Josh Bersin

Josh Bersin

我有需求

In 2001, Josh Bersin founded Bersin & Associates, which became the leading research and advisory company for corporate learning, talent management, and HR. In 2012, Josh sold the company to Deloitte, when it became known as Bersin by Deloitte. As a Deloitte partner, Bersin was involved in many HR and learning engagements and was a principal author of Deloitte’s annual Human Capital Trends Report. He retired from Deloitte in 2018.
最新动态
  • Josh Bersin
    BetterUp Manage: Pioneering AI-Powered Platform For Leaders BetterUp公司最近在其Uplift大会上推出了一个名为BetterUp Manage的领导力发展平台，这一平台采用人工智能驱动的评估和个性化学习方案，彻底改变了专业发展的途径。该平台具有高度的可扩展性和可定制性，能够与Workday、Oracle和SAP等主要系统无缝连接。BetterUp Manage不仅为领导者提供服务，也支持任何寻求发展专业能力的个人。通过整合最新的人工智能技术，BetterUp Manage为传统的领导力培训行业带来了革命性的变革。 这次大会中，BetterUp还邀请了英国的哈里王子Prince Harry, Duke of Sussex 和亚当·格兰特，哈里王子是BetterUp的首席影响官。。。 This week I attended the BetterUp Uplift conference and I really was impressed. This is a company that exploded into the market with an innovative coaching and employee wellbeing network built around an assessment called the “whole person model.” Through a set of shrewd marketing and sales strategies BetterUp established a leadership position in this market, growing to a billion dollar+ valuation. This success encouraged many competitors to form and now the market for AI-enabled, targeted coaching is large and crowded (vendors include Torch, CoachHub, Growthspace, Sounding Board, Bravely, and a new breed of AI systems). Essentially what BetterUp did was democratize business and professional coaching. Before this trend coaching was a rarified, expensive offering reserved for under-performing leaders or high-potential executives. Today, with BetterUp, anyone can go through a meaningful assessment, get assigned a relevant coach, and start a coaching session in minutes. The system is well designed and easy to use and BetterUp’s coaches are all trained (most of the coaching vendors use a lot of the same certified coaches – they are not BetterUp employees). As a corporate solution, BetterUp goes much further. The data collected through assessments is available for analysis (anonymized) so companies can find pockets of stress in the organization. You can look at assessments by team (minimum of 10 people), tenure, level, and other factors. This lets companies like Chevron or Cisco understand the issues new employees or new managers have, for example. In the last few years the company moved into wellbeing by offering a solution called BetterUp Care, which targets benefits buyers. But the more strategic and interesting offering is the new platform I saw this week, now named BetterUp Manage (it was originally called Connect). BetterUp Manage is the first highly personalized, scalable management development platform I’ve seen. It brings together AI-enabled assessment, personalized learning, coaching, and AI-driven narrative support. It’s quite an impressive product, much of it was developed by the team at Motive, who was acquired by BetterUp in 2021. BetterUp Manage is an out of the box personalized leadership development solution. And you don’t need to be a “leader” to use it. The system steps you through the Whole Person assessment, then asks you questions about the types of soft-skills issues you face (many specific scenarios), and then gives you a customized learning path, week by week, along with a professional coach. Since it’s built on an AI platform there is very little manual work behind the scenes so it’s enormously scalable. Large companies will want to customize it and BetterUp is prepared for some of these requests. And the system connects to Workday, Oracle, SAP to automatically understand your role and level. The reason I’m so excited is this: the management training industry is a confusing, messy, red ocean. There are thousands of consultants, coaches, books, courses, and executive education programs. L&D executives have to constantly build custom solutions, evaluate vendors, and hope that an offering will stick. This pure complexity, coupled with the fact that every company is unique, has led to many specialized leadership development firms (and some big ones like Franklin Covey). So what most companies do is mix, match, and custom-build leadership solutions. And they’re not simple: we developed a model we call the 4-E’s to understand this: Education (courses), Experience (developmental assignments), Exposure (mentoring and coaching from leaders), and Environment (a company-wide focus on leadership values and behaviors). All these elements play a role in developing leadership skills. Companies like IBM, Cisco, and Marriot can afford to custom build these solutions, but many companies don’t have the focus. BetterUp Manage is a way to personalize, scale, and democratize this solution and leverage the increasingly important role of AI. I met Alexi Robichaux almost a decade ago and his passion and energy still drives the company. While BetterUp is a bigger company going through the growing pains of any $billion valued growth business, the culture and passion for clients is clear. Remember that buying L&D solutions is not as simple as buying a product and turning it on. Every training solution, platform, or program you buy must be carefully aligned with your company’s culture and rolled out with care. Otherwise people simply say “another training program from corporate I can ignore.” BetterUp, for all its startup-like innovations, has overcome this problem. Customers value the system, they get strong adoption from employees, and the company works hard to advise and consult. It has always been interesting to me that very few content companies ever become very big (Skillsoft is the only one that never seems to stop). And the reason for this is simply the nichey, highly diversified needs of many industries and companies. BetterUp, as a platform-centered company delivering a high-touch solution, has the potential to break this paradigm. It has enormous potential, given the rapid acceleration of AI behind the scenes. I consider BetterUp one of the “Trailblazers” I talk about with clients, and BetterUp Manage is definitely something to watch.
