Josh Bersin :劳动力市场已完全改变：您真的准备好了吗？Josh Bersin 最新撰文谈到，随着以婴儿潮一代为主的劳动力队伍的衰落和具有独特期望和职业模式的新一代的崛起，劳动力市场发生了巨大的变化。这一新劳动力的特点是偏好组合职业和副业，他们要求尊重、灵活性和精心设计工作的机会。企业在适应这些变化时面临着挑战，职位普遍空缺，人员流动增加。文章强调，企业需要采用一种动态的组织模式，优先考虑授权、内部流动性和员工积极性，以便在这个新的劳动力市场中茁壮成长。这种适应的关键在于了解劳动力现在寻求的是成长、灵活性以及他们的价值观与工作之间有意义的结合。
英文原文如下，推荐了解
The labor market has changed before our eyes. Employers and HR teams better watch out.
Over the last five decades baby boomers defined the workforce. Today things could not be more different, and this change impacts all of us.
I was born in the 1950s, growing up in a world where the middle class experienced steadily increasing standards of living. My father was a scientist, my mother sold art, and my brother and I had a nice middle-class life.
This included a three stage career: education | work | retirement. I went to college, studied hard, and got a good job as an engineer. My career went on a predictable path. I worked for Exxon and then IBM – each company giving me training, development, and potential for long-term career. I met many great people, learned about work, got married and had a family.
My cohort, the baby boomers, was huge. Companies built entire talent systems for us – onboarding, training, predictable career growth, developmental assignments, leadership development, and retirement programs. We strapped ourselves in and enjoyed the journey.
Fast forward to now: things are very different.
Today’s working population bulge (median age 33, born in the early 1990s,) entered the workforce in a disrupted world. They joined companies during a boom, experienced the pandemic in their 20’s, and live in a world where everything is on the internet. While my generation revered our employers, these workers see every corporate mistake in real-time. They expect their bosses to earn their respect, otherwise they’ll “quietly quit” or start moonlighting on the side.
While my generation expected to work for only a few employers during a career, today people build what Lynda Gratton calls “a portfolio career.” More than 2/3 of workers have side-hustles and their resume is filled with projects, businesses, activities, and professional interests. If you look at the LinkedIn profiles of most high performers they look like personal journeys, far different from the linear career paths we had in the past.
While most of these changes came slowly, the end result is profound: the expectations, needs, and demands of workers are different. And businesses have struggled to keep up. Companies have vast amounts of unfilled positions, we suffer high turnover in almost every role, and labor unions are growing in number.
What do companies do? We have to accept and understand that the labor market has totally changed.
We live in a world where employees will live into their 100s. Young workers are postponing getting married and having children and they see their career as a long series of experiences. The norms of a long-term linear career have ended: people try new things, change industries, and live in what I call a “pixelated” job market.
And rather than blindly trust employers, people bring high expectations to work. Young workers don’t expect to “become the job,” they want the job to “become them.” (Often called “job crafting.”) And given the shortage of workers in every role, this trend is just getting bigger.
While economists believe the job market will soften and employers will have more power over time, I think those days are over. Life just isn’t going back to the way it was. Despite the growth of AI, companies are more dependent on their workforce than ever. And with 70% of the jobs now service-related (healthcare, retail, hospitality), employees really are our product.
I look at it this way. Companies and employers live in a pool of labor: it’s the needs and expectations of people who decide what we can and should do. People are upset about inflation. They’re worried about climate change. They want CEOs to behave ethically. And they want flexible work that lets them live a joyful life.
And every year the workforce becomes more educated and connected. (The percentage of US workers with degrees has gone up to 54%, up from 38% fifteen years ago.) People know about the company’s financial results or other issues far before an announcement even comes out.
While many of these trends are obvious, many companies aren’t ready. Last year I talked to the CHRO of Boeing and he told me the problems were highlighted by employees years ago. They simply were not listening, and now they’re a company in crisis. And that leads to the topic of “employee activation.”
In the old days senior leaders made decisions, workers carried out the orders. Ideas and strategies were “top-down.”
Today much of the intelligence we need to grow our companies is sitting with front-line workers. We need to “activate employees” and listen to them directly. The worker in the store, plant, or front office who feels frustrated by some system or process is the person who should advise us what to do. The old idea of “management by walking around” must come back. (Our Org Design Superclass explains this in detail.)
I don’t mean chaos, holacracy, or lack of controls. Successful companies have a clear mission, a series of strategic initiatives, and budgets to hold people accountable. But they empower everyone to be a leader, unleashing power from the bottom up. (Come to Irresistible and learn about how Marriott and Delta airlines exemplify this model.)
The key is building what we call a “Dynamic Organization” – one which is flat, team-centric, connected, and accountable. Our research shows that only 7% of companies operate this way: most are still very hierarchical and slow to adapt. But change is coming, as companies like Delta, Marriott, Telstra, Unilever, Novartis, Seagate, and Bayer have found out.
(This week the CEO of Bayer announced a radical transformation to a team-centric management model, dramatically reducing the number of “bosses.”)
A dynamic organization does two things well. First, it adapts to change, sees new markets, and mobilizes quickly for change. But even more importantly, it empowers people, encourages internal mobility, and focuses on meritocracy, skills, and collaboration to thrive. (Read about Talent Density to learn more.)
