• 观点
    工作的技术转型——德勒(Deloitte)人力资源服务负责人Michael Gretczko访谈 迈克尔,在过去几年中,您认为企业职场和劳动力在哪些方面发生了重大的改变? 事情正在发生变化,变化的步伐每天都在加快。巨大的外部压力迫使企业改变他们的经营方式。个人作为消费者和员工也具有更大的影响力,组织越来越多地从企业转向我们所谓的社会企业。 社会企业的崛起意味着,对于组织来说,需要更加迫切地去了解更广泛的社会、职场以及迅速变化的员工、零工工人以及其他商业伙伴。 从企业到社会企业的这种转变的关键在于组织问题不再被单一功能理解或解决,它需要每个CXO(交响乐团的首席执行官)强有力的协作和行动——明确有力的方向使得大家团结一致,优化组织绩效。 同时,技术还在不断改变着工作方式,不仅在认知和社会技术方面,而且组织和工作需要以不同的结构来释放这些新进展的潜力。未来的组织必须“永远跟随”,不断适应最新的机遇。 今天商业领袖面临的最大人力资本挑战是什么? 在这个混乱的世界中,商业领袖必须始终专注于在面对新的竞争对手,颠覆性技术以及日益互联和无国界的世界时保持竞争力。当组织在一个日益严峻的环境里挑战时,一个不变的因素是组织的员工对于提升竞争优势的重要性。劳动力是一切组织的支柱,因此他们的参与和忠诚是成功的底线。通过关注影响员工的挑战,企业领导者可以促进持续的绩效。我们相信,每个组织都需要关注5个截然不同且普遍存在的人力资本问题,以帮助人力资源和企业从人力中获取最大价值,去征服未来的世界。这5个关键问题是:转向工作的未来,创造简单不可抗拒的经验,优化人力资本资产负债表,激活数字组织,以及维持组织绩效。 然而,仅仅关注这五个问题是不够的。企业今天面临的混乱局面意味着在孤岛中工作将不再有效(如果有效的话),更紧密的协作至关重要。 HR和商业/职能部门领导者如何更有建设性地合作来应对这些挑战,并将人力资本转化为持续的竞争优势? HR和商业领导者始终需要团结一致,以释放员工的价值。在今天的环境中发生的变化是人力资本的破坏。我们的劳动力和职场正在发生变化,市场上的许多创新从根本上改变了工作的完成方式。HR和企业领导者需要重新构想利用这些中断的工作。HR领导者有责任帮助企业领导者了解和理解外部市场趋势和力量,了解当前的劳动力的构成以及正确的未来构成,然后建立伙伴关系,开发最佳、最合适的品牌来吸引和留住未来可用的员工。所有这些都需要人力资源部门和业务部门协同工作,因此人力资本是未来业务战略的一个组成部分。 企业中怎样保持员工敬业度?为了让“下一代”员工有意义地投入工作,企业/职能部门领导者和人力资源领导者需要培养什么样技能和思维方式? 今天的职场趋势表明,人们在团队中工作得更多,而文化是一个复杂的主题,它是你的队友,经理,办公室和工作场所的许多其它组成部分共同作用的结果。尽管如此,文化仍然从根本上处于领导层。高管应该保持同步,以提供一致的、受支持和有价值的员工敬业文化。员工敬业度不是一个抽查测验,而是组织的一种习惯和独特体验,它需要一个整体的方法才能成功。一个交响乐团首席执行官似的人物比那些隔离的部门更能了解员工的需求和期望。 入职培训突然成为热议话题。它可以提高保留率并改善绩效结果。谁拥有入职培训 - HR或业务/职能部门负责人?您认为今天的企业级雇主在入职策略上有什么典型的失误? 入职培训是企业的一个流程。我们认为HR有责任去推动它,但在此过程中,企业应该充分的责任参与。在推动与同事和领导者的沟通方面,负责人发挥着重要作用,围绕重点和问责制明确优先事项,并确保新员工获得正确支持所需的支持。入职也应从offer被接受的那一刻开始,并持续一年。 在当今竞争激烈的世界中,人才招聘,尤其是经验丰富的招聘人才,对于组织的成功至关重要。但这个过程可能很慢,需要人工操作,而且很耗时,而且往往是在新员工的第一天工作开始。在今天不断沟通的数字世界中,新员工需要从招聘信签署之日起就感觉自己是公司的一部分。这意味着拓展,信息,接触点等,员工应该在正式工作前轻松完成福利登记、笔记本电脑选择和培训等入职工作,并能在舒适的家庭中开始工作,以便他们从在工作的第一天起就可以立即开始增值。行政流程的质量通常可以强烈地向潜在员工表明组织的数字化程度和办事效率,从一开始就做到这一点就会定下正确的基调。这个过程应该简单的,自动化的和热情的,这样新员工可以立即获得组织的积极体验。 根据BambooHR的一项研究,31%的新员工在前六个月内离职。在那些离开的人中,15%的人将其归因于缺乏有效的入职流程。不要因陷入这样的麻烦而失去顶尖人才。数字化入职流程是期望,而不是例外。 新员工入职与现有员工换岗的实际方法有何不同?此外,高级水平与初级水平区别在哪? 我们认为,无论内部或外部流动性如何,无论资历如何,入职培训都应具有相同的属性。入职是一个关键的业务流程,对新员工到退休员工的基本原则是一样的——打造世界级的、极具吸引力的体验。通过简化新职位的入职,员工在第一天就能担任新职位开始工作,最终能提高生产力,同时节省公司时间。我们还认为,从高管和内部入职的典型案例中吸取了一些教训可以帮助改善“新加入者”入职程序,像组织关系构建程序(例如,“与执行团队见面”)和来自管理人员的热情接待,这些活动对新加入者的积极体验具有高度影响力。 HR Tech是当今人力资源领导者的巨大投资领域。对于那些想要投资HR Tech stacks 以帮助团队的人力资源领导者,您有哪些重要的实用技巧? 人力资源技术市场正在经历技术市场中一些最大的混乱。 我们认为领先的人力资源平台的有以下几个特点: 令人信服且直观的用户体验:员工将消费技术体验带入今天的工作场所,并期望他们所使用的人力资源技术具有现代性和直观性,能够适应日益多样化的劳动力的需求。 可操作的见解:许多组织一直在努力有效地利用人员分析,因为他们的人力资源技术平台没有提供可用于推动业务流程优化的信息。 强大的生态系统:人力资源技术平台正在快速发展,并利用了机器学习、聊天机器人和自然语言处理等新兴技术。最可持续的人力资源技术平台已经开发出一种生态系统方法,它不会限制组织从单一解决方案中进行创新。 任何选择技术的过程都应该考虑这些结果,以确保技术能够实现并加速组织内部能力的转变。 虽然技术确实可以促进人力资源职能的规模和转型,但当涉及有效参与企业范围内的业务转型时,人力资源主管应该优先考虑什么? 主要的技术转型计划经常会失败或成功,这取决于组织中的人员是否改变其行为,采用新的工作方式。 对一个组织的任何改变都会对该组织内的人员产生影响,领导者应该努力确保他们的员工感到舒适,知情,受过培训并期待改变。通过优先考虑人员,转型更有可能取得成功,因为变革不会在真空中发生。我们认为,启用员工应该成为任何技术变革的关键焦点,并且应该成为转型开始的重点,在此期间,最重要的是在“上线”之后,当没有获得人员的持续关注,改革就会失败。 随着我们进入下一个十年,哪些新技术对员工体验(EX)的影响最大?您将跟踪该领域的哪些趋势和发展? 员工经验是劳动力技术市场中一些最激动人心的变化的巨大驱动力。