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    滴滴出行选用NICE,以提供基于实时 AI 的个性化服务 NICE has partnered with DiDi Global to enhance customer and employee experiences through its cloud-based Workforce Management (WFM) and Employee Engagement Manager (EEM) solutions. This collaboration aims to streamline DiDi's global contact center operations, improving operational efficiency and customer satisfaction with AI-driven forecasting and scheduling. The implementation of NICE's solutions facilitates real-time management and self-scheduling for agents, boosting employee engagement and operational efficiency. DiDi's choice of NICE highlights the importance of advanced, flexible technology in supporting the dynamic needs of modern, app-based transportation services. 领先的移动出行平台通过利用 NICE 的客户体验 AI 技术,使其员工能够提供轻松且高效的客户服务体验 新泽西州霍博肯-NICE (纳斯达克: NICE) 今日宣布,滴滴出行已经选用了 NICE 劳动力管理 (WFM) 和员工参与管理 (EEM) 作为其云端创新技术的一部分。滴滴现在可以全面预测、规划和管理其全球客户联系中心的运作;同时提升运营效率和员工的参与度,并确保客服代表能够在首次通话中解决问题。Betta作为全球最大的 WFM 客户群之一的支持者,在实施过程中与 NICE 价值实现服务携手合作,负责执行集成,并在多国提供咨询、培训和支持服务。 滴滴出行寻求一种能够满足其核心业务、功能及技术需求,并能够随公司成长而扩展的劳动力管理解决方案。NICE WFM 结合了 AI 技术与灵活性,能够满足跨多个大洲、具有特定区域特色的运营需求,这不仅成本效益高,而且精确度高,确保维持最佳的服务水平。通过精准预测,确保在合适的时间有合适技能的代理人,从而大幅提升客户满意度。 通过引入 NICE EEM,可以实时解决人员配置需求,使得客服代理能够自我调节工作时间表,从而增强员工参与度和工作满意度。此外,利用智能日内自动调整功能,能够主动地进行调整,预防问题的发生。 滴滴出行国际客户体验执行总监 Caio Poli 表示:“基于多个考量因素,NICE 显然是我们的首选。我们寻找的是一个顶尖的云端劳动力管理解决方案,能够使我们的全球运营在保证运营效率和员工参与度的同时,提供卓越的客户体验。NICE 的智能日内自动化功能给我们留下了深刻印象,我们的选择是基于 AI 驱动的策略以及云技术的速度和灵活性。” NICE 美洲总裁 Yaron Hertz 表示:“随着滴滴持续全球扩张,NICE 很高兴有机会为这家数字时代最具创新和活力的应用型运输公司之一提供服务。我们相信,通过采用 NICE 的 AI 驱动预测和机器学习来进行最适合的调度安排,对于联系中心和员工而言,这将有助于推动滴滴的未来发展。” 关于滴滴出行公司 滴滴出行公司是一个领先的移动技术平台,它在亚太地区、拉丁美洲及其他全球市场提供一系列基于应用的服务,包括网约车、叫车服务、代驾以及其他共享出行方式,还涵盖某些能源和车辆服务、食品配送和城市内部货运服务。滴滴为车主、司机和配送伙伴提供灵活的工作和收入机会,致力于与政策制定者、出租车行业、汽车行业及社区合作,利用 AI 技术和本地化智能交通创新解决全球的交通、环境和就业挑战。滴滴力图为未来城市构建一个安全、包容和可持续的交通与本地服务生态系统,以创造更好的生活体验和更大的社会价值。更多信息,请访问:www.didiglobal.com 关于 NICE 借助 NICE (纳斯达克: NICE),全球各地不同规模的组织现在可以更容易地创造卓越的客户体验,同时满足关键的业务指标。作为世界领先的云原生客户体验平台 CXone 的提供者,NICE 是 AI 驱动自助服务和代理辅助客户体验软件领域的全球领导者,服务范围超出了传统的联系中心。超过 25,000 个组织在超过 150 个国家,包括 85 家以上的财富 100 强公司,都选择与 NICE 合作,以改造并提升每一次客户互动。www.nice.com 商标说明:NICE 和 NICE 标志是 NICE Ltd. 的商标或注册商标。所有其他标志属于它们各自的所有者。NICE 商标的完整列表,请访问:www.nice.com/nice-trademarks。
    资讯
    2024年02月27日
  • 资讯
    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.