    Josh Bersin
    2024年04月12日
  • Josh Bersin
    Will Chatbots Take Over HR Tech? Paradox Sets The Pace. 在快速发展的人力资源技术领域，Paradox.ai 已成为领跑者，其先进的对话式人工智能平台彻底改变了招聘流程。通过利用自然语言处理和人工智能，Paradox.ai 提供了一个全面的解决方案，涵盖了从最初的职位申请到入职的整个招聘过程。该平台不仅简化了筛选和面试安排等繁琐流程，还提升了应聘者的整体体验，显著改善了招聘时间和招聘质量指标。 Paradox.ai 由亚伦-马托斯（Aaron Matos）于 2016 年创立，目前为联合利华、CVS Health 和通用汽车等大客户提供服务，实现了 90% 以上的招聘流程自动化。 Paradox.ai 凭借其强大的集成能力和大幅缩短招聘时间、降低招聘成本的能力，在人力资源技术领域充分体现了对话式人工智能的变革力量。 Chatbots used to be tinker-toys. You type, try to get help, but usually result in “please call support.” Well all this has changed. Thanks to advanced NLP (natural language processing) and AI (retrieval-augmented generation) chatbots are entire applications. They can answer complex questions, search databases, and invoke transactions on your behalf. Pretty soon we’ll be able to ask our phones “please find me a flight to Los Angeles next Tuesday morning” and the system will check your location and calendar, look at flights, and book you a seat. Where is this going in HR? Well the leader in this space is Paradox.ai, a company that pioneered the application of conversational AI in recruiting. And their system “defines the category.” Let me explain. Recruiting Is The Perfect Market For Conversational AI Recruiting is a goldmine for automation. When you post a job, applicants want to ask many predictable things: “How much does it pay?” “What are the hours?” or “What uniform do I need” or “What are the benefits?” The recruiter, a person devoted to filling positions, has to answer all these questions and more. They have to screen candidates, schedule interviews, check for qualifications, and look at credentials, experience, and more. It’s time-consuming, error-prone, and filled with wasted time. (That’s why talent acquisition teams have many “scheduler” and admins.) The average “time to hire” is over 45 days and often the process goes on for months. And throughout the experience the job seeker is left wondering “when will they call back” or “what else do I need to know?” (CEOs cite hiring as the third most time-wasting process in companies, following emails and meetings, estimated at “40% wasted time.”) Paradox uses Conversational AI to solve this problem. And because this is a “narrow but deep” space, the system does many things we can learn from in all our AI efforts. Paradox was founded by Aaron Matos in 2016. Aaron’s vision was to transform the candidate experience, revolutionizing the way candidates apply to jobs. Today Paradox has become a complete Conversational AI Recruitment Platform (chat to apply, scheduling, candidate support, ATS, assessments, onboarding, career site, and more), serving clients like Unilever, CVS Health, Pfizer, L’Oreal, Nestle, McDonald’s FedEx, Compass Group, Disney, and General Motors. The platform automates tasks such as screening for requirements, interview scheduling, reminders, offers, and new hire onboarding. And because it’s so easy to use, it helps companies radically improves time-to-hire and quality of hire. Based on my conversations with clients, Paradox can automate more than 90% of the end-to-end hiring process, saving hiring managers hours every week and increasing candidate conversion by more than 10 times. But this innovation did not happen overnight. As you know, going to a candidate website and looking for a job is a frustrating process. There are often hundreds of jobs listed, a complex scrolling website and very hard to even determine what job to apply for. You might argue that the website paradigm for job applications was never really a good idea in the first place. People don’t want to browse for jobs: they want to apply for a job that’s best for them. So the first thing Paradox did was create an easy to use assistant (Olivia) so candidates could ask questions and schedule interviews. And this meant that Paradox had to build integrations with every ATS and personal email and calendar tools out there. Then, as companies started to use Paradox for scheduling, the company added more. Today