While these ideas are not new, urgency is critical. Employees demand growth, flexibility, and agency – and we can’t deliver it unless our reward and development systems change. Today more than 70% of US jobs are in the service sector: health care, retail, entertainment, and transportation. If we don’t empower people in these roles our products and services will suffer.
Let me conclude with this: we just woke up in a totally new labor market. If you don’t focus on empowerment, growth, and employee activation, talent will just go elsewhere.
labor market
2024年03月31日
labor market
How Generative AI Adds Value to the Future of Work
这篇Upwork的文章深入探讨了生成式人工智能（AI）在重新塑造工作价值方面的变革力量，强调了自动化和创新不仅改变了工作岗位，还在各个行业提高了生产力和创造力。文章着重讨论了对劳动力市场的细微影响，强调了技能发展和道德考虑的重要性，并对人工智能与人类合作的未来提供了前瞻性的视角。
Authors: Dr. Ted Liu, Carina Deng, Dr. Kelly Monahan
Generative AI’s impact on work: lessons from previous technology advancements
In this study, we provide a comprehensive analysis of the initial impact of generative AI (artificial intelligence) on the Upwork marketplace for independent talent. Evidence from previous technological innovations suggests that AI will have a dual impact: (1) the displacement effect, where job or task loss is initially more noticeable as technologies automate tasks, and (2) the reinstatement effect, where new jobs and tasks increase earnings over time as a result of the new technology. Take for example the entry of robotics within the manufacturing industry. When robotic arms were installed along assembly lines, they displaced some of the tasks that humans used to do. This was pronounced in tasks that were routine and easy to automate. However, new tasks were then needed with the introduction of robotics, such as programming the robots, analyzing data, building predictive models, and maintaining the physical robots. The effects of new technologies often counterbalance each other over time, giving way to many new jobs and tasks that weren’t possible or needed before. The manufacturing industry is now projected to have more jobs available as technologies continue to advance, including Internet of Things (IoT), augmented reality, and AI, which transform the way work is completed. The issue now at hand is ensuring enough skilled workers are able to work alongside these new technologies.
While this dynamic of displacement and reinstatement generally takes years to materialize, as noted above in the manufacturing example, the effects of generative AI may be taking place already on Upwork. For the platform as a whole, we observe that generative AI has increased the total number of job posts and the average spend per new contract created. In terms of work categories, generative AI has reduced demand in writing and translation, particularly in low-value work, while enhancing earnings in high-value work across all groups. In particular, work that relies on this new technology like Data Science and Analytics are reaping the benefits. The report highlights the importance of task complexity and the skill-biased nature of AI's impact. Skills-biased technology change is to be expected as the introduction of new technologies generally favors highly skilled workers. We observe this on our platform as high-skill freelancers in high-value work are benefiting more, while those in low-value work face challenges, underscoring the need for skilling and educational programs to empower freelancers to adapt and transition in this evolving work landscape.
Understanding the lifecycle of work on Upwork and the impact of gen AI
Generative AI has a growing presence in how people do their work, especially since the public release of ChatGPT in 2022. While there’s been extensive discussion about the challenges and opportunities of generative AI, there is limited evidence of such impact based on transaction data in the broader labor market. In this study, we use Upwork’s platform data to estimate the short-term effects of generative AI on freelance outcomes specifically. The advantage of the Upwork platform is that it is in itself a complete marketplace for independent talent, as we observe the full life cycle of work: job posts, matching, work execution, performance reviews, and payment. Few other instances exist where a closed-system work market can be studied and observed. Thus, the results of this study offer insights into not only the online freelance market, but also the broader labor market.
How technological progress disrupts the labor market is not a new topic. Acemoglu and Restrepo (2019) argue that earning gain arises from new tasks created by technological progress, which they term the “reinstatement effect,” even if the automation of certain tasks may have a displacement effect in the labor market initially. What this means is that there may be a dynamic effect going on: the displacement effect (e.g., work loss) may be more noticeable in the beginning of a new technology entry, but as new jobs and tasks are being created, the reinstatement effect (e.g., rates increase, new work) will begin to prevail. In the broader labor market, such dynamics will likely take years to materialize. But in a liquid and active independent work marketplace like Upwork, it’s possible that we’re already observing this transition happening.
Existing studies such as this provides a useful conceptual framework to think about the potential impact of generative AI. It’s likely that in the short term, the replacement of generative AI will continue to be more visible, not just at Upwork, but also in the broader labor market. Over time and across work categories, however, generative AI will likely spur new tasks and jobs, leading to the reinstatement effect becoming stronger and increasing rates for those occupations with new tasks and a higher degree of task complexity. We’ve already seen evidence of new demand as a result of gen AI on our Upwork platform, with brand new skill categories like AI content creator and prompt engineer emerging in late 2022 and early 2023. We test this hypothesis of both work displacement and reinstatement, and provide insights into how generative AI affects work outcomes.
Impact of generative AI on work
To understand the short-term impact of generative AI on the Upwork freelance market, we capitalize on a natural experiment arising from the public release of ChatGPT in November 2022. Because this release was largely an unanticipated event to the general public, we’re able to estimate the causal impact of generative AI. The essential idea behind this natural experiment is that we want to compare the work groups affected by AI with the counterfactual in which they are not. To implement this, we use a statistical and machine-learning method called synthetic control. Synthetic control allows us to see the impact that an intervention, in this case, the introduction of gen AI, has on a group over time by comparing it to a group with similar characteristics not exposed to the intervention. The advantage of this approach is that it allows us to construct reasonably credible comparison groups and observe the effect over time.
