• 员工体验
    2027员工健康险续保前，别只盯涨幅：先做一次 Second Opinion，也重新看看你的 Broker 每到员工健康险续保季，很多企业最先关注的都是一个数字：今年保费涨了多少？ 但对于企业负责人和 HR 来说，续保真正值得思考的问题其实不只是“涨了几个百分点”，而是：当前保险方案是否仍然适合员工？Employer Contribution 是否合理？Network、Deductible 和 Copay 有没有改善空间？现有 Broker 是否真正帮助企业提前准备、分析方案并处理日常员工福利问题？ 2027 年员工健康险续保正在逐步进入准备期。NACSHR Insurance Services 推出免费的 Group Health Renewal Review / Second Opinion，希望帮助企业在正式做出续保决定之前，多获得一次独立的专业判断。企业无需先更换 Broker，也不需要一开始就准备完整的员工 Census，只需要从现有 Renewal Notice 和基本公司信息开始。 续保真正要回答的，不只是“涨了多少” 保险成本上涨当然重要，但企业最终要管理的是员工福利的整体价值。 一份 Renewal Notice 背后，至少还涉及当前 Plan Design、员工自付水平、Network 使用体验、Employer Contribution，以及是否存在值得进一步比较的替代方案。NACSHR 的 Renewal Review 会从这些维度帮助企业先做判断，再决定是否需要进入下一步 Quote 和 Proposal 比较。 如果当前方案已经合理，企业完全可以继续保持现有安排；如果确实发现明显的优化空间，再进一步比较市场方案。换句话说，Review 的目的不是为了“必须换保险”，而是让企业在续保前知道自己还有没有更好的选择。 这也是 Second Opinion 最重要的价值。 已经有 Broker，为什么还需要 Second Opinion？ 很多企业其实并不是没有 Broker，而是已经习惯了当前的服务方式。 一年到了 Renewal，Broker 发来续保通知；企业看到价格变化，讨论几次方案，然后继续续保。整个过程看起来没有问题，但企业可能从来没有认真问过： 当前 Broker 是否提前帮助我们规划 Renewal？ 除了续保之外，平时员工福利问题是否有人持续支持？ 员工对 Network、Deductible 或 Plan Choice 有意见时，是否有人主动分析？ 企业员工人数、州别或业务发生变化以后，福利方案有没有重新评估？ 如果企业并不确定这些问题的答案，那么在下一次 Renewal 前获得一次 Second Opinion，本身就很有价值。 NACSHR 当前的 Renewal Review 不要求企业先终止现有 Broker 关系，也不要求先做 Broker of Record 变更。企业可以先了解当前方案和潜在选择，再决定下一步。 但有时候，该换的可能不是保险，而是 Broker 这也是我们希望企业在 2027 Renewal 前进一步思考的问题。 如果当前 Carrier、Network 和员工保险计划总体上都没有明显问题，但企业长期感觉 Broker 服务不够主动、沟通不足、缺少提前规划，或者 HR 在实际处理员工福利问题时得不到足够支持，那么企业未必需要第一时间更换保险方案。 更值得考虑的，可能是先更换服务关系。 更换 Broker 与更换保险计划并不是同一个决定。对于团体健康险，Broker 的变化主要涉及服务关系、后续管理以及谁代表企业协调 Renewal 和员工福利事务；企业并不一定因为更换 Broker，就必须同时更换当前保险计划。具体 Broker of Record 的要求、生效时间及操作流程，仍需要根据当前 Carrier、Administrator 和保险安排进行确认。 因此，NACSHR 正在建立另一条更直接的服务路径： 让 NACSHR 先接手你的续保服务，不必先换保险，提前准备 2027 续保。 对于已经对现有 Broker 服务不满意、希望下一次 Renewal 有人更主动参与的企业，可以先进行 Broker Transfer Check。我们会先了解企业当前 Carrier、员工人数、所在州和 Renewal Month，确认适用的 Broker 转换要求，再由企业决定是否正式授权 NACSHR 接手。 这意味着企业可以把两个决定拆开： 第一步，决定谁来为企业提供 Broker 服务。 第二步，再决定保险 Carrier、Plan 和员工福利方案本身是否需要调整。 这样做的好处，是企业不用为了“换 Broker”而被迫同时重新设计全部员工保险，也不用等到 Renewal Notice 已经摆在桌上时，才临时寻找新的服务团队。 NACSHR 希望接手的，不只是一次 Quote 我们希望建立的 Employee Benefits 服务，不是一年只在续保时出现一次。 当 NACSHR 接手企业员工福利服务以后，重点应该包括 Renewal Planning、计划与成本分析、员工福利相关沟通、Carrier 协调，以及在确有需要时帮助企业进一步比较不同方案。 尤其对于在美国经营的华人企业，很多 HR 和企业负责人面对的并不只是“买哪一个医疗保险”，而是员工增加、跨州用工、福利沟通、保险续保和日常 HR 管理交织在一起的实际问题。 因此，我们更希望扮演的是一个长期的员工福利服务伙伴，而不是单纯在续保季提供一个价格。 企业现在可以从两个入口开始 如果你目前只是想知道： “我的 2027 Renewal 是否合理？” “当前 Plan 有没有优化空间？” “我还不准备换 Broker，只希望先听一次不同意见。” 那么可以先申请 NACSHR 2027 企业员工健康险免费 Renewal Review。 第一步只需要 Renewal Notice，以及公司名称、员工人数、所在州和 Renewal Month。确认确实值得进一步比较后，再补充 Census、Current Benefits 等资料。NACSHR 当前设计的完整流程是：发送 Renewal Notice、提供基本信息、进行约 20–30 分钟 Review，需要时再补充资料，最后才进入 Quote 与 Proposal 比较。 如果你已经开始考虑： “现有 Broker 服务是不是不够？” “明年 Renewal 我不想再按照原来的方式处理。” “能不能让 NACSHR 接手，但现有保险先不要动？” 那么可以进一步进行 Broker Transfer Check。 先确认，再决定；先接手服务，再决定保险方案是否需要调整。 2027 Renewal，不要等到最后一个月才开始 越早了解 Renewal 状况，企业就越有时间判断当前方案、听取不同意见、比较市场选择，并安排后续员工沟通。NACSHR 当前也建议企业在收到 Renewal Notice 后尽早开始 Review，以便在需要市场比较、Enrollment 或员工沟通时保留充足的准备时间。 所以，今年我们希望给企业一个更简单的建议： 员工健康险续保前，先做一次免费的 Second Opinion。 让 NACSHR 先接手你的续保服务，不必先换保险，提前准备 2027 续保。 如果现有方案很好，我们会帮助你更有把握地继续；如果存在优化空间，我们再一起比较；如果真正需要改变的是 Broker 服务关系，那么也没有必要等到保险本身出现问题以后才行动。 先看清楚，再决定。先把续保的主动权拿回来。 申请 2027 企业员工健康险免费 Renewal Review： https://insurance.nacshr.org/renewal-review-2027 了解 NACSHR Broker Transfer / Broker 服务转换： https://insurance.nacshr.org/switch-broker NACSHR Insurance Services Employee Benefits · Business Insurance 本文仅提供一般性保险服务信息，不构成法律、税务或特定保险合同意见。Broker / Agent of Record 变更要求、生效时间及具体保险安排，应以相关 Carrier / Administrator 的正式规则和确认为准。
    员工体验
    2026年08月18日
  • 员工体验
    2026员工幸福感回升至三年高位，但年轻员工与科技行业仍在“掉队” NACSHR核心摘要：员工终于“更快乐”了吗？BambooHR 最新 2026 Employee Happiness Index 显示，H1 2026 eNPS 回升至40，创2023年以来最好上半年。但平均值背后出现明显分化：26–30岁员工满意度偏低，工作2–3年成为员工体验最低谷；长期员工反而重新回升。更值得关注的是，高幸福感企业的员工流失明显低于低幸福感企业，而科技行业却成为八大行业中唯一持续下滑的行业。 对HR来说，未来员工体验不能只看一个公司平均eNPS，而需要按照年龄、工龄、团队与职业阶段进行精细化管理。员工调查的下一步，不是“测量”，而是把数据真正转化成经理行动和留任结果。 在经历连续数年的下降后，员工的整体幸福感终于出现较为明确的恢复迹象。 最新发布的《2026 Employee Happiness Report》显示，2026年上半年员工净推荐值（Employee Net Promoter Score，eNPS）升至40，同比增长4.4%，达到自2023年以来表现最好的上半年水平。2024年11月至12月，该指标一度降至37的阶段性低点，而2026年的数据意味着员工对工作和所在组织的整体感受正在逐步改善。 不过，对于企业HR而言，比“员工幸福感回升”更加值得关注的是平均数字背后的结构性变化：不同年龄、工龄和行业的员工体验出现明显分化，而员工幸福感与人员流失之间也呈现出值得企业管理者关注的关联。 员工幸福感回升，但还没有回到过去的高点 从长期趋势来看，员工幸福感仍处于“恢复期”。 数据显示，2020年7月eNPS曾达到48的历史高点，此后员工幸福感经历连续数年下降。2022年至2023年下降7.0%，2023年至2024年继续下降2.8%，并在2024年底降至37。进入2026年后，员工情绪开始持续改善，上半年eNPS升至40，目前已经接近2023年的水平。 这意味着经历疫情后的工作模式调整、通胀压力、劳动力市场变化以及过去几年频繁的组织重组之后，员工整体情绪可能正在逐渐企稳。 但40只是一个整体平均值。进一步拆解数据会发现，不同员工群体的体验恢复速度并不相同，这也是企业HR在解读员工敬业度数据时更需要注意的问题。 高幸福感企业，员工流失明显更低 报告中最值得企业管理者关注的一项发现，是员工幸福感与人员流失之间的明显关联。 数据显示，员工幸福感最高的企业，其员工流失水平相比员工幸福感最低的企业低约46%。按照报告测算，对于低幸福感企业来说，相当于每100名员工每年可能多出现约18次人员离开。 这种差距在中小型企业中尤其突出。 对于1—24名员工的企业，高eNPS企业员工流失率约为34%，而负eNPS企业达到53%；25—75人规模企业分别约为41%和60%；76—150人企业则分别为42%和60%。也就是说，对于150人以下的企业，员工幸福感较低的组织每年可能多流失18—19个百分点的员工。 相比之下，当企业规模扩大到301—500人时，高幸福感和低幸福感组织之间的人员流失差距缩小至约4.5个百分点。 对于中小企业而言，这组数据尤其值得重视。大型企业可能通过招聘规模、内部流动和人才储备消化一定程度的人员流失，但对于几十人或一百人左右的团队来说，每年额外流失十几名员工，很可能直接影响业务连续性、团队稳定性以及招聘和培训成本。 需要特别说明的是，报告同时强调，这些数据反映的是员工幸福感和人员流失之间的相关关系，而不能直接证明因果关系。员工不满意可能增加离职，也可能是频繁人员变动本身降低了团队幸福感，或者两者同时受到其他组织因素影响。 工作2—3年，成为员工体验最值得关注的“危险期” 如果从员工生命周期来看，2026年的数据呈现出一个非常清晰的“U型曲线”。 入职不到一年的新员工平均eNPS约为51，是员工体验相对较好的阶段；随着工作时间增加，满意度逐渐下降，其中工作2—3年的员工eNPS只有33，是整个员工生命周期中的最低点；而随着工龄进一步增加，长期员工满意度又重新回升，长期任职员工平均eNPS达到57。 这一趋势对HR管理具有非常现实的意义。 过去几年，越来越多企业把大量资源投入招聘体验和Onboarding。新员工入职后的前几个月通常拥有更加密集的培训、经理关注、团队欢迎和职业期待，因此容易形成明显的“蜜月期”。 真正的员工体验考验，往往出现在入职后的第二到第三年。 这一阶段，员工已经完成对组织、岗位和管理方式的基本了解，最初的新鲜感逐渐消失，同时开始更加现实地评估薪酬增长、晋升机会、职业发展、经理能力以及未来能否在组织内部获得新的机会。 报告将2—3年工龄称为持续出现的低点。该群体eNPS在2025年曾降至约30，虽然2026年上半年恢复至33，但仍显著低于整体平均水平。 这也提醒企业，与其仅仅把员工留任计划集中在入职前12个月，HR可能需要进一步建立针对“入职第2—3年”的人才管理机制，包括职业发展讨论、内部流动、薪酬调整、经理沟通和关键人才识别。 26—30岁员工幸福感最低，年轻员工恢复明显更慢 年龄也正在成为员工体验差异的重要变量。 数据显示，26—30岁员工的eNPS仅为31，比整体平均水平低9点；相比之下，51—60岁员工的eNPS比整体平均高8点，两类员工之间形成17分的明显差距。 更值得注意的是，在整体员工幸福感开始恢复之后，不同年龄层的恢复速度也并不一致。50岁以上员工的满意度改善明显，而30岁以下员工仅出现相对有限的改善。 这意味着，企业越来越难再通过一套统一的员工体验方案满足所有员工。 对于年轻员工而言，职业成长速度、经理反馈、工作灵活性、薪酬增长和职业安全感可能拥有更高权重；而对于更加资深的员工，工作稳定性、长期激励、福利和工作生活平衡的重要性可能更加突出。 因此，对于北美企业HR而言，仅查看公司整体eNPS或者年度员工满意度平均值已经越来越不够。年龄、职业阶段、工龄、团队甚至不同经理之下的员工体验差异，都应该成为People Analytics的重要分析维度。 科技行业成为少数逆势下滑的领域 行业之间的员工体验变化同样出现明显分化。 2026年上半年，建筑行业eNPS达到51，在所统计行业中继续保持领先；金融行业达到47，相比上一年明显提高；医疗行业升至40；教育行业为39，非营利组织为38。 相比之下，科技行业eNPS只有37。 更值得关注的是，科技行业是报告追踪的八个行业中唯一出现持续下降趋势的行业：2023年科技行业eNPS为42，当时仍处于各行业领先位置；2024年下降至37，2025年为38，到2026年上半年再次回到37，已经低于整体平均水平。 餐饮、食品与饮料行业的整体得分最低，2026年上半年eNPS为34；但从长期走势来看，科技行业持续走弱反而更值得HR和企业管理层警惕。 过去很长时间，高薪、高增长、股权激励以及快速职业发展共同构成了科技企业吸引人才的重要雇主价值主张。随着近几年科技行业持续经历组织调整、人员裁减和岗位重构，员工对于职业稳定性和未来发展的预期也在发生变化。 特别是在人工智能开始重新定义岗位职责、团队规模以及工作流程的背景下，科技企业如何重新构建员工的职业发展预期和组织信任，可能成为未来几年Employee Experience和人才留任的重要议题。 NACSHR观察：员工体验正在从“平均值管理”走向“分群管理” 对于北美HR而言，这份报告最值得关注的并不是eNPS从37回升到40，而是隐藏在平均值背后的员工体验分化。 一家企业整体eNPS可能表现良好，但26—30岁的员工、工作2—3年的员工，或者某些特定业务团队的员工体验可能已经出现明显问题。如果HR只关注公司层面的年度平均数据，很容易错过真正的人才流失风险。 这意味着员工体验管理正在进入新的阶段。 传统Employee Engagement的核心问题往往是“员工是否满意”，未来企业更需要回答的是：“哪些员工正在变得不满意？为什么？发生在哪个职业阶段？与哪类经理、岗位或者组织变化相关？接下来应该采取什么行动？” 对于HR部门而言，员工调查的价值也需要从“测量”进一步走向“行动”。将Employee Listening、People Analytics、经理能力、职业发展、内部流动和人才留任数据连接起来，持续识别不同员工群体的体验变化，可能比单纯追求一个更高的年度eNPS数字更加重要。 2026年的员工幸福感正在恢复，但这种恢复并不均匀。 而对企业来说，真正的人才竞争力，很可能就隐藏在这些平均数字没有显示出来的差异之中。 资料来源： BambooHR，《2026 Employee Happiness Report / Employee Happiness Index》，2026年8月6日。研究数据来自2019年1月至2026年6月的eNPS平台数据，覆盖1,400多家企业、超过51,000名独立员工及超过250万条匿名自报eNPS评分。 NACSHR（北美华人人力资源协会）整理报道
    员工体验
    2026年08月07日
  • 员工体验
    73%的美国HR将员工反馈列为首要指标：企业福利正在从“提供账户”转向“员工真正会用” NACSHR核心解读：这项调查覆盖300多名负责HSA及福利支出账户的HR专业人士。73%的受访者表示，员工反馈是重新评估福利供应商时最重要的因素。接近六成HR会收到员工关于合资格消费、报销申请、账户使用、截止日期和结转规则的问题。55%的HR希望获得更灵活的福利选项，52%希望供应商提供更简单的员工教育和更好的技术。虽然57%的HR已经在福利培训中使用AI，但很多员工仍然缺乏实际使用账户的信心。 这说明，福利科技的竞争已经从后台账户管理转向员工体验。供应商不仅要管理资金和合规，还要帮助员工在正确时间理解规则、完成操作，并减少HR承担的重复支持工作。 企业为员工提供健康储蓄账户、弹性支出账户和其他福利项目，并不代表员工能够真正理解和使用这些福利。 InComm Benefits近期发布的《The Spending Account Experience Gap》调查显示，北美企业HR对福利供应商的期待，与员工在实际使用福利账户时的体验之间，仍然存在明显差距。调查于2026年4月开展，覆盖300多名负责管理健康储蓄账户及其他福利支出账户的HR专业人士。 报告反映出的核心问题并不是企业没有提供福利，而是福利规则、技术平台和员工教育没有真正转化为简单、清晰、可操作的员工体验。 73%的HR将员工反馈作为重新评估供应商的首要因素 调查显示，73%的受访HR表示，在重新评估福利支出账户供应商时，员工反馈是最重要的考虑因素。“员工体验”也成为HR对现有福利账户供应商最主要的不满之一。 过去，企业评估健康储蓄账户和福利支出账户供应商时，通常更加关注管理费用、系统功能、投资选项、合规能力以及与薪酬或人力资源系统的集成。 但对员工而言，他们最直接的判断标准通常更加具体：账户是否容易使用，报销流程是否清晰，余额和处理状态能否随时查询，遇到问题时能否快速获得准确答复。 这意味着，福利供应商的竞争重点正在发生变化。账户管理和合规能力仍然是基础，但员工实际使用体验正在成为影响企业续约、更换供应商和福利满意度的重要因素。 近六成HR持续处理员工的账户使用问题 调查显示，接近六成受访HR会收到员工关于福利支出账户的问题或担忧。 员工最常提出的问题包括：哪些商品或服务属于符合资格的支出，如何提交报销申请，账户应该如何使用，报销或消费有哪些截止日期，以及未使用余额是否可以结转。 这些问题看起来基础，却会持续占用HR团队的时间。员工遇到不确定情况时，通常不会仔细阅读篇幅较长的福利手册或计划文件，而是直接向HR寻求帮助。 因此，企业即使已经购买了数字化福利管理平台，HR仍然可能成为事实上的福利客服中心。 对于北美企业HR而言，这一问题尤其值得重视。HR团队通常还需要同时负责招聘、入职、薪酬、绩效、员工关系、劳动合规和保险管理。如果大量时间被用于重复回答账户余额、消费资格和报销状态等问题，福利技术就没有真正实现降低行政负担的目标。 员工不是不关心福利，而是不确定如何使用 报告提出了一个值得企业重新思考的问题：员工使用福利的积极性不足，不一定代表员工不重视福利，也可能是员工不知道应该如何使用。 HSA、FSA及其他福利支出账户往往涉及税务规则、合资格支出、收据要求、年度选择、使用期限和余额结转。对于HR和福利专业人士而言，这些概念相对熟悉，但对普通员工而言，理解和操作门槛并不低。 如果员工无法确定一项医疗费用是否符合报销条件，担心操作错误，或者不了解资金的使用期限，他们可能会选择暂时不使用账户，甚至放弃原本可以获得的福利价值。 由此产生的结果是，企业投入了福利预算，员工却没有充分使用；HR不断回答问题，员工仍然认为福利复杂；企业认为已经提供了有竞争力的福利，员工却没有形成相应的价值感知。 灵活性、教育和技术成为三项主要改善方向 调查显示，55%的受访HR认为，更灵活的福利选项有助于改善员工体验；52%的受访者认为，企业和供应商需要提供更加简单的福利教育；另有52%认为，需要通过更好的技术工具改善员工体验。 这三个方向说明，改善福利体验不能只依靠增加预算或者增加更多账户类型。 福利灵活性需要建立在员工能够理解和选择的基础上。过多选项如果缺乏清晰解释，反而可能增加员工的决策负担。 福利教育也不能只集中在Open Enrollment期间。员工在年度注册阶段可能理解了账户的基本概念，但几个月后真正发生医疗支出时，往往已经忘记具体规则。 更有效的方法，是在员工需要采取行动的时间节点提供支持，例如在发生合资格消费时提供提示，在报销申请被拒绝时说明原因，在余额即将到期时提前提醒，并通过移动端或自助服务平台让员工快速找到答案。 技术的价值也不应只体现在后台效率，而应体现在是否能够减少员工操作步骤、降低错误率，并减少HR需要人工介入的次数。 57%的HR已经使用AI开展福利教育 报告显示，55%的受访HR对在人力资源部门使用AI工具持积极态度，57%的受访者已经在福利教育或培训中使用AI。 AI正在逐渐进入福利问答、员工沟通、培训材料制作和自助服务等场景，但调查结果也说明，仅仅部署AI工具，并不会自动解决员工福利体验问题。 如果AI只是将复杂的福利手册转换成聊天问答，员工仍然可能获得笼统、难以执行的回答。真正有价值的福利AI，应当能够结合员工所在的福利计划、账户类型、账户状态和实际问题，提供更加具体的操作指引。 与此同时，福利管理涉及医疗、税务和个人信息。企业在引入AI工具时，还需要关注数据隐私、答案准确性、计划文件优先级，以及复杂问题转交人工支持的机制。 AI可以帮助HR减少重复性咨询，但不能替代正式的福利计划文件、专业保险顾问和必要的人工判断。 北美HR应重新审视福利供应商的评估指标 这份报告对北美HR最直接的启示，是福利供应商的评估标准需要从传统的功能清单，进一步延伸至员工实际体验。 企业在下一次评估或续约福利账户供应商时，可以重点考察员工问题首次解决率、客服响应时间、报销处理周期、自助服务完成率、账户实际使用率、未使用余额情况、员工满意度，以及HR每月处理福利问题所投入的时间。 企业也可以定期收集员工反馈，了解员工在哪些环节最容易遇到困难。员工不使用某项福利，可能是因为福利本身缺乏吸引力，也可能只是因为操作复杂、说明不清或缺少及时提醒。 对于企业而言，真正有效的福利方案，不只是完成账户开设和年度注册，而是让员工清楚地知道自己拥有什么福利、何时可以使用、如何使用，以及遇到问题时可以向谁寻求帮助。 当员工能够独立、顺畅地使用福利时，企业的福利投入才能真正转化为员工满意度、留任能力和雇主品牌价值。 NACSHR保险服务：协助企业重新评估员工福利与商业保险方案 对于正在规划、续保或重新评估员工福利方案的北美企业，NACSHR保险服务可协助企业了解员工健康保险及相关保险需求，包括Medical、Dental、Vision等员工福利，以及Workers’ Compensation和企业商业保险方案。 NACSHR建议企业在续保或计划生效前提前启动评估，不仅比较保费和保险计划，也应综合考察员工实际需求、使用体验、企业预算、保险网络、福利沟通及后续服务能力。 企业HR或管理者如需了解员工福利保险及商业保险方案，可访问NACSHR保险服务网站：insurance.nacshr.org。
