Josh Bersin - 北美华人人力资源协会

Josh Bersin

AI Agents, The New Workforce We’re Not Quite Ready For (Agentic AI) Josh Bersin 刚刚谈到：AI代理人的兴起标志着工作方式的一次革命。这些AI代理人不仅仅是工具，而是未来的团队成员。从开发培训课程到管理招聘过程，AI代理人的能力正被企业系统广泛利用。科技领袖和投资者对此展现出了极大的兴趣和投资。企业需要为这种变革做好准备，包括安全性和管理实践的更新。我们一起来看下，英文原文附录链接在最后！ AI智能体，新一代劳动力，我们还没有做好准备智能体正在到来，智能体正在到来。如果你关注AI技术市场，你就会知道，最近有很多关于“智能体AI”的讨论。换句话说，我们的AI助手开始拥有更多自主能力。不再只是回答问题和写诗，它们现在可以代表我们“做事情”。这正是长久以来预测的AI下一个大趋势。埃里克·施密特最近谈到了这一点，微软也在讨论，像Mayfield这样的投资者正在投入资金。而这种演变确实将彻底革新我们的系统。可以这样想：“大语言模型”是我们过去两年一直在学习的内容，它们现在正逐步转变为“大行动模型”。智能体不仅仅会回答问题，它还会为我们做事情。消费场景是无穷无尽的：为我预订航班，为我买票，向我的朋友发送电子邮件。但在商业领域，这种转变将颠覆并破坏我们的许多企业系统。它还将改变我们工作的方式、管理的方式以及我们对团队的思考方式。考虑我们与供应商讨论的两个HR用例。学习与发展（L&D）AI智能体想象一下，你指示一个L&D AI智能体“为我们的销售人员创建一个15分钟的课程，以教授他们如何定位我们的新产品”。AI智能体将根据你的输入（课程时长、目标受众等），向主题专家发送电子邮件，视频记录他们的评论和专业知识，整合新产品信息，构建课程，并将其发送给L&D负责人进行验证。作为经理，你可以审查课程，并指示智能体收紧信息或添加更多主题，课程将重新创建，然后你可以说“可以上线了”。智能体随后会将课程发布到学习管理系统（LMS）中，向所有销售人员群发电子邮件，并开始监控学习活动。几小时后，智能体会运行分析，并向经理反馈进展情况。是的，这在今天完全可能。而且很快就会启动。再来看第二个例子。招聘AI智能体人才招聘负责人收到了大量关于高级软件工程师的职位要求。她指示招聘AI智能体开始搜索。智能体询问招聘人员的地点偏好、职位级别选择、薪资范围和技能要求，然后开始工作。智能体扫描LinkedIn和其他招聘工具，查看ATS中的现有候选人，同时也查看所有内部员工的合格技能。智能体随后优化这份名单，创建一个“面试候选人短名单”，并回到招聘负责人那里征求意见。在就地点和薪资范围达成一致后，智能体返回并向这些候选人发送了一封富有吸引力的电子邮件，并附上一个视频面试门户链接，让他们进行面试。面试被录制下来，AI智能体使用面试智能工具来评估和筛选候选人，询问他们的时间安排，并为他们安排现场面试。在此过程中，AI智能体会查看他们的背景，搜索社交媒体，查看他们的各种联系，并可能查看他们的GitHub等平台和其他凭证，然后为每位候选人创建一个档案。这些智能体很快就会出现，对我们许多人来说，它们看起来和感觉上会像“员工”一样。我们将不得不对它们进行培训、入职和指导。随着它们在各自的角色中“成熟”并成长，我们将它们连接到更多的系统、更多的人和更多的数据上。 Lattice的首席执行官萨拉·富兰克林大约一个月前实际上提出了这个概念，尽管遭到了反对声音，但我认为她是对的。这些智能体实际上将属于组织结构图的一部分。我们的工作将是管理它们，确保它们的安全，并监督它们的安全性。还有更多内容即将到来虽然感觉像科幻小说，但这一切正在发生。而且它不仅将改变我们的HR技术堆栈，还将改变整个企业技术格局，也让我们的HR角色变得更加轻松。原文来自: https://joshbersin.com/2024/09/agentic-ai-ai-agents-the-new-workforce-were-not-quite-ready-for/

Josh Bersin
2024年09月06日
Josh Bersin

Cornerstone Galaxy: Acquisition Of SkyHive Could Pay Off Cornerstone在人力资源技术领域长期以来一直是学习管理系统（LMS）的领导者。公司最近推出了Galaxy，这是一个集成了人工智能的全新人才管理平台。这一重大进展是在一系列收购之后实现的，尤其是最近收购了SkyHive，显著增强了公司的数据处理能力。Galaxy平台通过提供全面的技能发展、绩效管理和员工晋升系统，为HR技术空间树立了新标准。 Galaxy区别于市场上其他基于技能的或智能平台，例如Eightfold主要从人才获取开始，而Gloat着眼于人才流动性。Galaxy则从另一个角度出发，即员工发展，这是由Cornerstone在学习与发展（L&D）领域深厚的背景所支撑的。Galaxy系统内置了完整的用户界面，能够推断技能，让员工标记和评估自己的技能，帮助员工找到并完成各种学习形式，管理合规性和认证程序，通过任务、评估或管理辅导提升技能。通过整合性能管理、发展计划、继任计划，以及招聘过程，Galaxy使公司能够通过绩效管理推动技能发展。在收购SkyHive之前，Cornerstone试图仅使用其LMS信息的数据集来实现这一目标，但这些数据并不足以构建完整的人工智能语料库。通过这次收购，Cornerstone获得了一个完整的劳动力市场数据系统、一个公司中立的职位架构以及大量行业技能，使Galaxy能够与其他主要的人才智能和人才市场供应商直接竞争。 Cornerstone spent the last decade acquiring LMS and talent software companies, all in a goal to build an integrated skills platform. Finally, after years of hard work and integration, the company introduces Galaxy, an advanced offering in the world of AI-powered HR systems. Before I explain Galaxy, the history is important. Founded in 1999, Cornerstone started as an e-learning platform company (CyberU). The company established a foothold in the emerging LMS market and grew through strong marketing, sales, and product innovation. Since then the company has gone public, reached a $5.2 billion valuation, and was then acquired by a private equity firm (Aug. 2021, three years ago). The new management team continued to acquire companies (EdCast, SumTotal, Talespin, and most recently SkyHive) and has now stitched these systems together into a unified platform called Galaxy. Galaxy, as I show below, is a skills-powered integrated talent management platform, built around the core of learning management. And this is what makes it unique. The other talent intelligence or skills-based platforms started elsewhere. Eightfold started in talent acquisition; Gloat started in talent mobility; SeekOut started in recruiting; Beamery started in CRM; and players like Retrain.ai and NeoBrain started in more vertical domains. Each of these companies use large-scale profile data to infer skills, give companies tools to find and match candidates, and eventually to deliver learning. Cornerstone, with deep background in L&D, is coming at this from another direction: employee development. The Galaxy system, which is built into a complete user interface, infers skills, lets employees tag and assess their skills, helps employees find and complete many forms of learning, manage compliance and certification programs, and advance skills through gigs, assignments, assessments, or management coaching. And since Cornerstone is an integrated talent suite, the system lets companies drive skills through performance management, development planning, succession planning, and also recruiting. Before the acquisition of SkyHive, Cornerstone was trying to do this with its own data set of LMS information. This data, which includes billions of learning records, was simply not sufficient to build out the entire AI corpus. By acquiring SkyHive, Cornerstone gained an entire labor market system of data, a company-neutral job architecture, and lots of industry skills. This brings Galaxy into direct competition with the other major talent intelligence and talent marketplace vendors. I have not yet talked with Galaxy customers, but the user experience is integrated and shows the sophistication of thinking under the covers. Remember that Cornerstone acquired Evolv, Clustree, and EdCast before acquiring SkyHive, so the team has been building AI capabilities and use-cases for several years. And now that Cornerstone has a VR platform for learning, more use-cases are coming. While I don’t know Cornerstone’s revenues, the leadership team assures me that the company is growing and the profitability is high. This means the company has long-term sustainability and despite its many acquisitions, is likely to evolve to “Oracle-like” status. (Oracle has acquired hundreds of companies over the years and now looks at M&A as one of its core strengths). Here’s the major play in the market. With 7,000+ customers, Cornerstone has many customers shopping for new tools. If Galaxy is as solid as it looked in the demos, some percentage of these buyers could upgrade to Galaxy and avoid the purchase of Gloat, Eightfold, or another LMS. While we cannot be sure where Galaxy will play, for companies that want to deploy a skills architecture across all talent practices, it looks like a solid option. Cornerstone Vision: Cornerstone User Experience Cornerstone Career and Talent Marketplace Cornerstone Performance Management Skills in Goal Management Why Cornerstone Still Matters Cornerstone has a massive customer base. The users of Cornerstone, Saba, SumTotal, Lumesse, and Halogen include many of the world’s largest companies and thousands of mid-market organizations as well. These organizations have invested billions of dollars into learning infrastructure, content, and user portals to reach employees. If Cornerstone Galaxy delivers on its promise, the company can help many of these organizations avoid buying lots of standalone new tools. And given Cornerstone’s size, the company could become, as I mentioned above, the “Oracle” of the space. And note, by the way, that a recent survey by HR.com found that the top rated HR tech issue to address is L&D infrastructure, so this issue is on everyone’s mind. While the market is highly competitive and there are many skills-based tools in the market, Cornerstone’s focus on L&D is unique. None of the other major LMS vendors have the skills infrastructure of Cornerstone today. If your skills strategy is focused on building skills, Galaxy may be the answer. More to come as we talk with more Galaxy customers. Additional Information