    资讯
    2024年02月23日
  • 资讯
    Google Workspace推出Gemini:开启AI增强生产力的新篇章 Google Workspace推出了为各种规模的组织设计的Gemini Business计划,以及一个全新的、具有企业级数据保护的独立Gemini聊天体验。Gemini Business计划每用户每月20美元起,提供包括文档和邮件中的写作帮助、表格中的增强智能填充和幻灯片中的图像生成等功能。Gemini Enterprise计划则以每用户每月30美元提供更多使用量和额外的AI驱动会会议的AI功能,如闭幕字幕的翻译和会议记录。 此外,Gemini还提供了一个独立的企业级聊天体验,通过使用最大且最有能力的1.0 Ultra模型,确保了企业级的数据保护,不用于广告目的或改进生成机器学习技术,不被人工审查或与其他用户或组织共享。这些更新旨在提高工作效率和团队合作,同时保障用户数据的安全和隐私。 2024年2月21日 — Google Workspace引入了Gemini Business和Gemini Enterprise,这标志着在其套件内整合人工智能的重大进步。由Aparna Pappu(副总裁兼总经理)领衔的这一举措旨在满足组织多样化的需求,用AI增强日常操作。 向前迈出的革命性一步 本月,Google宣布Duet AI转变为Google Workspace的Gemini,提供了对先进AI模型的访问。此次升级将Gemini集成到广泛使用的Workspace应用中,旨在简化从个人事件规划到复杂商业战略制定等任务。 用AI赋能企业 以每用户每月20美元(需年度承诺)的竞争价格推出的Gemini Business,旨在为所有规模的组织普及生成式AI技术的使用。它提供了如Docs和Gmail中的“帮我写”,Sheets中的“增强智能填充”以及Slides中的图像生成等功能,目的是提高生产力和创造力。 以每用户每月30美元的价格,Gemini Enterprise扩展了这些功能,并增加了AI驱动会议的附加特性,包括实时翻译100多种语言以及即将推出的会议记录功能。现有的Duet AI客户将自动过渡到这个增强计划。 交互的新维度 一个突出的特点是与Gemini的新独立聊天体验,利用1.0 Ultra模型进行更深入、更有洞察力的互动。这个平台承诺提供企业级数据保护,确保通信的隐私和安全。 展望未来 Google Workspace不仅在增强当前的商业和企业产品,还在探索扩展到教育领域。这一举措反映了Google利用AI提高各类用户群体的效率和创新的承诺。 Gemini for Workspace代表了企业、教育机构和个人利用AI实现更大生产力和创造力的关键发展。随着Google Workspace的持续演进,Gemini的整合预示着一个技术和人类智慧无缝融合的未来。
    资讯
    2024年02月21日
  • 资讯
    2024年未来全球人力资源趋势 本博客重点介绍了 2024 年新兴的未来全球人力资源趋势。探索人力资源专业人士和企业在 2024 年保持竞争力所需采取的最具影响力的发展和战略。  人力资源世界正在经历一场巨大的变革。它是由快速发展的技术、不断变化的劳动力人口结构以及对员工福祉的重新重视所推动的。未来的工作是重塑组织吸引、管理和留住人才的方式。  这些人力资源趋势植根于创新,并受到对现代劳动力需求和愿望的更深入理解的推动,将在未来几年重新定义人力资源的角色。人力资源 (HR) 专业人员有一些令人兴奋且重要的事情需要学习和适应。     混合工作模式——工作的演变 近年来,混合工作模式已成为一个流行词。远程和混合工作的日益普及正在重新定义企业的运营方式以及员工如何履行其专业职责。  众所周知,疫情导致远程工作大幅增加。   混合工作模式是雇主期待的新解决方案。它提供的灵活性允许个人定制他们的工作时间表,以更好地适应他们的个人生活。  然而,在混合工作场所中,人力资源部的主要重点是制定政策和实践,确保员工在与同事保持联系的同时实现健康的工作与生活平衡。明确的指导方针、开放的沟通和信任的文化对于有效管理这种平衡至关重要。 混合工作模式预计将成为现代工作场所的关键部分,提供灵活性,改善工作与生活的平衡,并为人才招聘提供有吸引力的好处。尽管存在挑战,但技术和人力资源实践的快速发展将继续支持混合工作场所和远程工作的未来。人力资源专业人士和企业必须拥抱这种混合远程工作的趋势,并调整策略,在这个新的工作时代为员工创造一个既高效又充实的工作环境。 工作场所的多元化、公平性和包容性 工作场所的多元化、公平性和包容性 (DEI) 不仅仅是一个流行词,而且是 2024 年继续流行的人力资源管理新兴趋势之一。  大多数组织已经在努力建立一个多元化和包容性的工作场所,这必将帮助他们成长和成功。工作场所的包容性和多样性不仅仅是一项道德和伦理举措,它正在成为吸引、留住和聘用顶尖人才的战略举措。  在来年鼓励工作场所的多样性、公平性和包容性时,可以考虑一些建议:  确保领导者为整个组织定下正确的基调  明确制定和传达“工作场所多元化”政策,并向所有员工提供指导方针  在招聘启事、多样化的面试小组以及对代表性不足的群体的外展活动中使用公正的语言。  通过向所有员工提供多元化和包容性培训来提高意识  建立包容性的工作文化,让所有声音都得到倾听和重视  确保无论性别、种族或背景如何,薪酬和机会均等  庆祝工作场所的文化和个人行为差异  衡量 DEI 为建立工作场所多样性、公平性和包容性而采取的举措的进展情况,并在需要时实施新战略 为未来做好准备的劳动力的再培训和技能提升 员工成长和发展日益受到重视。