企业越来越认识到员工参与的重要性,创建世界一流的员工体验是其核心。我们认为最重要的技术是: 数字化工作场所:新技术正在改变员工之间的互动方式,团队如何沟通和管理他们的工作,以及领导者如何与团队成员进行沟通和互动,支持这些流程的技术正在从消费者技术的根源迅速发展而来,并迅速改变员工在工作中一整天的互动方式。 认知(cognitive)和人工智能:这些技术通过自动化任务和使用数据优化流程来不断改变工作方式。机器开始能够比人类更快地学习并且基于模式不断开发各种能力。这些技术正在改变所需的技能设置,我们相信认真整合认知和人工智能为员工提供“机器人辅助”,实际上将改善员工的工作,将他们的工作重点放在工作中需要独特的人力完成的部分,并取消常规的行政工作。 感知和见解:从数据中开发知识一直是职场技术发展的关注焦点,但这刚刚开始围绕员工体验展开。组织正在使用他们掌握的员工的数据,以及他们如何与他们的领导、企业技术进行互动,来创造个性化的经验,反映员工工作。这也是对消费技术的应用——改造平日感觉像“一对多”的标准化体验,并使其成为以人为本,量身定制的体验。 HRT:感谢您对如何最有效地利用技术促进人力资源增长的深入洞察,迈克尔。我们希望很快再次与您交谈! 原文链接:The Technological Transformation of Work: HR Tech Interview with Michael Gretczko of Deloitte 注:以上内容由AI翻译,观点仅供参考。
    观点
    2018年09月04日
  • 观点
    多元化和包容性是商业战略,而非人力资源规划—D&I Is A Business Strategy, Not An HR Program 文/JOSHBERSIN 译/杨喆 企业的多元化和包容性是一个非常热门的话题,几乎每个客户都就此与我交流过,为何会如此呢?随着‘ ME TOO’运动和‘BLACK LIVES MATTER’事件兴起,以及关于收入不平等、公平性所引发的持久政治讨论,公司开始也对此更为留意。 这些事是刻不容缓的,我们在招聘中严格规定禁止歧视,各州的法律指定了薪酬透明度,另外像FAIRYGODBOSS、VAULT、CAREERBLISS和KUNUNU等网站对其对待女性的态度进行了评估,并且也存在着大量的工具辅助公司,来识别与消除在招聘、绩效评估、薪酬和晋升方面的偏见。 以上都做的非常不错,许多研究表明:多元化的团队以及拥有女性董事会成员的公司表现会更出色,具有包容性的公司也会做出更优的决策。在如今劳动力市场的供不应求的情况下,公司不得不扩大范围,以吸引优秀的人才。 虽然有这样的关注和努力,但问题仍然存在,将其纳入人力资源规划中处理时,成效甚微。我们的研究发现,尽管超过70%的公司认为自己在这一领域处于领先地位,但实际上只有11%的公司意识到问题的严重性。 这有另一种方案:将其认知为商业策略,而非人力资源问题。 施耐德电气的故事 施耐德电气是位列全球最大的电力系统公司之一,近期我与其CHRO奥利维尔•布鲁姆见了面。(该公司上一季度的营收超过67亿美元,在全球拥有逾11万名员工,主要生产能够节约和管理能源的控制系统和开关) 施耐德是一家法国公司,多年来其管理团队都由法国人组成。正如奥利维尔在其领英的文章中所言,该公司的运营是“ONE-HEADQUARTERS(一个总部)”模式,即其领导与决策都由法国人自己参与。 奥利维尔作为企业高管,曾花了多年时间建立公司在中国和印度的业务。他发现这些快速增长的经济体,在文化上都非常的民族主义。中国和印度领导人希望为自己国家的公司工作;他们想要建立和支持自己国家的经济,也希望加入一家能有利于自我提升的公司。 过去几年里,施耐德、通用电气等公司通常会将美国或法国国民派遣到这些岗位。奥利维尔意识到这不再可行,正如我多年前在加拿大丰业银行的工作中所了解到的,建立当地业务的唯一途径是“成为当地经济的一部分”。这也就意味着必须本地化你的品牌、产品,以及人才和领导阶层。 今天的施耐德,如奥利维尔在其文章中所言,“是一种‘MULTI-HUB BUSINESS MODEL(多中心的商业模式)’,在这种模式下,我们希望公司里的每一个人都有同样的机会成功,不管他们来自哪个国家或地区。” 而之前几乎所有的决策和领导都来自法国,但如今公司将越来越多的销售、渠道和产品决策授权给当地业务部门。 这意味着多元化和包容性是施耐德当前的战略核心。该公司不再采用法国为主的领导团队,或任何形式的偏见、歧视或不包容的战略思维。因此,施耐德现在真的是所谓的“社会企业”。 我喜欢这幅漫画——它真的很有说服力。  施耐德电气真正致力于此。也许你可以了解一下施耐德关于多元化的宣言,非常的鼓舞人心。 如今,该公司拥有四个全球领导中心,分别在中国、印度、美国(波士顿)、巴黎。巴黎中心不比其他中心规模更大或更重要,每一个中心都在一套新的决策权下运作,这些决策权赋予了当地人员在本土做出决策的权力,以及对全球战略和商业策划的权力。 施耐德所做的这一切真的有效吗?数字足以说明一切:公司第一季度增长6.2%,亚太业务增长了14%,并且加速了向数字电源管理的转型。如果未将多元化作为战略重点,这些都是不可能实现的。 全球化意味着多元化、包容性和本土化 当我访问世界各地的公司时,我看到了类似但各具特色的进展。例如CHEVRON、 NESTLE、 DELOITTE和IBM等公司都是这么做的,它们在不断的前行中学习更多的东西。 如果你正在竭力于多样性指标的变动,那么问自己一个简单的问题:多元化与包容性只是人力资源规划,还是实际上对你的业务而言,更加至关重要? 当你的公司发展壮大时,你是否准备好授权给女性、少数族裔或当地居民? 你是否准备好让年轻的领导者取代年长的领导者,或者让70多岁的领导者重回工作岗位?(年龄歧视也需要考虑在内) 更为重要的是,你的CEO和其他领导是否明白,如果没有这些人才的话,你的公司将会失去竞争力? 如果你没有得出这样的结论,那你可能还没有理解其重要性。多元化和包容性是最强大的商业工具之一,如果认真去对待它,将会有非常显著的成效。
    观点
    2018年08月31日
  • 观点