    员工体验
    2026年08月05日
  • 员工体验
    经济与AI焦虑下员工选择“留下”：Mercer 调研显示 73%美国员工暂不跳槽 近日，全球人力资源咨询机构 Mercer 发布了其最新年度研究报告 Inside Employees’ Minds 2026，该报告基于超过 4,500 名美国雇员的调研结果，揭示了当前劳动力市场一个耐人寻味的趋势：尽管经济不确定性和人工智能（AI）快速变革带来了前所未有的压力，但大多数员工并未打算离开现有岗位。相较于近几年频繁的人员流动，73% 的美国员工表示他们目前没有认真考虑跳槽，这一比例较2023年的68%进一步攀升。 然而，这一看似“稳定留任”的现象，并不意味着员工对工作更忠诚或更满意，而是反映了他们在面对外部不确定因素时的理性权衡和风险规避心理。 一、理性留任背后的真实驱动力 在通胀持续、医疗成本上升和宏观经济波动加剧的背景下，员工在职业选择上的判断逻辑发生了变化。Mercer 报告指出，70% 的受访者因通胀和生活成本居高不下感到财务压力增加，76% 关注关税及其他宏观经济影响可能带来的连锁反应，56% 甚至担心这些因素最终会影响到自身的岗位稳定性。此外，预计医疗成本今年上涨 6.7%，为过去15年来最高涨幅，这对低收入和小时工群体的影响尤为显著。 在这样的经济现实中，薪酬再次成为员工考虑就业选择时最核心的因素。不论是吸引人才还是留住现有员工，薪资因素均位居首位，其次是医疗福利的保障。报告还指出，薪酬透明度已成为重要的基本期待——超过40%的候选人在没有看到薪资区间时不会投递简历。这一现象表明，对于求职者而言，仅有一个职位机会已不足以构成吸引力，明确的薪酬结构和晋升机制正在成为求职市场的基础条件。 二、AI落地缓慢但焦虑提前爆发 在技术驱动转型浪潮下，人工智能已成为企业内部讨论的重心之一。尽管多数组织倡导AI工具的采用，但员工端的实际使用情况却明显滞后——仅约四分之一的员工表示他们在日常工作中经常使用AI工具，而另一部分员工仍未开始应用AI。这种实际应用与企业预期之间的差距，反映出员工对于AI转型的认知尚未完全成熟。 更值得关注的是，超过一半的受访者认为新技术将影响工作安全性，显示出一种普遍存在的“焦虑预期”。与其说员工担心AI技术本身，不如说他们在担心无法清晰判断自身在未来岗位中的定位及技能匹配。这意味着企业如果不能提供明确的AI转型路线图、清晰的角色变化说明和可执行的技能发展路径，员工更可能将AI视为风险，而非机会。 Mercer 的研究团队指出：“当组织能够有效管理员工的日常工作量、明确技能优先级并持续投资员工发展时，AI可以成为推动个人和组织成长的通路，而非焦虑的根源。” 三、灵活性与可兑现的工作体验成为新期待 对于工作安排和福利体验，员工的关注重点已经从“福利多寡”转向“是否真的能用得上”。数据显示，大多数员工能够完整使用带薪休假，并且能够根据需要安排休假时间，这与员工的身心健康和家庭照护需求密切相关。无论是混合办公模式、弹性工时安排，还是带薪休假制度，员工更希望这些政策能够兑现，而不是停留在制度层面。 这一点在一线岗位和小时工群体中尤为突出。他们的日常工作安排和领导支持程度直接影响到他们能否真正享受这些休假权益，从而影响员工的整体幸福感和对组织的信任感。 四、内部发展机会成为留任关键 Mercer 报告显示，高敬业度和高留任意愿的员工往往能够在公司内部看到清晰的职业发展路径。在具有明确晋升机制和内部流动机会的组织中，员工更愿意选择“留下并积极投入”。这一趋势尤其在科技和金融服务行业表现明显，而在医疗与零售等行业中，员工对发展路径的信心则相对较弱。 这表明员工对于职业成长的关注已从外部跳槽机会转向企业内部的成长空间。他们不再简单地将跳槽视为晋升渠道，而是希望通过现有组织的技能提升和岗位轮换来实现职业进步。 五、员工分层体验差异明显 不仅整体趋势值得关注，行业和人群内部的体验差异同样显著。医疗、零售及低收入工种的员工普遍面临更大的财务压力和心理负担，而科技与金融服务行业的员工则表现出更高的敬业度和对职业发展的信心。此外，拥有五到十年工作经验的中坚力量员工在留任意愿和组织投入方面表现尤为突出。 这一分化趋势强调了HR在制定人才策略时不再适用于“一刀切”的方法，而需要根据不同岗位、收入水平和职业阶段设计个性化方案，以提升资源投入效能和员工满意度。 六、对北美HR的影响与行动建议 综合 Mercer 的调研结果可以看出，当前美国劳动力正在进入一种新的稳定与谨慎并存的阶段。员工不选择跳槽并不意味着他们真正稳定，而是在权衡风险和机会后做出的理性选择。在这一背景下，企业与HR组织应重点关注以下几点： 构建薪酬透明机制：公开薪资区间和晋升机制，以降低信息不对称带来的不确定感。 明确AI转型路线图：提供清晰的角色变化说明、技能要求及培训支持，使AI成为成长杠杆。 强化技能发展路径：结合岗位变化设计可执行的员工发展计划，将学习成长与绩效目标结合。 提升灵活性体验：确保弹性工作安排和带薪休假等政策真正可用，而非停留在制度层面。 分群制定人才策略：针对不同岗位、行业和职业阶段设计差异化留任方案，提高投入回报效率。 提升组织沟通透明度：高频、可信的沟通能够显著增强员工对组织的信任和对未来的预期感。 对于北美HR而言，未来的留才竞争已不再简单依赖市场供需状况，而更取决于组织能否提供“可预测的职业未来感”。能够有效降低员工的不确定性，并将短期留任转化为长期忠诚的组织，将在人才竞争中获得显著优势。
    员工体验
    2026年02月10日
  • 员工体验
    员工为何离职？2025年最新报告揭示了五大意外真相 2025年离职调查基准报告汇总并分析了2022至2024年间全球及北美地区的职员变动数据。研究由McLean & Company发布，旨在揭示员工自愿离职的核心原因，例如职业晋升机会匮乏、薪酬福利以及对高层管理缺乏信任等关键因素。报告结合了疫情后的经济背景，探讨了远程办公政策和生活成本危机如何影响人才留存。除了数据对比，文中还为人力资源部门提供了针对性的行动方案，包括改善领导层沟通和优化内部人才流动。通过对比不同年龄与任职时长的群体，该资料帮助企业利用数据驱动型策略来降低流失率并增强职场吸引力。最后，报告介绍了相关的诊断工具与专业咨询服务，以支持组织的长期健康发展。推荐阅读 引言：留住人才，知易行难 在当今竞争激烈的人才市场中，如何留住顶尖员工是所有现代企业面临的共同挑战。我们常常依赖过往的经验和假设来制定人才保留策略，但这些策略真的有效吗？为了拨开迷雾，我们需要真实、客观的数据。McLean & Company发布的《2025年离职调查基准报告》（该报告分析了2022至2024年的数据）为我们提供了全新的、以数据驱动的深刻洞见。本文将为您提炼该报告中最令人意外且最具影响力的五大发现，揭示员工选择离开的真正原因。 -------------------------------------------------------------------------------- 1. 成长悖论：员工为发展而来，因停滞而走 企业在招聘时总会大力宣传职业发展机会，并理所当然地认为这是吸引人才的王牌。然而，一个令人意外且痛苦的真相是：当初吸引员工加入的首要原因，恰恰成为了他们日后离职的首要原因。报告数据揭示，“职业机会”是求职者接受新工作的最主要原因（54.6%），而“职业晋升机会”同样是员工选择离开的首要工作相关原因（44.5%）。 这暴露了企业“员工价值主张”生命周期中的一个根本性断裂。从吸引到留任，承诺与现实之间形成了巨大的鸿沟，这不仅是错失了留住人才的机会，更是在主动地制造失望情绪。 员工加入组织是为了职业成长，但往往因为缺乏成长而离开。 对于人力资源领导者而言，这意味着仅仅在招聘时描绘美好的发展蓝图是远远不够的。组织必须将承诺转化为现实，通过建立清晰可见的职业路径和提供实质性的发展项目，才能真正留住那些为成长而来的优秀人才。 2. 薪酬并非万能，但基础薪资仍是关键 在一个将“企业文化”奉为圭臬的时代，许多领导者认为卓越的文化或灵活的福利可以弥补薪酬上的不足。然而，这份数据给出了一个 sobering 的现实提醒：在“生活成本危机”和“通货膨胀压力”的背景下，基础薪酬的重要性不容低估。“基本工资”依然是员工离职时最常提及的薪酬因素（42.5%），也是所有离职原因中提及频率第二高的，仅次于职业晋升机会。 此外，引用的《2024年员工敬业度趋势报告》显示，只有47%的员工对自己的总薪酬感到满意。这深刻地提醒我们，在设计复杂的“全面薪酬”策略之前，必须先做对最基础的事情。如果作为基石的基础薪酬在市场中缺乏竞争力，那么所有其他薪酬福利的杠杆作用都将被大大削弱。 3. 领导力信心差距：问题不在于“坏老板”，而在于“弱领导” 人们常说“员工离开的是老板，而不是公司”，我们脑海中浮现的往往是微观管理、从不赞美下属的“坏老板”形象。然而，数据揭示了一个更微妙、也更令人意外的真相：员工逃离的并非是“坏”老板，而是他们不信任其能力的“弱”领导。在与管理者相关的离职原因中，排在首位的并非人际冲突，而是“对管理者领导能力的信心”（27.9%）。 这指向一个更深层次的问题，它超越了日常管理技巧，关乎员工对其上司战略方向、决策水平和整体领导力的根本性不信任。当员工对领导的能力失去信心时，他们也就对自己在团队中的未来失去了信心。 在职业生涯的某个阶段，半数美国人都曾为了‘摆脱他们的经理’而离职。 这一发现警示我们，组织需要投资于真正的领导力发展，而不仅仅是基础的管理技能培训。员工需要的不仅是一个友善的管理者，更是一个能指引方向、值得信赖的领导者。 4. 新的底线：当工作与生活失衡时 曾几何时，“工作与生活平衡”被视为一项“锦上添花”的福利。最新的数据明确指出，这种假设已经变得非常危险。如今，它已成为员工不可协商的“底线”。报告显示，“糟糕的工作与生活平衡”（26.9%）是员工离职最主要的工作条件因素，其重要性远超“歧视”或“工作环境的物理安全”等选项十个百分点以上。 外部数据也印证了这一点：57%的员工表示，如果一份新工作会对他们的工作与生活平衡产生负面影响，他们将不会接受。这份数据标志着一个重要的信号：企业不能再将工作与生活平衡视为由各个团队自行管理的软性福利。它必须被提升为一项战略性的、由组织中央支持的人才管理支柱，其重要性不亚于薪酬和职业发展。 5. C级高管的信任赤字 直接上司对员工留任的影响已是共识，但这份报告令人震惊地指出，一个更大的组织层面驱动因素是员工对最高决策层的不信任。数据显示，“对高管领导团队缺乏信任”是员工离职时最常选择的组织层面因素（31.3%）。这表明，C级高管与普通员工之间的距离可能已经到达了一个危险的临界点。 报告分析，远程工作的增加、有效反馈渠道的缺失以及持续的裁员，都可能加剧了这种“信任鸿沟”。这是一个比单一管理者问题更严峻的系统性挑战。当员工对公司的掌舵者失去信任时，他们对公司的战略、未来和文化的信心都会随之动摇，这种根基性的侵蚀远比修复一段上下级关系要困难得多。 -------------------------------------------------------------------------------- 结论：前路在何方 McLean & Company的最新数据告诉我们，员工离职并非由单一原因造成，而是一个由职业发展承诺的落空、薪酬基础的缺失、贯穿上下的领导力信心危机、个人生活底线的挑战以及组织高层的信任赤字等多种因素交织而成的复杂网络。 数据已经清晰地指出了问题所在。真正的问题是：我们准备好倾听并采取行动了吗？
    员工体验
    2025年12月25日
  • 员工体验
    首席人事官展望：重塑工作世界 Chief People Officers Outlook 全球130位首席人事官共同描绘了未来工作的方向：CPO正从管理者转变为战略核心。视频揭示企业正经历从“效率导向”到“重塑组织”的深层变革，AI带来机遇也引发技能退化与伦理风险。未来竞争不在技术，而在人——唯有以人为中心的组织，才能在AI时代保持信任与增长。(download report) 当AI与不确定性交织，企业的核心竞争力正在转移 在AI、全球化和组织重构的浪潮中，企业的焦虑正在发生微妙转变。过去，焦点在“技术能带来多少效率”；如今，真正的问题变成了：“在技术快速推进的时代，组织如何让人不被边缘化？” 世界经济论坛（World Economic Forum）最新发布的《首席人事官展望 2025》（Chief People Officers Outlook 2025）报告揭示了一项关键趋势：人力职能正在从执行支持转变为战略中枢，CPO 已成为企业变革的共驱者。这份报告基于对全球 130 多位首席人事官的调研与访谈，呈现了未来工作世界的深层逻辑。 一、人力职能的战略跃迁：CPO 正走上企业的“驾驶席” 长期以来，企业往往把人力资源视为后台支持部门——招聘、薪酬、绩效考核。但如今，这个模式正在被彻底颠覆。 报告显示，超过九成的 CPO 认为人力职能已成为企业价值创造的战略驱动力。他们不再只是“执行人事政策”的管理者，而是与CEO并肩制定组织方向的战略合伙人。 “你再也无法将人与业务分开了。”——一位受访 CPO 的话成为报告的核心引语。 这种转变背后，是企业在动荡环境中寻求“人驱动的韧性”。从欧洲制造业到北美科技公司，CPO 开始直接参与组织重塑、业务模式转型与AI治理决策。在中国市场，这一趋势同样显现：无论是华为、字节跳动这样的科技巨头，还是制造业出海企业，都在让 HR 战略与业务战略同步规划。 二、谨慎中的加速：企业同时“踩刹车”和“踩油门” 报告揭示一个耐人寻味的矛盾：42% 的 CPO 预计未来一年劳动力市场将保持稳定，32% 认为会走弱，但多数企业却在加速内部转型。 这种“表面保守、实质重构”的现象，正在成为全球趋势。在美国，部分大型企业暂停外部招聘，却投入资源重塑岗位结构；在欧洲，不少集团通过人才再培训（reskilling）计划优化内部流动。中国的头部企业同样出现类似动作——“谨慎招聘+内部提效”成为2025年主流策略。 “谨慎是当前的环境设定，但转型是长期的机会。”——报告总结。 这说明企业正进入一个“战略蓄能期”：放慢扩张脚步，不是退缩，而是为了未来十年的结构性重构做准备。 三、年轻一代的挑战：他们不只是员工，而是“价值选择者” 报告指出，新一代员工正以前所未有的主动性进入职场。他们追求的已不再是稳定与薪酬，而是灵活性、意义感与价值契合。 “今天的人才自信、信息灵通，并且理直气壮地进行选择。”——报告中一位 CPO 的评论精准描述了这一代职场人的心态。 然而，这种觉醒也带来管理新矛盾。在北美，年轻员工因企业文化不符而主动离职的比例创历史新高；在中国，Z世代对“加班文化”与“管理层信任度”的敏感度远高于前辈。CPO 面临的新任务，不再是“招聘到人”，而是在多元文化与价值观冲突中重建组织共识。 这意味着HR策略必须向更“个体化”的方向演进：更多定制化成长路径、更灵活的绩效反馈机制，以及真正以员工体验为核心的文化体系。 四、AI的双刃：提升效率的同时，正在侵蚀人的能力 当AI渗透到招聘、绩效、培训的各个环节，CPO们的态度并非盲目乐观。报告显示，CPO 最担心的并不是“被AI取代”，而是“人因AI而失去成长能力”。 他们列出的三大风险值得所有HR关注： 员工无法及时学习新技能，无法跟上技术变革； 过度依赖AI导致技能退化、职业停滞； 数据隐私与算法伦理问题日益突出。 这让AI治理成为HR领域的新议题。欧美大型企业已经开始设立“AI使用守则”，强调人机协同边界；中国也有企业在推行“人本AI”理念——技术赋能，而非取代。 “成功的劳动力AI整合，不仅取决于技术部署，更取决于对工作的刻意重新设计与以人为本的实施承诺。”——报告原文。 未来的CPO，不仅要懂人，更要懂AI——懂得如何让技术成为释放潜能的工具，而非削弱人的拐杖。 五、重构组织，而非修补流程 在所有受访CPO列出的未来优先事项中，排名第一的并非招聘、薪酬或福利，而是——“重新设计组织结构与岗位”。53%的CPO将此列为头号任务。 这项数据揭示了一个本质趋势：组织变革已成为企业生存的必要工程。在全球范围内，企业正从层级制向网络化、敏捷化组织演进；岗位设计也从“职责导向”走向“能力导向”。例如，欧洲的能源企业正在用跨职能团队取代传统部门架构；中国的互联网公司则开始推行“灵活项目制”与“内部创业机制”。 这些调整的背后，是企业在应对不确定性时的共识： 组织的韧性，比组织的规模更重要。 未来竞争，不是技术之战，而是人之战 从世界经济论坛的这份报告可以看到一个清晰的趋势：技术的浪潮终将平衡，但“人”的力量正在重新定义竞争力。 CPO 的崛起象征着企业治理重心的变化——从流程管理转向价值共创，从效率导向转向人本驱动。在跨国企业与出海中企的实践中，这种转变已经显现：懂组织、懂人、懂科技的HR领导者，正在成为下一代企业的关键变量。 当AI继续重塑世界，我们或许应该问： 未来的企业，究竟是更高效的机器，还是更有灵魂的组织？
    员工体验
    2025年11月09日
  • 员工体验
    颠覆认知：全球劳动力报告揭示的5个反直觉趋势 当今的商业领袖和人力资源专家正面临一个前所未有的挑战：如何在全球范围内高效、合规地管理日益分散的团队？随着全球化团队的兴起，管理的复杂性呈指数级增长，旧有的模式正在失效。我们似乎都认为，更大的人力资源团队、更多的工具和更严格的控制是唯一的出路。 然而，Remote发布的《2025年全球劳动力报告》揭示了一些关于人力资源、技术和全球招聘的惊人真相，其中许多发现甚至与我们的直觉背道而驰。这份报告基于对10个国家的3,650名人力资源和商业领袖的调研，为我们描绘了一幅截然不同的未来工作图景。 本文将为您提炼出其中最关键的五个发现。准备好，这些洞察可能会彻底改变你对未来工作的看法，并为你的组织战略提供新的方向。 1. “精简人力资源”并非资源不足，而是一种新式超能力 传统观念认为，管理庞大的全球员工队伍需要一个同样庞大的人力资源部门。但数据显示，事实恰恰相反。小型人力资源团队（即使只有1-3人）在员工体验和留任率等关键指标上的表现，与大型团队相当，甚至更好。这并非偶然。 报告中的一个关键数据显示，**87%**的受访公司的人力资源或招聘团队规模不超过九人。这些精简的团队之所以能爆发出惊人的能量，其背后的秘密在于技术。他们正通过采用集成式全球人力资源平台、人工智能和自动化等创新工具，巧妙地实现了“以少胜多”。这些技术使他们能够轻松处理跨国薪酬、合规和员工体验等复杂事务，从而在全球舞台上产生巨大的影响力。 “随着公司在全球范围内的扩张，员工的敬业度和留任率不能靠运气。数据显示，业务表现与我们在增长过程中为员工提供支持的程度直接相关。那些无论在哪个地区都优先考虑文化和发展一致性的人力资源领导者，将能保持发展势能并留住顶尖人才。” Barbara Matthews Chief People Officer at Remote 2. 全球人才库已非备选项，而是默认配置 在过去，国际招聘通常被视为一种补充策略。然而，如今的格局已发生根本性转变：全球招聘已迅速成为企业获取人才的默认选项。 这一转变的规模是惊人的。报告预测，到2026年，**73%**的领导者预计其超过一半的新员工将来自公司的主要国家之外。这一趋势背后的主要驱动力是本地人才的稀缺——74%65%29%。然而，即使是较为谨慎的市场也显示出加速的迹象，法国计划中的国际招聘比例将在未来数月从29%上升至38%。 3. 人人都对全球合规充满信心——然而几乎人人都曾失败 在处理复杂的国际劳动法规时，信心是必不可少的，但过度的自信却可能是危险的。报告揭示了一个惊人的“信心差距”：一方面，高达**98%**的领导者对自己了解运营国家的法规充满信心。 但另一方面，现实却给了他们沉重一击：74%42,000美元，而其中31%50,000美元。这种信心与现实的巨大鸿沟，代表着全球扩张中最大的未管理财务风险之一，它将合规从一个法律复选框转变为财务规划的关键组成部分。 4. 人力资源领域的AI革命已至，但现实既混乱又棘手 人工智能无疑是人力资源领域最具变革潜力的技术。数据显示，**75%**的人力资源领导者预计，到2026年底，人工智能将处理超过一半的日常行政任务。这预示着一个更高效、更具战略性的未来。 然而，通往未来的道路并非一帆风顺。当前的现实是一场快速而混乱的实验：在过去一年里，28%停止使用某个人工智能招聘工具，但几乎同等数量（27%）的团队则开始使用一款新的人工智能工具。与此同时，**21%**的团队发现了由人工智能生成且包含误导性或虚假信息的简历。这一系列数据表明，真正的机会不在于零散地采纳各种AI工具，而在于建立一个整合的、治理良好的智能平台。 5. 你的人力资源团队讨厌他们的软件（并且正积极寻求替代品） 认为人力资源团队正在与他们的技术栈作斗争，这并非凭空猜测，而是一个可量化的行业现实。报告明确指出，“工具泛滥”问题已让人力资源团队不堪重负。这种现象普遍存在，超过80%的人力资源团队需要同时操作2到5个独立的系统来管理核心职能。平均而言，每支团队需要使用3.6个工具，而**32%**的领导者认为“过多孤立的工具”是他们技术栈面临的首要挑战。 这种挫败感已经达到了临界点。一个最具说服力的数据是：**近九成（nearly 9/10）**的人力资源领导者表示，如果能获得一个集成了全球薪酬和合规功能的一体化平台，他们愿意立即替换掉现有的核心人力资源信息系统（HRIS）。这种对整合平台的压倒性需求，不仅仅是为了追求用户便利，它更是实现“精简人力资源”模式的根本推动力，使得小型团队能够在不按比例增加人手的情况下实现全球化运营。 结论：面向未来的思考 《2025年全球劳动力报告》清晰地描绘了一种新的运营现实：精简且依赖技术的人力资源团队，肩负着驾驭全球人才的重任，而这项使命正不断受到复杂法规、混乱的人工智能应用以及碎片化软件格局的考验。人力资源部门正从传统的行政角色，演变为技术驱动的战略推动者，但这一转变过程伴随着巨大的压力和前所未有的复杂性。 随着这些趋势的不断加速，真正的问题不再是你的组织是否会适应，而是能否足够快地适应。你的团队为这个新现实做好准备了吗？
