Alexandra Levit's Water Cooler Wisdom

The Future of Jobs in the Age of Adaptability

Around 20 years ago, leaders started to ask me if nascent AI-based technologies would eliminate the need for human workers. My response then was the same as it is now: not quickly and not totally.

Nevertheless, human jobs are transforming at a rapid rate. According to a 2023 McKinsey report, in the period from 2019 to 2022, the labor market in the U.S. alone experienced 8.6 million occupational shifts. This is a 50% increase from the prior three-year period, and by 2030, an additional 12 million shifts are projected. McKinsey also estimated that 30% of all hours worked by humans today could be automated by 2030.

It might be simpler if the march toward an AI-driven future meant that all human workers would eventually lounge their lives away on cruise ships – depending on technology for their very existence as in the 2008 Pixar movie WALL-E. In reality, though, humans will continue to work as we always have. The work will just look different.

The exact manner in which human jobs are evolving is driven by organizational concerns around profit and productivity. As we shared in our 2024 Age of Adaptability trends report, companies seeking to boost flagging human productivity must focus on finding the right blend of people and technology. We can do this with a thoughtful approach to job redesign and how human work can best be distributed and evaluated in the near future.

Job Redesign

I briefly talked about job redesign in the first article in this series. Job redesign is the process of rearranging or replacing tasks to better align work with real-time conditions inside and outside the organization.

While leaders may be focusing a lot of attention on job redesign now, the need for it is not unprecedented. For example, the bookkeeper job, once essential for every organization no matter how small, was redesigned in the 1980s to reflect the widespread adoption of accounting software. Back then, if you were a bookkeeper who wanted to remain gainfully employed, you had to determine how to add value beyond the software’s capabilities.

To be fair, job redesign is a more complex proposition today because the onslaught of AI-based technologies in our workplaces is impacting a larger number of jobs. But the transition shouldn’t be overwhelming, as the progression to more complete AI integration is occurring more slowly than most people think. Despite the excitement around generative AI, for instance, practical use cases are still limited. Industry analysts at Gartner even predict that in the next few years, we are likely to fall into a “trough of disillusionment” regarding what AI-based partners can do and what they can’t.

Many organizations have already learned the hard way that strategic job redesign does not involve blunt force – or bringing in a new piece of automation or an AI-based software program and letting go of all of the human employees related to that function. The most effective job redesign initiatives assign smart technology components to handle straightforward, repetitive tasks while human employees remain to provide essential oversight.

Firms like Accenture have already quantified how this shakes out. According to a recent analysis on the impact of generative AI, a current human customer service role can be broken into 13 distinct tasks. Of those 13 component tasks, four must still be fully performed by humans, four could be fully automated, and five involve human and machine partnership. Although Accenture didn’t say this, I’ll point out that the five partnered tasks require substantially more human skill than the four transactional tasks technology is replacing.

For the rest of this article, check out the ManpowerGroup Global Insights blog.

The Future of Skills in the Age of Adaptability

In ManpowerGroup’s 2024 Age of Adaptability trend report, we shared how current demographic shifts are exacerbating labor shortages. Specifically, by 2030, members of Generation Z (born 1996-2012) will compose 58% of the workforce and a majority of the large baby boom generation will have retired.

The resulting knowledge deficit means it’s paramount to forecast the future of skills and use this understanding to fill gaps as efficiently as possible. However, for all of the talk about skills-based organizations – which deconstruct traditional roles, break them down into component parts, and then hire people to handle each part – the progress toward this shift in protocol isn’t as rapid as some would prefer. Between now and 2030, the evolution to a true skills focus will be gradual, and not as simple as merely declaring yourself a skills-based organization.

In this piece, we’ll explore how in the near future, the composition and acquisition of an in-demand, workforce-wide skills portfolio can move organizations toward the goal of a skills-based organization.

Skill Composition

The future of skills is complex and rapidly evolving. According to the World Economic Forum’s 2023 Future of Jobs Report, 44% of workers’ skills will be disrupted within five years.

But what skills will be most essential in a world of global, distributed, and automated work, where more surprises are likely around the corner? WEF’s 2023 research found that the hottest skills from an organizational perspective include cognitive and analytical thinking, creative thinking, self-efficacy (resilience, flexibility, and learning agility), curiosity, empathy, social influence, and quality control.