Olivia, the chatbot, can integrate with background check vendors, schedule interviews, deliver assessments (Paradox acquired a conversational assessment Traitify designed for this), and function as an ATS … all from a mobile phone. In many ways Paradox can be “the integration platform” for candidates and recruiters, stitching together the messy systems behind the scenes. This turned into a massive opportunity. Just as the Google Assistant or Siri hopes to be our single contact with the internet, Paradox partners with systems of record like Workday, SAP, and Oracle to bring conversational AI to any company. The company’s revenues have grown 11 times in the last four years, and are now nearly doubling each year. For customers Paradox has been amazing. As the candidate pipeline speeds up (by an order of magnitude), clients get higher quality candidates with dramatically reduced staff. (Staffing administrators can almost go away.) Consider high-volume hiring companies. These businesses (McDonald’s, Compass Group, Neighborly, FedEx, Disney) hire service-related workers on a regular basis. Their revenue is dependent on having enough people. With Paradox they can set up a “continuous recruitment process,” one that even hires people the same day they apply. Paradox has become essential to these companies growth, often paying for itself in less than a year (through reduced hiring staff, reduced spend on job ads, and reduced turnover.) Today, as Paradox built out its ATS, customers can rely on the platform to integrate front end tool (job portals and candidate support) to back end tools scheduling, ATS, onboarding) most of which are legacy. One of our clients has 27 recruiting tools and they anticipate replacing more than half of them with a platform like Paradox. What about higher level white collar roles? Paradox works here too. General Motors uses Paradox along with Workday (ATS), (branded Evie) to redesign the process. Interview Scheduling: Evie automates scheduling of phone screens and interviews between recruiters, candidates, and internal teams. This has reduced the time taken for interview scheduling from an average of five days to 29 minutes. Candidate Experience: Evie interacts with candidates from the moment they land on GM’s career site until the completion of their interview. Candidates appreciate the immediate communication from Evie after they apply or complete an interview, and enjoy the autonomy to select and change interview times. Efficiency and Cost Savings: The automation of interview scheduling has led to a major reduction in the cost of external contractors for coordination. Career Site Interaction: Evie sits on GM’s career site, answering questions from potential candidates about jobs, benefits, and company culture. This interaction enhances the candidate’s experience and provides them with immediate responses to their queries. Where Is Paradox Going The company is perfectly positioned to continue its growth as companies look for AI solutions to improve the productivity and effectiveness of recruiting. And demand is high: the 2024 PwC CEO survey found that recruiting was considered the #3 “most bureaucratic process” by CEOs (following email and meetings). The impact on recruiters? All positive. Clients tell us they can redeploy hiring staff to help recruiters focus on the most important part of their job: talking with candidates. But there’s a much bigger story. When a job candidate is handled efficiently and effectively the process becomes a brand-builder for the candidate, improving quality of hire. Ambitious job seekers will not put up with (or wait for) a messy, confusing hiring process. So not only is the process faster and more efficient, the quality of hire goes up. Companies are desperately looking for AI solutions that work. As Paradox has proven, when you focus deeply on the problem, conversational AI can be transformational. Listen to my conversation with Adam Godson (CEO) and you’ll hear the details. This is where the HR Tech market is going.