对于任何企业的成功,关注员工的持续学习和发展非常重要。  计划投资于员工培训、导师计划以及员工技能提升和再培训机会可能是企业的最佳选择。主动为员工提供咨询并为他们的职业发展制定明确的道路至关重要。这确保他们感到受到重视并能够在组织内看到未来。  持续学习、员工技能提升和再培训将有助于员工的内部流动。这也将有助于吸引和留住员工。  另一方面,就业市场也在不断变化。为了跟上工作场所不断变化的需求,员工必须专注于技能提升和再培训。他们将需要发展新技能,获得工作领域的专业知识,并根据新的行业趋势更新知识。 为未来做好准备的劳动力的再培训和技能提升将是来年未来人力资源的主要趋势之一。它将盛行并使员工和组织取得成功。  关注员工心理健康和工作场所福祉 快乐、健康和敬业的员工队伍不仅生产力高,而且更有可能对公司保持忠诚。随着压力和抑郁的专业人士比例不断增加,公司必须优先考虑员工的身体、心理和情感健康。  2024 年最新的人力资源趋势之一是关注员工的心理健康和福祉。员工援助计划和心理健康日将很快成为常态。事实上,雇主已经开始进行公开讨论并提供咨询服务。  通过提供灵活和支持性的工作环境并让员工保持健康的工作与生活平衡,可以照顾员工的福祉。这包括提供远程工作选项、灵活的日程安排以及为团队成员提供善解人意的经理。  未来的工作将观察到雇主将重点放在旨在为员工提供良好身体健康、营养和锻炼的健康计划上。有一些组织提供健身房会员资格、瑜伽课程以及心理和身体健康应用程序,以鼓励健康的生活方式。为了衡量这些努力的影响,采用数据驱动的工具和调查来评估员工的福祉和满意度。这将持续成为 2024 年及以后最突出的人力资源趋势之一。  用于数据驱动决策的人力资源分析工具  随着技术的进步,组织正在最大限度地利用人力资源分析来进行数据驱动的决策。  人力资源分析涉及收集和分析与员工绩效、敬业度和整体福祉相关的数据。这有助于获得洞察力,从而推动各个人力资源职能部门做出更好的决策。  使用人力资源分析工具和数据驱动的人力资源是当前人力资源趋势之一,并将在 2024 年继续占据主导地位。利用数据和人力资源分析力量的组织必将拥有竞争优势。  此外,人员分析将使人力资源专业人员能够:  识别员工相关趋势 衡量现有策略的有效性 做出数据驱动的决策,从而改善员工体验和组织成功 这些先进的人力资源数据分析工具将帮助雇主更好地了解员工流动率的关键驱动因素、培训和发展计划的影响、招聘策略的有效性等等。  积极的职场文化,共创美好明天  工作场所及其文化直接影响员工体验。因此,创造积极的职场文化当然需要一种具有前瞻性的方法,对于进入劳动力市场的新一代来说更是如此。 积极和包容的工作环境可以提高员工保留率、提高生产力和公司发展。因此,创造一个积极的工作环境,让员工感到受到重视、尊重和激励非常重要。  在未来的一年里,企业将需要塑造自己的工作文化,以体现多元化和包容性的价值观,并提供卓越的员工体验(满足员工的职业成长和个人福祉)。  简而言之,通过关注“工作文化”,人力资源部门将改变公司吸引、保留和聘用公司发展和成功所必需的顶尖人才的方式。  人工智能和人力资源流程自动化——2024 年全球热门未来人力资源趋势之一  利用人工智能 (AI) 进行人力资源自动化正在改变人力资源部门的运作方式。人工智能对人力资源的主要好处是它能够简化各种人力资源流程,从而提高效率和整体效益。 预计到 2024 年,人工智能和人力资源流程自动化将实现强大的结合。人工智能将深刻影响各种人力资源流程,从招聘和人才获取到绩效管理和员工敬业度。  基于人工智能的算法现在在简历筛选和候选人入围中发挥着至关重要的作用。这大大减少了招聘过程中花费的时间和精力。此外,聊天机器人和虚拟助理对于解决候选人的疑问并帮助他们完成申请流程至关重要。他们的主要目标是提高效率并提供用户友好的体验。  通过人工智能实现各种人力资源职能的自动化还简化了日常管理任务,例如工资单、福利管理和休假审批。提高准确性、减少管理开销和快速响应时间是其中一些好处。  可以说人工智能不会取代人力资源工作,但它肯定会让人力资源专业人员在塑造未来工作方面变得更具战略性。 零工工人,混合劳动力的新方面  近年来,零工经济已成为不断发展的人力资源格局的一部分。零工工人是指那些作为独立承包商、自由职业者或顾问工作的人。  如今,他们日益成为劳动力的重要组成部分。  专家预测,来年,雇主将不得不寻找方法来容纳零工劳动力。由于越来越多的人选择独立工作,而不是全职工作,远程零工工作将成为 2024 年人力资源管理的流行趋势之一。  为了保持积极主动,雇主必须制定有效管理零工工人的策略,认识到他们在灵活性、专业知识和成本效率方面带来的价值。人力资源专业人士还应优先创建一个欢迎全职员工和零工员工的多元化工作场所。需要实施灵活的工作场所政策和人力资源技术解决方案,以满足各种就业安排。  零工经济相信将成为 2024 年最重要的人力资源趋势之一,并将继续增长。  基于云的人力资源系统——对于成长型企业来说不是奢侈品而是必需品  2024 年人力资源的主要趋势之一是越来越多地采用云人力资源系统。 快速发展的技术不断重塑工作场所。人力资源技术趋势关注组织如何利用技术将其人力资源流程和数据管理转移到云端。人力资源专业人员正在使用云人力资源系统来提高灵活性和效率,并改变他们处理人力资源职能的方式。  云人力资源系统(例如Empxtrack)使人力资源专业人员能够安全地访问、更新和分析员工数据,即使他们在远程工作或在旅途中也是如此。  Empxtrack 是领先的人力资源管理系统之一,它简化了各种人力资源操作,包括薪资、福利管理、招聘、绩效管理等。该软件以其众多的配置选项以及出色的定制和集成功能而闻名,从而映射到每个客户的独特需求要求。