    员工体验
    2025年11月06日
  • 员工体验
    OpenAI 推出“ChatGPT for HR”实用场景指南，助力人力资源团队全面提效 近日，OpenAI Academy 在其官方平台发布了《ChatGPT for HR》专题资源，系统展示了 ChatGPT 在人力资源（HR）工作中的实际应用场景与 Prompt 模板，覆盖员工全生命周期管理，从招聘、入职、绩效，到调查、沟通与合规研究等多个环节。该资源旨在帮助全球 HR 团队利用生成式 AI 提升工作效率、洞察深度与沟通一致性。 根据 OpenAI 官方介绍，本次公开的 HR 应用案例分为多个板块，涵盖 政策与沟通撰写、人才获取与面试设计、员工参与与反馈分析、绩效与发展管理、合规与多元平等（DEI）规划 等关键领域。每个场景均附有可直接复制的 ChatGPT Prompt，方便 HR 专业人士快速落地使用。 例如，在内部沟通与政策制定方面，ChatGPT 可以帮助起草员工手册摘要、政策公告、常见问答及内部培训脚本；在招聘与入职环节，HR 可通过 Prompt 生成职位说明、行为面试题、入职计划表等内容；在员工调查与反馈分析中，ChatGPT 能对离职问卷、满意度调查、开放式回答进行语义分析，提炼主题与趋势，为管理层提供决策依据；而在合规与组织研究部分，系统还可协助分析全球法规差异、撰写合规报告，支持 HRBP 的战略研究工作。 业内专家认为，这份资源的最大价值在于其“可操作性”与“模板化”。不同于以往泛泛而谈的 AI 概念介绍，《ChatGPT for HR》提供的内容更像是一套可直接落地的工作工具，帮助 HR 团队将生成式 AI 技术真正嵌入日常流程。 目前，该资源已在 OpenAI Academy 网站公开上线（academy.openai.com/public/clubs/work-users-ynjqu/resources/use-cases-hr），无需额外注册即可浏览。这也是 OpenAI 在企业应用方向上进一步细化行业场景的重要一步，尤其在人力资源领域，为全球 HR 从业者提供了可复制、可扩展的 AI 实践框架。 HRTech 观察认为：AI 已经不再只是“辅助工具”，而正在成为 HR 专业能力的加速引擎。通过标准化的 Prompt 与结构化思维框架，HR 可以在更短时间内完成高质量内容生成与数据洞察，从而将更多精力投入到战略与人本决策之中。 ?原文参考：OpenAI Academy: ChatGPT for HR Use Cases
    员工体验
    2025年10月15日
  • 员工体验
    The best HR & People Analytics articles of July 2025 HR如何在AI时代掌握主动？David Green发布的7月《Data Driven HR Monthly》汇集全球顶尖报告与实践，聚焦“技能+任务”新范式、AI对员工体验与倦怠的双面影响，以及CHRO在企业AI战略中的领导地位。BCG数据显示，印度AI使用率达92%，但全球员工对AI培训满意度仅36%。Upwork报告揭示：高效AI用户更易疲惫离职。McKinsey与Gartner呼吁HR重构组织模型与人才规划体系。本期还探讨神经多元、NASA人才图谱与“Vibe Coding”等创新实践。 I always enjoy spending time in India, so I was delighted to arrive in Delhi yesterday ahead of People Matters Tech HR later this week. I’ll be delivering the opening keynote on how HR leaders can ace the next curve of change as well as leading a workshop on the science of better decisions. I’m looking forward to catching up with fellow speakers such as Jason Averbook (tip: subscribe to his Now to Next blog, if you don’t already), Pushkaraj Bidwai, Mukesh Jain, and Shefali Raias well as immersing myself in what is happening in the Indian HR tech scene. In this month’s edition of the Data Driven HR Monthly, which comes against the backdrop of CEOs flexing on the impact of AI on jobs, I’ve included new research from BCG and Upwork on AI at work, and the role of HR. Marc Effron is spot on here with his assessment that CHROs need to be leading the strategic conversation with the executive team on their desire to reduce costs through job reduction enabled by AI: “CHROs can lead this conversation through organization, operating model and job design, where we should be experts.” I expect plenty of discussion at Tech HR on this topic as well as the wider impact of AI on work, the workforce, and the workplace. One of the messages, I’ll look to get across in my keynote is: AI guides, but humans decide. We must prioritise the ‘H’ in HR. This edition of the Data Driven HR Monthly is sponsored by our friends at TechWolf Skills, Tasks, and Workforce Intelligence: Navigating the AI Transformation This month’s edition highlights an important conversation from the TechWolf Podcast, recorded live in New York, featuring Marc Steven Ramos, global learning leader with 25+ years’ global transformation experience with Google, Microsoft, Accenture, Novartis, Oracle, and Cornerstone, and Jeroen Van Hautte ?, CTO & Co-Founder of TechWolf. The discussion explores how task-based intelligence complements skills data to create a complete view of workforce capabilities, empowering organizations to navigate one of the largest business transformations in history: the AI-driven redefinition of work. Skills without context can be ambiguous. Tasks ground them in real work, and that’s where change, productivity, and AI come together — Marc Ramos Why This Matters Now: The pace of change in the workforce is unprecedented. Leading enterprises are already recognizing that workforce intelligence - the ability to understand, predict, and act on how work is changing in real time - is no longer optional. From skills to skills + tasks + jobs: Combining these data points allows organizations to connect individual capabilities to tangible outputs and outcomes. AI as a catalyst: AI is accelerating job evolution, making real-time visibility into tasks and skills essential for workforce planning and redeployment. Strategic urgency for boards: Workforce automation isn’t a distant trend — it is reshaping workforces today, creating pressure on executives to act on reskilling, redeployment, and workforce design at speed. To really understand a skill, you need to understand the context in which it’s applied — the tasks. And that’s where AI can add transformative clarity — Jeroen Van Hautte For HR leaders, this is an opportunity to lead. With skills and tasks as the foundation, HR is uniquely positioned to drive cultural alignment, manage change, and deliver on the board-level mandate to prepare workforces for the AI era. Listen to the Episode: ?️ Marc Ramos & Jeroen Van Hautte on Tasks, Skills & the Future of Work (TechWolf website summary) To sponsor an edition of the Data Driven HR Monthly, and share your brand with more than 145,000 Data Driven HR Monthly subscribers, send an email to dgreen@zandel.org. JULY ROAD REPORT Until flying to Delhi yesterday, as mentioned above for Tech HR India later this week, July had been a light month of travel other than a short trip to Switzerland to run an AI workshop with the HR leadership team of one of the companies that are part of the Insight222 People Analytics Program. For those interested, one of my speaking engagements from earlier this year, at the Wharton People Analytics Conference, is now available to view (see below). In the talk, I explore the critical role of data democratisation and adoption in driving workforce insights, enhancing decision-making, and scaling HR’s strategic impact. I also share best practices from our work and research at Insight222 for making people analytics accessible to leaders and employees alike, the challenges of adoption, and the key investments required to unlock the full potential of workforce data. Enjoy! Share the love! Enjoy reading the collection of resources for July and, if you do, please share some data driven HR love with your colleagues and networks. Thanks to the many of you who liked, shared and/or commented on June’s compendium. If you enjoy a weekly dose of curated learning (and the Digital HR Leaders podcast), the Insight222 newsletter: Digital HR Leaders newsletter is usually published every other Tuesday – subscribe here – and read the latest edition. HYBRID, GENERATIVE AI AND THE FUTURE OF WORK BCG - AI at Work: Momentum Builds, but Gaps Remain | JOHN BRAZIER AND NICK SOUTH - BCG’s AI at Work 2025 report: Four takeaways for HR leaders Companies are realizing that merely introducing AI tools into existing ways of working isn’t enough to unlock their full potential. The real magic happens—and value generated —when businesses go further and reshape their workflows end-to-end. BCG’s annual AI at work global survey of employees is packed full of insights and guidance for business and HR leaders looking to maximise value, adoption and employee experience with AI. The key takeaways include: (1) AI is now part of our daily work lives: 72% of respondents are regular AI users (although adoption amongst frontline employees has stalled at 51%). (2) Investment in training, leadership support and access to the right tools can break this ceiling: Yet only 36% of employees are satisfied with their AI training. (3) The Global South is showing higher adoption of AI. India leads the pack with 92% of regular users compared to the US (64%), UK (68%) and Japan (51%). (4) The next frontier: from adoption to value with end-to-end redesign. One-half of respondents say their company is starting to reshape processes. These companies also invest more in their people – and it pays off (see FIG 1). (5) AI agents are not widely deployed. Only 13% see agents integrated into broader workflows (see FIG 2). Kudos to the authors: Vinciane Beauchene, Sylvain Duranton, Nipun Kalra, and David Martin. For HR leaders, I also recommend reading John Brazier’s interview with BCG’s Nick South about the implications of the report’s findings for HR on the UNLEASH blog. FIG 1: The relationship between workflow redesign due to AI and investment in people (Source: BCG) FIG 2: Use of AI agents (Source: BCG) GABBY BURLACU AND KELLY MONAHAN - From Tools to Teammates: Navigating the New Human-AI Relationship Full time employees getting the most done with