It’s notable that technical AI and big data skills ranked of lower importance than all of these. Why is this the case when AI-related skills are the third highest priority in company training strategies from now until 2027 (nine percent), and the top training priority for companies with more than 50,000 employees?

Leaders may be realizing that it’s not the hard AI and automation skills themselves that are most critical, but the ability to have an effective partner orientation toward working with smart machines. In other words, honing our human “soft” skills is the best way to differentiate our capabilities from AI’s capabilities and provide competent and ethical oversight to the technological “employees” in our workplaces.

In a 2024 LinkedIn Pulse article, systems engineer Arif Sheikh agreed with this take, suggesting that as AI-based technologies automate a greater number of tasks, the value of traditional human skills might at first seem to diminish. But this perspective overlooks the foundational role such skills play in personal development, social interaction, and professional experience.

Sheikh suggested that individuals who learn to navigate social interactions without social media before relying on these platforms will have better outcomes. “This highlights the importance of direct, human connection – a nuance that AI, for all its sophistication, cannot fully replicate,” he said.

In any case, it’s likely that by 2030, the most marketable employees will be those whose skillsets are a blend of job-specific competencies and those that make it possible to work successfully with machines and other humans in a variety of contexts. This means that in terms of training dollars, we might want to put the horse before the cart.

We should also note that within the next ten years, a majority of jobs will have a green component, which may require the development of new skills such as carbon footprinting, sustainability consulting, and climate data analysis across a large swath of industries and functions.

For the rest of this piece, please visit the Manpower Group Global Insights blog.

 

The Future of AI in the Age of Adaptability

For the next several months, I'm going to be featuring a "Future of..." series I'm working on with ManpowerGroup as part of its new Global Insights team.

Within the next five years, we anticipate that the democratization of AI-based technology will lead to greater accessibility across the organization and that employees at all levels will be empowered to integrate AI into relevant job tasks as they see fit. 

As we discussed in “The Age of Adaptability” report, businesses anticipate a 23% churn in jobs over the next five years between the creation of new roles and the reduction of others. But, because more cross-industry examples will emerge detailing how best to deploy AI, organizations won’t be as mystified by its presence and impact on the workforce. AI will increasingly be seen as a force for good!

One might imagine that a futurist has extreme ideas about the future of AI. And while it’s true that I believe AI-based technologies will be true partners in work moving forward and will play a role in the development of the metaverse and immersive work environments that Manpower recently researched, I don’t think the AI of science fiction is likely to come to fruition anytime soon. We are still far from achieving what’s called artificial general intelligence, which is a form of AI that thinks and creates on its own, essentially surpassing human abilities in all types of work.

Since AI-based technologies are not in a position to take over all human jobs as is still feared, this piece will focus on the technologies that are available now – namely generative AI applications and talent intelligence applications – and the role they can realistically play in the workforce in the coming years.

Generative AI Has Legs, But It’s Not the End

Generative AI is capable of generating text, images, or other media by learning the patterns and structure of input training data and then generating new data that has similar characteristics. A workforce-related example involves the development of sophisticated digital assistants that can use an existing arsenal of HR information to respond more accurately to online employee queries, even if they weren’t trained on those exact questions.

The technology has been introduced to the market at a very rapid pace. ChatGPT was released in November of 2022, and then shortly thereafter, OpenAI released a large language model called GPT-4 that was a measurable improvement over the original ChatGPT. Microsoft, Google, and other big technology players are quickly getting in on the action. 

But generative AI is not necessarily the massive breakthrough people think it is. Its release is more the result of a logical linear progression, as we’ve had smart chatbots for quite some time now. Although there has been significant media interest in ChatGPT, it’s not substantially different from what came before. In its current state, generative AI still requires a great deal of human oversight and regulation, and the majority of organizations are just figuring out how to use it effectively for various business purposes. So, if you haven’t cracked the code yet, you shouldn’t lose sleep over it. You’re not behind.

For the rest of this piece, head over to the ManpowerGroup's Global Insights blog.

Talent Intelligence Platforms Use Deep Learning to Close Skills Gaps

The HR community is enthralled by the idea that artificial intelligence (AI) can provide tangible benefits in the quest to effectively source and hire in a tight labor market. But how does this work in practice? 
 
It starts by understanding a branch of AI called deep learning. Deep-learning algorithms, which are inspired by the actions of the human brain, continuously analyze data with a given logical structure. This structure encompasses multiple layers of algorithms called neural networks. 
 