    Recruiter 工作方法及状态调查结果 注:以下由AI翻译,观点和图表值得参考学习。传递观点仅供参考。   Recruiter正在慢慢在线寻找新客户 如果您愿意花费大量时间和金钱来完成任务,那么在线拓展业务的机会很大。此图表显示有些人在听。 事实上,35%的招聘人员的新业务来自在线渠道,包括电子邮件,社交媒体,搜索和在线广告。 但是,如果您是专门使用旧学校方法的人之一,如冷呼叫或严重依赖您的网络来创造更多业务,现在是时候分支和发展。 在寻找新客户时Recruiter面临着各种各样的挑战 招聘人员无法就寻找新客户的最困难方面达成一致。无论是来自其他招聘人员的竞争,为决策者寻找联系信息,还是让相同的决策者回复您的初步推广,招聘人员在寻找空缺职位时都会遇到很多挑战。 即使是经验丰富的招聘人员也会遇到障碍。一位有超过10年工作经验的招聘人员指出,他们最大的困难是“当他们看到具有可转移技能的候选人并不明显符合他们的要求时,帮助客户克服他们的决策瘫痪”。另一个人指出了一个类似的问题并评论说,即使通过快速学习可以证明显着的结果,也很难“影响决策者在雇用没有多年行业经验的人时承担计算风险”。 LinkedIn很容易成为最受欢迎的采购选择 当被问及招聘人员如何寻找新候选人时,看到LinkedIn在排名中占主导地位并不足为奇,超过50%的候选人通过免费版本的LinkedIn或LinkedIn Recruiter采购。 然而,请注意社交媒体开始削弱LinkedIn的领先优势。几乎15%的新候选人来自Facebook或Twitter,这是一个令人印象深刻的数字,因为它们都不被称为采购平台。 此外,值得一提的是,在采购工具的写入候选人中,Hiretual绝对主导了竞争(图中未显示)。可能值得查看他们的平台,看看为什么人们如此喜欢它。 在寻找新候选人时,初步接触是一项艰巨的挑战 超过1/3的招聘人员表示,采购的初始阶段是最困难的。寻找潜在候选人的联系信息或让他们回应您的初始请求对于招聘人员来说仍然是一个挑战。一名招聘人员清楚地总结了挑战。“我招聘高技术和专业的角色,这些角色也有很高的需求。挑战在于区分采购策略,使您与招聘人员每天接受的大量联系区分开来。频道有限,我们都使用相同的频道(主要是InMails和冷话/电子邮件)。需要更多战略性的采购平台。“ 对于那些努力解决这个问题的人,请继续关注即将发表的文章,探讨如何从人群中脱颖而出。 联系人查找工具是招聘人员最热门的应用程序 当我们向您询问您每天使用的应用和订阅服务时,您的响应非常明确。联系查找应用程序,如Hiretual,Lusha,Snovio和ContactOut,是常用工具列表的首选。鉴于招聘人员在采购候选人时面临的具体挑战,这应该不足为奇。 然而,尽管它们很受欢迎,但许多招聘人员仍然在努力有效地使用这些工具。多名招聘人员注意到他们对工具的准确率感到沮丧,而其他人则希望能够更好地与现有的ATS或招聘营销平台整合。 招聘人员对新技术的愿望清单是多种多样的 当我们向您询问您希望存在的可以使您的工作更轻松的工具时,您的答案列表很长且多种多样。 有些人希望简单地改进他们现有的软件,要求“实际上按招聘人员的方式工作的ATS”和“具有更好的用户工作流程的ATS”。 其他人则把注意力集中在改善面试和招聘流程上,要求“一种方式来跟踪哪位招聘人员采访了哪位候选人,他们在聘用后在公司内的状态以及他们是否在培训后立即退出”和“统一的筛选平台” ,面试和考试候选人,包括移动访问“。 还有一些人专注于自动化招聘流程,谈论“候选人采购系统,允许输入候选人资料,职位档案和公司简介。然后,该系统利用匹配的人才来源,评估人才优势,人力资源分析,确定“最佳企业”人才,并提供“十大潜在客户名单”以吸引和招募“,”这个工具将需要工作描述并在插入我们使用的各种简历网站之前分解元数据。它将根据每个网站的特定样式创建布尔搜索,并自动生成潜在客户列表,在重复的配置文件中交叉引用最新简历“和”可以告诉我候选人准备就绪的服务(使用评分算法) )考虑新的命题“。 最后,一些想要的工具可以让他们掌握自己的技能,例如“允许招聘人员/来源分享最佳实践的服务,包括组织技能和桌面实践的工作”,以及“一个有凝聚力的线下社区,用于招募学习和发展” 招聘是一项艰巨的工作 调查中最大的收获很简单 - 招聘不适合胆小的人。这项工作需要多样化的技能来管理许多活动部件。虽然有一些方法可以将简化日常任务的流程系统化,但没有办法解决这样一个事实:为了获得报酬,您必须经常说服招聘经理,人力资源专家,企业主和候选人共同努力符合他们的集体最大利益。这是一项说起来容易做起来难的任务。 一位招聘人员说得最好。他说,“作为招聘人员最困难的部分是管理一个招聘周期,在那里你几乎无法控制候选人和招聘经理的决定。你生活在一个充满偶然的世界里,我们坚持着我们可以控制的一小部分事物。“   以上AI翻译,几个观点和图片非常值得学习和查看~ 仅供参考。 文章来源:talentheromedia
    观点
    2018年08月27日
  • 观点
    Workday观点:如何解决企业未来的人才? Taking the Next Steps for Tomorrow's Talent 作者:Leighanne Levensaler,workday高级副总裁,企业战略,工作日兼董事总经理兼Workday Ventures联席主管 文章导读: 我和一群商业和教育领袖,参加了在纽约举行的彭博下一个论坛(Bloomberg Next forum)。这次论坛的主题是:在如此大的变革中,我们如何才能更好地培养和支持我们的员工队伍。 它涵盖了一系列挑战:从如何让毕业生更好地为工作做好准备,到如何在人工智能和自动化时代让在职员工重新掌握技能,再到企业和教育工作者如何更好地合作。 在Workday与彭博资讯(Bloomberg Next)密切合作的原因是积极参与寻找解决这些复杂问题的方法。 我们在纽约进行了富有洞察力和启发性的讨论,以下是一些想法: 首先解决当地的问题 我们的世界面临着与劳动力发展有关的重大挑战。最好从当地开始。 例如, 是否有社区大学或贸易学校提供课程,让工人为预期的技能转变做好准备? 您的组织是否可以扩大与当地高等教育学校的沟通,让学生更好地掌握他们所需要的技能? 随着不断的创新,所需技能也不断变化。在Workday,与社区内的大学合作,让技术专家担任客座讲师,帮助学生为现实世界做准备。  寻找外部人才的新来源  企业说他们找不到需要的人才。但问题是否源于只招具有特定高等教育学位或工作经验的候选人?公司需要考虑他们是否过度要求实行纯种招聘。 在Workday,我们已经取得了巨大的成功,这些人才并没有遵循从高中到大学再到职业生涯的传统道路,但事实证明,它们都是出色的同事。多元化和包容性的员工队伍会让工作场所更快乐,并带来更大的商业成果。 从内部来源 一些最优秀的人才不一定能充分发挥他们的潜能或提供充分发展潜能的机会。这就是为什么真正了解自己的才能至关重要。 具体做法:通过定期使用技术来盘点你的员工和他们的技能,并建立一种流动和机会的文化。 拥抱创新的速度 创新对我们所有人来说都是一件好事,但它给劳动力发展带来了挑战。随着不断的创新,所需技能也要不断变化。 问题是,没有很多的公司愿意在重新培训技能中投入更多资金。在Workday和Bloomberg Next的调查中,半数受访企业预计,在应对新兴技术对劳动力影响的计划时,都面临预算紧张。 只有30%的企业和39%的教育工作者表示,他们正在合作帮助员工重新技能和重新培训。 我们可以在如何共同应对创新的影响方面更具创新性。另一个想法是:如何与教育机构的研究人员合作,帮助定义未来在不同行业中的角色? 我们都需要持续学习。学习如何去了解比去了解更好。 