AI are also the most burned out, disengaged, and disconnected from their teams. In their study for the Upwork Research Institute, Gabriela (Gabby) Burlacu and Kelly Monahan, Ph.D. identify a crucial message for the future of work: while AI is undeniably boosting productivity – with a reported 40% jump for many workers – it's also creating a human paradox. Alarmingly, top AI performers are experiencing high burnout (88%) and are twice as likely to leave, often feeling disconnected from strategy and even trusting AI more than human colleagues (see FIG 3 and 4). The report offers three urgent calls to action for business leaders: (1) Redesign work for human-centered, AI-empowered talent and workflows, prioritising autonomy, trust and psychological safety. (2) Cultivate flexible and resilient talent ecosystems, combining full-time employees, freelancers, and AI capabilities to create agile, resilient, and high-performing teams. (3) Redefine AI strategies to focus on the end-to-end human experience, including new roles, norms, and governance. For HR leaders, these findings are a wake-up call. We must prioritise the relational side of AI, ensuring human connection, well-being, and purpose are augmented, not eroded. It's about preventing burnout in our most productive AI users, fostering alignment, and learning from agile models like freelancers to build a truly sustainable human-AI collaborative future. FIG 3: The human cost of AI productivity (Source: The Upwork Research Institute) FIG 4: The rise of human-like relationships with AI (Source: The Upwork Research Institute) COBUS GREYLING - Do AI Agents Substitute Human Workers — Or Enable Humans To Succeed In New Ways? | L. ELISA CELIS, LINGXIAO HUANG, AND NISHEETH K. VISHNOI - A Mathematical Framework for AI-Human Integration in Work AI Agents are good at tasks not jobs… In his article, Cobus Greyling provides an insightful and accessible analysis of a new study by Elisa Celis, Lingxiao Huang, and Nisheeth Vishnoi, which presents a mathematical framework that models jobs, workers, and worker-job fit, and introduces a novel decomposition of skills into decision-level and action-level subskills to reflect the complementary strengths of humans and GenAI. Greyling’s incisive analysis offers a helpful perspective for HR leaders navigating the future of work. His core message is clear: AI agents are fantastic at tasks, not entire jobs. They're not just substitutes, but powerful amplifiers of human capability, especially for less experienced workers, effectively compressing productivity gaps and fostering extraordinary collaboration. Here are four key learnings for HR: (1) Agentic AI Augments Human Potential: AI agents boost efficiency and performance, particularly for junior talent, by handling structured tasks and freeing humans for higher-order work. (2) Redefine Skills & Development: While AI takes on the mundane, HR must strategically ensure continuous skill development, focusing on uniquely human capabilities like judgment, creativity, and complex problem-solving. (3) Design for Human-AI Synergy: Organisational design must pivot to foster premium collaborations between humans and AI. It's about combining complementary strengths to achieve outcomes greater than the sum of the parts. (4) HR Leads Strategic Integration: Our role in HR is pivotal. We must orchestrate the strategic integration of agentic AI, balancing its efficiency gains with the imperative to preserve and nurture human ingenuity, driving both innovation and connection. FIG 5: Al for work: skill difficulty continuum (Source: Cobus Greyling) PEOPLE ANALYTICS KETAKI SODHI AND COLE NAPPER - Who Needs a “Human in the Loop” When AI Gives Itself Feedback Ketaki Sodhi, PhD, Program Owner for Agentic Listening and Analytics at Microsoft, and Cole Napper provide a fascinating perspective on the "human in the loop" concept for Generative AI, provocatively asking: which human, and how? This isn't just a technical question; it's where I/O Psychology and People Analytics come into their own. The article frames AI "evals"— the systems for assessing whether AI outputs are useful, accurate or aligned —as essentially performance management for Large Language Models. Just as we've wrestled with defining "good" in complex human knowledge work for decades, we now face the same challenge in building AI systems. In a world of infinite " " answers, AI evals demand the same nuance we apply to human systems: competency models, multi-rater input, calibration, and context. One of the key takeaways from Ketaki and Cole is that true success lies not in chasing perfect answers from AI, but in designing smart, human-informed systems. These are the systems that can discern between good, better, and what genuinely drives impact for your organisation. For people analytics leaders and I/O psychologists, this is a clarion call to leverage their deep expertise in human performance to shape the very fabric of our AI-driven future. FIG 6: Source – Ketaki Sodhi BEN BERRY - The future is built by everyone: What is Vibe Coding and why should People Analytics teams adopt it | ROSARIO GERMINO - From People Analytics to People Economics and Impact | ADRIAN PEREZ – GitLab People Analytics Team Handbook | DOMINIK TOMICEVIC - Can NASA’s People Graph and LLMs Revolutionize Workforce Planning? | MORGAN DEPENBUSCH - How to let color do the storytelling In each edition of the Data Driven HR Monthly, I feature a collection of articles by current and recent people analytics leaders. These are intended to act as a spur and inspiration to the field. Five are highlighted in this month’s edition: (1) In a particularly insightful piece, Ben Berry examines whether vibe coding, a product management practice of using AI tools to rapidly build functional prototypes to help turn rough ideas into working concepts, should be adopted in people analytics. (2) In her thoughtful article, Rosario Germino argues that to elevate people decisions to the same level of strategic investment as product or finance, we need a new way of thinking—and a new kind of function – People Economics and Impact, which she then breaks down into the why (see FIG 7 on the multi-dimensional aspect of informed decision making), what and how. (3) In a recent post, Adrian M. Pérez provides open source access to GitHub’s People Analytics Team Handbook, a rich resources covering areas such as (i) data governance framework, (ii) tools and methodologies, (iii) survey administration, and (iv) Tableau dashboard strategies. (4) Dominik Tomicevic provides a compelling account of how NASA’s People Graph is supporting a range of priorities from upskilling to workforce planning – with insights from the NASA team of David Meza, Madison Ostermann and Katharine Knott, MBA: “Knowledge graphs offer flexibility, since you don’t need a full schema upfront. We began with known relationships and expanded as we uncovered more insights in the data.” (5) In an edition of her excellent Trending Up newsletter, Morgan Depenbusch, PhD offers some compelling guidance on the use of colour in data visualisation and storytelling. FIG 7: Informed decisions are multi-dimensional. Financial logic makes them investable (Source: Rosario Germino) THE EVOLUTION OF HR, LEARNING, AND DATA DRIVEN CULTURE MCKINSEY - HR Monitor 2025 The gap is widening between what is needed from an efficient, effective HR function and what most organizations currently offer McKinsey's HR Monitor 2025 benchmark study of workforce and HR trends across Europe, delivers a sharp analysis of the critical shifts shaping the HR profession, emphasising that the next 12-24 months are decisive for the function. The report identifies five key trends: (1) Workforce planning is not approached strategically enough – see FIG 8 - (“…with rapid changes driven by gen AI and shifting skill needs, workforce planning must move beyond short-term staffing forecasts to include a longer-term view and future-scenario planning”). (2) Talent acquisition is becoming more complex: with only 56% offer acceptance rates, 18% of new hires leaving during their probationary period and the overall hiring success rate in Europe standing at a lowly 46%, a more strategic and coordinated approach to attracting and hiring talent is required. (3) Employee development continues to be highly fragmented (“To prepare the workforce for future challenges, organizations must connect performance management, learning and development, and talent development in one cohesive strategy”). (4) Employee experience is essential—and underdeveloped (“A more tailored, data-driven approach to the employee experience is needed to build motivation and long-term commitment to employers”). (5) Gen AI and shared-services centres could boost efficiency and effectiveness (“HR departments must modernize their operating models by expanding SSC adoption and using automation and gen AI to increase speed, scalability, and strategic impact”). For Chief People Officers, the message is clear: You must align HR strategy directly with business priorities, strengthen your HR operating model, and aggressively build digital and AI skills within HR. This is about laying the foundation for a modern, AI-enabled HR function that is both deeply people-centric and laser-focused on organizational performance. Kudos to the authors: Julian Kirchherr, Vincent Bérubé, Charlotte Seiler, Dr. Kira Alexandra