Deep-learning algorithms can’t predict the future or give answers that a human would agree with 100%. Yet they are still valuable. If you’ve ever used a modern search engine and been amazed by the results or if you’ve ever watched the perfect show recommended by your streaming network of choice, you have experienced the power of deep learning. 
 
The main challenge of deep learning is data — specifically, the massive amount required. The talent space alone needs billions of data points about people, career trajectories, skills, and experiences. 
 
But while AI’s reach was once limited by computing power and the availability of data, that’s no longer the case. Today, global neural nets can identify more than a million skills across the world’s 8 billion people. 
 
Then, using this data, AI engineers can develop deep-learning algorithms to determine the best answers to a defined class of questions. In the case of deep talent, such questions might include: Who is the best fit for this specific job requirement? What job is this individual most likely to hold next in their career? 
 
Understanding deep learning’s ability to harness a massive amount of data is only the first step, however. Next, we must explore how deep learning can help us identify skills and transform how we hire people. 
 
The Power of Skills Adjacency 
 
Skills adjacency refers to the inference that a person good at skill A often excels at skill B, and it helps us complete our picture of a human’s true potential and the transferable skills they possess. 
 
In my recent book, “Deep Talent,” my co-authors and I tell the story of Nico Iannotti, a top sales engineer in Europe. Nico wasn’t always involved with either sales or technology. He was, however, previously involved with customer service as a sommelier and waiter. As he put it, skills are interchangeable assets that individuals can leverage in a variety of industry roles and life situations. 
 
“Many of the skills I acquired prior to my corporate career have been very helpful in my role as a client-relationship manager and solution engineer,” he told us. “What is the link between pairing wines and selling software? Both are customer-facing roles, and both provide solutions to a customer’s problem. In both cases, you are building relationships, demonstrating empathy, and selling an emotional experience based on a specific budget. It’s just a change of context, not a completely different skillset.” 

For the rest of the piece, head over to the UKG Workforce Institute.

Don't Be Intimidated by Job Redesign

The need for job redesign is on most HR leaders’ radars in 2024. But in most organizations, it still seems to be more of a talking point than a reality. However, given that Dayforce’s 14^th Annual Pulse of Talent survey found that 37% of respondents said there is a different role with their current employer that better matches their skillset, the process seems ripe with opportunity.

Job redesign is the process of rearranging or replacing tasks to better align work with evolving conditions both inside and outside the organization. And it’s really nothing new. For example, the telegraphist or telegraph operator was one of the first tech-related jobs of the 19^th century. The telegraphist used the most modern equipment available at the time to send and receive Morse code via radio and telephone.

In the 1970s, the telegraph was mostly replaced by telex, a communications network to send text-based messages. So, if you were a telegraphist and you wanted to remain gainfully employed, you had to adapt and learn telex. In other words, the telegraphist job was redesigned with a lot of the same skills and responsibilities – minus the telegraph.

Job redesign may feel more complex and overwhelming today because the pace of technology is faster and has a broader impact in terms of affected occupations. In particular, the arrival of generative AI has leaders wondering exactly how to execute job redesign to incorporate the benefits of this technology.

Before we get into how to make the process more turnkey, let’s address what job redesign is NOT. For example, job redesign is not bringing in a new piece of automation and letting go of all the human employees previously involved in the job targeted by the automation. When integration of automation is done well, the technology takes over more straightforward, repetitive tasks while human employees provide the necessary strategic input, creativity, judgment, and oversight. And that’s where job redesign comes in.

Three practical steps for job redesign
In most knowledge-driven and in many frontline worker occupations, shifting business requirements and emerging technologies mean that employees need new skillsets. Therefore, the process of job redesign involves understanding the individual tasks that encompass the work being done, and then matching or training for skills necessary for those tasks.

Step one: Engage in task analysis

Target a small category of jobs to start, and then assemble a diverse group of stakeholders from across the organization. Make sure this group includes people across levels, and not just leadership, so you have representation from those who are close to the work.

Document the critical tasks currently associated with each job, and note where there are redundancies, areas where technology could be efficiently deployed, and places where you can build a job to become more flexible in structure and environment. You can also rank your tasks according to importance, how often they are performed, how long they take, and the skills required or how people learn how to do each task.