The units of analysis we use are work groups on the Upwork platform; we analyze variables such as contract number and freelancer earnings. Instead of narrowly focusing on a single category like writing, we extend the analysis to all the major work groups on Upwork. Moreover, we conduct additional analysis of the more granular clusters within each major group. The synthetic control method allows for flexibility in constructing counterfactuals at different levels of granularity. The advantage of our comprehensive approach is that we offer a balanced view of the impact of generative AI across the freelance market.
Generative AI’s short-term impact on job posts and freelancer earnings
Looking at the platform as a whole, we observe that generative AI has increased the total number of job posts by 2.4%, indicating the overall increased demand from clients. Moreover, as shown in Figure 1, for every new job contract, there is an increase of 1.3% in terms of freelancer earnings per contract, suggesting a higher value of contracts.
Figure 1 Effect of Generative AI on Freelancer Earning per Contract
The Upwork platform has three broad sectors: 1. Technological and digital solutions (tech solutions); 2. Creative & outreach; 3. Business operations and consulting. We have observed both positive and negative effects within each of the sectors, but two patterns are worth noting:
The reinstatement effect of generative AI seems to be driving growth in freelance earnings in sectors related to tech solutions and business operations. In contrast, within the creative sector, while sales and marketing earnings have grown because of AI, categories such as writing and translation seem disproportionately affected more by the replacement effect. This is to be expected due to the nature of tasks within these categories of work, where large language models are now able to efficiently process and generate text at scale.
Generative AI has propelled growth in high-value work across the sectors and may have depressed growth in low-value work. This supports a skills-biased technology change argument, which we’ve observed throughout modern work history.
More specifically and within tech solutions, data science & analytics is a clear winner, with over 8% of growth in freelance earnings attributed to generative AI. This makes sense as the reinstatement effect is at work; new work and tasks such as prompt engineering have been created and popularized because of generative AI. Simultaneously, while tools such as ChatGPT automate certain scripting tasks (therefore leading to a replacement effect), it mainly results in productivity enhancements for freelancers and potentially leads to them charging higher rates and enjoying higher overall earnings per task.
In terms of contracts related to business operations, we observe that accounting, administrative support, and legal services all experience gains in freelance earnings due to generative AI, ranging from 6% to 7%. In this sector, customer service is the only group that has experienced reduced earnings (-4%). The reduced earnings result for customer service contracts is an example of the aggregate earnings outcomes of AI, related to the study by Brynjolfsson et al (2023), who find that generative AI helps reduce case resolution time at service centers.
A potential outcome of this cut in resolution time is that service centers will need fewer workers, as more tasks can be completed by a person working alongside AI. At the same time, the reinstatement effect has not materialized yet because there are no new tasks being demanded in such settings. This may be an instance where work transformation has not yet been fully realized, with AI enabling faster work rather than reinventing a way of working that leads to new types of tasks. A contrasting case is the transformation that happened with bank tellers when ATMs were introduced. While the introduction of these new technologies resulted in predictions of obsolete roles in banks, something different happened over time. Banks were able to increase efficiency as a result of ATMs and were able to scale and open more branches than before, thereby creating more jobs. In addition, the transactional role of a bank teller became focused on greater interpersonal skills and customer relationship tasks.
When taken together, the overall gains in such business operations work on Upwork are an encouraging sign. These positions tend to require relatively intensive interpersonal communication, and it seems the short-term effects of generative AI have helped increase the value of these contracts, similar to what we saw in the banking industry when ATMs were introduced.
As of now, the replacement effect of AI seems more noticeable in creative and outreach work. The exception is sales and marketing contracts, which have experienced a 6.5% increase in freelance earnings. There is no significant impact yet observed on design. For writing and translation, however, generative AI seems to have reduced earnings by 8% and 10% respectively. However, as we will discover, task complexity has a moderating effect on this.
High-value work benefit from generative AI, upskilling needed for low-value work
Having discussed the overall impact of generative AI across categories, we now decompose the impact by values. The reason we’re looking at the dimension of work value is that there may be a positive correlation between contract value and skill complexity. Moreover, skill complexity may also be positively correlated with skill levels. Essentially, by evaluating the impact of AI by different contract values, we can get at the question of AI's impact by skill levels. This objective is further underscored by a discrepancy that sometimes exists in the broader labor markets – a skills gap between demand and supply. It simply takes time for upskilling to take place, so it’s typical for demand to exceed supply until a more balanced skilled labor market takes place. It is worth noting, however, freelancers on the Upwork platform seem more likely than non-freelancers to acquire new skills such as generative AI.
For simplicity, let’s assume that the value of contracts is a good proxy for the level of skill required to complete them. We’d then assume that high-skill freelancers typically do high-value work, and low-skill freelancers do low-value work. In other words, our goal is also to understand whether the impact of generative AI is skills-biased and follows a similar pattern from what we’ve seen in the past with new technology disruptions. Note that we’re focusing on the top and bottom tails of the distribution of contract values, because such groups (rather than median or mean) might be most susceptible to displacement and/or reinstatement effects, therefore of primary concern. We define high-value (HV) work as those with $1,000 or more earnings per contract. For the remaining contracts, we focus on a subset of work as low-value (LV) work ($251-500 earnings).