Josh Bersin
2024年09月03日
Josh Bersin

Josh Bersin: With Thoughtful Design And Culture, Dropbox Proves Remote Work Is A Winner Dropbox, a company with a $7 billion market cap and over $2.5 billion in revenue, has adopted a "Virtual First" strategy in response to the pandemic, transforming its work model from lavish San Francisco offices to a remote-first approach. This shift was led by CEO Drew Houston and Chief People Officer Melanie Rosenwasser, moving away from an office-centric culture to enhance productivity and teamwork through remote work. The strategy includes home office stipends, Dropbox Studios for face-to-face interactions, and innovative meeting management services. Despite initial challenges, this approach has led to high employee satisfaction and a strong talent strategy, allowing Dropbox to thrive in a competitive tech landscape. One of the most interesting tech companies we’ve studied is Dropbox, a $7 billion market cap rocket ship generating more than $2.5 billion in revenue. This kind of company, which sells a platform that competes with Microsoft, Google, and other major players, lives in a world of brutal competition: competition for product leadership, sales deals, and talent. And today, as AI engineers are in short supply, Dropbox has to attract the best and brightest to continue its growth. In its early days, Dropbox was a typical San Francisco-based tech company with gourmet food, gorgeous offices, and a culture of lavish benefits. In the pre-pandemic 2010s this was the rage, and Dropbox became a hot place to work. The pandemic upset that applecart. Not only did “work at home” obsolete the company’s real estate and gourmet investments, it forced the company to rethink its culture. The Chief People Officer, Melanie Rosenwasser, told me that the first few months of the pandemic were traumatic. Employees were upset by working at home and weren’t sure what the company stood for. She and Drew Houston, the CEO, had to rethink the whole operating model. As Melanie described it to me, they took a risky, irreversible move. They decided to totally shift their operating model from that of “San Francisco gourmet offices” to “energized, empowered, team-based, remote work.” Not an easy decision. Note that just this week Eric Schmidt, the ex-CEO and board member at Google, blamed Sundar Pichai for “remote work laziness” as cause for Google’s “falling behind in AI.” So the debate about remote work continues, and some of the most successful leaders still haven’t figured it out. Well Drew, Melanie, and the Dropbox team placed a bet. Knowing that the pandemic had interrupted their campus investments, they dramatically shifted to a “Virtual First” strategy. And they told the company “we are moving away from an office-centric culture” and going to a model of remote-first work. And this included converting offices to Dropbox Studios as well as a carefully architected approach to teamwork, collaboration, and periodic face-to-face activity. Rather than ask people to “come in 3 days a week” (this kind of policy bugs people because they drag themselves into the office just to zoom with others at home), they designed one of the most sophisticated approaches I’ve seen. Employees receive a generous stipend for home office improvements and the company now offers a series of programs, services, and tools to make team and personal productivity thrive. While it seemed risky it worked exceedingly well. By holistically thinking about culture, management, teamwork, and productivity, the company developed a set of innovations that empower people to work at their best, meet with their teams at least one week per quarter, and come together when and where it makes sense. And this model, which looks like an HR innovation, became a business innovation that helps the company thrive. While Dropbox lost a significant number of employees at first, now the company has one of the highest Glassdoor ratings in its industry (4.3, 85% recommend CEO, higher than Google). Dropbox wins awards for employment brand. And not only does Virtual First create productive operations, it helps the company build “tools for the new world of work,” which is where every company is going. Work at home is complicated. In between dogs, kids, gardeners and delivery people we’re futzing with MS Teams, Zoom, Webex, Google Docs, and dozens of other tools. Most of them work well but they’re each different and inconsistent. Dropbox, as a “system designed for remote work” simplifies this enormously. Virtual First helps Dropbox test its products on itself. Why has Virtual First succeeded? As Melanie and the team explains, the shift turbo-charged its talent strategy. Now Dropbox can hire people from any geography in the world (reducing labor cost) and they look for high-energy, passionate, high-performers (not employees who like the offices). Teamwork is stronger than ever. I know, from our company, that this works well. We have 40+ people in our organization and we rely on frequent face-to-face meetings, an open culture, and tremendous amounts of training and communication to grow. Back when I ran our company in an office we hardly talked with each other unless we had a meeting. Things are much more collaborative and productive now. Dropbox has proven this at scale. You can read about Virtual First on the Dropbox website, but one of the innovations I want to point out is the company’s “concierge service” for meetings. (The Offsite Planning Team.) When you as a leader want to have a meeting, this team helps you decide your objectives, reviews the outcomes you want to achieve, and then puts together a detailed plan (location, logistics, agenda, tools) to help you make it work. This removes enormous amounts of wasted time from managers and helps the company operate productively. I cannot tell you how much time I’ve wasted “managing offsite meetings.” To have a seasoned, professional group that helps with this entire strategy in process is a godsend. For Dropbox, this team now knows precisely how the teams work and can continuously improve its consulting services to make sure face-to-face meetings are impactful. A “new manager introduction” meeting, for example, is different from a “get product ready for launch meeting” as you can imagine. How does this apply to your company? Regardless of industry, I guarantee you have remote work teams. Many companies have front line workers (healthcare, retail, manufacturing, transportation) who have to locate with customers. But think about finance teams, IT teams, scientific teams, and HR. We all need productive remote work practices, and Dropbox has proven that a strategic focus on this area will pay off. Melanie and I will be doing a webcast in the near future and she is joining us at our Irresistible 2025 Conference as well. Dropbox has taken the lead in this new world, and they want to share their learnings with all of us.

Josh Bersin
2024年08月30日
Josh Bersin

Josh Bersin:当组织失去信任时，价值观的价值在当前激烈的政治环境中，我有一个简单而重要的想法。当一个组织放弃其价值观时，随着时间的推移，它往往会遭受损失。例如，波音公司是如何牺牲其工程价值观，从而破坏其安全文化的？我相信这是许多“以追求利润为中心”的小决策最终导致了一次飞机坠毁。星巴克的股票为什么会经历十年的停滞？许多“追求收入增长”的小决策逐渐使公司从其被视为“第三空间”的受人尊敬的地位变成了一个价格昂贵的咖啡零售商。不涉及美国政治，很明显，数百个“小决策”可以诱使一个机构牺牲其价值观。感觉在这里也发生了这种情况。看看Edelman Trust Index如何持续下降。无论你的政治倾向如何，美国政治都损害了我们的机构。一些政客为了获胜而煽动不信任。这种价值观的丧失对商业有害。虽然政府是最不受信任的机构之一（拜登帮助其有所增加），但今天有59%的美国人不相信商业领袖说实话。对我来说，这是我们自己需要解决的问题。这种不信任导致对创新的信心低下。令人惊讶的是，今天只有30%的美国人信任AI，主要是因为他们认为这是夺取工作的技术。这就是为什么70%的人希望CEO公开谈论技术对工作、职业和经济增长的影响。人们渴望可靠的信息来源，我认为我们在Intuit和UKG上周的公告中看到了这种诚实。虽然问题很复杂，但信息很明确。每个机构，尤其是我们的公司，必须遵循其价值观，以建立与客户、员工和利益相关者的信任和信誉。大多数CEO以增长、盈利和市场份额为价值观。这些价值观虽然看似清晰，但远远不够。如果你的公司没有更广泛的使命或目的，单纯追求利润可能会让你迷失方向。为什么？因为利润不是最终目标，而是实现使命的结果。当你失去使命并追逐财务结果时，你会失去信任、忠诚和长期价值。在我们的国家，许多“政治动机”决定导致了我们今天的状况。在你的公司中，只有你，作为领导者，才能质疑何时价值观偏离了方向。我每天都会与许多令人惊叹的公司领导会面。在我最钦佩的公司中，总是有一套坚定的价值观。微软致力于帮助人们提高生产力。Gucci相信奢侈体验能帮助人们找到自我。Colgate相信为人类、宠物和地球创造一个更健康的环境。这些宏大的理念有时看起来很愚蠢，但在机构中，它们比你想象的更有价值。组织每天做出成千上万个决策（雇佣谁，如何服务客户，如何分配资源），当价值观被“利润”或“增长”所取代时，这些决策可能会降低你的价值。当“无价值观”的决策积累起来时，灾难可能会发生。波音的刑事起诉协议或安然的最终破产就是很好的例子。在美国，我们的信任排名显示了同样的情况。（美国是GDP全球排名第一的经济体，但信任度排名第46位。）当价值观被抛弃时，文明也会受损还有一点。我刚刚读了一份来自SHRM的令人失望的报告，关于美国的文明状态。在政治辩论中，善意和尊重也在下降。信不信由你，38%的美国工人觉得他们的工作场所不文明，58%的人认为过去两年的不文明程度显著增加。“文明”一词意味着言语中的尊重、礼貌和礼节。我认为今天的政治家和媒体中的“不文明”行为只会使信任变得更加困难。（今天只有9%的美国人信任国会，12%信任电视新闻）。我们在商业中的责任是以价值观来运行我们的组织，并在这些价值观内相互尊重。我将企业价值观等同于公民意识，即对更大社会的责任感。在这些政治变化的不确定时期，让我们关注公司内部的价值观和文明。我可以向你保证，这将赋予你力量、持久力和繁荣。