    Josh Bersin
    2024年04月04日
  • Josh Bersin
    Josh Bersin :劳动力市场已完全改变：您真的准备好了吗？ Josh Bersin 最新撰文谈到，随着以婴儿潮一代为主的劳动力队伍的衰落和具有独特期望和职业模式的新一代的崛起，劳动力市场发生了巨大的变化。这一新劳动力的特点是偏好组合职业和副业，他们要求尊重、灵活性和精心设计工作的机会。企业在适应这些变化时面临着挑战，职位普遍空缺，人员流动增加。文章强调，企业需要采用一种动态的组织模式，优先考虑授权、内部流动性和员工积极性，以便在这个新的劳动力市场中茁壮成长。这种适应的关键在于了解劳动力现在寻求的是成长、灵活性以及他们的价值观与工作之间有意义的结合。 英文原文如下，推荐了解 The labor market has changed before our eyes. Employers and HR teams better watch out. Over the last five decades baby boomers defined the workforce. Today things could not be more different, and this change impacts all of us. I was born in the 1950s, growing up in a world where the middle class experienced steadily increasing standards of living. My father was a scientist, my mother sold art, and my brother and I had a nice middle-class life. This included a three stage career: education | work | retirement. I went to college, studied hard, and got a good job as an engineer. My career went on a predictable path. I worked for Exxon and then IBM – each company giving me training, development, and potential for long-term career. I met many great people, learned about work, got married and had a family. My cohort, the baby boomers, was huge. Companies built entire talent systems for us – onboarding, training, predictable career growth, developmental assignments, leadership development, and retirement programs. We strapped ourselves in and enjoyed the journey. Fast forward to now: things are very different. Today’s working population bulge (median age 33, born in the early 1990s,) entered the workforce in a disrupted world. They joined companies during a boom, experienced the pandemic in their 20’s, and live in a world where everything is on the internet. While my generation revered our employers, these workers see every corporate mistake in real-time. They expect their bosses to earn their respect, otherwise they’ll “quietly quit” or start moonlighting on the side. While my generation expected to work for only a few employers during a career, today people build what Lynda Gratton calls “a portfolio career.” More than 2/3 of workers have side-hustles and their resume is filled with projects, businesses, activities, and professional interests. If you look at the LinkedIn profiles of most high performers they look like personal journeys, far different from the linear career paths we had in the past. While most of these changes came slowly, the end result is profound: the expectations, needs, and demands of workers are different. And businesses have struggled to keep up. Companies have vast amounts of unfilled positions, we suffer high turnover in almost every role, and labor unions are growing in number. What do companies do? We have to accept and understand that the labor market has totally changed. We live in a world where employees will live into their 100s. Young workers are postponing getting married and having children and they see their career as a long series of experiences. The norms of a long-term linear career have ended: people try new things, change industries, and live in what I call a “pixelated” job market. And rather than blindly trust employers, people bring high expectations to work. Young workers don’t expect to “become the job,” they want the job to “become them.” (Often called “job crafting.”) And given the shortage of workers in every role, this trend is just getting bigger. While economists believe the job market will soften and employers will have more power over time, I think those days are over. Life just isn’t going back to the way it was. Despite the growth of AI, companies are more dependent on their workforce than ever. And with 70% of the jobs now service-related (healthcare, retail, hospitality), employees really are our product. I look at it this way. Companies and employers live in a pool of labor: it’s the needs and expectations of people who decide what we can and should do. People are upset about inflation. They’re worried about climate change. They want CEOs to behave ethically. And they want flexible work that lets them live a joyful life. And every year the workforce becomes more educated and connected. (The percentage of US workers with degrees has gone up to 54%, up from 38% fifteen years ago.) People know about the company’s financial results or other issues far before an announcement even comes out. While many of these trends are obvious, many companies aren’t ready. Last year I talked to the CHRO of Boeing and he told me the problems were highlighted by employees years ago. They simply were not listening, and now they’re a company in crisis. And that leads to the topic of “employee activation.” In the old days senior leaders made decisions, workers carried out the orders. Ideas and strategies were “top-down.” Today much of the intelligence we need to grow our companies is sitting with front-line workers. We need to “activate employees” and listen to them directly. The worker in the store, plant, or front office who feels frustrated by some system or process is the person who should advise us what to do. The old idea of “management by walking around” must come back. (Our Org Design Superclass explains this in detail.) I don’t mean chaos, holacracy, or lack of controls. Successful companies have a clear mission, a series of strategic initiatives, and budgets to hold people accountable. But they empower everyone to be a leader, unleashing power from the bottom up. (Come to Irresistible and learn about how Marriott and Delta airlines exemplify this model.) The key is building what we call a “Dynamic Organization” – one which is flat, team-centric, connected, and accountable. Our research shows that only 7% of companies operate this way: most are still very hierarchical and slow to adapt. But change is coming, as companies like Delta, Marriott, Telstra, Unilever, Novartis, Seagate, and Bayer have found out. (This week the CEO of Bayer announced a radical transformation to a team-centric management model, dramatically reducing the number of “bosses.”) A dynamic organization does two things well. First, it adapts to change, sees new markets, and mobilizes quickly for change. But even more importantly, it empowers people, encourages internal mobility, and focuses on meritocracy, skills, and collaboration to thrive. (Read about Talent Density to learn more.) While these ideas are not new, urgency is critical. Employees demand growth, flexibility, and agency – and we can’t deliver it unless our reward and development systems change. Today more than 70% of US jobs are in the service sector: health care, retail, entertainment, and transportation. If we don’t empower people in these roles our products and services will suffer. Let me conclude with this: we just woke up in a totally new labor market. If you don’t focus on empowerment, growth, and employee activation, talent will just go elsewhere.
