Meta一边挥刀赶走老白兔，一边改绩效发甜枣

字母榜01-14

新年的钟声敲响不过两周，Meta员工陆续收到关于绩效体系变更的通知。新的系统有一个名字：Checkpoint，它会在今年年中正式启用，几乎覆盖Meta员工接下来整个2026年的绩效考核周期。评级被大幅简化，奖励被明显拉开，顶级表现者将拿到前所未有的高额回报，而绩效体系本身，也被要求更快、更直接。几乎在同一时间，另一条消息传出：Meta计划再度裁员。这一次，Reality Labs一下被裁掉了...

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dates","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"USAW.SI":0.6,"META":1.97},"content_text":"新年的钟声敲响不过两周，Meta员工陆续收到关于绩效体系变更的通知。新的系统有一个名字：Checkpoint，它会在今年年中正式启用，几乎覆盖Meta员工接下来整个2026年的绩效考核周期。评级被大幅简化，奖励被明显拉开，顶级表现者将拿到前所未有的高额回报，而绩效体系本身，也被要求更快、更直接。几乎在同一时间，另一条消息传出：Meta计划再度裁员。这一次，Reality Labs一下被裁掉了1500人。从去年初一次性裁掉约5%的“绩效不佳”员工，到随后在Reality Labs、AI基础设施等部门持续缩减人手，Meta的目的并不复杂，它指向效率与聚焦。乍看之下，这像是两条彼此独立的新闻：一边是“奖励更多优秀的人”，一边是“清理掉不够优秀的人”。但如果把它们放在一起看，就会发现它们其实指向同一件事。Meta正在用更极端，也更直接的方式，重新分配资源。公司不再试图让大多数人都“还不错”，而是要尽可能放大少数关键个人的产出；而裁员，也不再只是成本控制手段，而是试图让组织更轻盈，或说，更适应AI时代的战斗模式。更重要的是，Meta并不是个例。在AI热战全面展开的背景下，科技巨头纷纷对绩效体系和组织层级动手，方向高度一致：它们正在重新决定，哪些人值得被押注。Meta：更多人优秀，拿更多奖励，全员善用AIMeta这次的绩效体系改革，一言以蔽之就是：大幅倾斜资源奖励顶级表现者，同时加强对低绩效者的管理，来最大化公司人力资本的回报率。具体来说，新体系叫“Checkpoint”，将从今年年中启用。由于年中回顾的是那之前半年的绩效表现，所以Meta员工整个2026年的绩效考核其实都将在新体系下完成。在Meta的旧体系中，每年有两次绩效打分。一次是年中，比较简单，三个评级：包括超出预期、达到预期、低于预期。另一次是年终，相对复杂，有七个评级：重新定义预期（最高等级）、大幅超出预期、超出预期、完全达到预期、大部分达到预期、部分达到预期、未达到预期。年中和年终的评级不一样，又这么复杂，就导致了繁文缛节滋生。这次Meta就透露，过往管理者每年光是处理绩效相关任务就要花费大约80小时，而员工每个周期在同事反馈上的总花费时间也高达33万小时。而员工彼此之间的评价反馈真的有用吗？Meta透露，只有不到25%的管理者认为反馈有用。除此之外，在旧体系下，Meta强调强制性低绩效比例分配，2024年低绩效比例为12-15%，到2025年进一步扩大到15-20%，这直接导致了2025年约5%的绩效相关裁员（大约4000人）。而在新体系Checkpoint之下，事情就清爽多了。还是年中和年终这两个节点做绩效审核，但是采用一样的评级，且只分三级：· 杰出（Outstanding）：占比20%，代表“远超预期”，奖金系数200%；· 优秀（Excellent）：占比70%，被描述为“高绩效文化基线”，奖金系数115%；· 需要改进（Needs improvement）：占比7%，适用于绩效存在差距且预期能够改进的员工，奖金系数50%；· 未达预期（Not Meeting Expectations）：占比3%，适用于“未达到”Meta标准的用户，奖金系数为0。这样一来，整个绩效体系被大大简化了，而且也不难看出其中占比的倾斜，优秀及以上的占比90%，占大多数。奖励也同样大幅倾斜，除了以上常规评级之外，Meta还设置了一个额外奖励（Meta Award），选出少数有“真正杰出贡献”的员工，给予300%的奖金。