Rupietta, Kristina Stoerk, Nina-Marlene Senst, and Simon Gallot Lavallée. ...with rapid changes driven by gen AI and shifting skill needs, workforce planning must move beyond short-term staffing forecasts to include a longer-term view and future-scenario planning FIG 8: Engagement in workforce planning (Source: McKinsey) FIG 9: Predicted impact of gen AI on HR department (Source: McKinsey) ESER RIZAOGLU AND STEPHANIE CLEMENT - How CHROs Can Prepare Their Function and the Enterprise for AI Transformation CHROs play a key role in safely using AI at scale to deliver business outcomes. Recent research by Eser Rizaoglu and Stephanie Clement for Gartner provides a helpful roadmap for CHROs steering their organisations through AI transformation, by focusing on HR's pivotal role in shaping the future of work. The report highlights three key actions for CHROs to enable their organisation's AI approach: (1) Assist in delivering business outcomes using AI: Leverage GenAI for HR productivity first, then expand to drive enterprise-wide improvements with a broader AI portfolio. (2) Manage behavioural outcomes of AI: Cultivate a culture of innovation, build human-centred change management plans, and introduce new HR roles to foster human-machine partnerships. (3) Enable workforce readiness for AI: Implement AI literacy programs for all (see FIG 10), while targeting upskilling efforts on segments most impacted, building empathy, and tracking readiness indicators. For CHROs in Steady-AI-Pace organisations, the focus is on foundational AI literacy and policy. Those at an Accelerated-AI-Pace must deepen this by targeting high-impact workforce segments and deploying AI champions to drive effective, human-centric change. FIG 10: AI Literacy Program Roadmap (Source: Gartner) DAVE ULRICH - Navigating Eight Paradoxes of AI for HR When algorithms combine with human empathy, judgement, and creativity, sustained progress occurs. In his article, Dave Ulrich highlights eight paradoxes on the AI for HR agenda that he believes business and HR leaders need to navigate to move up the s-curve and waves of HR impact (see FIG 11) to deliver more value. As Dave explains: “Navigating (not just managing) paradox means highlighting and working through opposing ideas—each of which is valid—that combine to create more value.” The eight paradoxes identified in the article are: (1) AI and AI: Artificial Intelligence * Authentic Intimacy. (2) Remove jobs and redefine work. (3) Bottom line efficiency and top line growth. (4) Distribute and concentrate power. (5) Lower and increase risk. (6) Expand perspective and reduce cognition. (7) Provide answers and explore questions. (8) Isolate and connect. FIG 11: Five stages of AI for HR evolution (Source: Dave Ulrich) EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING JARED WEINTRAUB - A day in the life of a GenAI-enabled workforce Deloitte forecasts that 25 percent of companies currently using GenAI will launch agentic pilots this year, rising to 50 percent by 2027 Jared Weintraub, PhD, SPHR's article for Deloitte paints a tantalising picture of a 'Gen-AI enabled workforce,' showcasing how AI agents are already transforming our daily work. Through a fictional Fortune500 company, Jared brings to life three key personas: (1) New Hire (Riley): Experiences personalised onboarding, with AI agents helping her navigate culture and quickly excel in her role. (2) VP (Taylor): Sees optimised leadership workflows, receiving instant summaries, personalised action items, and even real-time feedback on calls. (3) CEO (Angelina): Gains powerful support for strategic decision-making, with AI agents providing real-time insights and even coaching for high-stakes events like public town halls. These examples demonstrate AI's profound potential not to replace workers, but to fundamentally enhance human potential, leading to a significantly improved employee experience where individuals, teams, and organisations can thrive and perform at their absolute best. Thanks to Brian Heger for highlighting in his excellent Talent Edge Weekly. WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS SCOTT REIDA AND KRISTIN SABOE - Applying the Rule of 72 to Workforce Skill Obsolescence and Productivity Degradation Amazon's Scott Reida and Google's Kristin Saboe, Ph.D. introduce a powerful financial concept to HR: the "Rule of 72." Traditionally, it's a shortcut to estimate how long an investment takes to double, by dividing 72 by its annual growth rate. They ingeniously flip this, applying it to skill evolution: by dividing 72 by a role's weighted average 3-year Compound Annual Growth Rate (CAGR) of its skills, one estimates the "years to obsolescence" if no upskilling occurs. This provides critical directional clarity on how fast job competencies are shifting. Their framework, illustrated in FIG 12, categorises skills into four key zones: (1) Emerging (low adoption, high growth, representing the cutting edge). (2) Table Stakes (widely adopted, foundational must-haves with steady growth). (3) On the Cusp (moderate adoption, sustained expansion, offering long-term value). (4) Sunset (declining demand, requiring intentional upskilling). This enables smarter workforce planning. HR can now target training budgets where skill erosion is rapid, shifting from reactive to proactive strategies. It transforms talent into a dynamic portfolio , informing sharper hiring and career development in our accelerating world. FIG 12: Categorising skills into four key zones (Source – Scott Reida and Kristin Saboe) McKINSEY - The new rules for getting your operating model redesign right When people feel invested in and supported, they are more likely to embrace change, contribute meaningfully, and sustain the behaviors that drive long-term impact. New research from McKinsey updating their nine golden rules for operating model redesign, which finds that five original (evergreen) rules have stood the test of time while four new (evolved) rules have emerged (see FIG 13). The study identifies a key finding: redesign success jumps from 59 percent when using all nine original rules to 97 percent when using all nine in the refreshed set. The article also presents four broad redesign themes for leaders to focus on: (1) Create alignment among leaders and decision-makers, grounded in strategy. (2) Invest deeply in rewiring workflows. (3) Make significant investments in people. (4) Create a performance-oriented culture for durable impact. For Chief People Officers, the key takeaway is that they need to become the architects of dynamic, human-centric operating models. Their focus shifts from traditional talent management to proactively designing how work gets done, emphasising skills and capabilities over static roles. CPOs should also lead on ethical AI integration, foster a culture of continuous learning, and empower leaders. This creates a workforce built for perpetual reinvention, driving sustained value in an increasingly uncertain world. Kudos to the authors: Brooke Weddle, J.R. Maxwell, Tristan Allen, Deepak Mahadevan, Elizabeth Mygatt, and Olli Salo. FIG 13: The refreshed golden rules of organisational redesign (Source: McKinsey) LEADERSHIP, CULTURE, AND LEARNING JEFF WETZLER - The Right Way to Prepare for a High-Stakes Conversation Curiosity increases your ability to process new information and respond creatively to complex problems. It activates the brain’s learning and reward centers, increasing your capacity for insight and creative problem-solving. In his recent HBR article, Jeff Wetzler introduces a helpful concept for leaders: The Curiosity Check (see FIG 14). This diagnostic is designed to fundamentally shift your mindset from defensive certainty to productive curiosity, and so improve your effectiveness in high-stakes discussions and boost your influence. It’s all about unlocking crucial, often hidden, insights. Wetzler outlines three actionable steps: (1) Choose Curiosity Over Certainty: Actively ask yourself "What am I missing?" challenging your assumptions. (2) Make It Safe to Speak Up: Create an environment where people feel secure sharing their true thoughts, proving safety through action, not just words. (3) Pose Quality Questions: Shift from shallow or leading questions to open-ended, neutral, and deeper inquiries that encourage genuine reflection. Wetzler brings this to life with examples, highlighting how leaders often miss critical information when they assume team alignment, never probing for the "unspoken thoughts" that hold the real insights. This approach empowers you to tap into wisdom you might otherwise completely overlook. Thanks to Amy Edmondson for highlighting. FIG 14: The Curiosity Curve (Source: Jeff Wetzler) MCKINSEY RESEARCH AND INNOVATION LEARNING LAB – Reimagined: Development for the Future of Work – Evolving Trends in L&D Article | Full report Leaders must prepare for a future defined by radical candor regarding the impacts of AI on work and the workforce. The 2025 McKinsey Learning Perspective spotlights three interconnected themes crucial for people development in a rapidly changing world: (1) Fluid Development Ecosystems: Organisations must design work to be inherently developmental, shifting from rigid structures to dynamic, data-driven ecosystems. This means de-siloing HR functions and embedding learning into daily work, making growth continuous and seamless. The goal is to make daily