云人力资源软件减少了管理工作量,确保数据安全,并让人力资源部门腾出时间专注于战略业务目标。  人力资源管理系统的重要性在未来几年只会增长。每个致力于打造高效、敬业和快乐员工队伍的企业都将在 2024 年实施并继续使用人力资源管理系统。  员工体验——2024 年未来全球人力资源趋势之一  2024年,“员工体验”将成为重点关注点。员工体验,通常缩写为 EX,是指员工在公司工作时的感受和经历。它的重点是让员工的工作场所变得更加愉快、有意义和高效。  这一趋势表明,快乐且敬业的员工更有可能留在公司并提高工作效率。这反过来对员工和组织都有好处。  来年,公司将投资各种举措来改善员工体验。其中一些举措包括:  了解员工的独特需求和偏好。这包括灵活的工作安排、创造舒适的物理工作空间等等。  提供职业发展机会。最好的方法是投资于培训、指导计划和技能提升机会。  关注工作场所员工的福祉。公司将提供咨询服务、灵活的时间表,并鼓励工作与生活的平衡。  促进工作场所的开放式沟通。创建一个让员工公开讨论他们的需求和挑战的工作场所。  定期提供反馈。为员工提供建设性的反馈和正确的指导。 员工体验不仅仅是一种趋势,而且将成为 2024 年人力资源部门的首要任务。 最后的想法  人力资源管理的未来趋势让我们对未来有了令人兴奋的看法,未来工作将更加灵活、包容和数据驱动。  成功当然取决于创新、技术以及让员工感到受到重视的工作场所。因此,组织需要拥抱这些人力资源技术趋势,才能走在最前沿并妥善管理员工队伍。  了解员工的期望并正确使用技术来满足他们的需求至关重要。遵循 2024 年未来全球人力资源趋势可能会在未来几年改变人力资源部门的游戏规则。 
    资讯
    2024年02月18日
  • 资讯
    在加州的雇主必须在2月14之前向加州工人提供竞业禁止信息披露 今年生效的两项州法律使加州工人的竞业禁止制度无效。 加州雇员雇主必须向雇员发送书面通知,声明根据新法律,竞业禁止条款和协议无效的最后期限即将到来。  议会法案 1076于 2023 年 10 月 13 日签署成为法律,要求公司在 2 月 14 日星期三之前向加利福尼亚州受非竞争条款约束的现任雇员和前雇员(2022 年 1 月 1 日后雇用)发送通知除非属于法定例外情况,否则这些协议无效。 根据 AB 1076,员工必须收到有关其最后已知地址和电子邮件地址变更的个性化通知。 White and Case 律师事务所表示,根据《反不正当竞争法》 ,违反该法案被视为不正当竞争行为,每次违规将被处以 2,500 美元的罚款。  参议院第 699 号法案于2023 年 9 月 1 日签署成为法律,“无论合同何时何地签署”,竞业禁止均无效,这使得该法律适用于在加州雇用工人的金州以外的雇主。  管理方公司Ogletree Deakins的律师在 2023 年 10 月 18 日的博客文章中写道:“AB 1076 和 SB 699 共同强调了加州对竞业禁止协议的不信任。 ” 为了遵守规定,律师建议雇主:对与现有员工以及 2022 年 1 月 1 日之后聘用的前员工的雇佣协议进行审核,看看是否包含任何竞业禁止条款;修改与现有工人的协议,其中包含可能无效的非竞争条款;并向受临近截止日期影响的员工发送个性化的书面通知。  这两项法案均于 2024 年 1 月 1 日生效。
    资讯
    2024年02月13日
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    Free immersive online training available for California caregivers 加州的护理工作者和家庭照顾者现可通过Front Porch与Embodied Labs合作开发的免费沉浸式在线培训课程,从所照顾人的视角看世界。该培训平台获奖无数,旨在通过第一人称视角体验,包括临终对话、护理转换、阿尔茨海默病、黄斑变性等多种经历,让正式和非正式的护理工作者能够体验并理解他人的视角和条件,这种独特的理解方式是传统培训工具无法提供的。Front Porch承诺将Embodied Labs程序免费提供给500名直接护理工作者和5000名家庭及朋友护理者,通过沉浸式体验,促进更加人性化的护理服务。 Front Porch Center for Innovation and Wellbeing partners with Embodied Labs to provide direct care workers, friends and family caregivers with cutting edge technology GLENDALE, Calif., Feb. 12, 2024 California caregivers can see the world through the eyes of the people they care for through a free immersive online training developed by Embodied Labs, in partnership with Front Porch and the Front Porch Center for Innovation and Wellbeing (FPCIW). The award-winning caregiver training platform is available for paid care workers, as well as for family or friend caregivers of older adults