Figure 2 shows the impact of AI by work value, across groups on Upwork. As we discussed before, writing and translation work has experienced some reduction in earnings overall. However, if we look further into the effect of contract value, we see that the reduction is largely coming from the reduced earnings from low-value work. At the same time, for these two types, generative AI has induced substantial growth in high-value earnings – the effect for translation is as high as 7%. We believe the positive effect on translation high-value earning is driven by more posts and contracts created. In the tech solutions sector, the growth in HV earnings in data science and web development is also particularly noticeable, ranging from 6% to 9%. Within the business solutions sector, administrative support is the clear winner.
There are two takeaways from this analysis by work value. First, while we’re looking at a sample of all the contracts on the platform, it’s possible that the decline of LV work is more than made up for by the growth of HV work in the majority of the groups. In other words, except for select work groups, the equilibrium results for the Upwork freelance market overall seem to be net positive gains from generative AI. Second, if we assume that freelancers with high skills (or a high degree of skill complexity) tend to complete such HV work (and low-skill freelancers do LV work), we observe that the impact of generative AI may be biased against low-skill freelancers. This is an important result: In the current discussion of whether generative AI is skill-based, there exists limited evidence based on realized gains and actual work market transactions. We are one of the first to provide market-transaction-based evidence to illustrate this potentially skill-biased impact. Finally, additional internal Upwork analysis finds that independent talent engaged in AI-related work earn 40% more on the Upwork marketplace than their counterparts engaged in non-AI-related work. This suggests there may be additional overlap between high-skill work and AI-related work, which can further reinforce the earning potential of freelancers in this group.
Figure 2
Case study: 3D content work
To illustrate the impact of generative AI in more depth, we have conducted a case study of Engineering & Architecture work within the tech solutions sector. The reason is that we want to illustrate the potentially overlooked aspects of AI impact, compared with the examples of data science and writing contracts. This progress in generative AI has the potential to reshape work in traditional areas like design in manufacturing and architecture, which rely heavily on computer-aided design (CAD) objects, and newer sectors such as gaming and virtual reality, exemplified by NVIDIA's Omniverse.
Based on activities on the Upwork platform, we see that there is consistent growth of job posts and client spending in this category, with up to 12% of gross service value growth year over year in 2023 Q3, and over 11% in job posts during the same period. Moreover, applying the synthetic control method, we show a causal relationship between gen AI advancements and the growth in job posts and earnings per contract. More specifically, there is a significant increase in overall earnings because of AI, an average 11.5% increase. Additionally, as shown by Figure 3, the positive effect also applies to earning per contract. This indicates a positive impact on freelancer productivity and quality of work, due to the fact that we’re measuring the income for every unit of work produced. This suggests that gen AI is not just a facilitator of efficiency but also enhances the quality of output.
Figure 3 Effect of Generative AI on Freelancer Earning per Contract in EngineeringIn a traditional workflow to create 3D objects without generative AI, freelancers would spend extensive time and effort to design the topology, geometry, and textures of the objects. But with generative AI, they can do so through text prompts to train models and generate 3D content. For example, this blog by NVIDIA’s Omniverse team showcases how ChatGPT can interface with traditional 3D creation tools.
Thus, the positive trajectory of generative AI in 3D content generation we see is driven by several factors. AI significantly reduces job execution time, allowing for higher productivity. It facilitates the replication and scaling of 3D objects, leading to economies of scale. Moreover, freelancers can now concentrate more on the creative aspects of 3D content, as AI automates time-consuming and tedious tasks.
This shift has not led to a decrease in rates due to the replacement effect. In fact, this shift of workflow may create new tasks and work. We will likely see a new type of occupation in which technology and humanities disciplines converge. For instance, a freelancer trained in art history now has the tools to recreate a 3D rendering of Japan in the Edo period, without the need to conduct heavy coding. In other words, the reinstatement effect of AI will elevate the overall quality and value proposition of the work, and ultimately enable higher earning gains. This paradigm shift underscores generative AI's role in not just transforming work processes but also in creating new economic dynamics within the 3D content market. Fortunately, it seems many freelancers on Upwork are ready to reap the benefits: 3D-related skills, such as 3D modeling, rendering, and design, are listed among the top five skills of freelancer profiles as well as in job posts.
A dynamic interplay: task complexity, skills, and gen AI
Focusing on the Upwork marketplace for independent talent, we study the impact of generative AI by using the public release of ChatGPT as a natural experiment. The results suggest a dynamic interplay of replacement and reinstatement effects; we argue that this dynamic is influenced by task complexity, suggesting a skill-biased impact of gen AI. Analysis across Upwork's work sectors shows varied effects: growth in freelance earnings in tech solutions and business operations, but a mixed impact in the creative sector. Specifically, high-value work in data science and business operations see significant earnings growth, while creative contracts like writing and translation experience a decrease in earnings, particularly in lower-value tasks. Using the case study of 3D content creation, we show that generative AI can significantly enhance productivity and quality of work, leading to economic gains and a shift toward higher-value tasks, despite initial concerns of displacement.
Acemoglu and Restrepo (2019) argue that the slowdown of earning growth in the United States the past three decades can partly be explained by new technologies’ replacement effect overpowering the reinstatement effect. But with generative AI, we’re at a point of completely redefining what human tasks mean, and there may be ample opportunities to create new tasks and work. It's evident that while high-value types of work are being created, freelancers engaged in low-value tasks may face negative impact, possibly due to a lack of skills needed to capitalize on AI benefits. This situation underscores the necessity of supporting freelancers not only in elevating their marketability within their current domains but also in transitioning to other work categories.
