• generative AI
    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.
    generative AI
    2024年02月23日
  • generative AI
    Indeed:生成式人工智能的技能能够带来近 50% 的薪资增长 Indeed的最新报告显示,掌握生成式人工智能(AI)技能的技术工作者平均薪资可达174,727美元,比没有这些技能的竞争者高出47%。随着2023年的职场波动让位给2024年的稳定,企业恢复延期的项目并推进AI实施,对技术人才的需求日益增长。数据科学家、机器学习工程师和软件工程师等角色尤为抢手。报告强调了AI技能在竞争激烈的就业市场中的价值,并指出市场上对AI相关技能的短缺。尽管对提升技能和学习AI技能的兴趣浓厚,但仅有不到四分之一的开发者表示其雇主提供了升级技能或学习AI技能的时间。 根据周三发布的 Indeed 报告,与不具备生成式人工智能技能的求职者相比,进入市场的求职者的平均薪资提高了47%。该公司在其平台上审查了职位发布的薪资数据。 根据该公司的分析,能够胜任生成式人工智能的技术人员的平均薪资预计高达174,727 美元。 生成式人工智能与其他关键技能一起为求职者带来高薪,包括深度学习、计算机视觉以及特定软件语言和框架(如Rust 或 PyTorch )的知识。 在技术行业,一个新的趋势正在改变就业市场的面貌——掌握生成式人工智能(AI)技能的工作者,其平均薪资相较于其他技术工作者高出将近50%。根据Indeed最新发布的报告,这类技术人才的平均薪资可达174,727美元,显示出市场对于此类技能的极高需求。 随着2023年的职场不确定性逐步平息,2024年迎来了更多的稳定与项目复苏,尤其是在AI实施方面。数据科学家、机器学习工程师及软件工程师等角色变得极其抢手,他们掌握的技能成为了获得高薪的关键。 报告指出,AI技术领域的半数最高薪技能都与AI直接相关,强调了AI技能在激烈的就业市场中的价值。此外,就业市场对于AI相关技能的渴求与可用人才之间存在明显差距,这一点从几乎400,000个活跃的技术职位空缺和对于数据科学家等专业人才的需求中可以看出。 然而,尽管对于提升技能和学习AI技能的需求日益增长,少于四分之一的开发者表示他们的雇主提供了学习或提升这些技能的时间。这揭示了一个问题,即尽管技术行业对于AI技能的需求日益增长,但在培养这些技能方面,企业和教育机构还有很长的路要走。 Indeed的报告不仅仅是一个薪酬调查,它也是对于技术行业未来走向的一个预示。生成式AI技能的价值在不断上升,对于那些希望在职业生涯中获得成功的技术专业人士来说,现在是最好的时机去掌握这些未来技能。 在这个由技术驱动的时代,生成式AI不仅仅是一个工具或者一个概念,它代表了未来的方向和无限的可能性。对于技术工作者而言,掌握这些技能不仅能够带来薪酬上的优势,更能在竞争激烈的就业市场中脱颖而出,成为真正的行业新贵。
    generative AI
    2024年02月22日
  • generative AI
    Autonomous Corporate Learning Platforms: Arriving Now, Powered by AI Josh Bersin 的文章通过人工智能驱动的自主平台介绍了企业学习的变革浪潮,标志着从传统学习系统到动态、个性化学习体验的重大转变。他重点介绍了 Sana、Docebo、Uplimit 和 Arist 等供应商的出现,它们利用人工智能动态生成和个性化内容,满足了企业培训不断变化的需求。Bersin 讨论了跟上多样化学习需求所面临的挑战,以及人工智能解决方案如何提供可扩展的高效方法来管理知识和提高学习效果,并预测了人工智能将从根本上改变教学设计和内容交付的未来。推荐给大家:   Thanks to Generative AI, we’re about to see the biggest revolution in corporate learning since the invention of the internet. And this new world, which will bring together personalization, knowledge management, and a delightful user experience, is long overdue. I’ve been working in the corporate learning market since 1998, when the term “e-learning” was invented. And every innovation since that time has been an attempt to make training easier to build, easier to consume, and more personalized. Many of the innovations were well intentioned, but often they didn’t work as planned. First came role based learning, then competency-driven training and career-driven programs. These worked great, but they couldn’t adapt fast enough. So people resorted to short video, YouTube-style platforms, and then user-authored content. We then added mobile tools, highly collaborative systems, MOOCs, and more recently Learning Experience Platforms. Now everyone is focused on skills-based training, and we’re trying to take all our content and organize it around a skills taxonomy. Well I’m here to tell you all this is about to change. While none of these important innovations will go away, a new breed of AI-powered dynamic content systems is going to change everything. And as a long student of this space, I’d like to explain why. And in this conversation I will discuss four new vendors, each of which prove my point (Sana, Docebo, Uplimit, and Arist). The Dynamic Content Problem: Instructional Design By Machine Let’s start with the problem. Companies have thousands of topics, professional skills, technical skills, and business strategies to teach. Employees need to learn about tools, business strategies, how to do their job, and how to manage others. And every company’s corpus of knowledge is different. Rolls Royce, a company now starting to use Galileo, has 120 years of engineering, technology, and manufacturing expertise embedded in its products, documentation, support systems, and people. How can the company possibly impart this expertise into new engineers? It’s a daunting problem. Every company has this issue. When I worked at Exxon we had hundreds of manuals explaining how to design pumps, pressure vessels, and various refinery systems. Shell built a massive simulation to teach production engineers how to understand geology and drilling. Starbucks has to teach each barista how to make thousands of drinks. And even Uber drivers have to learn how to use their app, take care of customers, and stay safe. (They use Arist for this.) All these challenges are fun to think about. Instructional designers and training managers create fascinating training programs that range from in-class sessions to long courses, simulations, job aids, and podcasts. But as hard as they try and as creative as they are, the “content problem” keeps growing. Right now, for example, everyone is freaked out about AI skills, human-centered leadership, sustainability strategies, and cloud-based offerings. I’ve never seen a sales organization that does quite enough training, and you can multiply that by 100 when you think about customer service, repair operations, manufacturing, and internal operations. While I always loved working with instructional designers earlier in my career, their work takes time and effort. Every special course, video, assessment, and learning path takes time and money to build. And once it’s built we want it to be “adaptive” to the learner. Many tools have tried to build adaptive learning (from Axonify to Cisco’s “reusable learning objects“) but the scale and utility of these innovations is limited. What if we use AI and machine learning to simply build content on the fly? And let employees simply ask questions to find and create the learning experience they want? Well thanks to innovations from the vendors I mentioned above, this kind of personalized experience is available today.  (Listen to my conversation with Joel Hellermark from Sana to hear more.) What Is An Autonomous Learning Platform? The best analogy I’ve come up with is the “five levels of autonomous driving.” We’re going from “no automation” to “driver assist” to “conditional automation” to “fully automated.” Let me suggest this is precisely what’s happening in corporate training. If you look at the pace of AI announcements coming (custom GPTs, image and video generation, integrated search), you can see that this reality has now arrived. How Does This Really Work Now that I’ve had more than a year to tinker with AI and talk with dozens of vendors, the path is becoming clear. The new generation of learning platforms (and yes, this will eventually replace your LMS), can do many things we need: First, they can dynamically index and injest content into an LLM, creating an “expert” or “tutor” to answer questions. Galileo, for example, now speaks in my own personal voice and can answer almost any question in HR I typically get in person. And it gives references, examples, and suggests follow-up questions. Companies can take courses, documents, and work rules and simply add them to the corpus. Second, these systems can dynamically create courses, videos, quizzes, and simulations. Arist’s tool builds world-class instructional pathways from documents (try our free online course on Predictions 2024 for example) and probably eliminates 80% of the design time. Docebo Shape can take sales presentations and build an instructional simulation automatically, enabling sales people to practice and rehearse. Third, they can give employees interactive tutors and coaches to learn. Uplimit’s new system, which is designed for technical training, automatically gives you an LLM-powered coach to step you through exercises, and it learns who you are and what kind of questions you need help with. No need to “find the instructor” when you get stuck. Fourth, they can personalize content precisely for you. Sana’s platform, which Joel describes here, can not only dynamically generate content but by understanding your behavior, can actually give you a personalized version of any course you choose to take. These systems are truly spectacular. The first time you see one it’s kind of shocking, but once you understand how they work you see a whole new world ahead. Where Is This Going While the market is young, I see four huge opportunities ahead. First, companies can now take millions of hours of legacy content and “republish it” in a better form. All those old SCORM or video-based courses, exercises, and simulations can turn into intelligent tutors and knowledge management systems for employees. This won’t be a simple task but I guarantee it’s going to happen. Why would I want to ramble around in the LMS (or even LinkedIn Learning) to find the video, or information I need? I”d just like to ask a system like Galileo to answer a question, and let the platform answer the question and take me to the page or word in the video to watch. Second, we can liberate instructional design. While there will always be a need for great designers, we can now democratize this process, enabling sales operations people, and other “non-designers” to build content and courses faster. Projects like video authoring and video journalism (which we do a lot in our academy) can be greatly accelerated. And soon we’ll have “generated VR” as well. Third, we can finally integrate live learning with self-directed study. Every live event can be recorded and indexed in the LLM. A two hour webinar now becomes a discoverable learning object, and every minute of explanation can be found and used for learning. Our corpus, for example, includes hundreds of hours of in-depth interviews and case studies with HR leaders. All this information can be brought to life with a simple question. Fourth, we can really simplify compliance training, operations training, product usage, and customer support. How many training programs are designed to teach someone “what not to do” or “how to avoid breaking something” or “how to assemble or operate” some machine? I’d suggest its millions of hours – and all this can now be embedded in AI, offered via chat (or voice), and turned loose on employees to help them quickly learn how to do their jobs. Vendors Watch Out This shift is about as disruptive as Tesla has been to the big three automakers. Old LMS and LXP systems are going to look clunkier than ever. Mobile learning won’t be a specialized space like it has been. And most of the ERP-delivered training systems are going to have to change. Sana and Uplimit, for example, are both AI-architected systems. These platforms are not “LMSs with Gen AI added,” they are AI at the core. They’re likely to disrupt many traditional systems including Workday Learning, SuccessFactors, Cornerstone, and others. Consider the content providers. Large players like LinkedIn Learning, Skillsoft, Coursera, and Udemy have the opportunity to rethink their entire strategy, and either put Gen AI on top of their solution or possibly start with a fresh approach. Smaller providers like us (and thousands of others) can take their corpus of knowledge and quickly make it come to life. (There will be a massive market of AI tools to help with this.) I’m not saying this is easy. If you talk with vendors like Sana, Docebo, Arist, and Uplimit, you see that their AI platforms have to be highly tuned and optimized for the right user experience. This is not as simple as “dumping content into ChatGPT,” believe me. But the writing is on the wall, Autonomous Learning is coming fast. As someone who has lived in the L&D market for 25 years, I see this era as the most exciting, high-value time in two decades. I suggest you jump in and learn, we’ll be here to help you along the way. About These Vendors Sana (Sana Labs) is a Sweden-based AI company that focuses on transforming how organizations learn and access knowledge. The company provides an AI-based platform to help people manage information at work and use that data as a resource for e-learning within the organization. Sana Labs’ platform combines knowledge management, enterprise search, and e-learning to work together, allowing for the automatic organization of data across different apps used within an organization. Docebo is a software as a service company that specializes in learning management systems (LMS). It was founded in 2005 and is known for its Docebo Learn LMS and other tools, including Docebo Shape, its AI development system. The company has integrated learning-specific artificial intelligence algorithms into its platform, powered by a combination of machine learning, deep learning, and natural language processing. The company went public in 2019 and is listed on the Toronto Stock Exchange and the Nasdaq Global Select Market. Uplimit is an online learning platform that offers live group courses taught by top experts in the fields of AI, data, engineering, product, and business. The platform is known for its AI-powered teaching assistant and personalized learning approach, which includes real-time feedback, tailored learning plans, and support for learners. Uplimit’s courses cover technical and leadership topics and are designed to help individuals and organizations acquire the skills needed for the future. Arist is a company that provides a text message learning platform, allowing Fortune 500 companies, governments, and nonprofits to rapidly teach and train employees entirely via text message. The platform is designed to deliver research-backed learning and nudges directly in messaging tools, making learning accessible and effective. Arist’s approach is inspired by Stanford research and aims to create hyper-engaging courses in minutes and enroll learners in seconds via SMS and WhatsApp, without the need for a laptop, LMS, or internet. The company has been recognized for its innovative and science-backed approach to microlearning and training delivery. BY JOSHBERSIN 
    generative AI
    2024年02月18日
  • generative AI