Josh Bersin
2024年07月18日
Josh Bersin

是时候重塑人才招聘了 -Research Shows It’s Time To Reinvent Talent Acquisition Josh Bersin 的文章 "研究表明，是时候重塑人才招聘了 "强调了人才招聘亟需进行的变革。由于只有 32% 的人力资源高管参与战略规划，而且许多人觉得自己只是个接单员，因此这篇文章呼吁进行战略改革。在劳动力短缺和急需技能型招聘的情况下，目前削减成本和减少招聘力度的方法与对技能型专业人才日益增长的需求相矛盾。文章敦促企业将人才招聘作为一项重要的战略职能，利用现代技术并将其与学习和发展相结合，以提高效率并关注内部人才流动。原文如下： This week we published a disappointing research study, Talent Acquisition at a Crossroads. The study, conducted in partnership with AMS, points out that talent acquisition leaders (this is a senior position) are largely left out of their company’s strategic planning process and many feel they operate as “order takers.” In today’s world of labor and skills shortages, this is a wakeup call for change. Here’s the data: Among these 130+ HR executives only 32% are involved in any form of strategic workforce planning, 42% believe their company has no workforce plan at all, and 46% say “they’re running around to keep up.” And when layoffs do occur, often the recruiters go first. (Witness Tesla this week.) All this is happening in a world where 58% of companies feel skills shortages are significantly impacting their business plans, more than three-quarters believe they must transform their talent practices to grow, and “skills-based hiring” is a top priority yet difficult to implement. Here’s the paradox: companies are cutting their talent acquisition spending at the same time CEOs feel that skills shortages are getting worse. What’s going on? Talent Acquisition Needs A Reinvention Let’s just face it: recruiting as a business function has to change. Once considered the “staffing department,” where companies posted jobs and scanned resumes, talent acquisition has become highly strategic operation. What skills do we need? How do we find people who will fit our culture? What internal candidates should fill our key positions? Who are the right leaders for us to hire? Unfortunately, almost 80% of talent acquisition functions are quite tactical. PwC’s CEO survey found that CEOs rate “hiring” as the third most bureaucratic process in their companies, tied with “too many emails” and “too many meetings” as a time-wasting process. And that explains why two-thirds of TA leaders are being asked to cut costs. I had a conversation last week with a former TA leader for one of the Big Three automakers. He told me that in the fervor to hire staff for EV engineering he was asked to hire “any engineer he could find, regardless of skill,” because the company was in such a hurry. No time for skills assessment, competitive planning, or even location analysis. Just “go out there and hire engineers.” We have been studying the auto industry as part of our GWI study and found that important EV roles (reliability engineer or power plant engineer, for example), are quite specialized and hard to find. Strategic recruiting departments need to understand these roles and source these individuals carefully. Just hiring engineering grads from a local community college is not going to move this needle. (Consider the data by Draup on what these roles are. Talent Acquisition teams with talent intelligence skills can pinpoint who to hire.) And it gets worse. In our Dynamic Organization research we found that high performing companies focus heavily on internal hiring, talent intelligence tools to find hidden talent, and continuous internal development to fill skills gaps. We can’t simply throw job requisitions over to the recruiting function any more: the people we need may be buried inside the company. This week Tesla announced a layoff of 10% of their workforce. Was their time to balance and redeploy talent internally? Absolutely not. According to my sources every business unit had to let 10% go, and and many of the people being fired were talent acquisition leaders, the very people who help with these issues. We talk with many HR executives and there is an enlightened group. Companies that understand this issue (about one in eight) have elevated Talent Acquisition to a strategic function, they merge or integrate TA with L&D, and they redefine their recruiters as “talent advisors.” Mastercard, as a leader, just renamed their recruiters as “Career Coaches,” demonstrating their role in helping people find the right jobs. Despite the onslaught of AI, this role is becoming even more human-centric. High-powered recruiting teams source internal candidates, understand company culture, and have a deep knowledge of jobs, roles, and organizational dynamics. When well supported and trained, these professionals are strategic advisors, not just “recruiters.” And companies that understand this often outsource or automate much of the administration in recruiting. Technology plays a major role in this reinvention. Most large companies have dozens of legacy systems, many of which make the candidate experience difficult. When organizations focus on modernizing and streamlining their technology, talent acquisition can become 10-100X more efficient. This, in turn, gives recruiters and talent advisors the time to search for the right skills, carefully select the best candidates, and focus on internal hiring and development as a strategy. Technology Is Here But Not The Entire Answer Of all the HR technology markets, recruiting is the most innovative of all. New AI-powered systems like HiredScore (just acquired by Workday), Paradox (leader in conversational AI), Eightfold, Gloat, Draup, and Lightcast (pioneers in talent intelligence), and many others can reduce time to hire from months to weeks and weeks to days. But none of this technology works if the Talent Acquisition team is left on an island. In the last year I have met with more than 50 heads of talent acquisition and once the door is closed and we talk honestly, they always tell me the same thing. “We are not treated as a strategic function, we are being asked to cut costs, and we are constantly running from fire to fire to keep executives happy.” This type of “service-delivery” focus simply will not work in the new economy. What should companies do? As part of our Systemic HR initiative, we help companies evolve their TA Function to operate in a more strategic way. Organizations like Bayer, Verizon, and many others have elevated the role of recruiter to talent advisor, they’re building skills in talent intelligence, and they’re integrating the recruiting function with L&D, career management, and employee engagement. I’ve always felt that recruiting is the most important things HR professionals do. If we can’t get the “right” people into the company, no amount of management can recover. But what does “right” mean? And how can we source, locate, and attract these particular people? This is a highly strategic operation, and one that must integrate with internal mobility, culture, and employee experience. I encourage you to read our Systemic HR research, join our Academy, or reach out to us or AMS for advice. In this new era of talent and skills shortages, we simply cannot run recruiting in this tactical way any longer.

Josh Bersin
2024年04月24日

Josh Bersin

世界幸福报告能教给我们关于工作的什么? What The World Happiness Report Teaches Us About Work 最新《世界幸福报告》揭示，尽管经济增长，美国幸福感下降。研究强调，高薪并非幸福的关键，而公平薪酬、良好的企业文化才是。特别是年轻人，受到气候变化、政治纷争等影响，幸福感低落。企业需关注文化建设、弹性工作，关照员工心理健康。工作场所的信任、社区感和公平至关重要。我们要反思：真正的幸福是什么？我每年都认真研读《世界幸福报告》，今年的报告特别引人深思。以下是我对一些关键发现的解读。首先，美国的幸福指数（10分满分）降至第23位，比全球最幸福的国家芬兰低了13%。实际上，在过去15年中，美国的幸福度几乎下降了8%，呈现出持续的年降趋势。对于我们这些生活在美国的人来说，这可能并不陌生：坏消息、政治争斗以及人们在价值观上的分歧似乎无处不在。这一切发生的同时，美国的GDP增长却持续领先世界上大多数主要经济体。这意味着我们作为一个国家正在变得更加富裕，却显著地变得不那么幸福（下文将详细解释）。从企业角度来看，这个观点很简单：仅仅提高薪资并不能使人们感到更加幸福。尽管每个人都希望得到公平的报酬，但高薪酬并不直接转化为高参与度。我们2023年的《薪酬公平终极指南》发现，与薪酬水平相比，薪酬公平与员工参与度的关联性高出7倍。其次，报告指出，在美国，年轻人的幸福感明显低于老年人（这一点并非在所有国家都适用，但在大多数发达国家中是这样的）。在美国，30岁以下人群的幸福评分为6.4，而60岁以上人群的评分为7.3，幸福度低了12%。我们对年轻人的这一低幸福评分使美国在全球青年幸福排行榜上仅位列第62位，远低于我们的总体排名。这反映出我在上周播客中讨论的现象。如今的年轻工作者担忧全球变暖，他们在年轻时就经历了疫情的冲击，他们对于战争、通货膨胀、社会问题以及政治不和感到沮丧。埃德曼信任度量尺表明，年轻人认为相比政府，企业在为社会带来创新方面更值得信赖，高出近20%。但令人担忧的是，这种信任程度也在下滑。从企业的视角来看，这进一步强化了播客中提到的观点：我们（美国）的劳动力中位年龄现已达到33岁。这表明许多关键员工对生活的热情有所下降，这迫使雇主需要采取更多措施。我们对企业文化、员工福祉、工作灵活性和个人成长的关注，现在比以往任何时候都显得更为重要。这就是像四天工作周、灵活工作时间以及其他诸多福利（如生育支持、儿童看护、心理健康、健身、财务福利）变得越来越普遍的原因。（最新的劳动统计局数据显示，我们在福利上的支出占工资总额的31.1%，比三年前的29%有所增加。在信息行业，这个比例高达35.5%，是有史以来的最高值。）此外，重点强调：对企业来说，重振早期职业发展计划至关重要。许多企业在20世纪60、70年代建立了这些计划，但随后这些计划逐渐被忽视。如果你正在从大学招聘顶尖人才，并投资于校园招聘（这一趋势正在上升），那么确保你有一个坚实的1-2年发展计划、工作轮岗以及面向年轻人的群体参与计划是非常重要的。我最近与康卡斯特讨论了他们的计划，他们的早期职业发展计划正在直接为他们的领导力管道做出贡献。第三，也是最引人注目的一点是，报告强调了社会关系和信任在幸福感中的巨大作用。进行这项研究的学者团队发现，幸福感的“坎特里尔阶梯”（一个简单的“你觉得自己多幸福”的1-10评分问题）可以分解为六个贡献因素：人均GDP（财富）、社会支持（密切关系的数量和质量）、预期寿命（健康）、生活选择的自由（按个人意愿生活的能力）、慷慨（向他人给予金钱和时间的倾向）以及腐败感知（相信“系统”是公平的）。这些因素对幸福的贡献度大开眼界。令人惊讶的是，社会关系是幸福感的最大贡献者，而健康只占大约1.4%。请注意，第二重要的因素是对腐败的感知或者说是公平感，这解释了为什么薪酬公平非常重要。我们再次发现，财富对幸福感的影响相对较小。这对我们的工作有何启示？这里有一些简单的启示：关系很重要。如果管理层和主管不能建立起团队合作感，员工便会感到不适。尽管我们面临财务和运营压力，但我们仍需抽时间了解员工、倾听他们的声音，并与他们共度愉快时光。通过聚集人员并创建跨功能团队，我们即使在远程工作情况下也能建立社交关系。信任至关重要。我曾在高层领导贪婪、不忠、不诚实的环境中工作过，公司内的每个人都能感觉到这一点。信任是经年累月建立起来的资产，我们必须不断地进行投资。通过道德、诚实和倾听来培养信任，你的领导模式中包含了这些元素吗？薪酬的影响可能比你想象的要小。虽然每个人都希望赚更多钱，但人们更希望感觉到奖励是公平且慷慨的。因此，不应仅仅过度奖励表现突出的员工，而忽视其他人的努力。生活选择的自由极为重要。众多研究显示，与薪资相比，员工更加重视工作的灵活性，因此，考虑将四天工作周和灵活工作选项作为你的雇佣政策的核心部分是非常重要的。多年前，我在一个人力资源领导者的大型会议上发表了关于企业公民责任的演讲。我指出，公司就像小型社会一样，如果我们的企业“社会”不公平、不透明、不自由，那么我们的员工就会感受到痛苦。演讲结束时，我不确定听众的反应如何，但来自宜家的一大群人向我走来，给了我一个热情的拥抱。宜家这家公司，深深植根于瑞典的社会主义文化，是地球上最长久的公司之一。他们真心相信集体思维、公平和对每个个体的尊重。原文来自：https://joshbersin.com/2024/03/what-the-world-happiness-report-can-teach-us-about-work/