To ensure as many people as possible benefit, there’s an imperative need to provide educational resources for them to gain the technical skills, and more importantly skills of adaptability to reinvent their work. This helps minimize the chance of missed opportunities by limiting skills mismatch between talent and new demands created by new technologies. Upwork has played a significant role here by linking freelancers to resources such as Upwork Academy’s AI Education Library and Education Marketplace, thereby equipping them with the necessary tools and knowledge to adapt and thrive in an AI-present job market. This approach can help bridge the gap between low- and high-value work opportunities, ensuring a more equitable distribution of the advantages brought about by generative AI.
Methodology
To estimate the causal impact of generative AI, we take a synthetic control approach in the spirit of Abadie, Diamond, and Hainmueller (2010). The synthetic control method allows us to construct a weighted combination of comparison units from available data to create a counterfactual scenario, simulating what would have happened in the absence of the intervention. We use this quasi-experimental method due to the infeasibility of conducting a controlled large-scale experiment. Additionally, we use Lasso regularization to credibly construct the donor pool that serves the basis of the counterfactuals and minimize the chance of overfitting the data.
Moreover, we supplement the analysis by scoring whether a sub-occupation is impacted or unaffected by generative AI. The scoring utilizes specific criteria: 1. Whether a certain share of job posts are tagged as AI contracts by the Upwork platform; 2. AI occupational exposure score, based on a study by Felten, Raj, and Seamans (2023), to tag these sub-occupations. We also use data smoothing techniques through three-month moving averages. We analyzed data collected on our platform from 2021 through Q3 2023. We specifically look at freelancer data across all 12 work categories on the platform for high-value contracts, defined as those with a contract of at least $1,000, and low-value contracts, consisting of those between $251 and under $500.
The main advantage of our approach is that it is a robust yet flexible way to identify the causal effects on not only the Upwork freelance market but also specific work categories. Additionally, we control for macroeconomic or aggregate shocks such as U.S. monetary policy in the pre-treatment period. However, we acknowledge the potential biases in identifying which sub-occupations are influenced by generative AI and the effects of external factors in the post-treatment period.
About the Upwork Research Institute
The Upwork Research Institute is committed to studying the fundamental shifts in the workforce and providing business leaders with the tools and insights they need to navigate the here and now while preparing their organization for the future. Using our proprietary platform data, global survey research, partnerships, and academic collaborations, we produce evidence-based insights to create the blueprint for the new way of work.
About Ted Liu
Dr. Ted Liu is Research Manager at Upwork, where he focuses on how work and skills evolve in relation to technological progress such as artificial intelligence. He received his PhD in economics from the University of California, Santa Cruz.
About Carina Deng
Carian Deng is the Lead Analyst in Strategic Analytics at Upwork, where she specializes in uncovering data insights through advanced statistical methodologies. She holds a Master's degree in Data Science from George Washington University.
About Kelly Monahan
Dr. Kelly Monahan is Managing Director of the Upwork Research Institute, leading our future of work research program. Her research has been recognized and published in both applied and academic journals, including MIT Sloan Management Review and the Journal of Strategic Management.
labor market
2024年02月23日
labor market
HR Predictions for 2024: The Global Search For Productivity2024年的HR预测强调了生产力和AI在商业和雇佣实践中的关键作用。这篇文章讨论了公司在动态的经济条件和不断变化的劳动力市场背景下，如何适应他们的人才管理和招聘策略。强调了员工赋权的增加，劳动力市场的变化，以及技能发展的重要性。文章还探讨了劳动力囤积、混合工作模式和员工激活等关键概念。此外，还涉及领导力挑战、薪酬公平、DEI计划，以及可能的四天工作周。
一起来看Josh Bersin 带来新得见解
For the last two decades I’ve written about HR predictions, but this year is different. I see a year of shattering paradigms, changing every role in business. Not only will AI change every company and every job, but companies will embark on a relentless search for productivity.
Think about where we have been. Following the 2008 financial crisis the world embarked on a zero-interest rate period of accelerating growth. Companies grew revenues, hired people, and watched their stock prices go up. Hiring continued at a fevered pace, leading to a record-breaking low unemployment rate of 3.5% at the end of 2019.
Along came the pandemic, and within six months everything ground to a halt. Unemployment shot up to 15% in April of 2020, companies sent people home, and we re-engineered our products, services, and economy to deal with remote work, hybrid work arrangements, and a focus on mental health.
Once the economy started up again (thanks to fiscal stimulus in the US), companies went back to the old cycle of hiring. But as interest rates rose and demand fell short we saw layoffs repeat, and over the last 18 months we’ve seen hiring, layoffs, and then hiring again to recover.
Why the seesaw effect?
CEOs and CFOs are operating in what we call the “Industrial Age” – hire to grow, then lay people off when things slow down.
Well today, as we enter 2024, all that is different. We have to “hoard our talent,” invest in productivity, and redevelop and redeploy people for growth.
We live in a world of 3.8% unemployment rate, labor shortages in almost every role, an increasingly empowered workforce, and a steady drumbeat of employee demands: demands for pay raises, flexibility, autonomy, and benefits. More than 20% of all US employees change jobs each year (2.3% per month), and almost half these changes are into new industries.
Why is this the “new normal?”