    Josh Bersin
    2024年03月31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
    Workday收购HiredScore的意义，这可能颠覆人力资源科技领域 Workday计划收购HiredScore，这是人力资源技术领域的一次重大变革。HiredScore是一家领先的基于AI的招聘匹配工具提供商，此举将大大增强Workday在人才智能和招聘方面的能力。这次收购预计将整合HiredScore的专长到Workday的系统中，显著改善其应聘者追踪系统（ATS）、技能云和整体人才智能产品。此战略性收购可能会重塑人力资源软件市场，迫使其他供应商加速他们的AI计划，可能激发一轮新的收购热潮。 以下是原文： This week Workday announced intent to acquire HiredScore, a leading provider of AI-based matching tools for recruiting (called “talent orchestration”). While it wasn’t discussed much in the earnings call, this deal is a big positive for Workday and could have many implications for the HR Tech market. Let me explain. (I have not been briefed by Workday yet, so more information will come as I learn more.) Right now there is a massive marketplace war for high-powered AI-based recruiting tools (estimated at $30.1 billion). Historically dominated by applicant tracking systems (ATS), this market provides essential technology to help every company grow. The ATS market, which is more than 25 years old, has been rapidly transformed with high-powered AI tools that help with candidate matching, search, skills inference, and sourcing. And now that AI tools are readily available, these systems are becoming big data platforms loaded with billions of employee profiles, running complex AI models to help match people to jobs, projects, and gigs. Most ATS vendors (including Workday) have slowly extended into this space through matching. The original idea of a resume parser (software that reads a resume and scores it against a job description) has evolved into complex text analysis and AI-powered inference technology, forcing ATS vendors to invest. As the ATS vendors enhance their AI capabilities, a parallel universe of AI-first Talent Intelligence vendors emerged. These vendors, like Eightfold, Gloat, Beamery, Phenom, Seekout, Skyhive, Retrain, and Techwolf are building skills-centric big data platforms to match people to jobs, gigs, and mentors. These systems do much more than rate matches: they identify skills, find adjacent skills, match people to careers, find mentors, and more. They are essentially open big-data AI platforms built on vector databases that can be used for many enterprise apps (job architecture design, skills planning, internal mobility, pay equity analysis, etc.). In many ways they represent the future of HR Tech. (Read our Talent Intelligence Primer for more.) As the Talent Intelligence vendors grow, they start to deliver “HCM-threatening” platforms that impinge on the HCM “System of Record” idea. If you have all your employees, candidates, alumni, and prospects in Eightfold, Phenom, Seekout, or Gloat, for example, Workday or SAP look like a tactical payroll and workflow management system. (ServiceNow also understands this, and is building talent intelligence into its workflow platform.) Up until now the big HCM vendors like Workday, Oracle, and SAP have struggled to build these new systems, largely because