulatory pressure on employers. Even as federal regulations stall or are rolled back under the Trump administration, businesses are facing higher minimum wages, paid leave mandates, and other new regulations at the state and local level. This trend has continued so far in 2019. While the new Democratic majority in the House of Representatives plans to push for an increase in the federal minimum wage from $7.25 to (eventually) $15 an hour, their intent is largely to put political pressure on Republicans with regard to labor issues, and the effort is unlikely to bear much fruit as long as Republicans control the Senate and the White House.

    Meanwhile, however, the patchwork of state and local wage floors is rising and growing more complex. Minimum wages are going up this year in at least 22 US states plus Washington, DC, as well as a number of cities and counties. Most of these increases reflect automatic increases or inflation indexing built into the states’ minimum wage laws, while a few are the result of legislation or referenda passed last year.

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    Google Will Require Full Benefits for its Contractor Workforce by 2022

    Google Will Require Full Benefits for its Contractor Workforce by 2022

    Google revealed on Tuesday that it was phasing in a policy that will require its outside suppliers to provide health insurance, paid parental leave benefits, and a $15 minimum wage to employees working for the tech giant on a temporary or contract basis. The announcement was made in an internal memo issued to all employees and shared with the Hill:

    Google will now require that the outside companies employing the workers provide them with comprehensive health care, a minimum wage of $15 per hour, 12 weeks of parental leave and a minimum of eight days of sick leave.

    Google is beginning the efforts in the U.S., where there are not specific regulations around paid parental leave or comprehensive health care. Other countries in which the company operates have specific legislation around paid parental leave and other benefits. The company said it made sense to start in the U.S. because Google is setting a standard.

    Google is giving the “suppliers” — companies that employ the temporary workers and contractors — until January to institute the minimum wage requirements. A Google spokesperson said it will give suppliers until 2022 to institute comprehensive health care benefits.

    Google has faced increasing pressure from its “TVC” (temporary, vendor, and contractor) workers, as well as an activist community of its full-time employees, to improve the conditions under which TVCs work for the company. A day before the memo was issued, the Guardian reported on a letter signed by more than 900 Google workers calling for significant changes in the way the company deals with its contingent workforce. The letter originated from TVCs working on the global “personality team” responsible for crafting the voice for Google Assistant, most of whom had their contracts abruptly and unexpectedly shortened in early March:

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    The New Candidate Journey Has Changed the Candidate Experience Game

    The New Candidate Journey Has Changed the Candidate Experience Game

    The nonprofit Talent Board has released its 2019 Candidate Experience Awards, a benchmarking report covering over 200 companies in North America and 130,000 job seekers that looks at what organizations focused on in their talent acquisition strategies in 2018 and what they are planning for this year, particularly with regard to candidate experience and employer brand. These issues were top of mind for recruiters going into 2019, Talent Board president Kevin Grossman tells SHRM’s Roy Maurer, with employers paying more attention to the perceptions and experience of not only job applicants, but passive and potential candidates as well:

    “The candidate experience begins during talent attraction and sourcing, even before a potential candidate applies for a job,” he said. “Attracting candidates is one area of talent acquisition that has been given more and more attention and investment due to such a strong job market throughout 2018, with many more employers big and small across industries understanding just how competitive attracting and sourcing quality candidates truly is.”

    The Talent Board’s report shows that 70 percent of candidates do some research on a prospective employer before applying for a job, leaning primarily on employers’ careers sites, job alerts, and careers pages on LinkedIn. According to our research at Gartner, however, candidates are doing less in-depth research into prospective employers before submitting applications than they did a generation ago. That means candidates aren’t engaging that much with employers’ recruitment marketing and branding materials early in their job search. As Craig Fisher, an industry thought leader and head of marketing and employer branding at Allegis Global Solutions, explains to Maurer: “A lot of candidates just apply, apply, apply and don’t really get into the employer brand materials you work so hard at creating until they get further into the process. They’ll begin to scout around when they’re brought onto the company’s careers site to start an application.”

    Indeed, this shift is the key insight of our recent research at Gartner on the changing shape of the candidate journey.

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