There are several reasons. First, as we discuss in our Global Workforce Intelligence research, industries are overlapping. Every company is a digital company; every company wants to build recurring revenue streams; and soon every company will run on AI. Careers that used to stay within an industry are morphing into “skills-based careers,” enabling people to jump around more easily than ever before.
Second, employees (particularly young ones) feel empowered to act as they wish. They may quietly quit, “work their wage,” or take time out to change careers. They see a long runway in their lives (people live much longer than they did in the 1970s and 1980s) so they don’t mind leaving your company to go elsewhere.
Third, the fertility rate continues to drop and labor shortages will increase. Japan, China, Germany, and the UK all have shrinking workforce populations. And in the next decade or so, most other developed economies will as well.
Fourth, labor unions are on the rise. Thanks to a new philosophy in Washington, we’ve seen labor activity at Google, Amazon, Starbucks, GM, Ford, Stellantis, Kaiser, Disney, Netflix, and others. While union participation is less than 11% of the US workforce, it’s much higher in Europe and this trend is up.
What does all this mean?
There are many implications.
First, companies will be even more focused on building a high-retention model for work (some call it “labor hoarding.”) This means improving pay equity, continuing hybrid work models, investing in human-centered leadership, and giving people opportunities for new careers inside the company. This is why talent marketplaces, skills-based development, and learning in the flow of work are so important.
Second, CEOs have to understand the needs, desires, and demands of workers. As the latest Edelman study shows, career growth now tops the list, along with the desire for empowerment, impact, and trust. A new theme we call “employee activation” is here: listening to the workforce and delegating decisions about their work to their managers, teams, and leaders.
Third, the traditional “hire to grow” model will not always work. In this post-industrial age we have to operate systemically, looking at internal development, job redesign, experience, and hiring together. This brings together the silo’d domains of recruiting, rewards and pay, learning & development, and org design. (Read our Systemic HR research for more.)
What does “business performance” really mean?
If you’re a CEO you want revenue growth, market share, profitability, and sustainability. If you can’t grow by hiring (and employees keep “activating” in odd ways), what choice do you have? It’s pretty simple: you automate and focus on productivity.
Why do I see this as the big topic in 2024? For three big reasons.
First, CEOs care about it.
The 2024 PwC CEO survey found that CEO’s believe 40% of the work in their company is wasted productivity.
As shocking as that sounds, it rings true to me: too many emails, too many meetings, messy hiring process, bureaucratic performance management, and more. (HR owns some of these problems.)
Second, AI enables it.
AI is designed to improve white-collar productivity. (Most automation in the past helped blue or gray collar workers.) Generative AI lets us find information more quickly, understand trends and outliers, train ourselves and learn, and clean up the mess of documents, workflows, portals, and back office compliance and administration systems we carry around like burdens.
Third, we’re going to need it.
How will you grow when it’s so hard to find people? Time to hire went up by almost 20% last year and the job market is getting even tougher. Can you compete with Google or OpenAI for tech skills?
Internal development, retooling, and automation projects are the answer. And with Generative AI, the opportunities are everywhere.
What does all this mean for HR?
Well as I describe in the HR Predictions, we have a lot of issues to address.
We have to accelerate our shift to a dynamic job and organization structure. We have to get focused and pragmatic about skills. We have to rethink “employee experience” and deal with what we call “employee activation.” And we are going to have to modernize our HR Tech, our recruiting, and our L&D systems to leverage AI and make these systems more useful.
Our HR teams will be AI-powered too. As our Galileo™ customers already tell us, a well-architected “expert assistant” can revolutionize how HR people work. We can become “full-stack” HR professionals, find data about our teams in seconds instead of weeks, and share HR, leadership, and management practices with line leaders in seconds. (Galileo is being used as a management coach in some of the world’s largest companies.)
There are some other changes as well. As the company gets focused on “growth through productivity,” we have to think about the 4-day week, how we institutionalize hybrid work, and how we connect and support remote workers in a far more effective way. We have to refocus on leadership development, spend more time and money on first line managers, and continue to invest in culture and inclusion. We have to simplify and rethink performance management, and we have to solve the vexing problem of pay-equity.
And there’s more.
DEI programs have to get embedded in the business (the days of the HR DEI Police are over). We have to clean up our employee data so our AI and talent intelligence systems are accurate and trustworthy. And we have to shift our thinking from “supporting the business” to “being a valued consultant” and productizing our HR offerings, as our Systemic HR research points out.
All this is detailed in our new 40-page report “HR Predictions for 2024,” launching this week, including a series of Action Plans to help you think through all these issues.
And let me remind you of a big idea. Productivity is why HR departments exist.
Everything we do, from hiring to coaching to development to org design, is only successful if it helps the company grow. As experts in turnover, engagement, skills, and leadership, we in HR have make people and the organization productive every day. 2024 is a year to focus on this higher mission.
One final thing: taking care of yourself.
The report has 15 detailed predictions, each with a series of action steps to consider. The last one is really for you: focus on the skills and leadership of HR. We, as stewards of the people-processes, have to focus on our own capabilities. 2024 will be a year to grow, learn, and work as a team. If we deal with these 15 issues well, we’ll help our companies thrive in the year ahead.
Details on the Josh Bersin Predictions
The predictions study is our most widely-read report each year. It includes a detailed summary of all our research and discusses fifteen essential issues for CEOs, CHROs, and HR professionals. It will be available in the following forms:
Webinar and launch on January 24: Register Here (replays will be available)
Infographic with details: Available on January 24.