这与Meta近年来强调的“高绩效文化”高度一致，该文化源于公司CEO扎克伯格（Mark Zuckerberg）在2025年将该年定义为“激烈之年”，其间公司通过一系列措施来提升团队效率和AI创新能力。除此之外，在整个新绩效体系下，AI工具的使用也备受重视。在去年12月的时候，Meta就推出了一个叫“AI绩效助手”的工具，员工（包括管理者）使用AI来起草、总结和优化绩效内容，让整个绩效评估流程更高效。在Checkpoint推行后，AI工具的使用被强化，虽然不是强制但是也差不多了。说起来很有意思，Meta对AI的痴迷在内部管理中也有所体现。从去年开始，Meta就把“AI驱动的影响”作为绩效考核的重要指标，也就是说员工绩效好不好，必须纳入“有没有好好用AI提高工作效率”的考量。绩效评估的过程本身也是一项工作，鼓励员工用“AI绩效助手”写评估，那么就形成了“用AI工具写关于有没有善用AI的评估”的循环。AI热战，各大厂都在调整绩效体系Checkpoint系统是Meta在AI时代对人力激励的战略升级。扎克伯格希望通过统一评级标准和AI辅助工具简化绩效流程、减少官僚负担，还通过“富矿”式奖励机制大幅强化了对高输出者的倾斜，这将直接影响2026年Meta在新模型研发、智能眼镜等AI核心项目中的竞争力。公司把有限的奖金池/股权资源像“富矿”一样集中砸给高产出者——尤其是AI贡献突出的人，目的是最大化投资回报率，刺激全员向顶级冲刺，同时高效控制整体人力成本。这种“赢家通吃”模式在AI人才战争中特别有效，因为顶级AI工程师/研究员的产出往往决定模型代差。也不止有Meta对绩效体系下手，在AI热战之下，国内外的大厂这两年动作频频。去年12月，字节跳动宣布四大措施：增加奖金（含绩效期权）投入，2025全年绩效评估周期相比上个周期提升35%；大幅增加调薪投入，较上个周期提升1.5倍；提高所有职级薪酬总包的下限（起薪）和上限（天花板）。据澎湃新闻，字节当时在内部邮件开头就说得很清楚：“我们所处的行业正面临新的机遇和挑战，公司希望更好地吸引、激励和保留优秀人才，鼓励大家和公司业务一起，再上一个比过去更大的台阶。”核心目的只有一个——让优秀的人才拿到更多钱。要注意的是，整体来说字节的调整更像是“全员吃肉”，但是由于不同层级的放大比例不同，越是顶端的人才，奖励“膨胀”得越明显。如评级由低到高，“M”的激励月数上限增加1.5个月；“M+”下限增加1.5个月，上限增加2.5个月；“E”下限增加3.5个月，上限增加3个月。在2025年绩效周期前，Google对其GRAD（Google Review and Development）体系进行了内部调整。多家媒体援引员工信息称：公司扩大了高绩效评级（如Outstanding Impact）的奖励权重，提高顶级绩效的奖金和股权回报；与此同时，中间档位的激励被有意压缩，以维持整体预算稳定。这意味着，Google并没有“多发钱”，而是重新分配钱。对员工而言，回报不再是线性差距。亚马逊2025年也强化了Forte系统，这是一种绩效管理工具，强调员工证明个人成就。亚马逊要求员工列出3-5个“最大成就”来证明自己的生产力，并将把“领导力原则”正式嵌入评级，形成三层打分机制。这维持了亚马逊的强制排名机制（stack ranking），即经理需按比例分配高低评级。这个做法常导致团队竞争激烈。值得注意的是，亚马逊仍然维持其高度竞争性的分布逻辑。也就是说，高绩效比例有限，低绩效后果明确。这使它成为所有大厂中，对“持续输出”要求最严苛的一家。Microsoft在2024年底至2025年初，对内部绩效与人事规则进行了调整，重点不在奖励“有多高”，而在低绩效的后果更清晰。公开报道显示，微软进一步收紧了对长期低绩效员工的管理工具，包括内部流动限制、绩效改进周期等，同时弱化了一些与核心产出关联度不高的考核要素。这使得绩效评估更直接地服务于业务结果，而非文化或过程指标。把这些大厂的动作放在一起，不难看出共性：把这些改革放在一起看，会发现一个清晰结论：公司不再追求“多数人满意”，而是更明确地把资源集中给少数真正创造关键成果的人。中等表现的回报空间正在被压缩，而顶级贡献者获得的激励差距被显著拉大。这是AI时代下，大厂在激烈的模型与算力竞争中，主动将资源集中到关键产出者身上的现实选择。