    The best HR & People Analytics articles of January 2024 2024 is set to be a momentous year. With economic uncertainty, rising geopolitical conflict, and rapid advances in technology, it is also set to be a stormy 12 months for the world, for organisations, and for HR professionals too. Perhaps this explains the slew of insightful resources in January, which has made compiling this month’s collection as challenging as it has been enjoyable. One of the key focuses has been on ‘productivity’, and I’ve brought together a number of resources on this topic. There are also new studies from the likes of PwC, McKinsey, Glassdoor, Accenture, and Deloitte as well as articles featuring practitioners from companies including Spotify, Microsoft, Ericsson, Lloyds Banking Group, and Standard Chartered. There’s lots to enjoy and learn from. Join me for a webinar on February 21 to discover how Leading Companies shift People Analytics from insight to impact Are you an HR or People Analytics Leader seeking to transform your organisation’s People Analytics from mere insights to impactful business outcomes? If so, I invite you to join me for a webinar that Insight222 is hosting on February 21. Naomi Verghese and I will walk through the findings from the Insight222 People Analytics Trends research, unveiling the distinctive characteristics of ABCD Teams that propel organisations to new heights. Naomi and I will be joined by Alan Susi, VP and Global Head of Organisational Analytics and People Insights at S&P Global. Alan will share insights into how S&P Global successfully elevated their approach to people analytics, turning data into tangible business outcomes. You can register for the webinar here – or by clicking the image below. Jürgen Klopp – a study in leadership, culture, and analytics As a fervent supporter, I’m still processing the totally unexpected news that Jürgen Klopp will be leaving his post as the manager of Liverpool at the end of the current football season. In his press conference on taking the reins at Anfield in October 2015, Klopp stated his goal was to turn Liverpool from “doubters to believers.” He has done this with some aplomb amassing a haul of seven trophies (to date) including the Champions League in 2019 and then, the following year, the Holy Grail of Liverpool’s first league title in 30 years. But Klopp is more than a brilliant football manager. He is the epitome of an empathetic leader. His emotional intelligence and natural humility not only endears Klopp to his players, but to supporters too for whom he is adored. The reaction to the news reduced many Liverpool supporters to tears. I’m still hoping – probably forlornly - that like Alex Ferguson in 2002, Klopp will change his mind and stay. In the likely event that he does depart, I’m sure that multiple studies will be made on Klopp’s time at Anfield, and that his leadership skills, use of data and analytics, and ability to build an inclusive winning culture will be deservedly celebrated. YNWA. Looking for a new role in people analytics or HR tech? Before we get to this month’s collection of resources, I’d like to highlight once again the wonderful resource created by Richard Rosenow and the One Model team of open roles in people analytics and HR technology, which now numbers over 500 roles. Looking for a people analytics event to attend in 2024? Richard Rosenow has also been busy compiling a study of People Analytics Conferences to attend in 2024 with the data collected from practitioners themselves. Society for Industrial and Organizational Psychology (SIOP), People Analytics World and the Wharton People Analytics Conference all come out well as does the Insight222 Global Executive Retreat. Thanks to Richard for putting this together. Share the love! Enjoy reading the collection of resources for January and, if you do, please share some data driven HR love with your colleagues and networks. Thanks to the many of you who liked, shared and/or commented on December’s compendium (including those in the Comments below). If you enjoy a weekly dose of curated learning (and the Digital HR Leaders podcast), the Insight222 newsletter: Digital HR Leaders newsletter is published every Tuesday – subscribe here. THE QUEST FOR PRODUCTIVITY MCKINSEY - 2024 and beyond: Will it be economic stagnation or the advent of productivity-driven abundance? | PwC - 27th Annual Global CEO Survey: Thriving in an age of continuous reinvention | JOSH BERSIN - HR Predictions for 2024: The Global Search For Productivity | ERIK BRYNJOLFSSON - How AI Will Transform Productivity | BEN WABER AND NATHANAEL J. FAST - Is GenAI’s Impact on Productivity Overblown? When I talk with CHROs and People Analytics Leaders at the companies we work with at Insight222, one of the words I’m hearing most at the moment is ‘productivity’. Continuing economic and geopolitical uncertainty, the promise of AI, and challenging talent demographics are all fuelling the demand for productivity from CEOs. Here are five resources that can be filed under the ‘productivity’ umbrella: (1) McKinsey’s Ezra Greenberg, Asutosh Padhi, and Sven Smit present a model for businesses to capture the three-sided productivity opportunity (see FIG 1). (2) Amongst a ton of takeaways, the standout theme from the annual PwC CEO survey is that the vast majority of participating companies are already taking some steps towards reinvention, while CEOs believe that 40% of their work is wasted productivity (see FIG 2). (3) Josh Bersin draws from the PwC survey in his 2024 predictions, where he outlines The Productivity Advantage where “If you can help your company move faster (productivity implies speed, not only profit), you can reinvent faster than your competition.” (4) Stanford professor Erik Brynjolfsson offers leaders an overview of how AI will transform productivity. (5) Finally, Ben Waber and Nathanael Fast’s absorbing essay in Harvard Business Review cautions leaders on leaning into the hype on GAI’s supposed positive impact on productivity too heavily. The authors break down two of the key challenges with LLMs: a) their persistent ability to produce convincing falsities and b) the likely long-term negative effects of using LLMs on employees and internal processes. FIG 1: The three-side productivity opportunity (Source: McKinsey) FIG 2: CEOs estimate administrative inefficiency at 40% (Source: PwC) GERGELY OROSZ AND ABI NODA - Measuring Developer Productivity: Real-World Examples Continuing the productivity theme, this is an invaluable resource by Gergely Orosz and Abi Noda in The Pragmatic Engineer newsletter. It provides detail on developer productivity metrics at 17 tech companies including Google, Microsoft, Spotify, and Uber (see summary in FIG 3). FIG 3: Developer productivity metrics at 17 tech companies (Source: Pragmatic Engineer) 2024 HR TRENDS AND PREDICTIONS JASMINE PANAYIDES - Nine Ways to Put HR Trends and Predictions into Practice in 2024 There has been a flood of articles advising what the key HR trends, predictions, and opportunities for 2024 are, but how are HR professionals supposed to make sense of these? In her article for the myHRfuture blog, Jasmine Panayides provides actionable tips on how HR professionals can apply the trends, predictions and opportunities to their work, and their organisations so they can deliver value to the company and the workforce. Jasmine also helpfully summarises the trends/predictions from a variety of sources into one table (see FIG 4), including from: Visier Inc., Gartner, Bernard Marr, UNLEASH, Mercer, and Culture Amp as well as my own 12 Opportunities for HR in 2024 article. FIG 4: Analysis of HR Trends and Predictions for 2024 (Source: myHRfuture) KATARINA BERG - HR Trends for 2024 | GARTNER - 9 Future of Work Trends for 2024 | GLASSDOOR – 2024 Workforce Trends | HUNG LEE - Forecasting 2024 in Recruitment Part 1, Part 2, Part 3, and Part 4 | KEVIN WHEELER - What Does 2024 Hold in Store for Us? | STACIA GARR AND DANI JOHNSON – 2024 Mega Trends and how people leaders should respond (Webinar) The deluge of commentators offering their HR trends and opportunities continued in January. As such, it is a challenge to sort the wheat from the chaff but in addition to those I highlighted in this compendium in December, and in Jasmine’s article above, I recommend diving into the following: (1) Spotify’s chief people officer, Katarina Berg, highlights ten trends with the common theme being each trend is a bridge, connecting the past with the future, and HR professionals are the architects crafting these vital links – including “Staying Human in the Age of AI – The Humanity Bridge”. (2) Gartner’s Jordan Turner and Emily Rose McRae highlight nine future of work trends for the year ahead (see FIG 5). (3) Aaron Terrazas and Daniel Zhao identify eight workforce trends based on Glassdoor’s data on workplace satisfaction, culture, and conversations. (4) Hung Lee is at the cutting edge of recruiting and HR tech, so his four-part series on recruiting in 2024 is definitely worth checking out – two examples include: “Multi-generational replaces neurodiversity as DEIB hot topic” and “Capital Allocation Shifts from Sourcing & Engagement to Assessment & Verification Tech”. (5) Futurist Kevin Wheeler offers seven insights and predictions together with his self-assessed certainty rating including “Generative AI will dominate, and every product will attempt to incorporate AI. 90% certainty” and “More firms will embrace a four-day workweek 50% certainty”. (6) Finally, I strongly recommend viewing the 2024 Mega Trends webinar hosted by Stacia Sherman Garr and Dani Johnson for RedThread Research, which breaks down the key macro factors impacting the world of work and how HR can respond. FIG 5: 9 Future of Work Trends for 2024 (Source: Gartner) GREG NEWMAN - 10 important topics that HR will likely ignore in 2024 Greg Newman takes an alternative, wry and contrarian approach by focusing his list of “predictions” on ten things most HR teams will continue to ignore in 2024. My favourite three are: (1) speaking the language of the business, (2) focusing AI conversations on ethics before technology, and (3) learning that good data is required to realise the dreams of AI and analytics. By aligning HR language with business terminology, we can more effectively demonstrate the value of our initiatives in a way that resonates with business stakeholders. GENERATIVE AI AND THE FUTURE OF WORK ELLYN SHOOK AND PAUL DAUGHERTY - Work, workforce, workers: Reinvented in the age of generative AI A new study from Accenture, co-authored by Ellyn Shook and Paul Daugherty, on how generative AI is impacting work, provides guidance on how leaders can: “Set and guide a vision to reinvent work, reshape the workforce and prepare workers for a generative AI world, while building a resilient culture to navigate continuous waves of change.” The report reveals a trust gap between workers and leaders on key elements related to GAI’s impact on work, the workforce, and workers. The authors also highlight four accelerators for leaders to navigate the journey ahead: (1) Lead and learn in new ways, (2) Reinvent work, (3) Reshape the workforce (see example in FIG 6), and (4) Prepare workers. FIG 6: Illustrative example of how work and roles can be reallocated in a GAI future (Source: Accenture) ROGER W. HOERL AND THOMAS C. REDMAN - What Managers Should Ask About AI Models and Data Sets The decision on whether to deploy AI models within an organisation ultimately lies with business leaders who may not be qualified to identify risks and weaknesses related to AI models and data sets. In their article, Roger Hoerl and Tom Redman provide (1) A framework (see FIG 7) designed to equip leaders with context and based on their concept of the right data. (2) A set of six questions for leaders to ask their AI model developers before and during modelling work and deployment. (3) Guidance for leaders on how to assess AI model developers’ answers to those six questions. FIG 7: The Right Data Framework (Source: Roger W. Hoerl and Thomas C. Redman) PEOPLE ANALYTICS STEVE HATFIELD, SUE CANTRELL, AND BRAD KREIT - Beyond the quick fix: How workforce data can drive deeper organizational problem-solving The premise of this thoughtful article by Steve Hatfield, Susan Cantrell, and Brad Kreit is that without the right context, even simple measurements can undermine efforts to convert people data into value. They then explore several examples – in the workforce, in the workplace, and in the work – where organisations might be limiting their analysis to the surface level and how deeper analysis can reveal systemic issues that lead to opportunities for transformation. Guidance on three actions leaders can take to help ensure they are not missing important context in their data analysis are provided: (1) Bring data from different domains and sources together for analysis. (2) Make sure you’re measuring what you should—not just what you can. (3) Identify potential biases in data collection algorithms. If organizations want to move beyond quick fixes and use work and workforce data to drive deeper—and often more challenging—problem-solving, it is important that they look at the data in context. NAOMI VERGHESE - How to Measure the Value of People Analytics My Insight222 colleague Naomi Verghese digs how to measure the commercial value of people analytics, highlighting a powerful case study from Jaesun HA and LG Electronics. Naomi provides detail on four key areas where people analytics adds value (business performance, workforce experiences, driving an analytics culture and societal benefit) as well as providing data on the characteristics of companies that ARE creating commercial value from people analytics (see FIG 8). FIG 8: Characteristics of people analytics that disclosed and measured commercial value of people analytics solutions (Source: Insight222 People Analytics