英文原文: By Leighanne Levensaler, Senior Vice President, Corporate Strategy, Workday & Managing Director and Co-Head, Workday Ventures I recently joined a group of business and education leaders for a Bloomberg Next forum in New York that focused on how we can work together to best nurture and support our workforces in the midst of so much change. Aptly named Tomorrow’s Talent, the forum covered a number of timely challenges, ranging from how we can better prepare graduates for the workplace, to how we can reskill current workers in the age of artificial intelligence and automation, to how businesses and educators can better collaborate. Knowing that people are the heart of every enterprise, we at Workday are passionate about being an active participant in finding the solutions to these complex issues. That’s why we partnered closely with Bloomberg Next on the event, including a study that surveyed business and education leaders’ views on these topics and more. Not surprisingly, the findings confirm there’s a lot more work to do. So where do we start? I shared some ideas in a blog prior to the forum. Following our insightful and inspiring discussions in New York, here are some additional ideas. Solve Locally First Our world faces significant challenges related to workforce development. We’d all like a systematic macro answer. The reality is that these problems are far too broad and complex to be addressed with a single universal solution. It’s best to start working locally to learn and gain momentum. For example, are there community colleges or trade schools that offer classes that could prepare workers for an anticipated shift in skill sets? Are there local higher education feeder schools that your organization could broaden the dialogue with on how to better prepare students with both the hard and soft skills they need? With constant innovation comes the constant change of needed skills. At Workday, we’ve partnered with universities in our communities to have our technologists serve as guest lecturers and help students prepare for the real world. I would encourage all organizations to explore these types of opportunities, because as one participant said, “If you’re sitting still, you’re falling behind.” Seek Out New Sources of External Talent Businesses say they can’t find the talent they need. But could the problem stem from always returning to the same pond to fish—a pond that only has candidates with specific types of higher education degrees or job experiences? Companies need to consider whether they are practicing pedigree hiring by over-credentialing job requirements. A willingness to learn “how” is a stronger attribute than a willingness to learn “what,” especially in today’s rapidly changing world. What’s more, pedigree hiring works against an organization’s efforts to create a more diverse and inclusive workforce. At Workday, we’ve had great success partnering with organizations such as Year Up and Opportunity@Work to gain talent that