challenges catalysts for growth, supported by real-time data and foresight. (2) Responsible AI Adoption: This defining moment demands leaders preserve employee trust by showing AI will help them thrive, not just automate work. It's about fostering powerful human-AI collaboration, offloading repetitive tasks to AI to unlock human creativity and higher-order skills. Responsible adoption hinges on equipping employees with uniquely human capabilities like critical thinking and judgment. (3) Resilient and Adaptable Individuals and Organisations: Thriving organisations anticipate challenges, adapt, and grow, building structural and cultural foundations for resilience. This involves unlocking the potential of diverse, multigenerational workforces, supporting recuperation to prevent burnout, and enabling organisational resilience through sustainable workflows. It means seeing resilience as a shared, cultivated capability, not just an individual trait. Read the article by Heather Stefanski, Benjamin Hall, Jake Gittleson, and Jessica Glazer, and then dive into the full report, which also includes contributions from the likes of Sandra Durth. DIVERSITY, EQUITY, INCLUSION AND BELONGING ROBERT D. AUSTIN, NEIL BARNETT, CHLOE R. CAMERON, HIREN SHUKLA, THORKIL SONNE, AND JOSE VELASCO - How Neuroinclusion Builds Organizational Capabilities Leaders should consider neuro-inclusion as a strategic capability-building opportunity rather than a diversity initiative In a rapidly evolving world, neuro-inclusion is emerging as a critical organisational capability, as highlighted by Robert Austin, Neil Barnett, Chloe Cameron, Hiren Shukla, Thorkil Sonne, and Jose Velasco in the MIT Sloan Management Review. This isn't merely a diversity initiative; it's a strategic imperative that unlocks competitive advantage by leveraging the rich, natural variation in human cognition. By intentionally designing processes for neurodistinct individuals, organisations can profoundly improve: (1) Hiring, by tapping into overlooked talent pools with unique skills (as seen with SAP attracting highly credentialed candidates often missed by traditional interviews); (2) Innovation, through diverse perspectives that spark novel solutions (Microsoft's Teams ‘Blur’ feature emerged from a neurodistinct engineer's insights); and ultimately, (3) Culture, by fostering a more adaptive and truly inclusive environment for everyone. As the article reveals, EY, Microsoft, and SAP are prime examples of organisations already reaping these benefits, demonstrating that embracing neurodiversity enhances collective intelligence and drives superior business outcomes. FRANK DOBBIN AND ALEXANDRA KALEV - Achieve DEI Goals Without DEI Programs Many management innovations designed to improve performance actually boost workforce diversity as well, without inviting the backlash of formal DEI programs. Frank Dobbin and Alexandra Kalev, in their recent HBR article, challenge the traditional view of DEI. They argue that as formal DEI programs face headwinds, HR leaders can still drive significant diversity, equity, and inclusion by focusing on high-performance management techniques that naturally foster inclusion and improve business outcomes, all without the ‘DEI program’ label. They highlight five powerful techniques and provide examples of how these have been implemented by companies: (1) Referral programs: Companies like Oracle use these effectively, often boosting representation organically. (2) Skills upgrading: Walmart exemplifies this, investing in employee upskilling that broadens opportunities for diverse talent (see FIG 15). (3) Mentoring programs: IBM has long leveraged robust mentoring to support career progression across all groups. (4) Scheduling flexibility and stability: Gap demonstrates how providing predictable yet flexible schedules empowers diverse workforces. (5) Performance-based retention: Amazon uses data-driven approaches to identify and retain top performers, inherently benefiting those who excel regardless of background (also see FIG 15). This approach embeds DEI within the fabric of how we manage and develop our people, making it an undeniable component of business success. It’s about doing good by doing well. FIG 15: Walmart and Amazon’s changing workforces (Source: Dobbin and Kalev) HR TECH VOICES Much of the innovation in the field continues to be driven by the vendor and analyst community, and I’ve picked out a few resources from July that I recommend readers delve into: LISA K. SIMON - How Much Is a Skill Worth? In her article, Lisa K. Simon, Chief Economist at Revelio Labs, presents the findings of a new paper, she co-authored with David Dorn, Ludger Woessmann, Moritz Seebacher and Florian Schoner, which finds that the number and type of skills workers report are strong predictors of how much they earn: “In fact, differences in skills predict earnings better than differences in education or past experience. Workers who list more skills tend to be in better-paid jobs. On average, each additional skill listed on a resume is associated with 0.67 percentage points higher earnings.” Another finding is that not all skills are valued equally, with occupation-specific and managerial skills providing the largest boost to income, while a higher prevalence of general skills is associated with lower earnings (see FIG 16). Thanks to Seth Hollander, MBA for highlighting the article and paper. Workers who list more skills tend to be in better-paid jobs. On average, each additional skill listed on a resume is associated with 0.67 percentage points higher earnings. FIG 16: Only having general skills on a resume is associated with lower earnings (Source: Revelio Labs) WARDEN AI - State of AI Bias in Talent Acquisition This is an excellent new report from Jeffrey Pole and the team at Warden AI, which provides a comprehensive and data-driven review of AI bias, compliance and responsible AI practices in talent acquisition – the area of HR, which perhaps has the most significant adoption of AI. With a foreword by Kyle Lagunas, and contributions from the likes of Hung Lee (see quote below) and Sarah Smart, Sultan Murad Saidov and Trent Cotton, key findings include: (1) 75% of HR leaders say bias is a top concern when adopting AI. (2) 15% of AI systems fail to meet fairness metrics for one or more demographic group. (3) AI scores 0.94 vs 0.67 for humans, outperforming on average across fairness metrics (see FIG 17). (4) AI is up to 45% more fair than humans for women and racial minority candidates. Congrats too to Jeff and the team for raising $1.6m in a recent funding round. We are right to worry about AI bias, but we should not forget that the baseline, human only judgment, is far from bias-free - Hung Lee FIG 17: AI outperforms humans across fairness metrics (Source - Warden AI, State of AI Bias in Talent Acquisition) COLE NAPPER - From HR Skills…to HR Jobs When new trends emerge at work, they are likely to first appear as skills. As skills evolve, they consolidate into job titles and full occupations. The prolific Cole Napper highlights Lightcast data to paint a compelling analysis on the journey of people analytics, workforce planning and talent intelligence from trends to skills to jobs: “When new trends emerge at work, they are likely to first appear as skills. As skills evolve, they consolidate into job titles and full occupations.” In the article, Cole presents data visualisations and analysis on how job postings mentioning each of the three skills fluctuated over time, how this translated into job titles, and the wage premium (see FIG 18) that these three categories have on HR salaries in general (on the theme of people strategy and analytics salaries, read this post by Pallavi Narang) Look out for Cole’s book, People Analytics: Using data-driven HR and Gen AI as a business asset, which is available for pre-order now ahead of being published on August 26. FIG 18: Median salaries in HR areas (Source: Lightcast) PODCASTS OF THE MONTH In another month of high-quality podcasts, I’ve selected four gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below): PETER FASOLO - Leading with impact as a chief human resources officer – In this must-listen episode of Capital H, Peter Fasolo, Ph.D., former chief human resources officer at Johnson & Johnson, joins host Kyle Forrest to discuss the power of systems thinking, board collaboration, aligning your people agenda with enterprise strategy, and more. ANGELA LE MATHON - AI-Native HR Operating Model & AI Agents for Skills/Tasks – The brilliant Angela LE MATHON joins Cole Napper to discuss how AI is transforming the work that people analytics does and how the function operates as well as envisioning a new AI-native operating model for HR. SVENJA GUDELL, BROOKE WEDDLE, AND BRYAN HANCOCK - What the labor market isn’t telling you—yet – Svenja Gudell, chief economist at Indeed, joins Brooke Weddle, Bryan Hancock, and host Lucia Rahilly, on an episode of McKinsey Talks Talent to help leaders make sense of the current collision of labour market trends: generative AI, agentic AI, an aging workforce, shifting priorities, and more. BEN WEIN – How Bristol-Myers Squibb used skills data to solve a life-or-death talent shortage – Ben Wein, Director of Workforce Skills Enablement at Bristol Myers Squibb, joins Julius Schelstraete ? on The TechWolf Podcast to share how BMS is becoming a skills-based