Josh Bersin
2024年03月22日
Josh Bersin

Josh Bersin:3400亿美元的企业学习的市场将迎来巨大变革作者：Josh Bersin 本文探讨了企业学习行业的演变，特别是人工智能如何引领这一行业的巨变。企业每年在员工培训和发展上的开支超过3400亿美元，从传统的课堂培训到在线学习，再到以技能为中心的学习，行业一直在不断发展。现在，人工智能预计将彻底改变公司的学习管理系统（LMS）和学习体验平台（LXP），通过个性化和动态生成内容来提高学习效率和效果。文章强调了适应这种变化的重要性，以及AI在企业培训和人才发展中的潜力。企业在员工培训和发展上的年支出超过3400亿美元，平均每名员工每年花费超过1500美元。这笔巨额开支支撑着一个全球产业，涉及数百家内容和技术公司，现正站在重新定义的风口浪尖。请允许我详细解释这一过程。从电子学习到集体学习再到自主学习的演变 20世纪90年代末，随着互联网的崛起，以传统教室授课为主的培训产业发生了翻天覆地的变化。企业和内容提供者纷纷开发“电子学习”课程，试图在线复制面对面教学的体验。那是一个充满创新的时期，虽然今天看来有些过时，但它孕育了像Skillsoft（并购了众多竞争对手）、Cornerstone（同样并购了众多竞争对手）以及一大批传统的学习管理系统（LMS，例如Plateau、SumTotal、Learn.com、Pathlore等）公司，这些公司最终都被并购。如今，LMS市场的规模已超过200亿美元，这一切几乎都是在线培训推动的结果。虽然这些系统可能看起来笨重，但它们对全球每家公司的交易和记录保持都至关重要。当公司争相购买LMS系统——这是一个投资者非常关注的热门市场时，他们发现一个庞大的课程目录并不实用。因此，他们开始构建一套特征，我称之为“以人才为驱动的学习”，包括基于能力的学习、与职业角色一致的课程和职业发展路径系统。这些特征被添加到LMS中，使得这些系统不仅仅是教育工具，更像是“人力资源系统”，从而促使供应商扩展到更多的人才管理功能。早期的开拓者Saba和Cornerstone开始推出绩效管理工具。回顾起来，这些尝试可能看起来有些简单，但当时它们代表了一个重大突破。突然之间，公司不再单独购买LMS系统，而是选择购买包含多个功能的“人才管理套件”，这迫使专注于LMS的供应商开始涉足招聘、目标管理乃至薪酬管理。他们可能没有意识到，放弃核心业务最终会导致他们被市场颠覆。随着Facebook（2004年）、YouTube（2005年）和Twitter（2006年）的相继出现，内容世界发生了巨变。视频、文章和专家意见变得触手可及，那些笨重、以课程目录为导向的LMS系统显得格外难以使用。因此，随着公司寻求新的解决方案，原本投入巨资于人才管理的LMS市场开始显露老态。学习体验平台（LXP）市场随着Pathgather（2010年）、Degreed（2012年）、EdCast（2013年）的诞生而兴起，企业转向这一新兴领域投资。（更多历史，请参阅《从电子学习到集体学习》。） 2010年代初，整个行业的理念是尝试模仿Google，打造一个既具有Twitter式动态性又拥有YouTube式丰富内容的企业学习系统。传统的LMS和人才管理系统逐渐过时，供应商在缓慢的增长中寻求出路，最终合并为几家大型玩家。随后，微学习的概念兴起。iPhone成为了视频播放平台（2008年），Instagram（2010年）、Snapchat（2011年）及后来的TikTok（2015年）向我们展示了短视频和“微学习”可以是多么的有趣。过长的两小时在线课程变得不受欢迎，因此LXP供应商开始扩展自己的产品线。随着公司将越来越多的内容投入到LXP中，我们意识到需要一种方法来寻找、精准定位并个性化所有这些学习材料。此变化自然引发了内容市场的爆发。LinkedIn、Coursera、Udemy、OpenSesame、Go1等供应商决定开拓这个领域，推动了新材料的狂热消费。自那以后，内容市场继续繁荣发展，尽管仍然主要由小型玩家主导，但被更大的聚合商所整合，这些聚合商销售并分发多种品牌。（顺便提一下，Workday在2016年收购了视频公司Mediacore，以抓住这波趋势。由于缺少核心LMS功能，他们花费数年时间将其发展成为一个完整的LMS。）进入技能的世界。你可能不会相信，但“技能记录系统”的概念最初出现在LXP领域，供应商如Degreed和EdCast建立了一个搜索术语数据库，并用“技能”一词标记内容。在消费者市场，我们能接收到成百上千的信号来推荐广告，但LXP供应商只有少数工程师，因此他们的“技能分类”相对简单。这个概念迅速走红，公司开始专注于构建基于“技能”的培训，随后是招聘和人才战略。同时，L&D领域正处于创造性混乱之中。出现了如360 Learning、Fuse Universal、Kineo等数百家内容创作和分享系统的供应商，旨在帮助公司创作、分享视频内容，并按角色、技能或职能进行组织。这些并非严格意义上的LMS系统，但它们位于LMS前端，使员工能够轻松创建和消费动态内容。这一时期，从2018年至今，成为L&D领域的热潮。市场充斥着各式各样的视频内容工具，同时像STRIVR和Talespin这样的先锋公司开始为虚拟现实（VR）构建工具和内容系统。自创内容平台、视频平台和VR平台正在满足重要需求，而LMS市场则变得更加固定、枯燥和无趣。（Talespin最近被Cornerstone收购。）顺带一提，我仍然认为“能力学院平台”市场具有巨大潜力（这类平台提供综合的专业能力和小组学习功能，例如我们的Josh Bersin Academy）。Docebo、Learn-In、Nomadic、NovoEd和Intrepid等供应商仍在增长，但随着时间推移，这些系统可能被整合进人才市场。这一领域一直是行业的一个亮点。（想了解更多，请阅读《能力学院：L&D的未来方向》。）作为分析师，我得诚实说，过去几年对我来说有些单调。我们帮助了数百家公司决定该选择哪种L&D系统，但通常我们发现这些组织有太多平台，内容分散杂乱，缺乏一致性的数据处理，以及在这一领域的过度投资。