didn’t follow the traditional path from high school to college to career, yet have proved to be incredible colleagues. We know that a diverse and inclusive workforce makes for a happier workplace and results in greater business outcomes. Source from Within Some of our best talent is often right under our noses, but not necessarily in positions that can utilize their full potential or provide the opportunity to grow. That’s why it’s critical to truly know your talent. How do you do that? By regularly using technology to take inventory of your people and their skills across the organization, democratizing learning experiences so that everyone has access to them, and building a culture of mobility and opportunity. This requires being radically transparent in communicating opportunities for career growth. Embrace the Velocity of Innovation Our dear friend, innovation. There’s no stopping it and we don’t want to. Innovation is a great thing for all of us, but it creates challenges in workforce development. With constant innovation comes the constant change of needed skills. The problem is, not enough companies are willing to put more skin in the game when it comes to reskilling. In the Workday and Bloomberg Next survey, half of the corporate respondents anticipate facing budget constraints when deploying a plan to address the impact of emerging technologies on the workforce. So let me ask this: If a company is willing to put time, money, and resources behind responding to innovations that impact its competitive landscape or business model, why wouldn’t it also invest in innovations that impact its workforce? Only 30 percent of corporations and 39 percent of educators say they are collaborating to help reskill and retrain employees. Partnerships with other organizations can help ease the burden. Jon Kaplan, vice president of training and development at Discover Financial Services, discussed how their company is using Guild Education to manage a number of aspects of its recently announced Discover College Commitment program, which provides a full tuition ride for all employees seeking to pursue a university degree online from one of three selected universities. The program got a lot of interest from the forum audience because it’s truly unique. Consider that only 30 percent of corporations and 39 percent of educators say they are collaborating to help reskill and retrain employees, according to the survey. I’m sure we can be more innovative about how we work together to address the impact of innovation. Another idea: What about partnering with researchers at educational institutions to help define the roles of the future within various industries? I’ll end this post with one final thought: We all need to be in the business of continuous learning. Dr. Seuss is a favorite in our household with his endless wisdom and clever turns of phrase. And, as the good doctor says, “It’s better to learn how to know than to know.