organisation—starting with a business-critical talent shortage in cell therapy manufacturing. Ben explains how BMS uses skills data to drive faster hiring, smarter workforce planning, and ultimately, patient impact. VIDEO OF THE MONTH DJ PATIL - Data, Decisions, and the Future of Work: How AI and Curiosity Are Redefining Careers Many of the videos of the talks at the recent Wharton People Analytics Conference are now available on the Wharton School YouTube channel, including my talk on How Top Companies Scale People Analytics Adoption. There are some wonderful talks from the likes of Amy Edmondson, Ravin Jesuthasan, CFA, FRSA, Ben Waber, Karalee Close, Guru Sethupathy and Michael Fraccaro, but perhaps my favourite session of the two days was former US Chief Data Scientist DJ Patil’s fireside chat with Eric Bradlow on how firms can harness data science to navigate the future of work. They explore the evolving relationship between AI and human collaboration, the promises and pitfalls of algorithmic management, and how leaders can build ethical, resilient, and high-performing organizations in an increasingly data-driven world. BOOKS OF THE MONTH Given it’s the summer in Europe and North America, here are two books to read while you are getting some well-earned relaxation time: PETER HINSSEN – The Uncertainty Principle - Peter Hinssen's The Uncertainty Principle, his fifth book, is a vital read for HR leaders. It argues we're in a "Never Normal" world, where constant change is inevitable. Hinssen transforms uncertainty from a threat to an opportunity, urging us to move faster and think bigger. For HR, this means embracing ambiguity, leading cultural shifts, leveraging people data, and redefining talent and leadership for relentless evolution. It's about equipping our people to thrive and transform every challenge into a strategic advantage. For a preview of the book, I recommend Peter’s recent discussion with me on the Digital HR Leaders podcast: Uncertainty as an Opportunity: HR's role in Shaping the Future. JENNY DEARBORN AND KELLY RIDER - The Insight-Driven Leader: How High-Performing Companies are Using Analytics to Unlock Business Value - Jenny Dearborn, MBA and Kelly Rider's The Insight-Driven Leader is an inspirational guide to unlocking serious business value through people analytics. This book shows how to transform raw data into powerful workforce insights, solving critical challenges and driving success. You'll learn: (1) How to move beyond traditional rear-view HR metrics to actionable insights. (2) Real-life case studies from leading organisations, as well as cautionary tales. (3) Recommendations for becoming an insights-driven organization using workforce analytics. The book is a must-read for leaders aiming to align data with strategy and build a truly insight-driven culture. FROM MY DESK July saw four new episodes of the Digital HR Leaders podcast – all sponsored by our friends at Mercer (thanks IŞIL ÇAYIRLI KETENCI): ANSHUL SHEOPURI - How People Analytics is Powering Business Strategy - Anshul Sheopuri, Executive Vice President of People Operations & Insights at Mastercard, joins me for a conversation on how to embed analytics into enterprise-wide decision-making at scale. Thanks to Sasha Houlihan for organising. PETER HINSSEN - Uncertainty as an Opportunity: HR's role in Shaping the Future – As highlighted in the Books of the Month above, Peter Hinssen joined me to discuss what it really takes for HR to embrace uncertainty and lead in this era of the ‘Never Normal.’ RAVIN JESUTHASAN AND BRIAN FISHER - The Skills Revolution: Your Playbook for Workforce Agility – Ravin Jesuthasan, CFA, FRSA and Brian Fisher join me to explore why skills-based workforce planning has surged to the top of the HR agenda - and what leading companies are doing to turn intent into action. AMY BAXENDALE - How Arcadis Built a Skills-Powered Organisation – Amy Baxendale , Global Future of Workforce Director at Arcadis, provides a detailed guide on the journey the company has embarked to become a skills-powered organisation. The episode includes discussion on the business case, securing sponsorship, setting up governance, the partnership with Mercer and Eightfold, and the early benefits: We are early in the journey, but we are seeing some promising signs of progress. Our time to hire is trending downwards - that has a direct commercial impact for the business. We've also actually been able to calculate the financial impact of work that's being completed through gigs and show the actual impact on EBITDA LOOKING FOR A NEW ROLE IN PEOPLE ANALYTICS OR HR TECH? I’d like to highlight once again the wonderful resource created by Richard Rosenow and the One Model team of open roles in people analytics and HR technology, which now numbers over 525 roles with half of these being new. THANK YOU To HR magazine and Charissa King for including me again in their annual HR Most Influential list as one of the ten most influential practitioners The Talent Games for including the Digital HR Leaders podcast at #6 in its 27 Best Leadership Podcasts for HR Leaders. Steve Sands for including my work as part of his Human Resource Management Analytics night class at the National College of Ireland. A huge thank you to the following people who either shared the June edition of Data Driven HR Monthly and/or posted about the Digital HR Leaders podcast, conferences or other content. It's much appreciated: Emmanuel Duncan, Rob Baker, FCIPD, MAPP, Richard Hall, Robert Rogowski, Catherine de la Poer, Caroline Lambe, Jeremy Sholl, Narelle Burke, Edan Halili, Francesca Caroleo (SHRM-SCP, ICF-ACC), Uwe Gohr, Joseph Frank, PhD CCP GWCCM, Randeep Kaur, Aaron Chasan, Danial Singh Kang, Jorge-Luis Gonzalez, Anisha Moosaأنيشا موسى?????, Carlos Lopes, Danielle Farrell, MA, CSM, Kris Saling, Hiroyuki MIYAI, Ph.D., Yukiko Hosomi, Dr. Christoph Spöck, Joachim Rotzinger, Kevin Le Vaillant, Seung Won Yoon, Alexis Fink, Timo Tischer, Dr. Tobias Bartholomé, Jose Luis Chavez Vasquez, Meg Bear, Abhinav Tiwari, Esther Abraas, Gareth Flynn, Elizabeth Musso, Jana Glogowski, Maarten van Beek, K Nair, Joonghak Lee, Sameer Tahir, Robert Allen, Volker Jacobs, Bilal Laouah, Florent Maire, Oliver Kasper, Jaap Veldkamp, Patrick Coolen, Jeff Wellstead, Jean-Francois (Jeff) BOUBANGA MIGOLET, Dan George, Shujaat Ahmad, Alexandra Nawrat, People Edge Consulting Ltd., Andrew Spence, Roshaunda Green, MBA, CDSP, Phenom Certified Recruiter ?, Austin Brockert, MBA, Dan Riley, Sanja Licina, Ph.D., Anna A. Tavis, PhD, Stela Lupushor, Jeremy Shapiro, David Simmonds FCIPD, Catriona Lindsay, Aravind Warrier, Michael Arena, Greg Pryor, Isabella Cheshire, Amardeep Singh, MBA, Aline Costa, Anis Alexandros El Namparaoui, Adam Treitler, Helder Figueiredo, Sebastian Knepper, Sebastian Kolberg, Lewis Garrad, Kerry Ghize, Preetha Ghatak Mukharjee, Jacob Nielsen, Pete Jaworski, Søren Kold, Prabhakar Pandey, Avani Solanki Prabhakar, Ian Grant FCIPD, Erik Samdahl, Max Blumberg, Sergey Puchka, Romy Hobson, Bettina Dietsche, Hernan Chiosso, CSPO, SPHR ?, Paola Alfaro Alpízar, Sergio Garcia Mora, Hanadi El Sayyed, David van Lochem, Maria Nolazco Masson, David McLean, Clara W Estanqueiro, Shonna Waters, PhD, Kevin Martin, Kathi Enderes, Serena H. Huang, Ph.D., Smadar Tadmor, Tobias W. Goers ツ, Dr. Denise Turley AI.Impact.Equity, Stella Ioannidou, Apeksha Awaji, Evan Franz, MBA, L N Divya Mudundi, Ross Sparkman, Salman Farooq, Megan Reitz, Todd Tauber, Heather Muir, AJ Herrmann, Priyanka Mehrotra, Oliver Auty, Priya Subrahmanyan, Naotake Momiyama, Bill Banham, Matthew Yerbury, Prachi Agasti, Robin Haag, Fabian Stokes, MBA, SWP, Monika Manova, Barry Swales, Dean Carter, Ian OKeefe, Ying Li, Alexandre Monin, Mike Zarrilli, Natasha Fearon, Pedro Pereira, David Balls (FCIPD), Naomi Verghese, Geetanjali Gamel, Frankie Close, Warren Howlett, Stephanie Murphy, Ph.D., John Gunawan, Jesse Clark, MBA, Caitie Jacobson Mikulis, Meghan M. Biro, Dan Trares, Kouros Behzad, Kathleen Kruse, Nick Lynn, Mariana Allain Carrasqueira, Marina Pearce, PhD, Dawn Klinghoffer, Raquel Mitie Harano, Delia Majarín, Deborah M. Weiss, Courtney McMahon, Nirit Peled-Muntz, Hanne Hoberg, Adam McKinnon, PhD., Don Dela Paz, Matt Elk, Sophia Houziaux, Danielle Bushen, Nabil Dewsi, Sai Bon Timmy Cheung 張世邦, Dolapo (Dolly) Oyenuga Agnes Garaba, Wouter Minten, Olly Britnell, Nick Hudgell, Roxanne Laczo, PhD, Claire Masson, Daisy Grewal, Ph.D., Laura Cole, Brian Elliott, Erin Eatough, PhD Henrik Håkansson Gabe Horwitz Russell Klosk (智能虎) The final note this month is a sad one - rest in peace Diogo Jota and André Silva. ABOUT THE AUTHOR David Green ?? is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 100 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021. MEET ME AT THESE EVENTS I'll be speaking about people analytics, the future of work, and data driven HR at a number of upcoming events in 2025: July 31 - August 1 - People Matters TechHR India 2025, Delhi August 13-16 - GCHRA Africa, Accra, Ghana (I will join virtually) September 25 - Visier Outsmart Local London, London October 7-9 - Insight222 Global Executive Retreat, Atlanta (exclusive to the people analytics leader in member companies of the Insight222 People Analytics Program®) October 15-16 - People Analytics World, New York October 21-22 - UNLEASH World, Paris November 12-13 - HR Forum 2025, Oslo More events will be added as they are confirmed.