in California. The online program gives users a first-person perspective, allowing viewers to embody a variety of experiences including end-of-life conversations, transitions of care, Alzheimer's disease, macular degeneration and more. FPCIW is partnering as a Center of Excellence with Embodied Labs, a CalGrows Innovation Fund Award Winner, to offer free training to direct care workers and friends/family caregivers in California. "Front Porch is committed to sharing the Embodied Labs program for free to 500 direct care workers and 5,000 family and friend caregivers throughout California as well as to its community caregiver staff, residents and their loved ones," says Davis Park, vice president of FPCIW. "Through immersive experiences, formal and informal caregivers can embody the perspectives and conditions of other people, gaining a unique understanding not found in traditional training tools." Direct care workers, including home care aides, care coordinators or care managers, dementia care specialists, non-IHSS affiliated personal care assistants, activities coordinators, transportation providers, community health workers, and certified nursing assistants, can experience a VR or a desktop computer web-immersive experience. Friends and family caregivers can access short videos on their computers that allow participants to experience a 360-view from the perspective of an adult needing care. All content is available in both English and Spanish. More information on the program, including links to register, is available at the Center's website. "Embodied Labs is using the power of VR and immersive storytelling to help caregivers, family members, staff, and students see the world through the eyes of the people they care for and care about," said Kari Olson, president of FPCIW. "We are thrilled to expand access to this innovative training platform particularly because of the dynamic way it can bring people together and improve lives." Over 30 million Americans provided unpaid caregiving to older adults in the past year, according to the Family Caregiver Alliance. "Embodied Labs is positioned to support these heroes by providing caregiver training and tools that build empathy and understanding," says Park. "Our vision is to offer a deeper understanding of the perspectives and health conditions lived by others, through our shared immersive training experiences," says Carrie