Trends, 2023) ANDRÉS GARCIA AYALA - 5 Change Drivers Impacting People Analytics & How To Thrive In Them | WILLIS JENSEN - Attrition versus Retention: Which Should I Use? | KEITH McNULTY – Regression Modeling in People Analytics: Survival Analysis | LYDIA WU - The Market Sucks and You are Looking for a Job, Now What? | SEBASTIAN SZACHNOWSKI - 16 HR Metrics for IT | ERIN FLEMING AND NICK JESTEADT - People Analytics Perspectives from the Fringe: Current Priorities and a View on Optimized Teams in 2024 January saw a slew of articles from current and recent people analytics leaders, which typically act as a spur and inspiration for the field. Six are highlighted here: (1) Andrés García Ayala highlights some of the key change drivers impacting people analytics and ways to incorporate them into our work. (2) Willis Jensen builds on the recent primer on attrition metrics by Ben Teusch that I highlighted in December’s edition. He explains why we should be using attrition and retention as separate terms that lead to distinct metrics with different objectives (see also FIG 9). (3) Keith McNulty provides another indispensable practical guide for people analysts with a step-by-step tutorial to conducting survival analysis in R. (4) The prolific Lydia Wu turns her attention to providing some handy guidance for those looking for their next people analytics / HR tech role. (5) Sebastian Szachnowski provides a useful breakdown of 16 HR metrics for technology companies. (6) Last but definitely not least, Erin Fleming and Nick Jesteadt provide insights from their survey of fellow people analytics practitioners. Insights include a) 41% of respondents (n=49) operate as a one-person people analytics team, and ii) the main current focus areas of work include employee turnover, cultural engagement, return to office, and restructuring. FIG 9: When to use Attrition and Retention (Source: Willis Jensen) MAX BLUMBERG - The Big List of GPTs to Revolutionize Your People Processes | JOHANNES SUNDLO - GenAI for People Analytics Two articles addressing the opportunity for generative AI in the people space. (1) Max Blumberg (JA) ?? sets out 93 potential ways to upgrade your People Processes with AI and GPTs across four categories – workforce planning and strategy, recruitment, learning and development, and employee wellbeing. (2) Johannes Sundlo provides examples of companies using GAI in their people analytics work to support analyses on engagement data, skills, and tailoring training recommendations. GPTs are an amazing tool for scenario planning, forecasting future workforce needs, identifying talent gaps, and developing integrated talent strategies. THE EVOLUTION OF HR AND DATA DRIVEN CULTURE DAVE ULRICH, NORM SMALLWOOD, AND JOE GROCHOWSKI - Why and How to Move HR to an Outside-In Approach When asked the question, “What is the biggest challenge in your job today?” HR professionals will typically provide answers such as: “Build a skills-based organisation” or “Help our employees have a better experience”. As Dave Ulrich, Norm Smallwood, and Joe Grochowski write, these answers would be far more powerful when a “so that” is applied e.g. “Help employees have a better experience so that customer experience improves.” The article demonstrates that greater value is created with an outside-in approach that starts with the needs of external stakeholders (customers, investors, community) and then figuring out the implications inside the company for meeting those needs. Dave, Norm, and Joe also present their Human Capability Framework and a tool that provides an assessment of an organisation’s outside-in performance (see FIG 10). FIG 10: Human capability from the outside-in - diagnostic questions (Source: Dave Ulrich et al) WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS AMY WEBB - Bringing True Strategic Foresight Back to Business In her article for Harvard Business Review, Amy Webb defines strategic foresight as “a disciplined and systematic approach to identify where to play, how to win in the future, and how to ensure organizational resiliency in the face of unforeseen disruption.” Her article also advocates for the integration of strategic foresight as a core competency in every organisation, regardless of size. Moreover, Amy provides guidance on how to operationalise strategic foresight by unveiling a ten-step process. Read alongside another article authored by Amy for HBR: How to Do Strategic Planning Like a Futurist, which includes Amy’s Futurist’s Framework for Strategic Planning (see FIG 11). FIG 11: A Futurist’s Framework for Strategic Planning (Source: Amy Webb) WORLD ECONOMIC FORUM AND PwC - Putting Skills First: Opportunities for Building Efficient and Equitable Labour Markets As the introduction to this compelling collaboration between the World Economic Forum and PwC begins: “Skills and talent shortages are critical challenges facing societies and economies today. The absence of relevant skills impedes business growth, hinders economic prosperity, and inhibits individuals from realizing their full potential.” The report identifies five specific opportunities for intervention where the gains from skills-first solutions are most likely for employers and workers alike (see ‘Skills-first Framework’ in FIG 12). Additionally, the report also showcases 13 Skills First “Lighthouses”, including IBM, Siemens, Standard Chartered and Sanofi. It concludes by offering key takeaways regarding six success factors in implementing skills-first approaches including (1) Sponsorship from leadership, (2) Alignment with business needs, and (3) Data and evaluation for iteration. (Authors: Genesis Elhussein, Mark Rayner, Aarushi Singhania, Saadia Zahidi, Peter Brown MBE, Miral Mir, and Bhushan Sethi). A cultural shift to skills-first approaches needs both sponsorship from executives and governance from human-resources professionals FIG 12: Skills-first Framework (Source: World Economic Forum PETER SHEPPARD - Learning from our Skills Journey | BEN AUTY - What are the new skills people will need for the future of work? | TANUJ KAPILASHRAMI - How Standard Chartered is Unlocking the Power of Skills in the Workplace Many of the organisations we work with at Insight222 have embarked on the road to becoming a skills-based organisation. It is not an easy journey, so it is helpful to learn from other companies who are treading this path. Three of these are Ericsson, Lloyds Banking Group, and Standard Chartered. (1) In his article, Peter Sheppard shares learnings from Ericsson’s skills journey including a) it’s not jobs or skills; it’s skills and jobs, b) it’s a whole organisation activity, c) Less is more with skills, and d) Data drives value. (2) Ben Auty shares insights as to why Lloyds Banking Group is developing a learning culture to build the workforce of the future at the bank, the main skills they are focusing on, and the central role the recently established Reskilling Team is playing. (3) Tanuj Kapilashrami shares how Standard Chartered catalysed their work on skills by identifying adjacencies between ‘sunset’ and ‘sunrise’ roles. We looked at skills adjacencies between ‘sunset’ jobs and ‘sunrise’ jobs: so, what are the jobs that are going to go away? What are the skills that help employees get reskilled into some of these sunrise jobs? We ran five proofs of concept, we showed some real redeployment opportunities and started making the skills narrative real. EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING JENNIFER E. SIGLER WITH STEPHANIE DENINO - So Many Stakeholders, So Little Time: State of EX 2023-2024 The fifth annual State of EX study authored by Jennifer E. Sigler, PhD on behalf of The EXchange, Inc, TI PEOPLE and FOUNT Global, Inc. is a treasure chest of insights on the fast-evolving practice of employee experience. It highlights the top four priorities for EX as: (1) Redesigning experiences, (2) Getting broader buy-in for EX work across the organisation, (3) Building an EX roadmap for the organisation, and (4) Getting more / better data. One other standout finding from the study suggests that senior leaders are increasingly focused on EX with a majority of respondents (63%) saying their organisation’s senior leaders view EX as equal to or even more important than other corporate priorities. This bodes well for the future of EX. Thanks to Stephanie Denino and Volker Jacobs for highlighting the study. FIG 13: EX Team Priorities YOY Change (Source: The EXchange, TI People and FOUNT Global, Inc) LEADERSHIP AND CULTURE NADJIA YOUSIF, ASHLEY DARTNELL, GRETCHEN MAY, AND ELIZABETH KNARR - Psychological Safety Levels the Playing Field for Employees | PETER CAPPELLI AND LIAT ELDOR - Can Workplaces Have Too Much Psychological Safety? Two perspectives on psychological safety in the workplace. In the first article, Nadjia Yousif, Ashley Dartnell, Gretchen May, and Elizabeth Knarr present the findings of Boston Consulting Group (BCG) research, which finds how psychological safety benefits inclusion, reduces attrition in diverse groups and effectively acts as an equaliser - enabling diverse and disadvantaged employee groups to achieve the same levels of workplace satisfaction as their more advantaged colleagues. The study also highlights the direct relationship between empathetic leadership and feelings of psychological safety in the workforce, giving leaders a clear directive to be empathetic and thereby engender psychological safety. The second article by Peter Cappelli and Liat Eldor presents research that found that when you move from average to high levels of psychological safety, performance in routine jobs actually declined. FIG 14: Psychological safety has an outsize impact on retention for diversity groups (Source: BCG) RASMUS HOUGAARD, JACQUELINE CARTER, AND ROB STEMBRIDGE - The Best Leaders Can’t Be Replaced by AI While there are some areas where AI is already surpassing or will surpass human capabilities, there are several it cannot replace. Based on their research into employees’ comfort with AI in management, as well as their decades of research on the qualities of effective leadership, Rasmus Hougaard, Jacqueline Carter, and Robert Stembridge identify the promise (and perils) of AI-enabled management (see FIG 15), as well as the three uniquely human capabilities leaders need to focus on honing, especially as AI begins to figure more in management: (1) awareness, (2) compassion, and (3) wisdom. For more from Rasmus, I recommend listening to his podcast discussion with me: How To Be a More Compassionate Leader. Leaders who deepen their ability to lead with humanity will win at attracting, retaining, developing, and motivating top talent. FIG 15: AI versus Human: A matric of leadership activities (Source: Potential Project) DIVERSITY, EQUITY, INCLUSION, AND BELONGING JULIE COFFMAN, ALEX NOETHER, BIANCA BAX, CASSY REICHERT, AND KRYSTLE JIANG - The Business of Belonging: Why making everyone feel included is smart strategy Revealing data from a Bain survey of 6,000+ employees across four countries, which finds employees who have seen their companies intentionally invest in inclusion since 2020 are three times more likely to feel fully included than employees who have not seen such investment from their employers. Other findings include (1) Combining diversity and inclusion maximises a company’s capacity (by 4x) to innovate, and (2) Employees with inclusive leadership are 9x more likely to feel fully included at work (see FIG 16). (Authors: Julie Coffman, Alex Noether, Bianca Bax, Cassy Reichert, and Krystle Jiang). FIG 16: Employees with inclusive leadership are 9x more likely to feel fully included at work (Source: Bain) SHUJAAT AHMAD - DEIB Is At A Crossroads—It’s Time for Bold Action and Clear Metrics Given recent developments it’s reasonable to say that Diversity, Equity, Inclusion, and Belonging (DEIB) is at an existential crossroads. As Shujaat Ahmad writes in his excellent article for Round: “Boards, leadership teams, and investors hold the power to set the tone, shape the policies, and allocate the resources to support DEIB initiatives: for DEIB to work effectively, they must shift from well-intentioned wordsmiths to committed drivers that hold the organization accountable for outcomes and positive change.” Shujaat then unveils his blueprint to help leaders assess progress and drive meaningful change, clarifying the ‘why’ before diving into the ‘how’ covering measuring what matters and interventions (see FIG 17). For more from Shujaat, I recommend visiting Belong and Lead. FIG 17: Source – Shujaat Ahmad HR TECH VOICES Much of the innovation in the field continues to be driven by the vendor community, and I’ve picked out a few resources from January that I recommend readers delve into: ERNEST NG - If the Pitch is Too Smooth, It Probably Is: Why AI in HR is Difficult – Part 2 of an insightful essay from Ernest Ng, PhD of HiredScore (see also Part 1 on disclosures here) where he cuts through the hype to assess how we should be implementing AI in HR. LOUJAINA ABDELWAHED - A Tale of Two Cultures - In One Company - Loujaina Abdelwahed, PhD from Revelio Labs highlights the growing disparity between junior and senior employees (see FIG 18) and identifies the factors causing this malaise. Thanks to Ben Zweig for highlighting. FIG 18: The growing disparity in sentiment between junior and senior employees (Source: Revelio Labs) JEREMIE BRECHEISEN - Where Employees Think Companies’ DEIB Efforts Are Failing – Jeremie K Brecheisen presents findings from Gallup that reveals a disconnect between how well employees and HR leaders believe their organisations are doing when it comes to diversity, equity, inclusion, and belonging: 84% of CHROs say their organisations are increasing investment