资源倾斜与“大扁平”同时发生资源更多地向优秀者倾斜，从整体上来讲，自然对组织有益处，尤其是处在激烈竞争之中的时刻，固定顶尖人才至关重要。但事实向来是——在一个组织之中，平凡普通的员工占大多数。即便是“普调”存在，少数人拿到了更多，这样的横向比较也会加重焦虑。仍然以Meta的新绩效体系为例，虽然绩效“优秀”及以上的员工比例占90%，但其中最大头的、占比70%的“优秀”，奖励放大系数为115%，远低于更高等级奖励被放大的系数（200%与300%）。倾斜之下，可能产生的负面影响包括大家越来越容易职业倦怠（burnout），以及员工要面对内部竞争带来巨大焦虑感。而以往通过层层晋升成为“中层”的员工尤为尴尬——他们中的很多人在大厂卷生卷死多年，但在新绩效体系下很容易被明星员工“薪酬/奖励倒挂”。“裁员”也是悬在头上的一把剑。独立裁员追踪网站Layoffs.fyi的数据显示，2025年全球科技公司裁员超过12万人。而裁员的重灾区，恰恰是财务业绩强劲、利润屡创新高、给顶尖人才给钱不手软的科技巨头。如微软全年裁员1.5万人；亚马逊去年10月宣布裁员1.4万人，全年大约裁员3万人。Meta在去年年初，一口气裁员5%“业绩不佳”的员工，约涉及3600人。还有一些裁员发生在业务调整的震荡中，如秋季Meta裁了AI基础设施部门的600人。就在发稿前，当地时间1月13日，Meta计划再裁员Reality Labs的1500人。而在裁员中，中层也是重灾区，Meta和亚马逊都曾公开表示要精简中层。Business Insider将这称之为科技巨头的“大扁平化趋势”。扎克伯格曾公开表示“扁平化组织更快（Flatter is faster）”；亚马逊CEO安迪·贾西（Andy Jassy）在内部沟通中也提出“减少管理层将降低层级并让组织更扁平”；而谷歌CEO桑达尔·皮查伊（Sundar Pichai）则在2024–2025的重组与裁员中将减少10%的副总裁与管理岗位作为提升效率的举措之一。当绩效体系开始明显向顶级贡献者倾斜时，中层管理者手里的资源，往往也会随之变少。这并不是奖金制度调整带来的意外后果，而是公司在重新判断：哪些角色，才值得继续被重点投入。过去，中层往往掌握着不少实际权力——包括项目怎么排、人怎么用、激励怎么分；但当公司越来越强调直接产出和关键结果，这些权力要么被收回到更高层，以减少决策摩擦，要么被直接交到真正承担核心产出的个人手中。关键人才的项目归属、绩效评价和激励路径，开始绕过中层，通过更高层级的机制直接锁定，中层在人员和资源上的调配空间自然被压缩，更多时候承担的是执行协调和结果压力。同时，随着工具和系统越来越成熟，原本依赖中层完成的大量对齐、汇报和协调工作，也在被不断削弱存在感。绩效改革和组织扁平化几乎同步发生。它并不意味着公司在清算某一层级，这更像是一种取舍：公司不再优先维护层级结构，而是把有限的资源，直接押在少数被认为“能拉开差距”的人身上。说到底，这一轮绩效和组织调整，解决的是公司的效率问题，而不是员工的安全感问题。资源被更集中地押在少数人身上，确实可能跑得更快，但也意味着更多人被推到边缘。过去一年里，大厂里发生的变化其实指向同一件事：资源正在被重新分配。对公司来说，这是在AI时代追求效率和确定性的理性选择。但对个体而言，规则已经变了，过去依赖层级、资历和稳定晋升路径所建立的安全感正在减弱。新的体系正在形成，而它是否真的能同时带来效率与可持续性，仍需要时间来验证。","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"-1","news_tag":"executive","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":0,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":1,"commentSize":0,"repostSize":0,"favoriteSize":1,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 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