their original architectures were not AI-based. So they’ve attracted customers with offerings like the Workday Skills Cloud or SAP Opportunity Marketplace that aren’t fully completed yet. We have talked with dozens of Workday Skills Cloud customers, for example, and they see it as an important “skills system of record,” but its real AI matching and inference capabilities have been limited. Along comes HiredScore, a well respected AI-based matching system with 150 employees and 40+ seasoned AI engineers in Israel. These folks are experts at candidate matching (quite a complex problem), and they’ve built a very innovative “orchestration” system to help line managers coordinate activities with HR business partners and recruiters (more on this later). While I’m sure they’ll continue to build out HiredScore, they can also contribute to Workday’s overall talent intelligence offering, improving the entire system – including the Skills Cloud, Workday Learning, Workday’s Talent Marketplace. As large as the recruiting software market is, the market for internal career tools, talent mobility, skills inference, and corporate learning is five times bigger. This acquisition gives Workday a shot in the arm to accelerate its entire AI platform strategy. (As the Identified acquisition did back in 2014.  Identified was the roots of the Workday Skills Cloud.) Market Implications Of This Move This move could change the market for HR software in a few significant ways. First, Workday Recruiting customers will be thrilled. Workday’s ATS now benefits from a first class matching and candidate scoring solution. This helps Workday compete with the bigger ATS players and gives Workday a new revenue source as they sell HiredScore to the existing 4,000+ Workday ATS customers. (Similar to the Peakon acquisition in Employee Experience.) And the talent orchestration features (kind of like a “staffing copilot”) gives Workday a very unique feature set. Second, this forces Workday’s talent intelligence partners to step up their game. Remember when Apple acquired Dark Sky, the most compelling micro-weather app on the market? Once they integrated it into Apple’s other apps, the market for third party weather apps went away. Workday could limit its partner network to avoid letting HiredScore competitors into the ecosystem. Third, this forces HCM vendors to accelerate their AI. Since HiredScore is such a well-respected product (every client we talk with adores it), it will become part of Workday demos and sales proposals quickly. Workday’s HCM competitors will start scratching around to find a similarly mature AI vendor to acquire. And that could kick off another round of acquisitions, similar to the frenzy that took place in the mid 2010s. Finally, there’s one more scenario, and I give this good odds. Not to be outdone by Workday, the Talent Intelligence vendors may just expand their ATS capability and decide to go “full stack.” I wouldn’t be surprised to see this happen. Why Is AI-Based