in DEIB, while only 31% of employees say their organisation is committed to improving racial justice or equity in their workplace (see FIG 19). The article then outlines ten needs employees say are not being met and then offers strategies to help organisations address the disconnect. FIG 19: How employees and HR leaders differ on perceptions of DEIB progress (Source: Gallup) FRANCISCO MARIN - Navigating the ONA Landscape: Trends and Challenges for 2024 - Another good read from Cognitive Talent Solutions, as Francisco Marin explores the key trends and challenges shaping the ONA space in 2024. IAN WHITE - The three C’s of effective performance management – Ian White, CEO at ChartHop, presents the three C’s of performance management — continuous, contextual and cultural — designed to help companies understand their employees more holistically. CHRISTINA JANZER - The surprising connection between after-hours work and decreased productivity – Christina Janzer presents findings from Slack’s Workforce Index, which identifies findings on how to structure the workday to maximise employee productivity, well-being and satisfaction – including the connection between after hours work and decreased productivity. FIG 20: Source – Slack PODCASTS OF THE MONTH In another month of high-quality podcasts, I’ve selected five gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below): AMY EDMONDSON AND LAURIE RUETTIMANN – Right Kind of Failure – Amy Edmondson joins Laurie Ruettimann on the brilliantly named Punk Rock HR to explore the essential role of failure in our professional and personal growth. STACIA GARR, COLE NAPPER, AND SCOTT HINES - People Analytics & HR Tech Research by Industry Analysts – Stacia Sherman Garr, one of the industry’s top analysts, joins Cole Napper and Scott Hines, PhD on the Directionally Correct podcast to discuss the research Stacia and her team at RedThread Research do in the people analytics and HR technology space. RICHARD ROSENOW, MADDIE GRANT, AND SANJA LICINA - How to Build an Integrated Framework for Workforce Listening – In an episode of the Empowering Workplaces podcast, Richard Rosenow joins hosts Maddie Grant and Sanja Licina, Ph.D. to talk about The Three Channels of Workforce Information: conversations (“what people say”), surveys (“what people say they do”) and systems (“what people do”) as a way to build a comprehensive understanding of your workforce. McKINSEY - The shape of talent in 2023 and 2024 - In this episode of McKinsey Talks Talent, Bryan Hancock, Brooke Weddle and host Lucia Rahilly highlight the trends that shaped last year’s talent landscape—and those poised to ‘redefine its contours’ yet again in 2024. MATTHEW BIDWELL AND DAN LONEY – Forecasting 2024 Workplace Trends – Wharton Professor and convenor of the Wharton People Analytics Conference, Matthew Bidwell, joins host of the Wharton Business Daily Dan Loney to look at the year ahead in the workplace. VIDEO OF THE MONTH CHRIS LOUIE, TOMAS CHAMORRO-PREMUZIC, TERRI HORTON, AND LINDSEY SHINTANI - Power a dynamic workforce by embracing AI An enlightening panel discussion from the recent LinkedIn Talent Connect where Chris Louie, Dr Tomas Chamorro-Premuzic, Terri Horton, EdD, MBA, MA, SHRM-CP, PHR, and Lindsey Shintani discuss how AI is changing learning and career paths. They provide guidance on how to overcome AI anxiety and empower impactful futures. BOOK OF THE MONTH KEVIN WHEELER AND BAS VAN DE HATERD – Talent Acquisition Excellence An excellent new book published by Kogan Page and authored by Kevin Wheeler and Bas van de Haterd (He/His/Him). It provides an insightful and detailed analysis of how technologies such as artificial intelligence and machine learning in combination with analytics can improve talent acquisition and recruitment. RESEARCH REPORT OF THE MONTH YUYE DING AND MARK (SHUAI) MA - Return-to-Office Mandates A huge thank you to Nick Bloom for bringing my attention to this paper from Yuye Ding and Mark Ma, which studied the impact of 137 Return to Office mandates on the performance of S&P500 firms from 2020-2023. The key findings, as summarised by Nick, are illuminating: (1) RTO mandates are more likely in firms with poor recent stock performance, and in those with powerful male CEOs. (2) Glassdoor data finds RTO mandates significantly reduce employee ratings for job satisfaction, work-life balance, and senior management. (3) There is no significant impact of RTO mandates on either firm profitability or firm stock-returns. FIG 21: Distribution of firms’ RTO mandates (Source: Yuye Ding and Mark Ma) FROM MY DESK January saw the first three episodes of Series 36 of the Digital HR Leaders podcast, sponsored by our friends at ScreenCloud. Thank you to Luke Farrugia. DAVID GREEN - The best 60 HR & People Analytics articles of 2023 Part 1 | Part 2 – My tenth annual collection of HR and people analytics resources is spread across two articles and ten themes. Part 1 covers i) the future of work and people strategy, ii) workplace design and strategy, iii) AI and the world of work, iv) people analytics, and v) employee experience, listening and wellbeing. Part 2 covers: vi) the evolution of HR, HR operating models and the CHRO, vii) building a data driven culture in HR, viii) workforce planning, skills, and talent marketplace, ix) leadership and culture, and x) diversity, equity, inclusion and belonging. THOMAS RASMUSSEN, DAWN KLINGHOFFER, AND JEREMY SHAPIRO - HR in 2024: The Impact of People Analytics, AI & ML – In a special episode of the Digital HR Leaders podcast to kick off 2024, I was joined by Thomas Rasmussen, Dawn Klinghoffer, and Jeremy Shapiro to discuss the outlook for HR and people analytics in the coming 12 months. SERENA HUANG - How to Enhance Your Career in People Analytics - Serena H. Huang, Ph.D., who has led people analytics functions at companies including GE, PayPal and Kraft Heinz, joins me to discuss the common career paths observed in the people analytics field and how they have evolved over the years. KAZ HASSAN AND LUKE FARUGGIA - How to Bridge the Gap Between Customer and Employee Experience - What can HR learn from marketing's journey in using data, analytics and technology to understand and personalise the customer experience? How can we leverage these insights in HR to boost our employee experience initiatives? Kaz Hassan and Luke Faruggia join me to discuss these topics and more. THANK YOU Finally, this month I’d like to thank: Recruit CRM for nominating me as ‘The People Analytics Pioneer’ in their list of 50 Recruitment Influencers to Follow in 2024 Likewise, a huge thank you to 365Talents for including me as one of the Top 50 HR Influencers to Follow in 2024 Similarly, thanks to HRCap, Inc. for including me in their list of 10 HR Influencers who Provide Remarkable Insights The Social Craft (here) and The Talent Games (here) for also including me in their lists of HR and HR Tech leaders to follow. HRDConnect for quoting me in their article Data Literacy: A must-have for HR professionals in 2024. Gianni Giacomelli for including the Data Driven HR monthly in his list of seven must-read newsletters. HR Geckos for including Excellence in People Analytics as a book recommendation in their HR Bytes Newsletter for January 2024. Sebastian Szachnowski for including Excellence in People Analytics in his list of books to get better at people analytics. Leapsome for including the Digital HR Leaders podcast as one of its Top 10 HR Podcasts for 2024. Similarly, Alexandre Darbois for also including the Digital HR Leaders podcast as one of his 5 HR Podcasts. Melissa Meredith for using my 12 Opportunities for HR in 2024 article to highlight the importance of the HR-Finance partnership in building a thriving company. Bill Brown for also highlighting my 12 Opportunities for HR in 2024 article in his Eleven Trends Transforming the Future of Work in 2024. Mirro.io for including me as a contributor in their list of 15 HR Trends for 2024. Dhanesh K for including as one of his 10 Top HR Leaders to Follow. Lanteria HR for recommending me as one of their HR Experts to Follow in 2024. Semos Cloud for including my 12 Opportunities for HR in 2024 as part of their round-up of HR insights. Thomas Kohler for including my Best HR and People Analytics Articles of 2023 in their collection of HR resources to read. Thinkers360 for including me in their Top Voices EMEA 2023. ABOUT THE AUTHOR David Green ?? is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 90 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021. SEE ME AT THESE EVENTS I'll be speaking about people analytics, the future of work, and data driven HR at a number of upcoming events in 2024: Feb 21 - Discover how Leading Companies shift People Analytics from insight to impact (Webinar) Feb 28 - People Analytics World 2024: Exploring the Potential of Analytics and AI in Employee Experience (Zurich) March 4-6 - Gloat Live! (New York) March 14-15 - Wharton People Analytics Conference (Philadelphia) April 24-25 - People Analytics World (London) May 7-9 - UNLEASH America (Las Vegas) September 24-26 - Insight222 Global Executive Retreat (Colorado, US) - exclusively for member organisations of the Insight222 People Analytics Program October 16-17 - UNLEASH World (Paris) More events will be added as they are confirmed.
    generative AI
    2024年02月01日
  • generative AI
    Employers, Employees Disconnected over AI-related Job Displacements Looking at the fast-growing AI age, generative AI is having a great impact on job security. Most employees have expressed their 'psychologically unsafe' at work, while most employers are unconcerned about this. In fact, in order to generate values more efficiently, leaders are supposed to be open to generative AI and upskill their employees. 'Misaligned perceptions' among leaders, employees erode trust, report says. Employers and employees are not seeing eye to eye when it comes to the impact of generative AI in the workplace, hindering trust and preventing organisations from unlocking the potential of the technology at work. This is according to a new report from Accenture after collecting data from over 7,000 C-suite leaders and 5,000 employees of large organisations across 19 countries. According to the report,58%of employees are worried about generative AI's impact on job security. This comes amid recent research from the International Monetary Fund saying the rapid rise of AI will expose nearly 40% of jobs worldwide, while another report from Goldman Sachs said it will put at risk 300 million jobs. C-suite not concerned about AI But members of the C-suite don't appear too concerned about this outcome, as the report found that less than one-third of them feel job displacement is a concern for people. It also found a disconnect between employees and the C-suite when it comes to how gen AI will affect well-being. For 60% of employees, they believe it will increase stress and burnout, while only 37% of leaders see this as an issue. These disconnected views contribute to the lack of trust from employees, who don't believe their organisations will ensure positive outcomes when utilising generative AI, according to the report. "Misaligned perceptions between leaders and workers also erode trust," the report said. "This lack of trust puts the trifecta of opportunities at risk." 'Trifecta of opportunities' The report outlined three opportunities that organisations can maximise when it comes to gen AI and they are: Accelerating economic value Increasing productivity that drives business Fostering more creative and meaningful work of people But the lack of trust from their employees are preventing these organisations from leveraging these opportunities, despite 95% of them saying they see the value in working with AI, according to the report. Role of leaders in gen AI integration It also comes as two-thirds of employees said they don't have the technology and change leadership expertise to drive the reinvention need to take advantage of AI, according to the report. "There's a way, however, for leaders to close the trust gap and accelerate gen AI integration: Look at and emulate how leading organisations are leveraging gen AI in ways that are better for business and better for people," the report said. Only nine per cent of organisations in the survey were classified as "reinventors," who have achieved the capability for continuous reinvention and have maximised the potential of AI. More than half of these reinventors are already redesigning jobs and roles around AI as steps to reshape the workforce, according to the report. "Key to all of this: three-quarters are actively involving their people in their enterprise change efforts, while reskilling people," the report said. These organisations are being transparent to employees throughout the process to establish and foster trust, according to the report. Ellyn Shook, chief leadership and human resources officer, Accenture, underscored the role of leaders in the transition to gen AI. "Success starts with leaders who are willing to learn and lead in new ways, to scale gen AI responsibly, to create value and ensure work improves for everyone," Shook said in a statement. "It starts with asking a simple question: are people 'net better off' working here? This not only unlocks people's potential and drives bottom-line growth, but also paves the way for workers feeling comfortable, trusting and ready to work with gen AI. What we've learned from the past as leaders is that what happens next is up to us. The best outcomes are ours to shape." SOURCE HRD
    generative AI
    2024年01月22日
  • generative AI
    HR Predictions for 2024: The Global Search For Productivity 2024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.)