因此，这个静态期代表了过去3到5年的趋势，是企业整理过去十年购买历史的好机会。世界突然再次发生变化。技能分类的理念迅速蔓延，同时新兴的人才智能系统，如Eightfold、Gloat、Fuel50等纷纷涌现。这些新兴系统使公司能够按技能寻找人才、根据技能推荐职位和机会，并按技能动态规划职业路径，再次与L&D领域发生碰撞，促使我们将所有内容“整合”进这些新平台中。（更多信息，请阅读《人才智能入门》。）本周我刚与我最喜爱的L&D专家之一通话（他即将在我们的会议上演讲），他向我展示了他所在的大型制药公司如何将其LMS、LXP和人才市场融合成一个无缝、端到端的体系。他可能略微超前于当前趋势，但这正是事物发展的方向。然而，故事还在继绀。又一场变革已经到来，这一次的影响力与YouTube、Instagram或iPhone相媲美，甚至更大。没错，就是AI。 AI，如许多人所预料，将彻底颠覆这个行业。正如我们在电子学习和人才管理时代所见证的那样，这意味着供应商生态将彻底改变。 AI如何改变一切让我不夸大其词地告诉你。在这30年的故事中，有一点始终未变：企业培训关注的核心始终是内容。是的，我们希望内容更简短、更快速、能在手机上查看——但如果内容本身没有实用价值，不切实际，不易于消费，它就无法发挥作用。你们中有多少人为了得到学分而快速点击通过那些以页面为基础的合规课程，但实际上几乎没有注意内容？这正是我们面临的挑战。所有这些向视频、微学习、大规模开放在线课程（MOOCs）以及其他形式的转变，都是为了解决这个问题的尝试。比如，假设企业学习系统能识别你是谁，你只需提出一个问题，它就能生成答案、一系列资源和一组动态学习对象供你消费。有时候，你可能只需快速获取答案即可。其他时候，你可能会深入研究内容。还有时，你可能会浏览整个课程，并花时间学习所需的知识。假设这一切都是完全个性化的。这意味着你不会看到一个“标准课程”，而是根据你当前知识水平定制的特殊课程。这就是AI即将带给我们的。而且，这已经在今天开始发生了。不仅生成式AI能够回答问题和吸收内容（例如，Galileo™已经容纳了我们25年以上的每一项研究，包括视频、播客和文章），它还能生成视频、测试、测验甚至整个课程。它可以作为技术课程的教学助手，也可以作为领导力项目的教练或导师，并且能够进行语言转换。 AI能够根据你的身份动态生成内容，这意味着什么？那么，LMS市场、LXP市场、VR学习市场以及所有内容提供商将如何呢？在未来几年，我们将见证一场巨大的行业洗牌。供应商正在采取的行动虽然我无法确切知道每个L&D供应商正在做什么，但可以肯定，变化正在迅速进行中。 Docebo Shape能够从文档中生成高效的互动式培训材料（Arist也能做到这点）。Uplimit构建了一个完整的L&D平台，采用AI智能体和课程中自动生成的内容。我们的合作伙伴Sana不仅能自动生成内容，还围绕AI核心建立了一个完整的LMS系统。Cornerstone通过收购Talespin，能够动态创建角色模拟和几乎可以无限配置的场景。快速增长的“精确技能”供应商Growthspace，可以根据1100种具体的商业技能，为你匹配一个“技能教练”，与你的具体目标对齐。 LMS市场不会消失，但正如人才智能系统正在逐渐取代应聘追踪系统（ATS）和人力资源管理系统（HRMS）一样，AI驱动的内容平台将逐步侵蚀LMS市场。我的制药公司朋友希望他的LXP能成为他们的“动态内容系统”，但坦白说，我不确定LXP供应商是否已经准备好迎接这个挑战。许多供应商，从LinkedIn到Microsoft，将不得不重新考虑他们如何成为“动态学习”系统，以及他们希望在其中扮演什么角色。正如所有技术转变一样，通常情况下，从头开始构建的系统会超越旧有系统。对于Cornerstone或Docebo这样拥有数千客户的公司来说，当新技术出现时，他们不能简单地“替换”他们已经建立的系统。因此，新兴的AI驱动学习系统可能会由新的供应商推出，并随着这些公司的发展，开始取代和竞争现有的系统。尽管看上去简单，学习技术实际上非常复杂。Workday几乎花了十年时间从Mediacore发展到一个相对健全的LMS，并且他们才刚刚开始尝试AI。因此，不要期望你现有的供应商能够一夜之间彻底改变。但有一件事我可以确定：颠覆即将来临。就像Plateau、Saba和SumTotal在2000年代初期时“市场上最热门的供应商”一样，它们很快就成为了过时系统和收购目标，当市场变化时同样的情况也可能发生在今天。新兴供应商如Sana、Growthspace、Uplimit、Docebo、LMS365等将崭露头角。尽管风险资本家通常对这个市场持谨慎态度，但往往是那些拥有最佳管理团队的公司最终胜出。大型供应商如LTG、Cornerstone和Skillsoft拥有充足的资金，因此随着市场的发展，任何事情都有可能发生。但对我来说，一件事是明确的：前方是一个巨大的增长周期。 AI的机会是真实的，而且极为巨大想象一下我们公司中的遗留内容量。全球必然存在价值超过一万亿美元的合规培训、销售培训、运营培训、安全培训和领导力发展内容。如果AI能够在大规模上“重新利用”和“再创造”这些内容，我们将看到这个巨大的市场向新系统转变，最终实现知识管理和学习的完美结合。我来举一个简单的例子。我们的一位Galileo客户是一家拥有百年历史的大型航空航天公司，他们在工程、产品设计、航空和国防技术方面有着丰富的积累。他们构建了喷气引擎、导弹、核潜艇以及各种系统。对于一名新工程师，他们需要超过三年的时间来完成“入职培训”，因为需要掌握大量的知识产权、设计专长和系统操作。他们的资深工程师们都在逐渐退休！他们在我们的帮助下，开始了一个以AI为中心的试点项目，把多年累积的内容放到一个新平台中，供年轻工程师使用。我相信，这将带来翻天覆地的变化。Galileo将协助处理管理层面的问题，而一个类似的AI助手将帮助工程师学习、寻找文档、观看视频并参加相关课程。传统的LMS和HRMS工具可能不会在这一过程中发挥重要作用。考虑一下你的公司。你们囤积了多少内容、专业知识和旧有的培训资料？AI可以“释放”这些资源给你的员工，使其以前所未有的方式变得可用。这是一个激动人心的新时代，充满了即将到来的变革。