Candidate Matching So Important Why is this technology so important? Well if you’ve ever tried to recruit on Indeed or LinkedIn, you know why. The quality and reliability of “candidate matching technology” is a lynchpin of a talent platform. Just as Google Search crushed Yahoo, Excite, and Inktomi, a powerful next-gen matching tool adds an enormous amount of value. Not only does it speed talent acquisition, it fuels all the internal mobility, career portals, skills, and eventually learning and pay systems. Why do I say this?  A “match” is a sophisticated problem. Unlike a Google search which looks at text and traffic, when you search for a person to fill a role you have to think about dozens of complex relationships. What are this person’s skills and capabilities? What are their credentials or certifications? Who else are they connected with? How likely will they fit into the job, role, and company? What is the impact of their industry experience? What tools and technologies do they understand? And it gets much more complex. The Heidrick Navigator platform (built on Eightfold), uses AI to assess functional skills for management and leadership, identifies a person’s “ability to drive results,” and more. This important application of AI powers many of the most important decisions we make in business. That’s why the Talent Intelligence space is growing so fast. As of this week there are more than 1,800 Director or VPs of “Talent Intelligence” in LinkedIn, and that number is up almost six-fold from one year ago. Can Workday take the lead in this emerging space?  It’s impossible to tell at this point, but the horses have left the gate and the race is on. This deal sets the players in the right lanes and feels like the earthquake to shake things up.  
    Josh Bersin
    2024年03月01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
  • Josh Bersin
    2024年人力资源预测：全球追求生产力 In this fast-evolving era, all companies and individuals are seeking for change and efficiency. We can see the core of productivity in the new year: AI. Let's have a look at details on the Josh Bersin Predictions for 2024. 在过去的二十年里，我一直在写关于人力资源预测的文章，但今年不同。我看到这一年打破了范式，改变了商业中的每一个角色。不仅人工智能会改变每家公司和每一项工作，而且公司将开始不懈地寻求生产力。 想想我们的过去。2008年金融危机后，世界开始了加速增长的零利率时期。公司增加了收入，雇用了员工，并看着他们的股价上涨。招聘继续以狂热的速度进行，导致2019年底失业率创下3.5%的历史新低。 随之而来的是大流行，在六个月内，一切都停滞不前。2020年4月，失业率飙升至15%，公司将人们送回家，我们重新设计了我们的产品、服务和经济，以应对远程工作、混合工作制和对心理健康的关注。 一旦经济再次启动（由于美国的财政刺激），公司又回到了旧的招聘周期。但随着利率上升和需求不足，我们看到裁员一再发生，在过去的18个月里，我们看到了招聘、裁员，然后再次招聘以复苏经济。 为什么会出现跷跷板效应？ 首席执行官和首席财务官正处于我们所说的“工业时代”——招聘以增长经济，然后在事情好转时裁员。 今天，当我们进入2024年时，一切都不同了。我们必须“囤积人才”，投资于生产力，并重新开发和重新部署人员以实现增长。 我们生活在一个失业率为 3.8% 的世界，几乎每个职位都存在劳动力短缺，劳动力权力日益增强，员工需求不断涌现：对加薪、灵活性、自主权和福利的要求。每年有超过20%的美国员工换工作（每月2.3%），其中近一半的变化是进入新行业。 为什么这是“新常态”？ 有几个原因。首先，正如我们在全球劳动力情报研究中所讨论的那样，行业是重叠的。每家公司都是数字化公司；每家公司都希望建立经常性收入来源；很快，每家公司都将使用人工智能。过去停留在行业内的职业正在转变为“基于技能的职业”，让人们比以往任何时候都更容易跳槽。 其次，员工（尤其是年轻员工）感到有权按照自己的意愿行事。他们可能会悄悄地辞职，“做兼职”，或者抽出时间转行。他们看到自己的生活很长（人们的寿命比 1970 年代和 1980 年代长得多），所以他们不介意离开你的公司去其他地方。 第三，生育率持续下降，劳动力短缺加剧。