    generative AI
    2024年01月19日
  • generative AI
    2024年将人力资源趋势和预测付诸实践的九种方法 新的一年如约而至。 新年带来新的潮流引导者,新的推动者和新的撼动者,标新立异的想法随之而来,推动进步。而一些趋势会随着市场的发展而变化,年年如是。 每年我们都会回顾去年的成功与失败经验,同时展望2024年的新机遇。2024年将会是划时代的一年。 经济萧条逐渐结束,我们处于新时代的前沿——人工智能时代,在这个时代我们对于文盲的理解变成了“智能文盲”,在工作场景中愈发明显。与此同时产生了复合效应,一些地区的工人需要更公平的工作环境,改进的DEIB策略以及孤立高管层的持续性影响。对于人力资源领导者来说,成为这些变革的先锋从未像现在这样重要。 在2024年保持领先地位 领导者需要有勇气继续跳出人力资源的框框思考,使用新兴技术而不是害怕它,并利用多代员工的独特技能。 然而,了解哪些趋势将推动未来的工作是一回事,了解领导者如何将这些趋势付诸实践才是成功的关键。为了帮助您了解,我们汇总了一些2024年顶级人力资源趋势和预测的优秀示例,并提供了一些有关如何将其付诸实践的可行提示。 正如你所看到的,人力资源在2024年如何发展似乎没有定论。从领导力战略到新兴人工智能、技能投资、多样性、道德、灵活工作,相互交织,随着人力资源世界的发展而不断涌现。 但是,如果仔细观察上述每一个人力资源趋势,你会发现有一些共同点,我们都认为这些共同点将在2024年对人力资源发展产生巨大的影响。 1.领导力与管理发展 最优秀的人力资源领导者明白变革是不可避免的,应该接受改变。正如 Visier 在他们的文章《人力资源的新规则》中所说的那样,变革并不一定是一场技术驱动的革命。它可以像改变视角一样简单。 正如 Visier 首席客户官 Paul Rubenstein 所说,“首席人力资源官(CHRO)必须结合业务数据了解人的绩效、敬业度和生产力,以应对当今的复杂挑战”。 到2024年,人力资源领导者将不仅仅是人事领导者,他们必须在人事管理节奏之外密切参与业务战略,以了解他们与最高管理层一样的工作背景。 然而,根据 Gartner 关于2024年人力资源领导者的 5 大优先事项的报告,“73%的人力资源领导者确认他们组织的领导者和经理没有能力领导变革”。 为了解决这个问题,大卫·格林(David Green)优先考虑赋予人事领导者权力,承认他们的工作量不断增加——“75%的人力资源领导者表示,他们的经理对工作职责的增长感到不知所措(89),而超过50%的经理说自己感到筋疲力尽”。 伯纳德·马尔(Bernard Marr)正确地指出,我们需要在下一代的背景下思考管理和领导力发展,而不仅仅是下一代领导者,而是下一代劳动力。Culture Amp 的研究支持这一点,强调“我们工作场所的代际权力平衡正在发生变化”——非常重视培养当前和未来的领导者,以重新获得进入劳动力市场的信任。在复盘全球正在进行的大规模辞职现状,以及心理安全在有效的混合工作团队中发挥的重要作用时,这一点尤其明显。 因此,从重建习惯管理和管道调整,到取决于管理者独特技能而重新调整的工作流程(而不是期望每个管理者都以同样的方式领导),提供了大量的可能性,可以真正彻底改变2024年的领导方式。2.组织文化与混合工作 如果你认为弹性工作已经一去不复返是因为一群老板希望人们回到办公室,请你再想一想其他原因。因为混合时代才刚刚开始。 思考一下 David Green 关于他对2024年人力资源机会预测的文章中强调的要点: “十分之八的首席人力资源官表示,他们没有计划在未来12个月内减少远程工作的数量”。 “自大流行以来,90%的公司已经接受了一系列混合工作模式”。 “现在,大多数员工有超过25%的时间在远程工作”。 再加上2023年10月,美国近 30% 的带薪日是在家工作。 我们现在所处的时代,人力资源领导者在根据这些变化带领调整公司整个组织结构发展方向上占主要地位。 人力资源领导者应使用数据和分析来为个人发展和绩效设定更好的期望。这也将减少文化发展的“一刀切”方法,并创造Visier所说的“增加的确定性”。事实上,当他们的研究表明“这些执行办公室申报表的公司中有三分之一的公司很难招聘新员工”时,我们比以往任何时候都更需要实施真正的组织变革,以满足新员工的需求。 大卫·格林(David Green)对此的做法集中在“人性化领导”上,即将员工福祉和个性化服务放在人员管理和和企业管理的核心——“建立一个更公平、更健康、更人性化的组织不仅是对员工的‘正确做法’,也是推动企业成功的选择”。 当然,说起来容易做起来难——Gartner 说,“47%的人力资源领导者都不知道如何推动变革以实现所需的文化”。 但是,解决之道是否在于创造更有意义的体验?Culture Amp 延续了这一思维框架,强调创造“值得通勤的体验”对于保持团队创造力和动力至关重要。 伯纳德·马尔(Bernard Marr)考虑了混合工作时代团队凝聚力和有效管理的影响,Mercer在其文章《2024年5个人力资源趋势:你能做些什么来保持领先?》中也将其作为重中之重,尤其是以灵活的思维方式领导的想法。 总而言之,在劳动力规划、职业处理、办公室使用和绩效方面进行可持续的组织变革必须评估各种投入,例如技术、保留策略和员工倾听,还有许多方面将在下文讲。 3.技术集成与人工智能 现在我们正处于真正的时代趋势之中——人工智能,以及技术发展的前沿。 毫不奇怪,上面引用的每一项研究都强调人工智能(包括生成式人工智能),这是2024年人力资源的重大转变。但人工智能并没有从某个职业中剔除数百万美元,也不会导致公司大规模裁员、突然倒闭。人工智能正在改变工作方向,而不是工作本身,在人工智能时代,帮助工人培养人工智能相关技能将使人们在工作中保持安心和快乐。 仅从生产力、敬业度和业务成功的角度来看,人工智能就是一个游戏规则的改变者: Visier ——“29%的工人表示,使用生成式人工智能工具每天可以节省30分钟到一个小时,而18%的人可以节省三到四个小时”。 Unleash ——“76%的人力资源领导者已经在讨论如何在工作场所使用人工智能,38%的人正在正式评估这项新兴技术”。 Gartner ——“76%的人力资源领导者认为,如果他们不在未来12到24个月内采用和实施生成式 AI,他们将在组织成功方面落后”。 然而,在数字人力资源领域这样一个令人兴奋的领域里,成功取决于某个类似却独特的东西——了解自己的极限。例如,我们鼓励每位人力资源主管在阅读本文时问自己以下几点: 您了解组织人力关系与数字关系的局限性吗? 您是否审核了员工对数字化转型的准备情况? 您有没有评估过什么是好的变化,你知道如何衡量它吗? 最后,您是否了解人工智能供应商的格局——谁在制造什么,有什么作用,对你有用吗? 从这开始,您将更好地了解 AI 如何为您提供帮助。 4.基于技能的战略劳动力规划方法 “转型的头号挑战是缺乏工作能力和技能,但只有五分之二的人力资源专业人士了解其组织该有的技能”——Mercer《2024年5个人力资源趋势:你能做些什么来保持领先?》 战略性劳动力规划(SWP)需要一种默契,即战略本身意味着对招聘和留住人员的转变方式保持敏感,而平衡全部人力资源责任和预算潜力意味着要对 SWP 的流程进行长期审视。 这包括从更多基于技能的角度看待技术,尤其是在数字化转型时代。正如 Visier 所强调的那样,“86%的员工表示,他们的雇主应该在技能再培训方面发挥更多作用,以确保他们不会轻易被人工智能工具取代”。 Gartner 认为内部流动令人信服的影响是成功的关键,“66%的人力资源领导者(他们自己也同意)其组织内的职业道路与许多员工的职业道路相比并不引人注目”。 创造一个引人注目的工作文化不会付出很大的代价,而是意味着为员工和业务发展赋予意义,并为企业完美地穿针引线,帮助企业和个人发展相关专业知识。正如大卫·格林(David Green)所强调的那样,这意味着要推动以技能为基础的SWP招聘,并将更大的业务目标与人力资源优先级联系起来,Mercer证实了这一点。 5.人员分析和加强决策能力 如果数据不能产生影响,那它还有什么用呢? 说到这,David Green 再次强调了关于人员分析如何在 CHRO 层面创建增强决策文化的可用情报,该文化将集中在人员分析和 CHRO 之间改进的关系上, “Insight222 的第四届年度人员分析趋势研究发现,人员分析的重要性和影响力继续增长,22%的人事分析领导者正在向首席人力资源官报告”。 人员分析领导者和首席人力资源官都需要将大量不同的业务优先事项和数据集结合起来,以推动个性化决策。这包括将伦理、数据民主化、数据影响和业务优先事项的影响放在组织转型和成功的保护伞下。 这意味着最优秀的人员分析专业人员可以提供可分析并可付诸实施的洞见-正如 Visier 所强调的那样,这就是为什么如此多的小型和新兴公司处于竞争激烈的时代,因为他们可以使用大量超详细的大数据以更敏捷的方式创建更具吸引力、更敏锐的业务决策。 6.与业务保持一致 一致性对许多人来说有很大的意味,但从本质上讲,如果人力资源部门要继续并提升其价值并确保组织敏捷性,那么: HR 和最高管理层需要加强联系。 人力资源和财务部门需要更加紧密地联系在一起。 David Green 通过 Insight222 的研究来证实,人力资源和财务部门越来越需要同步工作——“在271家公司中,接受调查的65家公司确认他们已经与财务部门建立了合作伙伴关系,其中99%的公司报告说,人员分析团队在过去12个月中取得了巨的成果”。 在2024年,为人力资源分析构建业务案例不是我们必须做的事情,但可惜的是,这通常是正在进行的人力资源预算和投资的核心对话。 解决之道在于使用最清晰、最明显的工具——人员和数据——来讲述人力资源故事。这种共生关系正是Visier研究所强调的,并建议人力资源领导者将他们的人员管理思维方式转变为“人力资源是一种操作系统,而不是一种运营模式”。 7.提高人力资源和劳动力的技能 这场无休止的技能提升之战将持续到2024年。但它将有自己的特点,在某种程度上受到人力资源投资性质变化以及人工智能和新技术的光速发展的影响。 伯纳德·马尔(Bernard Marr)对此的独特见解说明了这一领域的情况-——“了解生成式人工智能等变革性技术将如何增强现有人员能力,以及需要哪些素质和能力(战略思维,解决复杂问题,创造力,情商)来补充机器的短板”。 在人工智能时代,人机界面的发展将对劳动力如何重新掌握技能和提高技能产生巨大影响,随着数字原住民担任越来越多的领导角色,一般计算机素养和用户体验/用户界面的持续发展也将产生巨大影响。但是,当“到2028年,44%的工人技能将被颠覆”时,技能提升应该被正确地推到投资组合优先事项清单的首位。 8.多元化、公平、包容和归属感(DEIB) 大流行后“大辞职”生态系统的一个支柱是工作场所中的平等——更公平的工作条件、更多的工作与生活平衡、更好的代表性和更具包容性的工作场所。 2023年,我们认为释放 DEIB 的力量是未来一年人力资源领导者的重要关注点,利用分析工具和情绪分析工具等多种工具来改善招聘可衡量指标。 那么我们现在处于什么位置呢?尽管我们为使 DEIB 脱颖而出所做的所有艰苦工作,但仍许多需要做,正如 Visier 在下面的研究。 DEIB 策略确实存在失去重点的风险。但请记住,一家拥有成熟的多元招聘文化、建立在包容性工作场所基础上的公司,对从公司业绩到 ESG 的方方面面都有深远的积极影响。正如大卫·格林(David Green)提醒我们的那样,大多数工人认为DEIB是一件好事,其商业案例也很清楚。 “Insight222 的研究发现,在2023年(连续第三年),DEIB 是人员分析增加最多商业价值的领域”。 2024年应该是我们推进 DEIB 的一年,保持势头并推动积极变革。 简而言之,坚持到底——现在放松警惕将导致长期劳动力规划(WFP)的严重失败,同时增加代表性不足的社区的变革机会。 9.提升员工敬业度和留任率的新方法 最重要的是,许多提高员工敬业度的新方法将决定未来一年的企业发展。 2023年独特的经济困境催化了英国、法国、德国和美国这一代人中一些最大规模的工作场所罢工,而普遍的技能短缺继续困扰着多个行业。伯纳德·马尔(Bernard Marr)将过去几年从被动接受不良工作规范到主动采取行动的转变带入了敏锐的视角——“根据美国劳工统计局的数据,涉及1,000多名工人停工,比2021年停工人数多了近 50%”。 Unleash 进行的研究表明,绩效和生产力已成为2024年人力资源领导者的首要任务,从敬业度中夺得桂冠。但在混合时代,二者缺一不可。敬业度被渗透到组织的方方面面,而2024年是实现这一目标的一年。 在2024年,我们需要通过加强员工体验的个性化,通过真实、有意义的参与来提高生产力(和幸福感),David Green 强调这是他为 HR 培养倾听组织的第12次机会。然而,正如 Unleash 所强调的那样,“不仅要关注员工调查中的指标,还要分享员工故事,以真正了解数据对高管的意义”。 为此,人力资源、员工和领导层之间应该建立一种,在道德领导、薪酬透明度(正如 Culture Amp 正确强调的那样)薪酬差距报告以及 Mercer 所强调的值得认可的基础上的关系。 将敬业度与业务和个人成果联系起来至关重要。Mercer薪酬调查和数据业务负责人Chi Tran完美地描述了这一演变。 “新冠肺炎疫情之前起作用的管理方式不再有效......留住员工将是一个重点,这意味着在职业道路、技能再培训和技能提升方面优先考虑员工福利。我们还看到,雇主将更大比例的薪酬预算用于可变薪酬,这些薪酬可以根据业务绩效进行调整。 2024年及以后的人力资源趋势 作为各地人力资源领导者的缪斯女神,Hung Lee 在他的文章《2024年:决定人力资源领域的7个趋势》中说到: “员工体验不容小觑——对于许多组织来说,这将是一场文化革命”。 在2023年经济动荡之后实施新战略将非常困难,而整个组织的支持是关键。如果能注意到上述情况,我们相信人力资源团队可以确保他们的组织采取积极主动的方法来提高工作场所绩效、幸福感、敬业度,以及至关重要的留住优秀员工。 2024年——充满无限可能性的一年! 利用 Insight222解锁人员分析功能 在 Insight222,我们的使命是通过将人员分析置于业务中心并提高人力资源专业的技能来使组织变得更好。Insight222 人员分析计划®是您通往知识、网络和成长世界的门户。该计划专为人员分析领导者及其团队开发,为您提供创造更大影响力所需的工具、见解和关系。 随着人员分析的格局变得越来越复杂,数据、技术和行业道德越来越重要,我们的计划汇集了一百多个组织,共同应对这些挑战。 Insight222 同行会议是 Insight222 人员分析计划®的核心组成部分。它们允许参与者一起学习、交流和共同创造,最终提高人员分析可以为其组织提供的业务价值。 SOURCE MyHRfuture  
    generative AI
    2024年01月17日
  • generative AI
    Hireology Named Best Applicant Tracking System of 2024 by Hotel Tech Report Hireology's recognition by Hotel Tech Report showcases their ability to understand the unique needs of the hotel sector and deliver innovative solutions. With an increasingly competitive job market, hiring the right personnel is crucial for hotels to maintain their high standards of service and guest satisfaction.   "We’re excited to announce that Hireology has ranked #1 overall on the Global Best Applicant Tracking Systems (ATS) list in the 2024 HotelTechAwards! The HotelTechAwards are produced by Hotel Tech Report, the leading authority on hotel software and digital transformation in the hotel industry." Often referred to as “the Grammys of hotel tech,” the HotelTechAwards rank the world’s best hotel software companies and products based on authentic, timely reviews from real users. Winners have been selected from more than 200 of the top technology products around the world. “The ranking process is simple, transparent, and unbiased — judging is based on time tested ranking factors developed specifically for the industry. Only verified hoteliers with hands-on experience using each product are allowed to participate in the voting process. This means that Hireology’s users decided the #1 ATS,” said Hotel Tech Report CEO, Jordan Hollander. With more than 10,000 customers, Hireology is the only applicant tracking system built to power better hiring for multi-location businesses that largely rely on skilled talent like hotels. Our platform makes it easy for users to source quality talent across key channels, streamline hiring with innovative recruitment automation, and make smarter hiring decisions rooted in data. “This recognition from Hotel Tech Report validates the work we’re doing at Hireology to help hotels capture more than their fair share of quality talent and fill critical revenue-driving roles faster,” said Adam Robinson, CEO at Hireology. “We’re grateful for every customer who helped us earn the top spot on this list, and we’re looking forward to helping even more hotels navigate today’s challenging hiring market and achieve their goals in 2024 and beyond.” In 2023 alone, Hireology launched several critical product updates that are designed to help their hotel customers not only attract better quality talent but also streamline the hiring process to fill critical roles faster, including: Indeed Sponsored Jobs integration: Sponsor jobs on Indeed directly from the Hireology platform — helping you maximize your reach to top candidates and make hires faster all without ever leaving Hireology Innovative ChatGPT integration: Leverage generative AI to instantly craft quality descriptions for new open jobs Enhanced candidate communication automations: Keep candidates engaged and reduce no-shows with automated messaging for routine updates Employee referral campaign templates and manager: Quickly launch optimized text and email campaigns and start driving quality referrals faster Hotel Tech Report’s lists are based on data from over 16,000 verified customer reviews during the HotelTechAwards period. These reviews were written and published between September 1,2023–December 15,2023, with participation from every major hotel brand and thousands of independents. In one review, a Hireology customer noted how they’ve driven better quality candidates and made smarter hiring decisions with our platform: “With Hireology I am able to track all of my candidates from the various recruiting websites and see all the candidates in one spot. With their screening tools I am able to pick out the candidate that has the most potential to be a good fit for the position. I have a better turn out and response rate for candidates that I have considered, and I have had a better quality of candidates who show up to the interview. The candidates that I have hired have become invaluable assets to my property.” Today’s announcement comes at the heels of the Winter G2 awards, where they placed in the top 10 in more than 200 reports and earned the top spot in 28—including referral programs, recruitment marketing, and HR analytics. Additionally, Hireology was recently named the American Hotel and Lodging Association’s (AHLA) Leadership Partner for Talent Technology. Learn more about this partnership here. To learn more about Hireology’s hospitality-specific ATS, take a self-guided virtual tour today! Or reach out to one of our experts for a free 1:1 consultation. SOURCE Hireology
    generative AI
    2024年01月10日
  • generative AI