    观点
    2018年08月09日
  • 观点
    人力资源和工作流程——生产力系统 HR & the flow of work – Systems of Productivity 文/J Jerry Moses 文章导读: 在TechHR18会议的第2天,德勤(Deloitte)的Bersin创始人乔什•伯辛(Josh Bersin)对新一代招聘、管理、学习、职业和员工体验工具是如何从根本上扰乱市场进行了分析。 他认为:技术与商业问题相一致,技术才有意义。 以下是Josh Bersin在TechHR 18会议上对人力资源技术趋势的一些见解: 技术、自动化、机器人技术都在发挥作用! 生产力是一个问题! 作社会型企业! 持续的性能管理具有巨大的影响——获取工具 大型人力资源技术供应商没有跟上步伐 人才管理需要工具来处理 我们给员工发工资方式将会被打乱 企业学习才是真正的事情! 员工福利市场具有真正的潜力 软件市场正在成长 员工体验进入工作流程 英文原文: On Day 2 of TechHR18, Josh Bersin,Founder of Bersin by Deloitte, presents a research-based analysis of how a new generation of recruiting, management, learning, career, and employee experience tools are radically disrupting the marketplace Micro trends are driving change – changes in the HR technology landscape, the way we work, and particularly, the changes in how organizations are being managed and are managing. The world of HR and HR tech is undergoing a significant shift. HR is now over Cloud, Social and Mobile – this is the time for a new breed of systems - intelligent platform strategies that are making HR and its processes real-time, productive, agile and data-driven. But “Nothing in technology makes sense unless its aligned with the business problems we are trying to solve” as Josh Bersin says. Here are a few insights on HR tech trends from Josh Bersin’s session at TechHR’18. Technology, Automation, Robotics are here and they work! According to Bersin’s research, 45 percent of companies are still focused on basic process automation. The business ecosystem is almost a decade into the economic growth, and has a plethora of generations working together in it. We are living longer, the average career spans 70-75 years, and technology is disrupting where we work along with our daily lives. Most of HCM trends, technology, robotics, AI, automation, is actually becoming real. However, we don’t know what to deal with it all because most companies are still struggling with the challenges of the right skills, structures, organizational design, and rewards systems. Productivity is an issue! Productivity is lagging. The real key for HR going forward is becoming the Chief of Productivity.  If employees use products and tools that the organizations provide to them, employes will feel better, happier, and engaged. And this is the secret of what is going to happen to HR technology – building systems for the HR that make people productive. With agility, team-centric organizations, burnout is becoming an issue while employee engagement and communication tools are overwhelming employees. This is the time for businesses to build HR software that really improves productivity and helps teams work better together? Business as a social enterprise!  CEOs are now being asked to take social positions on topics and act on behalf of communities, stakeholders, shareholders, and employees and customers. The future of business is in becoming a socially conscious enterprise and here, the most important thing would to be to develop a technology strategy that provides purpose, meaning, transparency and fairness. Businesses can no longer afford to buy technology that implements practices that someone else coded. Continuous Performance Management has a huge impact – get the tools Continuous performance management is transformative. It really and truly works! Ratings will not go anywhere but the crucial part will be to build newer and continuous processes for goal setting, coaching, evaluation, and feedback.  This is time for organizations to reconsider performance philosophy. Even with the success of the cloud HCM vendors in the market, a comprehensive solution for performance management is not available. “Team-centric” tools will be the future of HCM market in the future. Big HR Tech vendors are not keeping up Most of the ERP vendors are struggling to keep up with the evolution and changes in the business ecosystem. ERP vendors are not getting good marks for ease of use, integration, or value to the end users or employees. There is a stiff competition in the ERP market and it is becoming crowded. Talent management is done! The whole idea of Talent Management was about pre-hire to retire. But we don’t work like that anymore. Most of us work at many companies during our careers and organizations are also going through change, disruption and reorganization. Managing employees through the entire lifecycle is not really the problem but managing employees in a new management environment that is about teams, empowerment, mission, purpose, clarity and transparency of goals. It’s a totally different management environment and we need tools to deal with that. How we pay people will be disrupted The most disrupted area of HR to come is the way we pay people. Only 1 in 5 companies believes that their rewards system is actually aligned with their corporate strategy. We are still paying people the way we did in the past — salary bands, annul reviews, policies of secrecy and who is getting paid what – all this will be disrupted and we will have a whole new set of tools for employee experience. Corporate Learning is the real deal! Platforms like Degreed and Edcast are transforming corporate learning — experience platforms, micro-learning platforms, modernized LMS systems, AI-based systems to recommend learning, find learning, and deliver learning, and Virtual Reality-based learning are giving employees and organizations all the things they need. Employee wellbeing market has the true potential It’s all about the moments that matter. There is a need to improve productivity but there is a significant impetus on employee wellbeing, reducing the cognitive overload and augmenting human performance.  This vendor market is moving fast. The new world of work will be about “engagement, productivity, and wellbeing” all in one. ONA software market is now growing With the explosion of HRMS data, wellbeing data, networking data, among many other forms of structured and unstructured data, HR is struggling to deal issues of ethics, privacy, and becoming more transparent about the analytics they are doing. The Organizational Network Analytics is growing and so is a new world of “relationship analytics”. People Analytics will guarantee success. Getting into the Flow of Work Employee experience is the buzzword and we are trying to reform it in a way that applies and improves the work experience of every individual in an organization. Organizations define employee experience as a project of looking at the moments that matter, transitions, periods of time in career where one is stressed and what can HR do to make that easier. But none of the tools are designed to measure or map something like this. All tools are designed for the HR function, not this. There is a new category of software being built to help HR with the employee experience - to shield employees from the complexities of the backend HR systems and deliver all the different things the HR does in the flow of work.