日本、中国、德国和英国的劳动力人口都在萎缩。在未来十年左右的时间里，大多数其他发达经济体也将如此。 第四，工会正在崛起。由于华盛顿的新理念，我们看到了谷歌、亚马逊、星巴克、GM、福特、Stellantis、凯撒、迪士尼、Netflix等公司的劳工活动。虽然工会参与率不到美国劳动力的11%，但在欧洲要高得多，而且这一趋势正在上升。 这一切意味着什么？ 这有很多影响。 首先，公司将更加专注于建立高保留率的工作模式（有人称之为“劳动力囤积”）。这意味着改善薪酬公平，继续混合工作模式，投资于以人为本的领导力，并为员工提供在公司内部从事新职业的机会。这就是为什么人才市场、基于技能的发展和工作流程中的学习如此重要的原因。 其次，CEO必须了解员工的需求、愿望和要求。正如爱德曼的最新研究表明的那样，职业发展现在位居榜首，同时对授权、影响力和信任的渴望也排在首位。我们称之为“员工激活”的新主题：倾听员工的意见，并将有关他们工作的决定委托给他们的经理、团队和领导者。 第三，传统的“雇佣成长”模式并不总是奏效。在这个后工业时代，我们必须系统地运作，将内部发展、工作再设计、经验和招聘放在一起。这汇集了招聘、奖励和薪酬、学习与发展以及组织设计等独立领域。（阅读我们的系统性人力资源研究了解更多信息。） “业务绩效”的真正含义是什么？ 如果你是首席执行官，你希望增长收入、增加市场份额、提高盈利能力和可持续性。如果你不能通过招聘来成长（而员工不断以奇怪的方式“激活”），你还有什么选择？这很简单：您可以自动化生产并专注于生产力。 虽然这张图表令人印象深刻，但它给每个CEO都引出了一个问题：我们在这张图表上的位置是什么？我们的运营速度是否与同行一样快、一样高效？ 我认为这导致了一种我称之为“生产力优势”的策略。如果你能帮助你的公司更快地发展（生产力意味着速度，而不仅仅是利润），你就可以比你的竞争对手更快地进行重塑。这才是真正让CEO们夜不能寐的原因。 考虑一下普华永道最新的CEO调查数据。今年，我们必须比以往任何时候都更快地重塑我们的公司。到2024年，45%的CEO（去年为39%）认为他们的业务在十年内将无法生存。 生产力优势 为什么生产力如此重要？有四个原因。 首先，CEO们关心它。 2024 年普华永道 CEO 调查发现，CEO 认为公司 40%的工作浪费了生产力。 尽管这听起来令人震惊，但对我来说却是真实的：太多的电子邮件、太多的会议、混乱的招聘流程、官僚主义的绩效管理等等。（HR 就有其中一些问题。） 其次，AI让人生产力优势成为可能。 人工智能的应用旨在提高白领的生产力。（过去大多数自动化都有助于蓝领或灰领工人。）生成式 AI 让我们能够更快地查找信息，了解趋势和异常值，训练自己和学习，并清理我们随身携带的文档、工作流程、门户以及后台合规和管理混乱的系统。 第三，公司的发展需要AI。 当很难找招聘到人时，你将如何成长？去年，招聘时间增加了近20%，就业市场变得更加艰难。你能在技术技能上与谷歌或OpenAI竞争吗？ 内部开发、重组和自动化项目就是答案。有了生成式人工智能，机会无处不在。 第四，生产力推动重塑。 如果你考虑重塑你公司（新产品、利用人工智能、进入新市场等）的需求，最大的障碍是惯性。为什么诺基亚和黑莓的手机业务输给了苹果？因为这些公司“又胖又快乐”。在这个人才和技能短缺的时代，这是灾难的根源。 普华永道（PwC）估计，“效率低下”产生了对GDP10万亿美元的税收，相当于全球GDP的7%。这种税收阻碍了您的公司转型。每当我们简化、减少会议并更好地定义决策权时，我们都会加快并实现变革。 这一切对人力资源意味着什么？ 正如我在《人力资源预测》中所描述的那样，我们有很多问题需要解决。 我们必须加快向动态工作和组织结构的转变。我们必须专注于和务实地对待技能。我们必须重新思考“员工体验”，并处理我们所说的“员工激活”。我们将不得不对我们的人力资源技术、招聘和L&D系统进行现代化改造，以利用人工智能并使这些系统更加有用。 我们的人力资源团队也将由人工智能驱动。正如我们的Galileo™客户告诉我们的那样，一个架构良好的“专家助理”可以彻底改变人力资源人员的工作方式。我们可以成为“全栈”人力资源专业人员，在几秒钟而不是几周内找到有关我们团队的数据，几秒钟与一线领导分享人力资源、领导力和管理实践。（Galileo被一些世界上最大的公司用作管理教练。） 还有一些其他变化。随着公司专注于“通过生产力实现增长”，我们必须考虑每周 4 天的工作制，我们如何将混合工作制度化，以及如何以更有效的方式连接和支持远程工作者。我们必须重新关注领导力发展，在一线经理身上花费更多的时间和金钱，并继续投资于文化和包容性。我们必须简化和重新思考绩效管理，我们必须解决令人头疼的薪酬公平问题。 还有更多。 DEI 计划必须嵌入到业务中（人力资源 DEI 警察的时代已经结束）。我们必须清理我们的员工数据，以便我们的人工智能和人才情报系统准确且值得信赖。正如我们的系统性人力资源研究所指出的那样，我们必须将思维从“支持业务”转变为“成为有价值的顾问”，并将我们的人力资源服务产品化。 所有这些都在我们本周发布的40页新报告“2024 年人力资源预测”中进行了详细说明，其中包括一系列行动计划，以帮助您思考所有这些问题。 让我提醒你一个大观念。生产力是人力资源部门存在的原因。 我们所做的一切，从招聘到辅导，从开发到组织设计，只有在帮助公司成长的情况下才能成功。作为人员流动、敬业度、技能和领导力方面的专家，我们人力资源部门每天都在提高员工和组织的生产力。2024年是专注于这一更高使命的一年。 最后一件事：照顾好自己。 该报告有15个详细的预测，每个预测都有一系列需要考虑的行动步骤。最后一个真正适合你：专注于人力资源的技能和领导力。作为流程的管理者，我们必须专注于我们自己的能力。2024年将是成长、学习和团队合作的一年。如果我们处理好这15个问题，我们将帮助我们的公司在未来一年蓬勃发展。 Josh Bersin预测的详细信息 预测研究是我们每年阅读量最大的报告。它包括我们所有研究的详细摘要，并讨论了首席执行官、首席人力资源官和人力资源专业人士的15个基本问题。它将以以下形式提供： 包含详细信息的信息图。（点击这里) Source JOSH BERSIN
    Josh Bersin
    2024年02月01日
关于我们  | 投融资  | 回顾  | 发布招聘信息  | 资料下载  | 联系我们  | 订阅NACSHR月报  | NACSHR2024年度活动计划  | NACSHR6月夏季论坛启动  | Become a Speaker  | 北美HR需求指南-征集中  | 2024年度大奖评选  | 2024北美华人人力资源年度峰会  | 设计思维少儿体验课程  | 北美HR招聘平台-企业直招，内推  | 我有需求，想咨询  | 北美华人人力资源服务图谱  | 北美人力资源服务图谱  | NACSHR在北美HR图谱  | 洛杉矶·NACSHR论坛
Email:hi@nacshr.org
Copyright © 2025 NACSHR.org All Rights Reserved.