Step two: Create new job titles and descriptions

Next, based on your analysis, group related tasks into new job buckets. With smart technology now helping in new ways with some tasks, there may be room to remove or combine previous jobs. This may involve creating new “super jobs” that cross departmental lines. For example, the new job of people analytics manager might be technically housed in HR but include tasks traditionally housed in IT such as selecting appropriate technology applications, ensuring data quality, and communicating data-related insights to leaders and other constituents.

You can also use this exercise as an opportunity to standardize jobs titles and descriptions across the organization.

For the rest of the piece, head over to the Dayforce blog.

Goodbye to My Current WSJ Column, The Workplace Report

All good things must come to an end.

My syndicated WSJ column, The Workplace Report, is coming to an end. The last 20 months have involved an unprecedented amount of change in the workforce and human resources spheres. I'm leaving it with five major predictions for the near future world of work, featuring Workplace Report highlights from the last year and a half of coverage.

The demand for skilled workers will reach a crisis point due to demographic shifts and falling fertility rates. According to Manpower Group’s 2023 Talent Shortage Survey, 77% of global employers say they are already struggling to find workers with the right mix of technical skills and human capabilities.

Talent intelligence, internal talent mobility, skills-based hiring, and the rise of short-term, rapidly assembled teams comprised of a mix of people with different geographies and employment arrangements – including contract workers and the first permanent WFH employees – will alleviate the squeeze.

Generative AI spreads its influence across industries. Generative artificial intelligence is a form of AI capable of generating text, images, or other media by learning the patterns and structure of input training data and then generating new data that has similar characteristics.

In the coming years, we will see expanded accessibility and impact via AI democratization, the integration of AI into a variety of work functions, and numerous use cases developed and publicized. People are unlikely to lose their jobs due to Gen AI alone, but rather to a human who knows how to work with Gen AI. And managers will need a whole new skillset to supervise human workers empowered by AI to make independent decisions.

Organizations are called to step up holistic employee care. In keeping with the longstanding view of employees as commodities, most organizations have been unaccustomed to concerning themselves with aspects of employee lives outside what they did between office walls.

However, as the definition of full-time employment becomes more fluid and mental health and burnout numbers remain higher than pre-pandemic, some (but not all) organizations will answer their employees’ calls for help (retaining  COVID-19-era benefits and adding new ones, managing layoffs effectively, etc.).

Employee experience will rise to the forefront as an essential part of engagement. Across the employee lifecycle, from talent acquisition to onboarding to learning and development, performance management, and offboarding, companies are making progress customizing their employee experiences to different groups depending on their unique journeys and requirements. Diversity, equity, and inclusion and allyship strategies will continue to be a priority for the most forward-thinking organizations.

The employee experience of the next several years is high tech and high touch and focuses on two overarching themes: purpose and flexibility. Also, the employee experience of 2030 will likely begin to include the metaverse, which will greatly impact organizational culture and work structures.

HR compliance is rising to a never-before-seen level of complexity. This has involved hundreds of new regulations associated with re-opening, distributed and remote work, vaccination, and labor relations, as well as those associated with human capital disclosures, pay transparency, and the increasing use of AI in organizations.

It is just a matter of time before lawmakers draft guardrails to use these technologies ethically and to safeguard sensitive data. As these regulations will vary by country, state, or locality, this will be increasingly difficult for HR and workforce professionals to keep up with.

Why Labor Shortages Are Happening and What Leaders Should Do

Workforce futurists have been predicting mid-twentieth century labor shortages for some time now, but many forecasts seemed unduly alarming – until the pandemic. Now, a confluence of factors is rapidly decreasing the global worker supply.

Employers have noticed. According to Ceridian’s 2023 Executive Survey, 66% of the global leaders surveyed have experienced a labor shortage in the past 12 months. And 88% said it’s at least slightly likely shortages will continue over the next year.

The surveyed leaders aren’t wrong about the likely continuation of labor shortages. And many executives I’ve spoken to recently are wondering why there is a labor shortage and how they can protect their organizations from critical deficits in the near- and long-term.

So, why is there a labor shortage? Let’s look at some of the causes.

Fewer people in the workforce

The main culprit, as futurists have noted for decades, is demographic shifts. Specifically, falling fertility and labor force participation rates mean there are simply fewer workers available to be hired.