    观点
    2018年08月07日
  • 观点
    有关智能自动化将如何改变人力资源功能的见解Insights On How Intelligent Automation Will Change The HR Function 文/ Darren Burton 文章导读: 麦肯锡全球研究所(McKinsey Global Institute)最近的一项研究发现,60%的职业至少有30%的构成工作可以实现自动化,而全球3%至14%的劳动力将需要转换职业类别。 智能自动化将以各种方式直接影响人力资源——从它在组织中需要扮演的角色,提供的服务,到与人力资源相关的工作实际完成的方式。 影响: 更深入地研究如何使员工的表现最佳化。 自动化可以消除重复性的任务,解放员工工作日的部分工作。这引发了一系列潜在的问题: 员工应该如何利用剩余的时间? 组织如何向员工提供处理不同任务所需的技能? 员工的表现是否应该有不同的评价? 当基础任务现在由智能系统处理时,员工如何“学习基础知识”? 根据IA技能计划未来。 搞清楚开发、培训和维护智能自动化系统所需的技能,然后借用这些技能的最佳方式,在市场上做出区别。智能自动化技术还将有助于建立一种价值主张,能够吸引合适的人才,以满足公司当前和未来的需求。 让领导做好管理转型的准备。  领导除了平衡市场和短期预期的交付,他们还需要为个人和职业转型的团队成员提供指导。设定现实的期望,让人们参与变革过程,帮助个人适应数字化和人力劳动的世界。 英语原文: As a business executive and HR leader, it’s hard to keep track of all the predictions associated with the future of intelligent automation. For example, a recent study by the McKinsey Global Institute identified that 60 percent of occupations have at least 30 percent of constituent work activities that could be automated, and that three to fourteen percent of the global workforce will need to switch occupational categories. These studies make a series of assumptions regarding the types of jobs that will be automated, the pace at which automation will occur, and the various governmental policies that will help or hinder the adoption of these types of technologies. In today’s market, intelligent automation skills are at a premium.ISTOCK Regardless of exact magnitude of the change, it’s pretty clear that intelligent automation is going to directly impact HR in a variety of ways—from the role it needs to play within an organization, to the services it needs to provide, to the way HR-related work actually gets accomplished. Within KPMG, as we continue to work with clients in this space and look to transform our own internal HR capability, it is safe to say that HR will play a central role in helping the organization do a few key things: Dig deeper into how to best enable employee performance. As much of our early experience has demonstrated, automation can eliminate repetitive tasks and potentially free up a portion of a worker’s overall day. This, of course, raises a whole range of potential questions: What should employees do with the remainder of their time? How do we provide them with the skills needed to handle different tasks? Should their performance be assessed differently? How do they “learn the basics” when basic-level tasks are now handled by an intelligent system? These are precisely the types of questions that the HR professional of the future must be able to help business leaders answer so that they can design jobs and shift roles to make the most of employees’ skills and capabilities. Plan for a future dependent on IA skills. In today’s market, intelligent automation skills are at a premium. As one New York Times article joked, “Salaries are spiraling so fast that some joke the tech industry needs a National Football League-style salary cap on A.I. specialists.” Figuring out the skills that are needed to develop, train, and maintain intelligent automation systems and then determining the best way to either build, buy, or borrow those skills can make the difference between spending too much or too little in this marketplace. It will also help in building a value proposition that can attract the right talent to meet a company’s current and future needs. Prepare leaders to manage the transformation. The opportunities offered by intelligent automation are equaled by the potential magnitude of change executives will face as they come to terms with significant shifts in their industries and business models. In addition to balancing marketplace shifts with delivery on short-term expectations, they will need to provide guidance to team members who may be going through their own personal and professional transformations. The need to set realistic expectations, involve people in the change process, and help individuals adjust to a world of digital and human labor will test the capabilities of even seasoned change leaders. Interested in learning more about people challenges associated with intelligent automation? KPMG partners Mark Spears, Robert Bolton, and David Brown have authored two important perspectives, “Rise of the Humans” and “Rise of the Humans 2,” that provide useful insights into the topic.