Josh Bersin
2024年03月21日
Josh Bersin

Josh Bersin谈How To Create Talent Density 如何打造人才密度 Josh Bersin发表文章谈到：在过去几年里，我注意到大公司的表现开始不如小公司。我们现在看到苹果和谷歌都出现了这种情况，而微软应对这一挑战也有相当长的一段时间了。随着公司的发展，帮助我们推动组织绩效的一个重要理念就是人才密度。这篇文章讨论了人才密度的概念，即公司中技能、能力和表现的质量和密度。强调传统的员工绩效评估模型已导致平庸。建议采用人才密度方法，包括招聘增加或乘数效应的人才，基于帕累托分布管理绩效，以及专注于赋权、反馈和领导力。文章强调，为了创新和市场竞争力，尤其在AI和技术进步的背景下，维持高人才密度的重要性。 In this (long) article, I want to talk about a new concept called Talent density. And as I pondered the concept I think it represents one of the more important topics in management. So I hope you find it as interesting as I do. First of all, the concept of talent density, pioneered by Netflix by the way, is simple. Talent Density is the quality and density of skills, capabilities and performance you have in your company. So, if you have a company that is 100% high performers, you’re very dense. If you have a company that’s 20% high performers, you’re not very dense. It’s easy to understand, but hard to implement, because it gets to the point of how we define performance, how we select people to hire, how we decide who’s going to get promoted, how we decide who’s going to work on what project and how we’re going to distribute pay. So before I explain talent density, let’s talk about the basic beliefs most companies have. Most organizations believe that they’re operating with a normal distribution or bell curve of performance. I don’t know why that statistical model has been applied to organizations, but it has become almost a standard policy. (Academics have proven it false, as I explain below.) Using the bell curve, we identify the “mean” or average performance, and then categorize performance into five levels. Number ones are two standard deviations to the right and number fives are two standard deviations to the left. The people operating at level one get a big raise, the people operating at level two get medium raise, the people operating at level three get an average raise, the people operating at level four get a below average raise and the people operating at level five probably need to leave. Lots of politics in the process, but that’s typically how it works. As I describe in The Myth of The Bell Curve, these performance and pay strategies have been used for decades. And at scale they create a mediocrity-centered organization, because the statistics limit the quantity and value of 1’s. If you’re operating at 1 level and you get a 2, you’ll quit. If you’re operating at 3 level, you’re probably going to coast. You get my drift. And since the bulk of the company is rated 2 or 3, most of the managers are in the middle. As the saying goes, A managers hire A people, B managers hire C people. So over time, if not constantly tuned, we end up with an organization that is almost destined to be medium in performance. Now I’m not saying every company goes through this process, but if you look at the productivity per employee in large organizations it’s almost always below that of smaller organizations. Why? Because as organizations grow, the talent density declines. (Netflix, as an example, example, generates almost $3M of revenue per employee, twice that of Google and 10X that of Disney. And they are the only profitable streaming company, with fewer than 20,000 employees and a $240 billion market cap.) The traditional model was fine in the industrial age when we had a surplus of talent, jobs were clearly defined, and most employees were measure by the “number of widgets they produced.” In those days we could swap out a “low performer” for a “high performer” because there were lots of people in the job market. We don’t live in that world anymore. The world we now live in has sub 4% unemployment, a constant shortage of key skills, and a growing shortage of labor. And thanks to automation and AI, the revenue or value per person has skyrocketed, almost an order of magnitude higher than it was 30 years ago. So we need a better way to think about performance in a world where companies with fewer people can outperform those who get too big. Look at how Salesforce, Google, Apple, who are essentially creative companies, have slowed their ability to innovate as they get bigger. Look at how OpenAI, who is a tiny company, is outperforming Google and Microsoft. Today most businesses outperform through innovation, time to market, customer intimacy, or IP – not through scale or “harder work.” How do we maintain a high level of talent density when we’re growing the company and hiring lots of people? Netflix wrote the book on this, so let me give you the story. First, the hiring process should focus on talent density, not butts in seats. Rather than hire someone to “fill a role” we look for someone who is additive or multiplicative to the entire team. Hire someone that challenges the status quo and brings new ideas, skills, and ideas beyond the “job” as defined. Netflix values courage, innovation, selflessness, inclusion, and teamwork, for example. These are not statements about “doing your job as defined.” Netflix’s idea is that each incremental hire should make everybody else in the company and everybody else in the team produce at a higher level. Now this is a threatening thing for an insecure manager because most managers don’t want to hire somebody that could take their job away. But that’s why we have this problem. Second, we need to manage or create some type of performance management process that is built around the Pareto distribution (also called the Power Law) and not the normal distribution. In the Pareto distribution or the power law, we have a small number of people who generate an outsized level of performance, you can call it the 80/20 rule or the 90/10 rule. (20% of the people do 80% of the work) Studies have shown that companies and many populations work this way, and it makes sense. Think about athletes, where a small number of super athletes are 2-3 better than their peers. The same thing is true in music, science, and entertainment. It’s also true in sales and many business disciplines. Research conducted in 2011 and 2012 by Ernest O’Boyle Jr. and Herman Aguinis (633,263 researchers, entertainers, politicians, and athletes in a total of 198 samples). found that performance in 94 percent of these groups did not follow a normal distribution. Rather these groups fall into what is called a “Power Law” distribution. In every population of human beings there are a few people who just have God-given gifts to outperform in the job, and they just naturally seem to be far better than everyone else. Bill Gates once told the company that there were of the three engineers that he felt made the company of Microsoft. And I’ve heard this in many other companies, where one software engineer and the right role can do the work of 10 other people. Now, this is not to say that everybody will fall into one level of the Pareto distribution. At a given point in time in your career, you may be in the 80% and over time, as you learn and grow and find the things that you’re naturally good at, you’ll end up in the 20%. But in a given company this is a dynamic that’s constantly taking place. And that’s what Netflix is doing – constantly working on talent density. What does this mean for performance management? It means that in order to care for a population like this, we have to hire differently, avoid the bell curve, and pay high performers well. Not just a little more than everybody else, a lot more. And that’s what happens in sports and entertainment, so why not in business. If you look at companies like Google, Microsoft, and others, there are individuals in those companies that make two to three times more than their peers. And as long as these decisions are made based on performance, people are fine with it. What obviously does not work is when person making all the money is the person who’s the best politician, best looking, or most popular. And that leads me to item three: In the Netflix culture there’s a massive amount of empowerment, 360 feedback, candor and honesty. You’ve probably read the Netflix culture manifesto: it’s all about the need for people to be honest, to speak truth, to give each other feedback, and to focus on