Microlearning course on Predictions: Available on January 24.
Detailed Report and Action Guide: Available to Corporate Members and Josh Bersin Academy Members (JBA). (Note you can join the JBA for $495 per year and that includes our entire academy of tools, resources, certificate courses, and SuperClasses in HR.)
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2024年01月19日
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沃尔玛将商店经理的平均薪资提高至 128,000 美元In a strategic move to attract and retain employees amid a tight labor market, Walmart, the world's largest retailer, has announced a significant salary increase for store managers from $117,000 to $128,000. Alongside the 9% raise, Walmart is revamping its managers' bonus program to emphasize store profits more prominently in annual bonus calculations. Cedric Clark, Executive Vice President of Walmart U.S. Store Operations, highlighted that bonuses could now reach up to 200% of the base salary if targets are met. This change comes after years without salary adjustments for managers and reflects Walmart's efforts to navigate the challenges of retaining staff in an evolving retail landscape.
沃尔玛公司表示，由于这家全球最大的零售商希望在紧张的劳动力环境中吸引和留住员工，商店经理的平均工资将从 117,000 美元上涨至 128,000 美元。
除了 9% 的加薪外，该公司还表示正在“重新设计”经理的奖金计划。沃尔玛在其网站上表示，商店利润将在计算年度奖金中发挥更大的作用。沃尔玛美国门店运营执行副总裁塞德里克·克拉克 (Cedric Clark)在帖子中表示，如果所有目标均实现，奖金现在可能高达经理基本工资的 200% 。
公司发言人表示，十多年来，沃尔玛没有对商店经理的薪酬进行任何调整。此前，商店销售额是决定奖金的主要因素，经理最多可以获得基本工资150%的奖金。
随着员工越来越多地面临不守规矩的顾客以及商店盗窃事件的增加，零售商一直在努力保留员工。
尽管近年来，随着员工竞争加剧，工资大幅上涨，但有迹象表明，雇主的影响力正在回归，至少对于某些职位而言是这样。去年，作为调整工资结构的一部分，沃尔玛降低了一些新员工的起薪。较低的税率影响了在线订单拣货员、货架库存员和其他新员工。
据该公司称，约 75% 的商店经理在沃尔玛开始时都是小时工。
Anita Lettink Challenges HR Norms: Adapting to the Unpredictable Work Landscape of 2024ANITA LETTINK：Why I'm not writing 2024 HR trends
Anita Lettink, in her newsletter, discusses why she is not writing the 2024 HR trends. She emphasizes the importance of a dynamic, continuous strategy over annual predictions in HR. The article reflects on the evolving nature of work and the need for a fluid, adaptable approach. Lettink argues that understanding and navigating HR challenges require responsiveness to rapid changes in technology, economics, and workforce dynamics. She introduces the 2024 HR challenge, encouraging HR professionals to maximize the use of their HR solutions and focus on making incremental changes to better support their workforce.
推荐给大家；
Hey future of work friends,
I probably find you during budgeting and planning time. For me, it’s the end of conference season. I did my final keynote on the New Employee Experience at Indeed FutureWorks last week. And now I am back home, and will use December to read everything I bookmarked to surprise you with new keynotes and articles next year. I’ll also write my annual HR Tech Startup report.
And if you’d like an in-company webinar on what to expect from AI in HR or how to prepare for Equal Pay please reach out - I’ve got you covered!
Thinking about the Future of Work is important. And yes, you’d already assumed I would say that. I've spent years analyzing trends at the intersection of economics, business, technology, and human resources. Each year, I've distilled these insights into trend articles, aiming to forecast the year ahead. However, I've realized that our rapidly evolving world demands a different approach. In this newsletter, I'll share why I've moved away from annual trend predictions and why we need a more dynamic, continuous strategy in understanding and navigating HR challenges. I'll explore how embracing a fluid, responsive stance can better equip us to handle HR (tech) developments.
Why I am not writing 2024 HR trends
I've always been deeply invested in keeping a finger on the pulse of our industry. For years, it was a tradition of mine to sit down at the end of each year and write an article on emerging trends in Human Resources, based on my analysis of developments in economics, business, technology, and HR. I wrote them to reflect on the past year and help you - and me - prepare for the next.
I stopped this tradition. And if you wonder why, it's not for a lack of trends or changes in the industry—far from it. The HR landscape is as dynamic as ever, perhaps even more so. But I've realized that these annual trend articles, while insightful, may not be as beneficial as I once thought. Sure, they give a nice overview of what’s happening and what might happen, but you can’t run after every trend. And most years there were way too many of them.
The world of work is evolving at an unprecedented pace, and the tools and strategies that were groundbreaking a year ago might now be outdated. In this fast-paced environment, I believe that what we need isn't annual predictions but a continuous, adaptable approach to understanding and navigating HR challenges. When you want to provide a stable environment for employees and your company, thoughtful, strategic adjustments might be much more impactful.
So, instead of offering predictions, I'm taking a different path. I want to share with you the reasons behind this shift in my thinking and why I believe it's crucial for all of us in HR to adopt a more fluid, responsive stance towards industry trends.