Over the next decade, with most baby boomers entering retirement, the number of working-age people aged 15-65 is projected to decline by over three percent in some countries, including the United States. And even the people in this age range aren’t necessarily working to their full potential. Per a recent World Bank analysis, the global labor force participation rate has fallen steadily since 1990 from more than 65% of working-age people to less than 60% today.

These figures are already affecting unemployment. In April 2023, the U.S. Bureau of Labor Statistics’ Jobs Report showed that unemployment for 20-to-24-year-olds fell to 5.4%, the lowest it has been since 1969. As a result, newly minted college graduates are entering a job market that’s not only more robust than a year ago, but significantly stronger than it was before the pandemic.

Low-wage workers lack mobility

Labor shortages among low-wage workers are getting the most attention recently. And with good reason, as they are currently among the most dire shortages. One major factor is stricter immigration policies, and the other, economists speculate, is a “dual labor market” that doesn’t allow much room for mobility.

A new research paper published by economists at the Federal Reserve Board in Washington, D.C. shows this dual labor market is a problem for countries like the U.S. The researchers’ analysis documented a primary workforce comprising 55% of the population. These workers have high levels of employment stability and are only unemployed for short periods of time.

The secondary labor market, on the other hand, makes up 14% of the population and lives in a constant state of flux with poor wages and working conditions. These workers experience six times higher job turnover than those in the primary tier and are 10 times more likely to be unemployed. At present, extremely limited mobility between the two sectors negatively impacts the United States’ (and others’) ability to attract lower-wage workers who want to climb their way up.

For the full piece, head over the Ceridian blog.

Halfway Through 2023, The Return to Office Debate Still Rages

In workforce and HR circles, one of the main events of 2023 so far has been the return-to-office (RTO) debate – and specifically the opposing viewpoints of those who want to remain remote and those who yearn to be in the office again.

Last year, it seemed like most companies had settled into harmonious hybrid work arrangements, with many mandating that office-based employees report to physical locations one to two days per week. But recently, a growing number of organizations, including Apple and Starbucks, are walking back remote-work policies. And new Congressional legislation aims to decrease telework options for federal workers in the U.S.

Some employees aren’t accepting the changes. SHRM reports that weeks after Disney CEO Bob Iger said he would require corporate employees to return to the office four days a week, 2,300 of them signed a petition asking him to reconsider the policy.

Through companies like Apple, Starbucks, and Disney, we see the pro return-to-office perspective. But it’s clearly not the only point of view. Let’s summarize the main points of each argument in the return-to-office debate.

The pro-office point of view

In his memo to employees, Disney’s Iger stated that “creativity is the heart and soul of who we are and what we do at Disney. In a creative business like ours, nothing can replace the ability to connect, observe, and create with peers that comes from being physically together, nor the opportunity to grow professionally by learning from leaders and mentors."

Humans are social creatures who bond with one another and often ideate more effectively in a team context. This is why many leaders want people back in the office.

Then there are the financial realities – at least for organizations based in the U.S. As Bloomberg recently reported, U.S. cities and states grant billions in tax incentives to companies who open offices in their areas. These agreements often include an expectation that companies will deliver something in return: full-time jobs, done primarily on-site. These new jobs bring new payroll and tax revenues— but not if they’re performed remotely. Naturally, leaders don’t want to jeopardize these lucrative incentives.  

For the pro-remote point of view, check out the rest of the article on the Ceridian blog!

 

Trends Shaping Talent in 2023

Now that we’re into the second quarter of 2023, we can see that the talent acquisition (TA) world has a different tint. Despite the specter of recent layoffs and a looming recession, widespread skills shortages and a low overall labor force participation rate (LFPR, or the number of people in the workforce or actively looking for work) mean that organizations have had to deploy more innovative recruitment strategies.

These trends are reaching critical mass:

Internal Mobility

When it comes to lateral moves and internal opportunities, most organizations have always talked a good game. However, in practice, managers were more likely to hoard top talent. A poor infrastructure often restricted employee movement from one team to another, even if a manager was supportive. But during the COVID-19 pandemic, leaders recognized the utility of redeploying workers from a slow area of the business into a more viable one. Since then, internal mobility has gained momentum.

This year is different due to the more widespread usage of technologies that drive internal mobility – namely, talent intelligence and predictive analytics. Rather than waiting for an individual employee to express interest in a given position, artificial intelligence allows leaders to proactively determine who within the existing workforce might have the right skill set to meet a current or near-future need or who could be easily trained to do so.