    The best HR & People Analytics articles of December 2023 The December edition of my monthly compendium is an opportunity to reflect on the year that has nearly passed and look forward to what lies ahead. 2023 has proved to be another challenging year full of geopolitical tension, economic uncertainty, and climate inaction. For HR and people analytics professionals, it has been a year dominated by generative AI, skills, and the continuing journey of HR from support function to strategic partner. HR’s elevation to being a strategic partner is the underlying theme of my recently published 12 Opportunities for HR in 2024 article (see FIG 1). If you’d like to contribute suggestions for opportunities 11 and 12, please click here and add your suggestion in the comments. FIG 1: 12 Opportunities for HR in 2024 (Source: David Green) Despite managing to catch Covid on the flight home, I thoroughly enjoyed my recent trip to India, at the end of November, where I spoke at the Indeed FutureWorks event in Bangalore. A huge thank you to Aarti Deoskar, Jessie Paul, Rittik Mondal, Rohan Sylvester, and the Indeed team for inviting me. Looking for a new role in people analytics or HR tech? Before we get to this month’s collection of resources, I’d like to once again highlight the wonderful resource created by Richard Rosenow and the One Model team of open roles in people analytics and HR technology, which now numbers nearly 500 roles. Happy Holidays! I wish all readers who are taking a break over the festive season Happy Holidays, and a prosperous and healthy 2024. Thank you to everyone who has supported Insight222, myHRfuture and the Digital HR Leaders Podcast in 2023. It’s much appreciated. Share the love! Enjoy reading the collection of resources for December and, if you do, please share some data driven HR love with your colleagues and networks. Thanks to the many of you who liked, shared and/or commented on November’s compendium (including those in the Comments below). If you enjoy a weekly dose of curated learning (and the Digital HR Leaders podcast), the Insight222 newsletter: Digital HR Leaders newsletter is published every Tuesday – subscribe here. 2023 HR RETROSPECTIVES AND 2024 PREDICTIONS DAVE ULRICH - The State of HR: Looking Back and Envisioning Forward | McKINSEY - What matters most? Eight CEO priorities for 2024 | CULTURE AMP - 7 trends that will define HR in 2024 | KEN OEHLER - RADICL People Predictions for 2024 | VISIER – The New Rules of HR: 10 Workforce Trends for 2024 | i4CP – 2024 Priorities and Predictions Putting my own 12 Opportunities for HR in 2024 to one side, there are a plethora of other trends and predictions being published. Six resources that I recommend digging deeper into come from Dave Ulrich, McKinsey, Culture Amp, RADICL, Visier Inc. and Institute for Corporate Productivity (i4cp). (1) Dave Ulrich looks back on the main themes in HR in 2023, declares “Now is the time for HR,” and outlines four areas where his firm, The RBL Group, will be conducting think tanks in 2024. (2) Homayoun Hatami and Liz Hilton Segel of McKinsey present eight CEO priorities for 2024 including Learn to love your middle managers. (3) Didier Elzinga and Damon Klotz co-opt contributions from Stacia Sherman Garr, Justin Angsuwat, Dr Kirstin Ferguson AM, and Hung Lee for their thoughtful seven trends that will define HR in 2024 including greater pay transparency, staying human as intelligent tech evolves, and regaining trust. (4) RADICL’s Ken Oehler presents five people predictions for 2024, with my favourite being #4 Attention Shifts to Solving Distributed Team Effectiveness (see FIG 2 for RADICL’s model of distributed team effectiveness: Coordination, Connection and Competence). (5) Visier collect trends from a number of industry luminaries and practitioners including Wendy Evesque, Michael Salva, Melissa Arronte, and Eric Bokelberg, with the lead trend being: The CHRO Leads From the Outside-In. (6) Last but not least, in his Foreword to i4CP’s annual look at priorities and predictions, Kevin Oakes highlights the dominance of AI and provides an illuminating insight on the direct correlation between the adoption of AI and business performance: “AI Innovators are more likely to have higher market performance, increased levels of innovation and productivity, and healthier cultures than those that have been slower to adopt AI.” Now is the time for HR FIG 2: The Collaboration Opportunity for distributed team effectiveness (Source: RADICL) PEOPLE ANALYTICS ROB BRINER - Evidence-based HR and people analytics are the same, right? Afraid not Rob Briner examines the relationship between people analytics and evidence-based HR, explaining each of them, outlining the differences (see FIG 3) and concluding that: “While people analytics is a welcome and necessary development within the HR profession and certainly goes some way to helping HR become more effective, it is not, on its own, enough.” Rob also highlights the three key principles of evidence-based HR: (1) Incorporate multiple sources and types of evidence and information. (2) Adopt a structured and explicit process of gathering and using evidence. (3) Focus on the most trustworthy and relevant evidence. FIG 3: Differences between people analytics and evidence-based HR (Source: Rob Briner) PATRICK COOLEN - Establishing people analytics as a common practice (part II) This article by Patrick Coolen, which follows up Part 1 where he presented his People Analytics FIT model, dovetails nicely with Rob Briner’s article as it focuses on the evidence-based HR services provided by people analytics functions. In the article, Patrick recommends that to establish people analytics as a common practice companies should not only focus on becoming more mature in the evidence-based HR services but in integrating these services too. Patrick provides a roadmap to achieving this (see FIG 4) as well as outlining three reasons for integration: (1) Integration leads to faster and higher-quality delivery. (2) Integration attracts experienced people analytics leaders. (3) Integration supports being a strategic advisor. High impact people analytics practices integrate various evidence-based HR services FIG 4: Road map strategies for people analytics practices (Source: Patrick Coolen) JAAP VELDKAMP AND HELEEN GOET - How to determine your success KPIs in HR This is a great article by Patrick Coolen’s erstwhile colleague and successor as Head of People Analytics at ABN Amro, Jaap Veldkamp. In the article, Jaap – together with Heleen Goet – outline the process followed at ABN Amro for establishing a clear link between each HR service and its impact on business outcomes. It outlines a ‘define your success’ workshop conducted between the people analytics team and HR at the bank to link each service to output and outcomes (see example in FIG 5). The article also outlines two benefits of this approach: (1) It leads to better collaboration between various teams in HR. (2) It magnifies the broader advisory role of people analytics. FIG 5: Source: Jaap Veldkamp and Heleen Goet NAOMI VERGHESE AND DAVID GREEN - The Importance of Ethics in People Analytics for Leading Companies Naomi Verghese and I explore the critical topic of ethics, which is one of the eight characteristics of Leading Companies in People Analytics identified in the recently published Insight222 People Analytics Trends study. In the article, Naomi and I outline three key practices on ethics adopted by Leading Companies in their people analytics work. (1) Strong Ethical Principles - including the development of an Ethics Charter, with an example from Jaap Veldkamp of ABN AMRO. (2) Open Communication – including the ‘Fair Exchange of Value’, with a contribution from Dawn Klinghoffer on the importance of communicating value to employees. (3) Ethics Oversight – including the institution of an ethics and privacy council (see FIG 6). The “Fair Exchange of Value” is a key mantra for people analytics teams. If employees understand how their data will be used and see the benefit, it is far more likely that they will contribute data. FIG 6: Ethics and Privacy council for people analytics (Source: Excellence in People Analytics by Jonathan Ferrar and David Green) TOM REDMAN AND TOM DAVENPORT - The Rise of Connector Roles in Data Science In our research at Insight222, one of the characteristics of Leading Companies is that they invest in three key skills in their people analytics team: consultants, data scientists and behavioural scientists. In their article, Tom Redman and Tom Davenport outline the role of connectors, who bridge the organisational gaps that often thwart success with data science projects, and whose key responsibilities mirror many of those attributed to the people analytics consultant in the Insight222 Operating Model. These include: (1) Framing the problem to be solved. (2) Translating between business and technical people. (3) Communicating requirements, progress, and issues within the team. (4) Keeping track of progress toward the overall goal of deployment and organisational change when nobody else sees the big picture. The article outlines how connectors close the gap, provides guidance on how to manage connectors, and provides examples of what companies are trying in this area. Connectors help senior business leaders understand both the potential and challenges of data science, help data science leaders understand the top problems facing the business, and establish a portfolio of data science projects that aligns with business needs. BEN TEUSCH - An incomplete starter's guide to attrition metrics | SARA TIEW - Thriving Together: A Year on UOB's Culture Transformation Journey | JACKSON ROATCH – Lessons from Sports Analytics | LYDIA WU - HR in 2024: A Practitioner’s View | MATTHEW HAMILTON - How data quality is like a DIY haircut November has seen a number of articles written by current and recent people analytics leaders, which typically act as a spur and inspiration for the field. Five are highlighted here: (1) Ben Teusch, part of Meta’s people analytics team, provides a helpful to attrition metrics (see FIG 7). (2) Sara Tiew provides insights from UOB’s culture transformation journey over the last 12 months. (3) Jackson Roatch draws four lessons from sports analytics that we could look to apply in the “less perfect world” of people analytics. (4) Lydia Wu continues her prolific ‘Oops, did I think that out loud’ series by looking into her crystal ball to see what is in store for HR and people analytics in 2024. (5) The nearly as prolific Matthew Hamilton explains why the maxim of people assuming that the better the data quality, the better the analysis is often not correct. FIG 7: Source: Ben Teusch GENERATIVE AI AND THE FUTURE OF WORK PLACID JOVER - The Future of Work is Flexible In this article, Placid Jover, Chief Talent and Reward Officer, presents three innovations Unilever is making to embrace a move from owning to accessing talent. (1) The Skills Passport (“As companies jostle to build a complete picture of what they need and how to get there, we’re fast learning that the real currency is skills”). (2) The Internal Talent Marketplace (“We have already seen a 40% increase in productivity and a significant reduction in attrition directly linked to Flex Experiences”). (3) The Pixelated Workforce (“Breaking down work into its core elements or “pixels”, then dividing those up between permanent staff and contractors, with the AI recommending teams or individuals for missions based on how they work with others as well as how they perform”). For more from Placid, I recommend listening to this episode of the Digital HR Leaders podcast: How Unilever is Creating New Ways of Working for Its Employees. As companies jostle to build a complete picture of what they need and how to get there, we’re fast learning that the real currency is skills RICHARD FLORIDA, VLADISLAV BOUTENKO, ANTOINE VERTRANO, AND SARA SALOO – Rethinking Corporate Location Strategy: The Rise of the Meta City In their Harvard Business Review article, Richard Florida, Vladislav Boutenko, Antoine Vetrano, and Sara Nasir Saloo outline the structure and logic in where and how businesses locate their offices and compete for talent. Their research identifies the