Embracing a fluid approach
This change was sparked by several realizations. Firstly, the very nature of HR is fundamentally about people, and people are inherently unpredictable. People also like stability. And while trends can give us a broad outline, they can't capture the nuanced, often sudden shifts in employee needs, workplace dynamics, and organizational cultures. We all remember the start of the pandemic, when we put everything aside to make sure that employees could work safely, and where possible, from home. And while we might think this was a once-in-a-lifetime occurrence, we also know the world has become more unpredictable, and we should be ready to deal with similar sudden events.
And that means we should think more in terms of how we can offer a stable base that can handle these sudden shifts. That also means we should not be so quick in dividing work in “the past” and “the future”. While some people argue you should only look at the future of work, I believe we should take a much more nuanced approach.
As example, the picture above: it’s often used to show the past and the future of work. In my thinking, both sides represent the future. It’s not either/or, it’s and/and. And when I speak about the New Employee Experience, I use it to encourage HR professionals to cast a wide net: how can you offer all work options, so you appeal to a larger section of the workforce? It’s not about discarding the past and looking at the future. It’s embracing both where you can. Some people like the 9-5 day, working from an office. Some people find profit more important than purpose. It’s about offering a wide range of choices, to attract and retain people in a time when the labor market is tight. That’s especially important when you work in the Global North, and a next major shift is upon us: a shrinking workforce due to demographics in combination with the lack of skilled workers.
How useful are predictions anyway?
Secondly, I noticed a pattern over the years. Many of the trends I predicted would either rapidly evolve or be overtaken by entirely new developments before the year was out. Just look at Generative AI: at the end of last year, no one predicted that this would be the main topic of 2023. This rapid (r)evolution made me question the usefulness of annual predictions: why do we write them only at the end of the year? In a world where change is the only constant, static yearly forecasts seem almost counterintuitive. How can we even begin to predict what is coming, when recent events put everything we know upside down?
And lastly, I also started to wonder if focusing too heavily on future trends might pull us away from the present. When we always look ahead, we might miss crucial opportunities to address current issues effectively or fail to build on the strengths we already have. It can sometimes cause us to miss out on addressing the immediate needs and challenges facing our employees and organizations.
By constantly chasing what might be ahead or new, we risk not fully leveraging the strengths and successes we currently possess. It's vital to strike a balance between preparing for future changes and optimizing our current practices. This way, we can ensure that our efforts are not only geared towards what the 'future of work' might look like but are enhancing today’s HR strengths, thereby creating a more holistic and effective HR strategy.
2024 Challenge
And to illustrate the above with a practical example, let me ask you this: what percentage of your HR solution do you actually use? I am not asking for an exact number, just an estimated guess. When you look at its current functionality, do you use all of it? Half? Maybe even less?
When you close a contract for an HR cloud solution, the vendor will not only maintain the solution in its current state, but also improve it over time. And the fee you pay covers all those new features and functionalities. That means you get more bang for your buck. But if you don’t activate any of these features, then the vendor is wasting development capacity, and you are paying for something you will never see. Would you consider that good use?
And the problem isn't just the use; you will also miss out on the potential to support your workers better and change your workplace. Every unused feature in your HR solution is a lost chance to improve employee engagement, streamline processes, or uncover people insights.
So, here’s my 2024 HR challenge for you:
1. Guess: How much of your HR solution do you use today?
2. Pick one unused feature in your HR solution, explore it, and make it available!
Try to make a gradual change every month. Repeat that during the first six months of 2024 and then evaluate your success or learn from your mistakes! And don’t forget to tag me with the results! Instead of focusing on yet another 2024 HR trend, let’s make sure that we first use our HR solution to the fullest, one feature at a time. I think this will be more helpful to your organization than you might think.
Let’s continue the conversation
I don’t want to leave you with the impression that looking forward isn't important. On the contrary, it's crucial. If only for the reason that what we build today will affect our future workforce the most. But we should do it with the understanding that HR is less about predicting the future and more about creating it through proactive, ongoing engagement with our workforce, our company, and the world around us. To maybe not take giant leaps but make incremental changes that benefit the people we work with most. People are tired of constant change. However, we can draw inspiration from social media tools - by implementing small, gradual improvements, we can consistently enhance the experience, allowing people to smoothly adapt to these changes over time.
This shift is not just about how we talk about HR trends; it's about how we do HR. It's a move towards a more dynamic, responsive, and collaborative approach that recognizes the complexity and fluidity of our work. It's about creating a living dialogue that evolves with our ever-changing environment.
We must talk about the future. But it shouldn’t be confined to the end of the year. There is no reason for such a hard cut. I look forward to engaging with you, in continuous conversations about what we're seeing, doing, and expecting in real-time. This approach, I believe, will not only keep us more connected to the immediate needs of our organizations but also better prepared to adapt to whatever the future holds.
While I don’t write HR trend articles anymore, my commitment to helping you understand and make sense of the future of work is as strong as ever. I will keep you posted on the latest developments as I see them. I will continue to write this newsletter about my observations on how we can improve work with the help of technology, especially new tech.
Good luck with planning the year ahead. And let me know if you would have preferred a list of 2024 HR trends,
Have a great day, Anita
What’s next for compensation?
Pete Tiliakos, Anke Mogannam and I participated in an online #WDAYChats. We shared insights and POV’s on modern payroll operations and how payroll leaders can help their organizations minimize cost and accelerate innovation.
Decusoft asked me how companies can prepare for pay transparency and equal pay. You can find my answers here.
Indeed asked people if money really makes them happy. Find the surprising answers, an interview with yours tryly and more compensation charts in this insightful Dutch report: De toekomst van compensatie.
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