Shaw, founder and CEO of Embodied Labs. "By expanding our technology offering through our online platform, we can reach more people, and further build that bridge to understanding more effectively and empowering more humanistic care." About the Front Porch Center for Innovation and Wellbeing The Front Porch Center for Innovation and Wellbeing (FPCIW) is part of Front Porch, a dynamic not-for-profit organization, dedicated to empowering individuals to live connected and fulfilled lives through community and innovation. FPCIW pilots innovative solutions to solve real-world problems and meet the needs of older adults in collaboration with innovative partner organizations. Learn more at https://fpciw.org/. About Embodied Labs Headquartered in Los Angeles, California, Embodied Labs is the leader in immersive training for healthier aging. In use by a range of organizations in senior living, home care, government, academia and corporations, the training labs include: The Frank Lab (social isolation); The Beatriz Lab (Alzheimer's Disease); The Alfred Lab (Macular Degeneration and High Frequency Hearing Loss); The Clay Lab (End of Life Conversations); The Dima Lab (Lewy Body Dementia and Parkinson's Disease) and The Eden Lab (Trans Health & LGBT Aging).For more information, please visit www.embodiedlabs.com. Media Contact: Laura Darling, VP of CommunicationsFront Porch Communities and Servicesldarling@frontporch.net 818-482-7597 SOURCE Front Porch
    资讯
    2024年02月12日
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    探索人力资源科技的优势和挑战(Podcast) 技术总监@Humareso。Jamie Aquila是一位屡获殊荣的技术专家、设计师、建筑师和 4x 科技初创公司的首席技术官。他的项目被评为2018年 LinkedIn50强初创公司和2020年年度初创公司“100强初创公司”。Jamie 在将纽约市餐厅工作委员会 Harri.com发展成为服务行业的全球 HRIS 后,重新进入人力资源领域。 本播客中讨论的主题 “在我们深入探讨人力资源技术的复杂性之前,Jamie,您能分享一下您在人力资源技术领域的旅程吗?是什么激发了你对这个领域的兴趣,你的经历如何塑造了你对技术和人力资源交叉的看法?” “您能分享一个成功案例,其中人力资源技术的实施显著改善了公司的流程或成果吗?其他组织可以从这一成功中吸取哪些经验教训?” “根据您的经验,组织在采用人力资源技术时面临哪些常见的挑战或陷阱?如何缓解或克服这些挑战?” “鉴于人力资源技术的快速发展,您是否遇到过技术解决方案不符合预期或导致不可预见的问题的情况?你是如何处理这种情况的?” “你提到了对过度关注人工智能的担忧。组织如何在利用 AI 提高效率的同时确保在 HR 流程中保留人性化两者之间取得平衡?你觉得有什么具体的例子或策略是有效的吗?” “展望未来,您预计哪些趋势将塑造人力资源技术的未来?此外,在人力资源专业人士和组织驾驭不断发展的人力资源技术领域时,您会给他们什么建议?” “最后一个问题,Jamie,鉴于你分享的见解,你有什么信息或建议想留给我们的听众吗?此外,当我们展望2024年时,我们应该对人力资源技术的哪些方面感到特别兴奋,或者您想为 HR 专业人士和组织强调任何注意事项吗?” Source REC TECH media
    资讯
    2024年02月05日
  • 资讯