rise of a new type of city, the ‘Meta City,’ which combines elements of physical clustering with digital connectivity (see FIG 8). They argue that this makes location strategy even more important including corporate headquarters, innovation centres, and satellite offices — and more significantly, talent attraction and retention. A must-read for those involved in talent intelligence, hybrid work strategy and strategic workforce planning. FIG 8: Ranking the world’s Meta Cities (Source: Florida et al) PETER JOHN LAMBERT, NICHOLAS BLOOM, STEVEN DAVIS, STEPHEN HANSEN, YABRA MUVDI, RAFFAELLA SADUN, AND BLEDI TASKA - Research: The Growing Inequality of Who Gets to Work from Home Data is increasingly showing that there is a large and growing divide in terms of who gets to work from home. In their Harvard Business Review article, Peter John Lambert, Nick Bloom, Steven J. Davis, Stephen Hansen, Yabra Muvdi, Raffaella Sadun, and Bledi Taska, Ph.D. present research on job postings, which finds that remote work is far more common for higher paid roles, for roles that require more experience, for full-time work, and for roles that require more education. Managers should be aware of this divide, as it has the potential to create toxic dynamics within teams and to sap morale. For more from Nick Bloom, tune in to his conversation with me on the Digital HR Leaders podcast: Unmasking Common Myths Around Remote Work. FIG 9: Work-from-home opportunities are more common for highly-paid jobs (Source: Lambert, Bloom et al) RYAN ROSLANSKY - Talent Management in the Age of AI | GIANNI GIACOMELLI - Learning and Talent Management in the Age of AI | TOMAS CHAMORRO-PREMUZIC - 4 science-backed reasons AI is better at predicting your potential in a job | DAVID L. SHRIER, JULIAN EMANUEL, AND, MARC HARRIS – Is Your Job AI Resilient? | NADA R. SANDERS AND JOHN D. WOOD - The Skills Your Employees Need to Work Effectively with AI A key opportunity for HR in 2024 will be to prepare the organisation and HR for the age of AI. Here are five articles that support this imperative. (1) LinkedIn CEO Ryan Roslansky highlights three big shifts to support success a) redefine jobs as a collection of a skills and tasks, not titles, b) bring skills and workforce learning to the centre of talent management, and c) embrace AI to focus teams on human-to-human collaboration, and shares examples from IBM, Genpact, Unilever as well as LinkedIn. (2) Gianni Giacomelli provides more detail on the Genpact example cited by Ryan in his article explaining how they have connected internal mobility, learning, engagement and collaboration (see FIG 10). (3) The brilliant Dr Tomas Chamorro-Premuzic digs into the science to present four ways that AI is better at predicting potential including how AI can increase fairness and diversity. (4) David Shrier, Julian Emanuel, and Marc Harris outline their research on which jobs will be most affected by AI, including which stand to benefit the most from augmentation by AI (see FIG 11). (5) Nada Sanders and John Wood present findings from their research, which highlights two key areas of investment in skills related to AI: a) effective interpersonal skills, and 2) domain knowledge that can help workers get the most — and make the best decisions — when working with AI tools. FIG 10: Source – Gianni Giacomelli, Genpact FIG 11: AI Proficiency relative to human by cognitive task (Source: Shrier et al) THE EVOLUTION OF HR AND DATA DRIVEN CULTURE MARIE NEICU, JOAN BEETS, FRANK VAN DEN BRINK, BEAU HOES, AND EDIS PAJIC – Humanized Growth and Multistakeholder Value Creation: Perspectives from Chief Human Resources Officers| McKINSEY - How is the CHRO role changing? Two resources exploring perspectives from chief human resource officers and how the role is changing. Firstly, the KennedyFitch team of Maria Neicu, Joan Beets, Frank van den Brink, Beau Hoes, and Edis Pajic share the findings from structured interviews with 30 CHROs including Janine Vos, Katarina Berg, Paulo Pisano (also see episode of the Digital HR Leaders podcast with Paulo below), Mala S., and Loren I. Shuster. The report is framed around the concept of humanised growth, which is defined as: “Humanized Growth addresses the needs of all shareholders, consumers, colleagues, community and the capital Markets.” It explores the role of the people function as a strategic partner, how to harness technology for impact, how to advance diversity, equity and inclusion, and why humanised growth starts with the employee experience. The second article from McKinsey examines the evolution of the HR operating model, how CHROs are putting the ‘human’ back into human resources, how GenAI will affect the HR function, and how CHROs can build the leadership capabilities required for an agile transformation. WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS RICHARD ROSENOW - The SOAPI Framework - A New Lens for Modern Workforce Planning Richard Rosenow is one of the best thinkers in our field and demonstrates it with his paper for One Model introducing his SOAPI framework for workforce planning. As he explains, it is a methodology that offers a structured method to break workforce planning into component parts. Each component represents a pillar, collectively forming the discipline of workforce planning. These are: (1) Strategy, (2) Operations (3) Analytics, (4) Planning, and (5) Intelligence. The paper breaks each of these down, and details what happens if one of these pillars is missing (see FIG 12). FIG 12: Source: Richard Rosenow, One Model SCOTT REIDA - Zero-based workforce planning with ChatGPT in Tableau A brilliant, practical, and open-source guide on zero-based workforce planning with inputs from ChatGPT and outputs in Tableau, which has been created by Scott Reida, a workforce strategist at AWS. Scott defines zero-based workforce planning as “A methodology that can shape how businesses align their human capital with organizational goals and enable a more cost-effective solution that gets closer to having the right people at the right time.” His article provides a step by step guide to creating a dashboard (available here) that utilises outputs from ChatGPT for demand and aligns them with the supply of FTEs, facilitating the understanding of capability gaps. FIG 13: Source: Scott Reida JEFF WILLIAMSON AND DONNCHA CARROLL - How to Start Smart With a Talent Marketplace Despite some of the hype, launching an internal talent marketplace can be a significant challenge for organisations. In this article, Jeffrey Williamson and Donncha Carroll share the journey to implementing a talent marketplace at Booz Allen and the key lessons learned with regards to user adoption and change management. The article outlines four lessons: (1) Bring on the gamification (gamifying learning and offering recognition and rewards to employees who invested in their own development). (2) Data goals must be relevant to individual career goals. (3) Even change management needs to change (see FIG 14). (4) Momentum, motivation, and measurement matter a great deal. FIG 14: Four Culture Challenges to Conquer with a Talent Marketplace (Source: Jeff Williamson and Donncha Carroll) BRIAN FISHER, MELBA GANT, VASILIS HATZOPOULOS, KATIE JENKINS, HEATHER RYAN, AND PETER STEVENSON - 2023/2024 skills snapshot survey report: Skills-powered practices, future pay and effectiveness Mercer’s fourth annual Skills Snapshot Survey has a wealth of insights and guidance that highlight the progress many companies are making to embrace platforms and data to action skills-based strategies. In the paper, the authors (Brian Fisher, Melba Gant, Vasilis Hatzopoulos, Katie Jenkins, ?Heather Ryan , and Peter Stevenson) outline the benefits of skills-based practices (see FIG 15), how to build a skills foundation, how to determine the frequency of skill assessment, how to tackle skills-based rewards programs, and provide five steps to building a skills-based talent strategy: (1) Build the business case. (2) Align the key performance indicators. (3) Design with the end in mind. (4) Prioritise change management. (5) Drive and sustain. Also features contributions from Amy Baxendale and Anshul Sheopuri. FIG 15: The benefits of skills-based practices (Source: Mercer) EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING NICK LYNN - Can you have high employee engagement and high turnover? Nick Lynn reveals that nearly 20% of companies have both high employee engagement and high turnover; and then provides a wealth of guidance on what you can do about it if that’s the case for your company. He breaks down employee engagement and although it can be related to retention, why it is different. Nick shares insightful research from the CIPD on the and WTW on the drivers of employee engagement and experience, with the latter providing analysis and guidance on the links between engagement, performance, and retention. The article highlights WTW research by angela paul and Stephen Young, where they segmented 350 companies according to both the level of employee engagement and the level of retention, comparing each to their respective industry average (see FIG 16), and how companies in the top right quadrant (‘Value Drive’) also have a performance advantage, delivering the best profits and growth (also see FIG 16). Finally, Nick outlines a three-step approach for companies in the Value Risk category: Understand — Prioritise — Spark Change. I also recommend subscribing to Nick’s equally insightful EX Leadership Newsletter. FIG 16: Source – WTW INDRANEEL BANERJEE, AVINASH CHANDRA DAS, JATIN PANT, AND SHIKHA SHARMA - Employee experience still matters: Talent retention at GCCs While focused on ways to improve employee retention at Global Capability Centres, the five actions to improve employee experience outlined by Indraneel 'Indy' Banerjee, Avinash Chandra Das, Jatin Pant, and Shikha Sharma in their article for McKinsey could be implemented in other business areas. The five actions are (1) Use personas and journeys to customise EX. (2) Reimagine the role of manager to emphasise coaching and mentorship (see FIG 17). (3) Find new ways to embed culture and values for a hybrid work environment. (4) Redesign the office for collaboration and connection. (5) Rethink the traditional workday. Executives should treat EX as seriously as CX by being more scientific and more tailored in their approach. FIG 17: The roles of manager need to be redesigned to focus more on coaching and mentoring (Source: McKinsey) LEADERSHIP AND CULTURE RAINER STRACK, SUSANNE DYRCHS, AND ALLISON BAILEY - Use Strategic Thinking to Create the Life You Want How can we apply the learnings from corporate strategy projects to our own lives? That’s the unlikely – but ultimately captivating – exam question tackled by BCG’s Rainer Strack, Dr. Susanne Dyrchs, and Allison Bailey in their absorbing Harvard Business Review article. The authors present the seven steps they typically use to conduct a corporate strategy project and show how these can be adapted to an individual (see FIG 18). They then describe each of the seven steps with insights and powerful visualisations, as well as demonstrating how to develop a personal life strategy and summarise it on a single page. File under must-read. FIG 18: From corporate strategy to life strategy (Source: Strack et al) MCKINSEY HEALTH INSTITUTE - Reframing employee health: Moving beyond burnout to holistic health Jacqui Brassey, PhD, MA, MAfN (née Schouten), Brad Herbig, Barbara Jeffery, and Drew Ungerman present the key findings from a recent McKinsey Health Institute study that offers