judgement, courage, and accountability. Netflix only recently added job levels: they didn’t have job levels for many years. Giving people feedback is a challenge because it’s uncomfortable. So this has to to start at the top and it has to be done in a developmental, honest way. This does not mean people should threaten or disparage each other, but we all need to know that at the end of a project or the end of the meeting it’s okay for somebody to tell us “here’s what was great about that and here’s what wasn’t great about it.” One of the most important institutions in the world, the US military lives, eats and dies by this process. If you’re in the military and you mess something up, you can guarantee that somebody’s going to tell you about it, and you’re going to get some help making sure you don’t do it again. We don’t have life or death situations in companies, but we can certainly use this kind of discipline. The fourth thing that matters in talent density is leadership and goal setting. One of the things that really gets in the way of a high performing company is too many individual goals, too many siloed projects and responsibilities and people not seeing the big picture. If your goal setting and performance management process is 100% based on individual performance you are sub-optimizing your company. Not only does this work against teamwork, but there really isn’t a single thing in a company that anybody can do alone. So our performance management research continuously shows that people should be rewarded for both their achievements as well as that of the team. (Here’s the research to explain.) Why is talent density important right now? Let me mention a few reasons. First, we’re entering a period of low unemployment so every hire is going to be challenging. And thanks to AI, companies are going to be able to operate with smaller teams. What better time to think about how to “trim down” your company so it’s performing at its best? Second, the transformations from AI are going to require a lot of flexibility and learning agility in your company. You want a highly focused, well aligned team to help make that happen. And while AI will help every company improve, your ability to leverage AI quickly will turn into a competitive advantage (think back about how web and digital and e-commerce did the same). (I firmly believe the companies with the most ingenious applications of AI will disrupt their competitors. I’m still amazed at Whole Food’s hand recognition checkout process: I can see self-service coffee, groceries, and other retail and hospitality coming.) Third, the post-industrial business world is going to start to devalue huge, lumbering organizations. Many big companies just need a lot of people, but as Southwest Airlines taught us long ago, it’s the small team that performs well. So if you can’t break your company into small high-performing teams, your talent density will suffer. When the book is written on Apple’s $10 Billion car, I bet one problem was the size and scale of the team. We’ll see soon enough. By the way, I still recommend everyone read “The Mythical Man-Month,” which to me is the bible of organizing around small teams. What if you’re a healthcare provider, retailer, manufacturer, hospitality company? Does talent density apply to you? Absolutely! Go into a Costco and see how happy and engaged the employees are. Then go into a poorly run retailer and you’ll feel the difference. In my book Irresistible I give examples of companies who embrace what I call “the unquenchable power of the human spirit.” Nobody wants to feel like they’re underperforming. With the right focus on accountability and growth we can help everyone out-perform their expectations. Now is a time rethink how our organizations work. Not only should we promote and reward the hyper-performers, the Pareto rule and Talent Density thinking encourage us to help mid-level performers learn, grow, and transform themselves into superstars. Let’s throw away the old ideas of bell curve, forced distribution, and simplistic performance management. Companies that push for everlasting high performance are energizing places to work, they deliver outstanding products and services, and they’re great investments for stakeholders. AI中文翻译：在这篇篇幅较长的文章中，我想探讨一个被称为“人才密度”的新概念。思考此概念时，我认为它是管理领域中极其重要的议题之一。希望您能像我一样发现其趣味性。首先，Netflix首创的“人才密度”概念其实很简单。人才密度指的是公司内部技能、能力和表现的质量与密集程度。换句话说，如果你的公司全是高绩效人才，那么你的“人才密度”就很高。如果只有20%是高绩效人才，那么你的“人才密度”就不高。这个概念虽然容易理解，但实际执行起来却颇具挑战，因为它涉及到我们如何定义绩效、招聘员工的标准、晋升决策、项目分配以及薪酬分配。在详细解释“人才密度”之前，让我们先看看大多数公司的基本信念。许多组织相信，他们的员工表现遵循一个正态分布或钟形曲线。这个统计模型为何被广泛应用于组织之中，我并不清楚，但它几乎已成为标准做法。（实际上，如我下文将解释的，学术研究已证明这一模型是错误的。）采用钟形曲线，我们确定平均表现（即“平均线”），然后将员工的表现划分为五个等级。表现最好的被归为一级，标准为右偏两个标准差；表现最差的被归为五级，左偏两个标准差。一级表现者获得大幅度加薪，二级表现者获得中等加薪，三级表现者获得平均水平的加薪，四级表现者加薪低于平均，五级表现者可能就需要离开公司了。虽然这个过程充满了政治操作，但这就是它通常的运作方式。正如我在《钟形曲线的神话》中所述，这些关于绩效和薪酬的策略已经使用了数十年。而且，当这些策略在大规模下实施时，它们会造成以平庸为中心的组织文化，因为这种统计方法限制了顶尖人才的数量和价值。如果你是一级表现者却被评为二级，你很可能就会选择离职。如果你是三级表现者，你可能就会选择安于现状。你应该明白我的意思了。而且，由于大部分员工的评级为二级或三级，大多数管理者也就处于中等水平。常言道，A级的管理者招聘A级人才，B级的管理者则招聘C级人才。因此，如果不持续进行优化调整，组织最终几乎注定会变得中庸。我并不是说每家公司都会经历这一过程，但如果你查看大型组织的员工生产率，通常都低于小型组织的生产率。为什么呢？因为随着组织规模的扩大，“人才密度”往往会下降。（以Netflix为例，其每名员工创造的收入几乎为300万美元，是Google的两倍，是迪士尼的十倍。他们是唯一盈利的流媒体公司，员工不足20,000人，市值2400亿美元。）在工业时代，人才供过于求，工作职责明确，大多数员工的表现以“生产的产品数量”来衡量。那个时候，低绩效者可以轻松地被高绩效者替换，因为劳动市场上有大量的人才可供选择。但我们不再生活在那个时代了。在我们现在的世界里，失业率低于4%，关键技能持续短缺，劳动力整体也日益减少。而且，得益于自动化和AI技术，每位员工创造的收入或价值比30年前高出了几个数量级。因此，在一个人员更少的公司可以超越体量更大的公司的世界中，我们需要一种更好的绩效思考方式。看看Salesforce、Google、Apple这些本质上依靠创新的公司，随着规模扩大，它们的创新能力如何变缓。再看看OpenAI，尽管是一个小公司，却在超越Google和Microsoft。如今，大多数企业通过创新、市场响应速度、客户亲密度或知识产权而非规模或“更加努力的工作”来实现超越。在我们不断发展公司并招聘大量人员的同时，我们如何保持高水平的“人才密度”？Netflix在此领域有着开创性的工作，让我来分享一下他们的故事。首先，招聘过程应专注于提高“人才密度”，而不是仅仅为了填补空缺。我们寻找的不是简单地“填补一个角色”的人，而是能够为整个团队带来正面或倍增效果的人才。我们寻找的是那些能够挑战现状、带来新观点和技能，并超出传统“工作定义”的人。例如，Netflix重视勇气、创新、无私、包容和团队合作等价值观，并不仅仅是“完成既定工作”。 Netflix的理念是，每一次新增的招聘都应该使公司内每个人和团队的每个成员的生产力得到提升。这对于那些缺乏安全感的管理者来说可能是个挑战，因为大多数管理者并不希望招聘可能会取代他们的人。但正是这种思维方式导致了我们当前的问题。其次，我们需要建立或改进一种围绕帕累托分布（也称作幂律分布）而非正态分布的绩效管理流程。在帕累托分布或幂律分布中，少数人贡献了超出常规的绩效水平，这可以称作80/20规则或90/10规则。（即20%的人完成了80%的工作）研究显示，许多公司和人群实际上都是以这种方式运作的，这是合理的。想想那些在体育、音乐、科学和娱乐领域表现出色的人，其中少数顶尖人才的表现是同龄人的两到三倍。销售和许多商业领域也是如此。 2011年和2012年由Ernest O’Boyle Jr.和Herman Aguinis进行的研究（涵盖了633,263名研究人员、艺术家、政治家和运动员，共198个样本）发现，这94%的群体的表现并不遵循正态分布，而是呈现所谓的“幂律分布”。在每个人群中，总有少数人因为天赋异禀，在工作中表现出色，自然而然地比其他人优秀得多。比尔·盖茨曾经对微软说过，他认为公司中的三名工程师是公司的基石。我也在许多其他公司听到过类似的故事，其中一位软件工程师在合适的位置上可以完成其他十人的工作量。这并不意味着每个人都将被归入帕累托分布的某一层级。在你职业生涯的某个阶段，你可能处于80%的群体中，但随着你不断学习、成长并找到自己真正擅长的领域，你最终可能进入20%的群体。但在任何一个公司，这种动态都在不断发生。这就是Netflix一直在努力提升“人才密度”的原因。这对绩效管理意味着什么？这意味着，为了照顾这样一个群体，我们必须采取不同的招聘方式，避免使用钟形曲线，并且为高绩效者提供丰厚的薪酬。这不仅仅是支付比其他人稍微多一点的薪水，而是要多得多。这在体育和娱乐领域已经是常态，那么为什么不可以应用到商业领域呢？如果你观察Google、Microsoft等公司，你会发现，这些公司中的个别人物赚取的收入是他们同事的两到三倍。只要这些决策基于绩效，大家通常都能接受它。当然，不起作用的情况是，赚取高薪的是那些最擅长政治、外表最出众或最受欢迎的人。这就引出了第三点：在Netflix的文化中，存在着大量的授权、360度反馈、直率和诚实。您可能已经读过Netflix的文化宣言，它强调人们需要诚实、坦诚、互相提供反馈，并专注于判断力、勇气和责任感。直到最近，Netflix才引入了职级制度——在很多年里，他们根本没有职级制度。提供反馈是挑战性的，因为这会使人感到不适。因此，这个过程必须从高层开始，并以一种促进发展、诚实的方式进行。这并不意味着人们应互相威胁或贬低，但我们都需要明白，在项目结束或会议结束时，对方告诉我们“这是成功之处，这是失败之处”是完全可以接受的。美国军队是世界上最重要的机构之一，它依靠这种过程生存、发展和克服困难。如果你在军队犯错，你可以确信会有人告诉你，并且你会得到帮助以确保你不会再犯同样的错误。虽然公司里没有生死攸关的情况，但我们完全可以借鉴这种纪律性。在“人才密度”中很重要的第四点是领导力和目标设定。阻碍高绩效公司发展的一个常见问题是过多的个人目标、孤立的项目和职责，以及员工无法看到整体大局。如果你的目标设定和绩效管理过程完全基于个人表现，那么你就在削弱你的公司。这不仅阻碍了团队合作，而且实际上没有什么是公司内任何人能够独立完成的。因此，我们的绩效管理研究不断表明，人们应该同时因其个人成就和团队成就而获得奖励。（这是相关的研究。）为什么“人才密度”在当前尤为重要？我来列举几个原因。首先，我们正处于一个失业率低的时期，因此每次招聘都将是一个挑战。而且，随着AI技术的帮助，公司将能够以更小的团队运作。在这样一个时刻，有什么比考虑如何“精简”你的公司、使其发挥最佳表现更合适的时机呢？其次，随着AI的变革，你的公司将需要极大的灵活性和学习适应能力。你需要一个高度专注、良好协调的团队来实现这一目标。而且，尽管AI将帮助每个公司提高效率，但你快速应用AI的能力将变成一个竞争优势（回想一下网站、数字化和电子商务如何实现了同样的事情）。（我坚信，那些能够巧妙应用AI的公司将会颠覆它们的竞争对手。我对Whole Foods的手掌识别结账过程仍感到惊讶：我预见到自助服务咖啡、杂货及其他零售和酒店业务的出现。）第三，后工业时代的商业世界将开始贬低庞大、笨重的组织。许多大公司只是需要大量员工，但正如西南航空所示，小团队的表现通常更好。因此，如果你无法将你的公司划分为小型高效团队，你的“人才密度”将受到影响。当有关Apple的100亿美元汽车项目的书籍编写时，我敢打赌问题之一将是团队的规模和规模。我们很快就会发现。顺便说一下，我还是推荐每个人阅读《神话般的人月》，对我而言，这本书是关于围绕小团队进行组织的经典之作。如果你是医疗服务提供者、零售商、制造商或酒店业者，“人才密度”是否适用于你？当然适用！走进一家Costco，看看员工是多么的开心和投入。然后走进一个管理混乱的零售商，你就能感受到区别。在我的书《不可抗拒》中，我列出了那些拥抱我所称之为“人类精神不可磨灭力量”的公司的例子。没有人愿意觉得自己表现不佳。通过适当的关注责任和成长，我们可以帮助每个人超越他们自己的期望。现在是时候重新考虑我们的组织如何运作了。我们不仅应该提升和奖励顶尖表现者，帕累托法则和“人才密度”思维还鼓励我们帮助中等表现者学习、成长，并将自己转变为明星。让我们抛弃旧的钟形曲线、强制分配和简单化绩效管理的想法。不断追求高绩效的公司是充满活力的工作场所，他们提供卓越的产品和服务，并且对投资者而言是极好的投资。