    如何在2024年管理第三方风险:Venminder 的最新白皮书揭示了一切(白皮书) 肯塔基州伊丽莎白镇,Feb.2,2024   Venminder 是用于管理第三方风险管理计划的领先综合统一平台,发布了第八份年度“第三方风险管理状况”白皮书。该白皮书深入探讨了当今组织如何处理第三方风险,涵盖了当前实践、挑战、合规驱动因素和优势等关键方面。 第三方风险管理不是一种静态的实践,而是不断适应新的风险和监管要求的动态实践。过去的一年,世界面临前所未有的事件和挑战,例如三家地区银行的倒闭、各种监管变化、创纪录的数据泄露数量、人工智能的兴起及其风险等等,这些都表明制定有效的第三方风险管理计划是多么重要。这些发展甚至对最有经验的第三方风险管理专业人员提出了挑战,要求他们重新评估其计划的范围和有效性。 对于各种规模和行业的组织来说,第三方风险管理正变得越来越紧迫和重要。组织需要持续识别、评估、管理和监控第三方风险,现在可以利用Venminder的2024年白皮书将其绩效与同行进行比较。 Venminder首席执行官James Hyde表示:“第三方风险管理为组织带来了显著的好处,并帮助他们完善其治理、风险和合规管理计划。“通过阅读和审查我们调查中捕获的当前第三方风险管理环境和流程的数据、趋势和最佳实践,您可以深入了解您的组织与同行的对比情况,并用它来指导您今年及以后的计划改进。” 第三方风险管理状况调查揭示了以下主要发现: 第三方风险管理计划的成熟度总体上正在提高,71%的受访者表示他们已经完全制定了政策/计划(其中38%仍在进一步改进),17%的受访者表示他们已经制定了政策/计划,但流程尚未完全实施。 第三方风险管理活动被认为是有价值的,96%的受访者认为他们有积极的投资回报。 第三方风险管理计划在资源有限的情况下运作,58%的受访者拥有不超过2名专职员工。 软件工具被广泛用于促进供应商风险管理,77%的受访者依赖它们。 网络安全是第三方风险管理的主要关注点和挑战,51%的受访者在过去一年中经历过第三方网络安全事件。 人工智能给第三方风险管理计划带来了新的重大风险,需要更多的关注和监督。 第三方风险管理计划面临着越来越大的改进压力,68%的受访者感受到了这一点,其中34%的受访者将其归因于监管机构。 第三方风险管理的最大障碍是从供应商处获取正确的文档、拥有足够的内部资源以及有效地管理时间。 风险情报工具在监控第三方、第四方和第 n 方方面变得越来越流行,从而增强了可见性和控制力。 64%的受访者已经定义了衡量其第三方风险管理计划的健康状况、稳定性和有效性的指标。 三分之一的受访组织(37%)在过去一年中没有在审计或考试中发现任何结果,这表明其合规性和绩效水平很高,而28%的组织发现有需要改进的地方,17%的组织对其第三方风险管理没有反馈。 完整的调查结果可在Venminder的网站上免费下载,请点击这里。 Source Venminder
    资讯
    2024年02月05日
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    美国在1月份增加了353,000个工作岗位,远好于预期 工资增长也显示出强劲势头,平均时薪增长了0.6%,是月度预期的两倍。与去年同期相比,工资增长了4.5%,远高于4.1%的预期。 1月份就业增长令人意外,再次表明了美国劳动力市场稳固,并为支持更大的经济增长做好了准备。 美国劳工部劳工统计局周五报告称,本月非农就业人数增加了353,000人,远好于道琼斯(Dow Jones)估计的185,000人。失业率保持在3.7%,优于预期的3.8%。 工资增长也显示出强劲势头,平均时薪增长了0.6%,是月度预期的两倍。与去年同期相比,工资增长了4.5%,远高于4.1%的预期。工资增长是在平均工作时间下降的情况下发生的,降至每周34.1小时,也就是减少0.2小时。 本月就业增长普遍,以专业服务和商业服务业的74,000人为主。其他主要就业增长领域包括医疗保健(70,000)、零售业(45,000)、政府(36,000)、社会援助(30,000)和制造业(23,000)。 该报告还指出,12月的就业增长比最初报告的要好得多。本月发布了333,000个工作岗位,比最初估计上调了117,000个。11月发布的工作岗位数上调至182,000个,比上次估计高出9,000个。 虽然该报告显示了美国经济的韧性,但它也可能引发人们对美联储多久能够降息的质疑。 经济学家和政策制定者正密切关注1月份就业数据,以寻找大型经济体的发展方向。最近一些备受瞩目的裁员引发了人们对招聘这一强大趋势的持久性的质疑。 然而,更多的裁员数据,如劳工部关于首次申请失业救济人数的报告,表明在如此紧张的劳动力市场中,公司不愿与工人分道扬镳。 国内生产总值(GDP)增长也超出了预期。 第四季度GDP以3.3%的年化增长率强劲增长,结束了经济与普遍预测的衰退相悖的一年。尽管美联储为降低通胀而进一步加息,但经济增长还是出现了。 亚特兰大联储的GDPNow追踪器显示,2024年第一季度将增长4.2%,尽管今年前三个月的走势数据有限。 随着美联储寻求放松货币政策,经济、就业和通胀动态使情况变得复杂。本周早些时候,美联储再次维持基准短期借贷成本稳定,并表示可能会提前降息,但要等到通胀出现进一步减缓的迹象。 美联储主席杰罗姆·鲍威尔(Jerome Powell)在会后新闻发布会上表示,央行没有“增长任务”,并表示央行行长们仍然担心高通胀对消费者的影响,尤其是那些收入水平较低的消费者。 Source NBC NEWS
    资讯
    2024年02月05日