insights into how leaders can help create a workplace that prioritises physical, mental, social, and spiritual health. Three standout findings are (1) Employees who had positive work experiences reported better holistic health, are more innovative at work, and have improved job performance. (2) For employees, good holistic health is most strongly predicted by workplace enablers, while burnout is strongly predicted by workplace demands (see FIG 19). (3) Organisational, team, job, and individual interventions that address demands and enablers can boost employee holistic health. FIG 19: Source: McKinsey Health Institute DIVERSITY, EQUITY, INCLUSION, AND BELONGING McKINSEY - Diversity matters even more: The case for holistic impact The fourth report in a McKinsey series stretching back to 2015, investigating the business case for diversity. The main takeaway is that the 2023 study finds that the business case is the strongest it has been yet with leadership diversity being convincingly associated with business performance, societal impact and employee experience (see FIG 20). The full 52 page report details case studies from the likes of IHG Hotels & Resorts, DHL Group, and Air New Zealand, as well as presenting five levers for change for moving from commitment to action. Kudos to the authors: Dame Vivian Hunt, Sundiatu Dixon-Fyle, Celia Huber, Maria del Mar Martinez, Sara Prince, and Ashley Thomas. FIG 20: The business case for diversity on executive teams and financial outperformance (Source: McKinsey) HR TECH VOICES Much of the innovation in the field continues to be driven by the vendor community, and I’ve picked out a few resources from December that I recommend readers delve into: ERNEST NG - What Matters Now: Embracing the New Era of Disclosures for All HR Technology Stakeholders – Ernest Ng, PhD of HiredScore explains why disclosure is a critical tool to maintain trust and legitimacy across four areas (1) Employer Disclosure with Candidates/Employees. (2) Solution Provider Disclosures to the Buyer. (3) Organisational Disclosures to the Government. (4) Industry Analysts with Consumers – the latter is one, I’d personally like to see more of us talking about as we head into 2024. JAMAL MAZYCK - How Employee Resource Groups help build a culture of belonging - Jamal Evan Mazyck, Ed.D provides insights from Atlassian’s journey in building Employee Resource Groups, and how they engender a sense of belonging: “It’s not enough to recruit talent from underrepresented groups and give them equal access to opportunities; once they’re in the door, these employees need to feel that they belong.” STEVE HUNT - The Skills Management Revolution: one-year, two-year, and three-year predictions – SAP’s Steve Hunt breaks down skills management in his article, which covers what it is, why it’s important, the three ontologies companies are building with skills management solutions (labour market, organisational and employee/candidate/contractor), and a one, two, and three year outlook on how these solutions will reshape the nature of work and organisations. FIG 21: Source – Steve Hunt FRANCISCO MARIN - Reducing Employee Attrition with ONA: A Case Study from a European IT Company - Francisco Marin from Cognitive Talent Solutions presents a case study of a European IT company to showcase how ONA can be used to help predict and mitigate attrition, ultimately leading to a more stable and productive workforce. PHIL ARKCOLL - Developer Experience: The Developer Centric Approach to Productivity - Another great read from Philip Arkcoll of Worklytics. This time Phil outlines how by using active and passive listening with the objective of working to improve the developer experience, organisations can get developer buy in, boost productivity and attract top technical talent. FIG 22: Source – Phil Arkcoll, Worklytics PODCASTS OF THE MONTH In another month of high-quality podcasts, I’ve selected four gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below): JASON AVERBOOK - Generative AI: Revolutionizing the Employee Experience - In this episode of the Mercer | Leapgen AI-volution: Redefining HR podcast, Jason Averbook explores the transformative power of generative AI in shaping the future of employee experience. AARON DE SMET, ANGELIKA REICH, ROBERTA FUSARO, AND LUCIA RAHILLY - Who is productive, and who isn’t? Here’s how to tell - In an episode of The McKinsey Podcast, Aaron De Smet and Angelika Reich talk to hosts Roberta Fusaro and Lucia Rahilly about their latest research on employee productivity. KAYE SLAY, VANDANA BHAGTANI, STACIA GARR, AND DANI JOHNSON - Narrowing Scope & Purpose to Ease the Transition to a Skills-Based Organization – Another great episode of RedThread Research’s Workplace Stories podcast where Vandana Bhagtani and Kaye Slay-Pruitt, UXC share with Stacia Sherman Garr and Dani Johnson how they’ve worked together to develop a strategy for transitioning Hewlett Packard Enterprise to a skills-based organisation. DOUG SHAGAM, COLE NAPPER, AND SCOTT HINES - People Analytics at J&J & Playing Drums – Doug Shagam joins Cole Napper and Scott Hines, PhD on the Directionally Correct podcast to discuss some of the great work the J&J team is doing in people analytics. VIDEO OF THE MONTH AMY EDMONDSON, ADAM GRANT, AND DES DEARLOVE - Decoding failure, debunking feedback, & harnessing learning for success A fascinating conversation with Amy Edmondson and Adam Grant, who have just been recognised as #1 and #2 respectively on the prestigious Thinkers50 list of management thinkers. In the discussion with Des Dearlove, Amy and Adam discuss how to manage (and maximise learning from) failure and how to unlock hidden potential (it’s not about where you start; it's how far you can go). BOOK OF THE MONTH KATE BRAVERY, ILYA BONIC, AND KAI ANDERSON - Work Different: 10 Truths for Winning in the People Age I'm currently reading the recently published book by Kate Bravery, Ilya Bonic, and Kai Anderson, which is based around 10 'truths' that are shaping the world of work. Three of the truths are: (1) Purpose rules and empathy wins. (2) Intelligence is getting amplified. (3) Skills are the real currency of work. Packed with insights, guidance, and examples, the book should be an indispensable resource for executives, managers, board members, human resources professionals, and other business leaders. FROM MY DESK December saw the final four episodes of Series 35 of the Digital HR Leaders podcast, sponsored by our friends at HiBob . Thank you to Louis Gordon . MADELINE LAURANO - How to Buy HR Tech and Use It Effectively – Top industry analyst Madeline Laurano joins me to discuss the key themes on HR Tech in 2023, and what lies ahead in 2024 (see video below). SARAH REYNOLDS - A CMO's Approach to Mastering Pay Transparency – HiBob’s Sarah Reynolds joins me to discuss the intersection of HR and marketing, the business benefits of pay transparency and its importance for DEIB. PAULO PISANO - Booking.com’s 360-Degree View of Employee Experience – In our conversation, Paulo Pisano, Chief People Officer, outlines how Booking leverages data to enhance employee experience, streamline talent management across its international operations, and ensure that its workforce strategies are both effective and adaptable in a constantly changing business environment. HEBBA YOUSSEF - Navigating HR Tech Triumphs & Avoiding Failures – Hebba Youssef, Chief People Officer at Workweek joins me to discuss the common pitfalls of implementing HR technology and strategies for success. THANK YOU Finally, this month I’d like to thank: Abhilash Bodanapu for hosting me for lunch during my trip to Bangalore (see here) – it was wonderful to learn more about the people analytics journey bat Capgemini Raja Sengupta (see here) for such a wonderful discussion on people analytics in Bangalore. It was wonderful to finally meet in person! Geraldine Woloch-Addamine for including me in her list of Four Inspiring Voices on LinkedIn – it is humbling to be included in the same list as Amy, Adam, and Dave Teamflect for including me in their list of 18 HR Influencers to Follow Lanteria HR for including in their list of 10 favourite HR leaders of 2023 Dariush Franczak for including the November edition of the Data Driven HR Monthly in his list of HR resources Thinkers360 for including the Digital HR Leaders podcast in their comprehensive list of 125 Podcasts from Thinkers360 Thought Leaders CollectiveHR for including the Digital HR Leaders podcast with Nick Dalton in one of their Content of the Week collections The prolific Esther Abraas for including the Digital HR Leaders podcast episode with Laura Wright Shubert in her collection of resources on strategic workforce planning ___________________________________________________________________ ABOUT THE AUTHOR David Green ?? is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 90 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021.
    generative AI
    2023年12月24日
  • generative AI
    人工智能正在以比我预期更快的速度改变企业学习AI Is Transforming Corporate Learning Even Faster Than I Expected 在《AI正在比我预想的更快地改变企业学习AI Is Transforming Corporate Learning Even Faster Than I Expected》这一文中,Josh Bersin强调了AI对企业学习和发展(L&D)领域的革命性影响。L&D市场价值高达3400亿美元,涵盖了从员工入职到操作程序等一系列活动。传统模型正在随着像Galileo™这样的生成性AI技术的发展而演变,这改变了内容的创建、个性化和传递方式。本文探讨了AI在L&D中的主要用例,包括内容生成、个性化学习体验、技能发展,以及用AI驱动的知识工具替代传统培训。举例包括Arist的AI内容创作、Uplimit的个性化AI辅导,以及沃尔玛实施AI进行即时培训。这种转型是深刻的,呈现了一个AI不仅增强而且重新定义L&D策略的未来。 在受人工智能影响的所有领域中,最大的变革也许发生在企业学习中。经过一年的实验,现在很明显人工智能将彻底改变这个领域。 让我们讨论一下 L&D 到底是什么。企业培训无处不在,这就是为什么它是一个价值 3400 亿美元的市场。工作中发生的一切(从入职到填写费用账户再到复杂的操作程序)在某种程度上都需要培训。即使在经济衰退期间,企业在 L&D 上的支出仍稳定在人均 1200-1500 美元。 然而,正如研发专业人士所知,这个问题非常复杂。有数百种培训平台、工具、内容库和方法。我估计 L&D 技术空间的规模超过 140 亿美元,这甚至不包括搜索引擎、知识管理工具以及 Zoom、Teams 和 Webex 等平台等系统。多年来,我们经历了许多演变:电子学习、混合学习、微型学习,以及现在的工作流程中的学习。 生成式人工智能即将永远改变这一切。 考虑一下我们面临的问题。企业培训并不是真正的教学,而是创造一个学习的环境。传统的教学设计以教师为主导,以过程为中心,但在工作中常常表现不佳。人们通过多种方式学习,通常没有老师,他们寻找参考资料,复制别人正在做的事情,并依靠经理、同事和专家的帮助。因此,必须扩展传统的教学设计模型,以帮助人们学习他们需要的东西。 输入生成人工智能,这是一种旨在合成信息的技术。像Galileo™这样的生成式人工智能工具 可以以传统教学设计师无法做到的方式理解、整合、重组和传递来自大型语料库的信息。这种人工智能驱动的学习方法不仅效率更高,而且效果更好,能够在工作流程中进行学习。 早期,在工作流程中学习意味着搜索信息并希望找到相关的东西。这个过程非常耗时,而且常常没有结果。生成式人工智能通过其神经网络的魔力,现在已经准备好解决这些问题,就像 L&D 的瑞士军刀一样。 这是一个简单的例子。我问Galileo™(该公司经过 25 年的研究和案例研究提供支持):“我该如何应对总是迟到的员工?请给我一个叙述来帮助我?” 它没有带我去参加管理课程或给我看一堆视频,而是简单地回答了问题。这种类型的互动是企业学习的大部分内容。 让我总结一下人工智能在学习与发展中的四个主要用例: 生成内容:人工智能可以大大减少内容创建所涉及的时间和复杂性。例如,移动学习工具Arist拥有AI生成功能Sidekick,可以将综合的操作信息转化为一系列的教学活动。这个过程可能需要几周甚至几个月的时间,现在可以在几天甚至几小时内完成。 我们在Josh Bersin 学院使用 Arist ,我们的新移动课程现在几乎每月都会推出。Sana、Docebo Shape和以用户为中心的学习平台 360 Learning 等其他工具也同样令人兴奋。 个性化学习者体验:人工智能可以帮助根据个人需求定制学习路径,改进根据工作角色分配学习路径的传统模型。人工智能可以理解内容的细节,并使用该信息来个性化学习体验。这种方法比杂乱的学习体验平台(LXP)有效得多,因为LXP通常无法真正理解内容的细节。 Uplimit是一家致力于构建人工智能平台来帮助教授人工智能的初创公司,它正在使用其Cobot和其他工具为学习人工智能的技术专业人员提供个性化的指导和技巧。Cornerstone 的新 AI 结构按技能推荐课程,Sana 平台将 Galileo 等工具与学习连接起来,SuccessFactors 中的新 AI 功能还为用户提供了基于角色和活动的精选学习视图。 识别和发展技能:人工智能可以帮助识别内容中的技能并推断个人的技能。这有助于提供正确的培训并确定其有效性。虽然许多公司正在研究高级技能分类策略,但真正的价值在于可以通过人工智能识别和开发的细粒度、特定领域的技能。 人才情报领域的先驱者Eightfold、Gloat和SeekOut可以推断员工技能并立即推荐学习解决方案。实际上,我们正在使用这项技术来推出我们的人力资源职业导航器,该导航器将于明年初推出。 用知识工具取代培训:人工智能在学习与发展中最具颠覆性的用例也许是完全取代某些类型培训的潜力。人工智能可以创建提供信息和解决问题的智能代理或聊天机器人,从而可能消除对某些类型培训的需求。这种方法不仅效率更高,而且效果更好,因为它可以在个人需要时为他们提供所需的信息。 沃尔玛今天正在实施这一举措,我们的新平台 Galileo 正在帮助万事达卡和劳斯莱斯等公司在无需培训的情况下按需查找人力资源信息和政策信息。LinkedIn Learning 正在向 Gen AI 搜索开放其软技能内容,很快 Microsoft Copilot 将通过 Viva Learning 找到培训。 这里潜力巨大 在我作为分析师的这些年里,我从未见过一种技术具有如此大的潜力。人工智能将彻底改变 L&D 格局,重塑我们的工作方式,以便 L&D 专业人员可以花时间为企业提供咨询。 L&D 专业人员应该做什么?花一些时间来了解这项技术,或者参加Josh Bersin 学院的一些新的人工智能课程以了解更多信息。 随着我们继续推出像伽利略这样的工具,我知道你们每个人都会对未来的机会感到惊讶。L&D 的未来已经到来,而这一切都由人工智能驱动。
    generative AI
    2023年12月13日
  • 12