    员工体验
    2025年07月27日
  • 员工体验
    Is The HR Profession As We Know It Doomed? In A Strange Way, Yes. I just spent a week in London meeting with several dozen companies and most of the discussion was about AI. The overwhelming majority of the conversations were about how companies are struggling, pushing, and agitating about the implications of AI, both within HR and within their teams. Coming from the CEO and CFO, HR team are under intense pressure to automate, improve their services, and reduce headcount with AI. Yes, we know AI is a technology for growth and scale, but the main message right now is “hurry up and do some productivity projects.” And “Productivity,” as you know, is a veiled way of saying “Downsizing.” So before I get back to HR, let me discuss downsizing. It’s absolutely true that almost every company we work with has too many people. Why? We have a sloppy way of hiring people, allocating resources, and managing work. We delegate “headcount” to managers and they go out and hire as many people as they can. We don’t really teach (or incent) managers how to build “productivity,” we actually do the opposite. We tend to reward them for “hiring more people.” The result is a problem I just talked about with a large advertising company: too many weird jobs and no consistency or structure to our work. This particular company has around 100,000 employees and more than 60,000 job titles.  In other words almost every job is “invented for this person.” It’s insane. The whole reason we have companies (and not individual craftsmen) is to build scale. If we expect every individual manager to figure out how to scale, we’re more or less designing low productivity into the business. There are some simple models we use:  call centers, global services groups, shared services, capability communities, and centers of excellence. But that kind of high-level productivity design is now becoming obsolete. In this new era of high-powered multi-functional agents, we need to go much further. Elon Musk likes the “first principles” approach. Fire everyone and start from “first principles,” only hiring the people you urgently need to build, sell, and support your product. That may work in small companies but when you’re big there are too many “support services” to consider.   One of the companies we are working with has “program managers” and “project managers” and “analysts” sprinkled all over the organization in random places. In other words, their core staff don’t know how to manage projects, programs, or data. So there’s a bunch of overhead staff doing this for them.  Drives me crazy.  This took place because there was no discipline in hiring, so each group “bulked up” with staff. This is really business as usual. Organization design is an old, crusty, under-utilized domain so most companies barely think about it. IBM told me a few years ago that their “org design” strategy is to “hire a high performing executive and let him or her figure it out.” I hear that, it’s quite common. The bottom line is this: if we want to get a sound ROI from all these AI tools and agents we have to get a lot smarter about “work design.” And that is not building org charts, it’s the basics of figuring out our workflows, areas of common and uncommon process, and where and how we can automate. Most of our clients have tons of productivity systems already (ServiceNow, Salesforce, Workday, whatever), but they either don’t know how or don’t have the discipline to use them well. So they just keep hiring people. As an engineer I see this visibly all the time. It’s very easy to delegate a “problem” to a person, and not think about it as “plumbing.” But it is plumbing. As Tanuj Kapilashrami from Standard Charter put it, we need to focus on plumbing first, then we figure out where to apply AI. This means we can’t just cross our fingers and hope that the Microsoft Copilot is going to make everyone more productive. We need to look at business processes and skills at the core, and then literally reinvent our companies around these new AI tools. And skills are very important. The reason companies hire a bunch of “analysts” and “project managers” is because individuals and existing managers just aren’t good at their jobs. We all need to learn how to project manage, schedule, and analyze work. That way these high-powered specialists can work on big things, not sit in staff meetings taking notes (where AI note-takers do this well). (By the way, I have to guess that we’ll soon have AI agents for project management, program management, and functional analytics, so those staff jobs are going to be automated next!) How Does This Impact HR Let’s get back to HR. Given this massive effort to re-engineer and implement AI, where does HR fit? Well fundamentally HR is tasked to build process, expertise, and advisory services around the “people processes” in the company.  That means hiring, developing, managing, paying, rewarding, and supporting people.  It’s a big mission, and when we start to focus on “productivity” then HR must be involved. The general belief is that a “well run” HR team has about a 1:100 ratio to the company. In other words, if you have 10,000 employees you’re going to have around 100 HR people. And the HR team doesn’t just run around doing things, they buy and build HR technology for scale. So HR itself, as a “plumbing” type of operation, needs to be “lean and mean.” If your CEO wants you to hire 50 top notch AI engineers you can’t just start phoning everyone you know: you must decide precisely how you’re going to do this in a scalable, efficient, and highly effective way. (AI engineers are rare, they’re hard to hire!) So your little HR team has to think about productivity.  Should we outsource this? (Which is a cheap and dirty way to look productive.) Should we buy a talent intelligence or sourcing system?  Should we hire three high-powered recruiters?  You know where I’m going.  We have to find a way to “be productive” while we try to “make the company productive.” This means we, as a support and advisory function (HR professionals spend a lot of time coaching and supporting managers) have to stop creating forms and checklists and implement AI agents as fast as we can. Why? Because so much of our work is transactional, workflow-oriented, and administratively complex. And AI can do a lot of amazing things, like “assessing the skills of an AI engineer” for example. (Our AI Galileo can literally evaluate a recorded interview and give you a pretty good assessment of an individuals skills, mapped against the Lightcast, SHL, and Heidrick functional and leadership models.) Let’s assume we do this well, and HR technology vendors give us good products. We wind up with amazing recruiting agents, AI agents for employee training, onboarding, and coaching, AI agents that help with performance management, AI agents for succession and careers, and AI agents that deal with all the myriad of personal benefits and workplace questions people have.  Where do we end up? Do we “automate away” our own jobs? Well, in a way the answer is yes. AI, through its miraculous data integration and generation capabilities, can probably do 50—75% of the work we do in HR. All this is far from built out yet, but it’s clearly coming. (We just talked with a large pharmaceutical company that is “all-AI” and they manage a team of 6,000+ scientists and manufacturing experts with only ten people in learning and development. They’ve automated training, compliance tracking, onboarding, leadership support, and all the details of training operations.) Could you do all that for a fast-growing 6,000 person company with 10 people? I doubt it. Most companies would have more than 10 people in sales training and sales enablement alone. So here’s my point. HR, like other functional areas in our companies, is going to have a real-life identity crisis. If you can’t figure out how to move your HR function up the maturity level quickly (check out our Systemic HR maturity model) someone’s just going to cut your headcount (the Elon Musk approach). Then you’ll be figuring out AI in a hurry. (Galileo can assess your HR maturity with its “consulting mode,” by the way.) I’m not saying this is easy. The AI products we need barely exist yet. But the pressure is on. You shouldn’t wait for the CFO to point his “productivity gun” in your face, you have to get ahead of this wave. Start pushing yourself to fix plumbing, check out the new tools in the market, get your IT team involved, and redesign your work using your own expertise. Many surprisingly good things will happen. Let me give you an example. A few years ago Chipotle adopted an AI-based agent system for recruiting, effectively automating a complex workflow for hiring. Not only did it save millions of dollars, the “speed and quality” of hiring went up so high the CEO talked about it as their top “revenue driver” with Jim Cramer on CNBC. In other words this “identity crisis” in HR is a good thing. Our recruiting, training, and employee services groups are too big. AI can automate enormous amounts of this work. So my advice is this. As the AI wave sweeps across your company, get out your old “org design” book and start redesigning how your HR team operates right now. Then you can go to the AI vendors and tell them what you want. That’s the secret to keeping HR in tip-top shape. Will HR go away? Well a lot of the process, data management, and support roles will absolutely change. And yes, employees and job candidates will happily use intelligent bots instead of calling their favorite HR manager. But as a Superworker, you, as an HR professional will do more interesting things. You’ll become a consultant; you’ll manage and train AI systems; and you’ll have much more real-time information about the strength and weaknesses of your company.  We’re just going to have to lean into this AI wave to get there. As AI agents arrive, it’s time to seriously re-engineer HR. And this time it’s not a transformation, it’s a reinvention. Bottom line is this. Don’t wait for Workday, SAP, or some other vendor to “invent” a tool that changes your HR operation. You should do it yourself first and bring your IT people with you. That way you’ll buy and build the AI systems you need, and the result will be a new career, an even better HR function, and the opportunity to help your company move from “hiring” to “productivity” in the future.   我刚刚在伦敦与数十家企业进行了为期一周的交流，大部分讨论都围绕着AI展开。绝大多数对话的主题是：公司在应对AI带来的影响时，感到焦虑、推动、甚至焦躁不安，这种焦虑不仅体现在HR部门，也体现在各业务团队中。 在CEO和CFO的压力下，HR团队正被要求加速自动化、优化服务、并通过AI实现人员精简。虽然我们都知道AI是一种能够促进增长和规模化的技术，但当前传递出的主要信息是：“赶紧推动生产力项目。” 而所谓的“生产力”，实际上就是“裁员”的委婉说法。 先谈谈裁员 几乎我们接触的每一家企业，都的确存在人员过剩的问题。这是为什么呢？ 因为我们的招聘、资源配置和工作管理方式本身就非常低效。我们将“编制名额”下放给各级管理者，而他们则倾向于尽可能多地招聘人员。 我们并没有真正教导或激励管理者如何构建高效的生产力，反而往往奖励他们“扩大团队规模”。结果就是，像我最近在一家大型广告公司看到的那样，组织中充满了各种各样的职位，但缺乏统一性和结构性。这家公司有约10万名员工，却设有超过6万个不同的岗位头衔——几乎每个职位都是为某个人量身定制的，这种做法显然荒谬。 企业存在的根本目的，是为了实现规模化。如果每个部门经理都各自为战，自行搭建团队架构，那无异于将低效深植于企业之中。 虽然我们有一些基本的组织效率模型，比如呼叫中心、全球服务中心、共享服务、能力中心等，但这些传统设计在当下正逐渐过时。在高性能多功能AI代理全面普及的时代，我们必须走得更远。 从“第一性原理”重构组织？ Elon Musk 推崇“第一性原理”方法——即解散现有团队，只从零开始招聘最核心、最迫切需要的人员。这种方法在小型公司或许奏效，但在大型企业中，由于存在大量“支持服务”，简单地“砍掉重建”并不可行。 现实中，很多公司在各个角落散布着项目经理、程序经理、分析师等职位，因为核心员工缺乏管理项目、推进计划、或进行数据分析的能力。由于招聘过程中缺乏严格的标准和规划，各部门纷纷自行扩编，导致组织臃肿、效率低下。 组织设计本来就是一门古老且被严重忽视的学问，多数公司对此缺乏系统化思考。IBM 曾表示，他们的组织设计策略是“聘请一位高绩效高管，让他/她自己摸索出解决方案”——这实际上是行业普遍现象。 AI真正改变的，是“工作设计” 如果我们希望从AI工具和代理中获得真正的投资回报率，就必须彻底重新思考“工作设计”——不仅仅是画组织结构图，而是要厘清工作流程、标准化与非标准化的业务环节，并找出可以自动化的领域。 尽管大多数企业已经部署了大量的生产力系统（如ServiceNow、Salesforce、Workday等），但由于缺乏使用这些系统的能力或纪律，反而持续地通过“增加人手”来解决问题。 作为一名工程师，我对此体会尤深。将问题推给某个人远比优化底层“管道”来得容易。然而，管理工作流程就像修建城市水管系统——如果基础设施不合理，再先进的AI工具也无济于事。 正如渣打银行Tanuj Kapilashrami所说：“必须先修好管道，才能合理应用AI。” 这意味着，我们不能指望微软Copilot之类的工具神奇地提升员工生产力。我们必须从根本上重新审视业务流程与员工技能，并围绕AI重新设计整个企业运作模式。 员工技能，未来的关键 企业之所以聘请大量“分析师”和“项目经理”，往往是因为普通员工和管理者缺乏项目管理、时间安排、数据分析等基本技能。未来，所有人都需要掌握这些能力，而不再依赖大量辅助人员。高阶专业人才应当专注于重大事务，而不是出席会议做会议记录（AI记录工具早已能胜任此事）。 （顺便提一句，我预测很快就会出现AI项目经理、AI程序经理、AI数据分析师——这些岗位也将逐步被自动化！） 那么HR会怎样？ 回到HR领域，当企业致力于重塑流程、导入AI时，HR的角色至关重要。 HR的本质任务是构建并管理围绕“人”的各项流程：招聘、培养、管理、薪酬、激励与支持等。这项使命极为庞大，当公司将焦点转向“提升生产力”时，HR必须积极参与。 一般认为，一个运作良好的HR团队与公司整体人数的理想比例是1:100。也就是说，一家拥有1万名员工的公司，大约需要100名HR人员。而优秀的HR团队不仅自己高效运作，更会采购、搭建技术系统，以实现规模化管理。 举例来说，如果CEO要求你招聘50名顶尖AI工程师，你不能只是随便打几个电话，而是要设计一套高效、可扩展的方法。这可能包括外包、引进人才情报系统、招聘高端猎头，等等。总之，HR自身也必须成为高效运作的样板。 因此，HR团队必须迅速引入AI代理，取代大量重复性事务，尤其是那些依赖工作流、流程管理和行政性处理的工作。比如，我们的Galileo系统已经可以自动评估候选人的面试表现，并将其技能映射到Lightcast、SHL和Heidrick的领导力模型。 未来，HR工作会消失吗？ 某种程度上，答案是肯定的。 凭借出色的数据整合和生成能力，AI可以完成50%-75%的HR工作。目前这些AI系统尚未完全成熟，但趋势已经非常明显。 我们刚刚与一家大型制药企业交流，他们已经基本实现了“全AI化管理”，以仅10人规模的学习与发展团队，服务6000多名科学家和制造专家。他们通过AI自动完成了培训、合规追踪、入职辅导、领导力支持等任务。对于大多数公司来说，这种效率简直是难以想象的。 HR将迎来身份危机 未来，HR必须迅速向更高的成熟度迈进（可以参考我们提出的Systemic HR Maturity Model）。否则，就会像Elon Musk那样，被大规模裁员，并被迫在短时间内仓促上马AI项目。 我并不是说这条路轻松易行。事实上，市面上真正成熟的AI HR产品还非常有限。但压力已经到来。 HR不能等着CFO拿着“生产力枪”指着自己，必须主动出击，修好内部“管道”，试用新工具，联合IT团队，重新设计工作模式。这样，你将能主动选择适合自己公司的AI系统，并构建一个全新的、充满机遇的职业未来。 结语：HR的重塑与再创造 让我们看看Chipotle的案例。他们通过部署基于AI的招聘代理，成功自动化了复杂的招聘流程，不仅节省了数百万美元，还大幅提升了招聘速度和质量。甚至在接受CNBC采访时，CEO将这一成果称为公司的“主要营收驱动因素”。 这场HR身份危机，其实是一个难得的机遇。 我们今天的招聘、培训、员工服务团队规模普遍过大。AI将能够自动化其中大量工作。我的建议是：在AI浪潮席卷而来之前，立即拿起你尘封已久的组织设计手册，重新设计HR团队的运作方式。这样，当面对AI供应商时，你可以主动提出自己的需求，而不是被动接受他们的产品。 未来HR不会消失，但大量传统流程、数据管理与支持岗位将发生剧变。员工与候选人也会越来越习惯通过智能机器人，而非人力HR来解决问题。 不过，真正优秀的HR专业人士，将会变成超能型人才（Superworker）——你将成为企业战略顾问、AI系统训练师，并且能够实时掌握公司人才与流程的整体健康状况。 这次，不再是简单的“转型”，而是真正意义上的“再创造”。
    员工体验
    2025年04月26日
    • 12
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