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    ADP全国就业报告:1月份私营部门就业人数增加了107,000个工作岗位;年薪增长5.2% 本文是ADP2024年1月份全国就业报告亮点,美国私人企业就业人数变化按行业,地区,企业规模来划分。以及年薪中位数按行业,公司规模,州,性别和年龄等划分。 新泽西州罗斯兰2024年1月31日电/美通社/--根据1月份的数据,1月份私营部门就业人数增加了10.7万个工作岗位,年薪同比增长5.2%ADP全国就业报告™®由ADP研究所与斯坦福数字经济实验室(“斯坦福实验室”)合作制作。ADP全国就业报告是基于超过2500万美国雇员的实际匿名工资数据,对私营部门劳动力市场的独立衡量和高频视图。® 就业报告和薪酬洞察使用ADP的细粒度、匿名和汇总的薪资数据来提供私营部门劳动力市场的代表性图景。该报告详细介绍了本月的私人就业总变化,以及上个月的每周就业数据。由于基础ADP薪资数据库不断更新,该报告提供了对美国就业的高频、近乎实时的衡量标准。该指标反映了ADP客户工资单(Payroll Employment)上的员工人数,以提供对劳动力市场的更全面了解。ADP 的薪酬衡量标准独特地捕捉了近1000万名员工在12个月内的收入。 ADP首席经济学家Nela Richardson表示:“尽管招聘和薪酬放缓,但通胀的进展使经济前景更加光明。“在过去六个月中,经通胀调整后的工资有所改善,美国和全球经济似乎正在走向软着陆。” 2024年1月报告亮点* 在 www.adpemploymentreport.com 上查看ADP全国就业报告和交互式图表。 就业报告 私人雇主在1月份增加了107,000个工作岗位2023年的招聘放缓蔓延到1月,工资压力继续缓解。上个月,跳槽者的薪酬溢价降至新低。 美国私人企业就业人数变化:107,000 按行业划分的变化 商品生产:30,000 自然资源/采矿 6,000 建筑 22,000 制造业 2,000 提供服务:77,000 贸易/运输/公用事业 23,000 信息服务 -9,000 金融活动 7,000 专业/商业服务 2,000 教育/卫生服务 17,000 休闲/酒店业 28,000 其他服务 9,000 美国地区就业人数变化 东北部:32,000 新英格兰 5,000 大西洋中部 27,000 中西部:24,000 中东部 17,000 中西部 7,000 南部:57,000 南大西洋 39,000 东南中部 -1,000 西南中部 19,000 西部:2,000 山区 2,000 太平洋 0 按机构规模划分的变化 小型机构:25,000 1-19名员工 19,000 20-49名员工 6,000 中型企业:61,000 50-249名员工 53,000 250-499名员工 8,000 大型企业:31,000 500+ 员工 31,000 薪酬洞察 1月份 薪酬增长继续萎缩1月份,留职人员的同比工资涨幅达到5.2%,低于12月份的5.4%。对于换职者来说,工资上涨了7.2%,是自2021年5月以来的最小年度涨幅。 年薪变化中位数(ADP 匹配人员样本) 工作固定者 5.2% 换工作者 7.2% 按行业划分的留职人员年薪中位数变化 商品生产: 自然资源/矿业 4.7% 建筑业 5.6% 制造业 4.8% 服务提供: 贸易/运输/公用事业 4.7% 信息 4.5% 金融活动 5.6% 专业/商业服务 5.1% 教育/卫生服务 5.9% 休闲/酒店业 6.3% 其他服务 5.5% 按公司规模划分的留职人员年薪中位数变化 小公司: 1-19名员工 4.5% 20-49名员工 5.4% 中型企业: 50-249名员工 5.5% 250-499名员工 5.4% 大公司: 500+ 员工 5.1% 要查看按美国州、性别和年龄划分的 Pay Insights for Job-Stayers,请访问此处: * 由于四舍五入,组件的总和可能不等于总计。 12月新增就业岗位总数从164,000个修正为158,000个。历史数据文件和上个月的每周数据可在 https://adpemploymentreport.com/ 上获得。 1月份的报告提出了 ADP 全国就业报告的预定年度修订版,该报告更新了数据板块,使其与2023年3月的年度就业和工资季度普查(QCEW)基准数据保持一致。此外,本次修订还引入了技术更新,即重新加权ADP数据以匹配QCEW数据。历史文件已更新,以反映这些修订。 要订阅每月电子邮件提醒或获取有关ADP全国就业报告的更多信息,包括就业和薪酬数据、交互式图表、方法和发布日期日历,请访问 https://adpemploymentreport.com/。 2024年2月 ADP 全国就业报告将于美国东部时间2024年3月6日上午8:15发布。 关于ADP®全国就业报告™ ADP全国就业报告是衡量美国私人就业和薪酬变化的独立指标,该指标来自ADP所服务的客户公司的实际匿名工资数据,ADP是人力资本管理解决方案的领先提供商。该报告由ADP研究所与斯坦福数字经济实验室合作编写。 ADP全国就业报告每月免费向公众广泛分发,这是该公司承诺提供对美国劳动力市场的更深入见解,并为企业和政府提供可靠和有价值的信息来源的一部分。 关于ADP研究所® ADP研究所提供关于工作世界的数据驱动发现,并从这些见解中得出可靠的经济指标。我们提供这些发现,作为对整个经济提供可操作的见解,为使工作世界变得更好、更高效做出了独特的贡献。 关于ADP(NASDAQ – ADP) 通过尖端产品、优质服务和卓越体验设计更好的工作方式,使人们能够充分发挥潜力。人力资源、人才、时间管理、福利和工资单。以数据为依据,以人为本。了解更多信息 ADP.com Source ADP
    资讯
    2024年02月05日
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