Executive Freelancers

The professional contract workforce has been growing for the last decade, but traditionally, freelancing was mostly limited to individual contributors in professions like writing, marketing and information technology. Because these workers usually completed work that could be more narrowly defined within the scope of a “project,” this made sense.

In 2023, however, pervasive contract work has expanded to other professions, including law and finance. We are increasingly seeing organizations using “interim” c-suite executives to take over for a leader who is on leave, to trial a new hire for fit, or to temporarily fill the position while they search for a permanent hire.

Unfortunately, it is still the case that organizations often treat contract workers as second-class citizens. But as they become a more significant percentage of the employee mix, TA leaders must leverage technology to nurture their relationships with this population and deliver the appropriate opportunities, training and communications.

For more trends, or to check out my recent webinar on talent intelligence, head on over to the SilkRoad blog.

The Future of Skills-Based Hiring

A few weeks ago, I attended a dinner where some colleagues emphatically insisted that the future of hiring could not and would not become skills-based until organizations stopped selecting people based on educational pedigree.

I pointed out that this is already happening. When I graduated from college in the late 1990s, you had to have a bachelor’s degree to get an entry-level professional position. It didn’t matter what skills you had. Today, depending on the role, if you can show skill competency, many organizations will overlook a lack of formal education.

The real question is: Have we moved the needle enough to combat ever-increasing global labor shortages? The answer may indeed be no, and that’s likely because there’s no sense of urgency. Many organizations still think the traditional mode of hiring – via resumes and follow-up, subjective interviewing – works just fine.

Let’s look at the problems with the status quo and how your organization can reap the rewards from a new approach to talent acquisition. Skills-based hiring will be the future, but there’s no time like the present to move in that direction.

The trouble with resume-based hiring

Resume-based hiring has a variety of flaws, namely that people are notoriously bad at self-assessment. A resume only captures a small amount of what a person has done and can do. And even if their skills are presented somewhat effectively, the hiring manager may be negatively influenced by factors like what font the candidate used and whether too many words are crammed onto the page.

Resumes (and LinkedIn profiles) also capture just one moment in time. This means that unless a hiring manager is reviewing information that was just sent to them by a candidate for a specific job, the hiring manager has no idea how current the information is.

Finally, resume-based hiring assumes that the organization wants to hire someone for a static role. The hiring manager wants to see straightforward evidence that the candidate has already performed this role because they aren’t expecting it to change much. But this is an outdated view of jobs. Today, employers must approach hiring with career flexibility in mind.

Organizations need to hire people with as deep of a skills bench as possible so that those employees can move fluidly through the organization as business requirements evolve. It's hard to assess how well someone will be able to do this from a resume.

But if an organization isn’t going to hire employees based on resumes and wants to get to the heart of the skills candidates possess today, how can this be achieved?

How to get started with skills-based hiring

I’ll readily admit that skills-based hiring is a difficult task without technology, and specifically, without artificial intelligence. But new talent intelligence platforms allow organizations to leverage career data points to paint a much broader picture of the skills a given individual might have. Talent intelligence tools also allow organizations to focus on the skills necessary for success within a particular career path, which might not always be what human hiring managers think they are.

This technology is especially good at uncovering skill adjacencies. Using skill adjacency, you can infer that a person who is good at skill A often excels at skill B. For example, we can infer that someone who is good at trigonometry is probably also good at geometry. Or we could guess that an experienced marketing professional could more quickly learn public relations.

The rise of the flexible career experience

 

For recruiters who are accustomed to resume-based hiring, this is a whole new world. For example, when a company is hiring for a customer service manager, a recruiter may search for candidates with resumes containing that exact title. Until recently, we simply have not had the tools to surface candidates who may have the right customer skills based on their life experiences instead of the positions they’ve held.

By focusing on workers’ capabilities rather than exact job titles, companies can build a broader pool of diverse, qualified candidates. This is an especially useful approach post-pandemic, given that most workers accumulated a wide variety of transferable skills inside and outside their main jobs in the areas of communication, problem solving, and adaptability. Skills like this support success in any role but may not be found on these candidates’ resumes, so it’s wise to have another way to account for and assess them.

In short, hiring based on educational pedigree and resumes is the past while hiring based on skills and potential is the future. And technology can go a long way to help us transform hiring practices – both culturally and operationally.

For the original article,  head over to the Ceridian website.