Josh Bersin
2024年03月10日
Josh Bersin

Is DEI Going to Die in 2024? Josh Bersin 的文章讨论了 2024 年多元化、公平与包容（DEI）项目所面临的重大挑战和批评，特别强调了 "反觉醒 "评论家的攻击和克劳迪娜-盖伊（Claudine Gay）从哈佛辞职的事件。报告探讨了多元包容计划在当前的文化战争中扮演的角色、人们对它的看法以及法律挑战对多元包容计划招聘和投资的影响。尽管存在这些挑战，贝尔辛还是强调了发展型企业的实际商业利益，展示了成功的战略以及将发展型企业融入业务而不仅仅是人力资源的重要性。他认为，应将重点转向在所有业务部门嵌入包容、公平薪酬和开放讨论的原则，并指出，未来的企业发展指数至关重要，但需要适应和领导层的承诺才能茁壮成长。 Is DEI Going to Die in 2024? By Josh Bersin For anyone working in Diversity, Equity, and Inclusion (DEI), it is safe to say that it has been a tough start to 2024. For a while now, there has been a concerted attack on DEI programs, with ‘anti-woke’ commentators and public figures querying their value, worth, and even existence. Those attacks increased enormously in 2024 with the resignation of Claudine Gay from Harvard. While the call to resign was supposedly related to plagiarism, one can’t help but feel that her position as a leading DEI advocate also fuelled the demand. It means that DEI has come under increased and sustained fire, and despite the many benefits provided by a good DEO program – to both employer and employee – there is a feeling that 2024 could be the year that DEI fades away. How likely is this to happen, and what would the impact be if it did? DEI and the culture wars Anyone living and working in the US (or most other countries worldwide) over the past few years will have likely heard of the culture wars. Brought on by declining trust in institutions, growing inequalities, and the proliferation of technology, the culture wars involve opposing social groups seeking to impose their ideologies. All manner of things has been caught up in this, from what’s on the curriculum at schools to taking a knee at sporting events and from definitions of what constitutes a woman to allegations of tokenism in the workplace. DEI has played an unwitting but central part in the culture wars. There’s a perception that DEI programs are ‘woke’ and prioritize ethnicity and gender over achievement and ability. In August of 2023, an attorney filed (and won) a lawsuit against a VC firm that gives grants to black entrepreneurs. Similar suits have been filed against firms with diversity hiring programs, scholarships, and internships. The resignation of Claudine Gay has reinvigorated the commentary around DEI programs. Josh Hammer, a conservative talk show host and writer, wrote on the social media platform X that taking down Dr. Gay was a “huge scalp” in the “fight for civilizational sanity. ” It was described as “a crushing loss to DEI, wokeism, antisemitism & university elitism,” by conservative commentator Liz Wheeler, and the “beginning of the end for DEI in America’s institutions,” by the conservative activist Christopher Rufo, who had helped publicize the plagiarism allegations against Claudine Gay. When something is as consistently criticized and devalued as DEI programs have been, a toll is inevitably taken. That is certainly indicated by the latest hiring data for DEI professionals. According to data from labor market analytics company Lightcast, hiring for DEI positions in the US is down by 48% year over year, in the middle of an economic boom. Clearly, DEI investments are under attack. And when you look at companies doing layoffs, DEI jobs are frequently high on the list of jobs to cut. I even heard a recent podcast with four well-known venture capitalists – three agreed that “doing away with DEI programs” was top on their list. The value of DEI Given this criticism of DEI programs, one could be forgiven for thinking such programs carry no value to HR and the wider business. Yet many companies invest in DEI programs, and the value is high in almost every case I come across. Our Elevating Equity research in 2022 and 2023 found companies focus on diversity and inclusion for very pragmatic reasons, including: An inclusive hiring strategy broadens and deepens the recruiting pool. An inclusive leadership strategy drives a deeper leadership pipeline. An inclusive management approach helps attract diverse customers and markets. An inclusive board drives growth and market leadership. (proven statistically) An inclusive supply chain program improves sustainability of the supply chain. An inclusive culture creates growth, retention, and engagement in the employee base. Organizations are not prioritizing DEI programs because they are woken or as a box-ticking exercise. They do so because DEI provides real and tangible business benefits. Workday, one of the most admired HR technology companies in the market, has pioneered DEI internally and through its products, and the company has outgrown and outperformed its competitors for years. Their product VIBE, an analytics system designed for this purpose, shows intersectionality, and helps companies set targets and find inequities in leadership, hiring, pay, and career development. But some law firms have posited that these types of programs are illegal – is there a case to answer? DEI legality In response, it’s important to consider the massive and complex pay equity problem. Until the last few years, most companies had no problem paying people in very idiosyncratic ways. The Josh Bersin Company looked at leadership, succession, and pay programs worldwide last year and found that there are massive variations in pay with no clear statistical correlation in most larger companies. This problem is called “pay equity,” and when you look at pay vs. gender, age, race, nationality, and other non-performance factors, most companies find problems. Is this a “DEI” program? When we looked at pay equity in detail last year, we found that only 5% of companies have embarked on a strategic equity analysis. While most companies do their best to keep pay consistent with performance, these studies always find problems. Would it be considered illegal to analyze pay by race or nationality and then fix the disparities? The future of DEI DEI is undoubtedly a complex issue, and many organizations will be uncertain about the best course of action. Despite the current wave of criticism, there has been vast investment in DEI strategy over recent years, and business leaders are highly unlikely to let that fade away. Despite the anti-woke movement, political debates, and the inability of Harvard, Penn, and other universities to speak clearly on these topics, businesses will not stop. Affirmative Action was not created to discriminate; it was designed to reduce discrimination. At the University of California, where Affirmative Action was halted in 1995, studies found that earnings among African American STEM graduates decreased significantly. So, one could argue that they were making a real difference. DEI will not die – it is far too important for that to happen. However, it’s time to do away with the “DEI police” in HR and focus on embedding the principles of inclusion, fair pay, and open-minded discussions across all business units. Senior leaders must take ownership of this issue. In the early 2000s, companies hired Chief Digital Officers to drive digital technology implementation, ideas, and strategies. As digital tools became commonplace, the role went away. We may be entering a period where the Chief Diversity Officer has a new role: putting the company on a track to embrace inclusion and diversity in every business area and spending less time pushing the agenda from a central group. In every interview we conduct on this topic, we see overwhelming positive stories from various DEI strategies. Each successful company frames DEI as a business rather than an HR strategy. While HR-centric DEI investments are shrinking, it’s more like them migrating into the business where they belong. 中文翻译如下，仅供参考： 2024年，多样性、公平与包容（DEI）将走向消亡吗？作者：Josh Bersin 对于那些致力于多样性、公平与包容（DEI）领域的人士来说，2024年的开端无疑充满挑战。近期，DEI项目遭到了前所未有的集中攻击，包括一些“反觉醒”评论员和公众人物对其价值、意义乃至存在的质疑。特别是随着Claudine Gay从哈佛大学的辞职，这种攻击愈发激烈。尽管她的辞职表面上与剽窃事件有关，但不难察觉，她作为DEI领域的领军人物，这一身份似乎也是辞职呼声高涨的一个重要因素。这意味着，DEI正面临着前所未有的挑战。尽管高效的DEI项目能够为雇主和雇员带来众多益处，但人们仍担忧2024年可能成为DEI逐渐淡出视野的一年。这种情况发生的可能性有多大？如果真的发生，又会产生何种影响？ DEI与文化战争近年来，无论是在美国还是全球其他大多数国家，你可能都会听说过“文化战争”。这场战争源于对机构的信任下降、不平等现象的加剧以及技术的广泛传播，涉及到试图强加自己意识形态的社会对立群体。从学校课程内容、体育赛事中的下跪行为，到对“女性”定义的争议、以及工作场所中的代表性指控等，无一不被卷入这场文化战争。而DEI，在这场战争中虽不愿意却占据了核心位置。人们普遍认为DEI项目倾向于“觉醒”，过分强调种族和性别因素，而忽视了成就和能力。2023年8月，一位律师成功对一家支持黑人创业者的风险投资公司提起诉讼。类似的诉讼也针对那些实施多样性招聘、奖学金和实习计划的公司提起。 Claudine Gay的辞职再次引发了对DEI项目的广泛讨论。保守派脱口秀主持人和作家Josh Hammer在社交媒体平台X上表示，击败Gay博士是“为文明理智而战的一大胜利”。保守派评论员Liz Wheeler称之为“对DEI、觉醒主义、反犹太主义及大学精英主义的沉重打击”，而保守派活动家Christopher Rufo则称这是“DEI在美国机构中走向终结的开始”。如此一致的批评和贬低无疑对DEI项目造成了重创。根据劳动力市场分析公司Lightcast的数据显示，尽管经济蓬勃发展，但美国DEI相关职位的招聘量同比下降了48%。显然，DEI正面临严峻挑战。当提到公司裁员时，DEI相关职位往往是裁减名单上的重点。我最近听到一个播客，四位知名风险投资家中有三位认为“取消DEI项目”是他们的首要任务。 DEI的价值面对如此批评，人们或许会误以为DEI项目对人力资源和更广泛的商业活动没有任何价值。然而，实际上，许多公司对DEI项目的投资极具价值，几乎每个案例都能证明这一点。我们在2022年和2023年的《提升公平研究》中发现，公司出于实际原因关注多样性和包容性，这包括：包容性招聘策略扩大了招聘范围。包容性领导力策略深化了领导力储备。包容性管理方式吸引了多元化的客户和市场。包容性董事会推动了市场增长和领导地位（这一点已通过统计数据得到证明）。包容性供应链项目提升了供应链的可持续性。包容性文化促进了员工的增长、留存和参与。组织之所以优先考虑DEI项目，并非仅仅因为“觉醒”，或者作为勾选式行动。他们这样做是因为DEI确实带来了实际和有形的商业利益。例如，Workday这样的HR技术公司在市场上备受尊敬，它不仅在内部推广DEI，在其产品中也体现了这一点，多年来一直超越竞争对手的增长和表现。它们的产品VIBE，一个专门设计的分析系统，展示了交叉性，帮助公司设定目标，找出领导力、招聘、薪酬和职业发展中的不平等。然而，一些律所提出这类计划可能违法——这是否成立呢？ DEI的合法性面对这一问题，我们不得不考虑到复杂且广泛的薪酬公平问题。直到最近几年，大多数公司在个性化支付薪酬方面并未遇到太大问题。Josh Bersin Company去年对全球的领导力、继承计划和薪酬计划进行了研究，发现在许多大公司中，薪酬存在巨大差异，且大多没有明显的统计相关性。这个问题被称作“薪酬公平”。当涉及到性别、年龄、种族、国籍等非绩效因素时，大多数公司都存在问题。那么，分析基于种族或国籍的薪酬差异并加以解决，这会被认为是非法的吗？ DEI的未来 DEI无疑是一个复杂的议题，许多组织对于采取何种措施感到不确定。尽管面临当前的批评浪潮，但近年来对DEI策略的巨大投资表明，商业领袖们不太可能让这一切付诸东流。尽管存在反觉醒运动、政治辩论，以及哈佛、宾夕法尼亚大学等教育机构在这些议题上的模糊立场，但商界不会因此而停滞不前。平权行动的初衷不是为了歧视，而是为了减少歧视。例如，在加州大学，自从1995年停止实施平权行动以来，研究发现非洲裔美国人STEM专业毕业生的收入显著下降。因此，可以说这些措施确实产生了积极的影响。 DEI不会消亡——它对此太重要了。然而，现在是时候取消人力资源部门中的“DEI警察”，转而专注于在所有业务单元中嵌入包容性、公平薪酬和开放性讨论的原则。高级领导层必须对这一议题负起责任来。回顾21世纪初，许多公司聘请首席数字官来推动数字技术的实施、创意和战略。随着数字工具成为常态，这一角色逐渐消失。我们可能正处于一个新的时期，首席多样性官的角色也在发生变化：不再是从中心团队推动议程，而是引导公司在每一个业务领域都拥抱包容性和多样性。通过我们在这个话题上的每次采访，我们都能看到各种DEI策略的积极故事。每个成功的公司都将DEI视为一项业务策略，而非仅仅是人力资源策略。虽然以HR为中心的DEI投资正在减少，但这更像是它们向业务领域的转移，这正是它们应有的归属。

Josh Bersin
2024年02月23日
Josh Bersin

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

Josh Bersin
2024年02月18日

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