    观点
    2018年08月07日
  • 观点
    e成科技首席科学家陈鸿博士:面试机器人的未来是星辰大海 为大家带来一份科技感十足的干货——e成科技首席科学家陈鸿博士在7月27日2018招聘科技论坛上的演讲,深度解析招聘领域时下最热门的AI面试机器人背后的“黑科技”原理。 在上周五HR Tech China主办的2018招聘科技论坛上,e成科技首席科学家陈鸿博士亮相带着e成科技的“黑科技”招聘产品Chatbot面试机器人亮相,并发表了题为“机器人的识人之明——e成在面试机器人场景的探索”的演讲,为在座来宾科普了e成Chatbot面试机器人的科技内核和工作原理, 惊艳四座,反响热烈。 以下内容根据陈鸿博士2018招聘科技论坛现场演讲整理: 各位嘉宾大家好,我在e成科技负责数据和算法。今天我跟大家分享的是聊天机器人可能要在面试中开始使用了。第一,我们会讲一下面试机器人为什么不仅仅是一个聊天机器人,面试是一个很特殊的场景。第二,是我们的技术内核,就是知识图谱,这个聊天机器人不是一无所知的,需要有很多的知识才能面对挑战。第三,我会讲一些会话和分析的事情,这个直接决定了面试过程能否流畅,像人一样自主的展开。接下来是神经网络的一些技术细节,我会尽量用一些比较生动的例子让大家理解这个网络是如何可靠的。最后展望一下面试机器人后续会怎么样。 1、面试机器人不仅仅又是一个聊天机器人事实上,我们说到HR的工作可能有很多的理论模型,三支柱模型,钻石模型这些,但是HR的工作离不开两点,一个是做关于人的决策,一个是要做关于人的沟通。AI在赋能HR的时候,其实在这两点上都有贡献。首先,我们可以通过AI让关于人的决策变的更加明智,其次,AI可以让沟通工作变的更加高效,面试机器人就是AI让沟通变的更加高效的第一步。 说到面试,它和普通的聊天不一样,这里列出了一些区别,大家其实平时用微软小冰或者苹果的SIRI都用的挺多了,但是面试跟这个有挺大区别,人聊天是很放松的事情,但是去参加面试很紧张,因为面试官在主导这个对话,面试官是一个会话角色,意味着在面试过程中,面试机器人首先要主导这个对话,然后经过多轮的对话才能最终完成,最终还要给候选人一个评价,这和普通的聊天不一样,聊天完了以后那是消费者给你客服一个评价,面试完了以后是由面试机器人给候选人一个评价,过滤出合适的候选人进入下一个轮次,这个是很不一样的。 2、基于人才知识图谱的动态会话决策 你要想让面试机器人能够正常工作,它会和一般聊天不同的是,它要基于一个人才知识图谱,区别于普通的聊天机器人公司,市场上有很多的伙伴在研发这些技术,我们的区别是什么呢?他们更像是让一个人类的宝宝从小到大,越长越大以后,对话越来越流利,但是我们e成做一个面试机器人, 就像一个外国专家要开始学用汉语说话,专家肚子里面有很多的知识,但之前不会说中国话,现在要学习怎么说出来。 在每一个面试场景面试官都需要具备很多的知识, 因此需要让这个机器人面试官具有这些领域知识,不能一无所知去做这个工作。当面试机器人底层有了知识图谱的知识支撑就不同了,首先,机器人面试官可以基于知识图谱定制对话的目标,其次,知识图谱还能让面试机器人做出动态会话决策,最后,知识图谱构成会话进行的算法机制的一部分。 我们来分开看一下,我们都知道面试在正常情况下是一轮一轮进行的,每一轮面试都有自己独特的目标,技术面的时候,评估候选人的技术水平,直属领导在面试的时候,他是来评估这个人是否适合这个岗位的,如果是CIT面试只考核你的沟通能力和软性素质,如果是HRD或者老板最后终面,那就是评估候选人的价值观和动机,对于面试机器人来讲需要在不同的场景下定制自己的目标,这是一个比较高的要求,因为面试场景变化很大,在不同行业、不同公司,面试不同职能的人,考核候选人的点是不一样的,你需要为各种各样的岗位确定这个目标,也就是面试机器人需要一个设置面试评估目标优先级的灵活方案。 这个优先级是指什么呢?就是人有很多不同的属性,里面也会列出自己的需求,但这个里面不是所有的东西都是眉毛胡子一把抓,你如果没有优先级的话,对话发展起来就会一片混乱,优先级的设置挺重要的。 3、面试场景的会话结构分析 下一页是讲在图谱的知识下,可以让这个机器人来灵活规划会话的流程,现在的多轮会话机器人,如果在座有做这个技术的应该了解,业界现状一般是用Pipeline来设置这个过程,每个对话节点设置自己的条件,在符合条件的时候让这个对话进入下一个节点,多轮对话所有的节点就构成一个Pipeline的框架,但这个轮次非常多,因为要问很多的问题。整体框架也会因此非常难以维护。 所以我们是让机器人面试官基于知识图谱动态推演出整个面试的会话流程。举一个例子,现在机器人面试官的面试目标是要招一个工程师, 它就要确认这个工程师的技术水平是否适合来进行研发,候选人介绍说,“我当时在组里设计开发Chatbot的语义理解、实体识别、多轮对话等核心算法。”那么机器人的知识图谱里有语义理解,实体识别,多轮对话的相关知识,知道这些都是开发Chatbot的相关技能,那么机器人就可以抓住其中一个点,把这个对话深入展开下去,比如说,机器人可以抓住“多轮对话”接着问: 能具体介绍一下你采用的多轮对话策略吗? 这样整个过程就比较流畅,像人的面试,依赖预定义逻辑是无法做到的。 把知识图谱作为一个底层的知识以后,这些实体都已经嵌入了一个语义空间,被向量化了,使得我们可以得到整个对话在进入机器学习模型的时候能够给这些文本编码为合理的向量,否则依然停留在词语和关健词的级别,那么你依靠字符匹配做对话机器人就必然会陷入困境,大家可能玩SIRI的时候经常体验到这一点,你用一句话跟Siri沟通,它好像还可以,换一个词就不懂了,因为它硬编码了那几个词或某个句型,它是记住了那个词,但没有映射到其他的近义词或等价表述上。而当我们要让机器人真正掌握一个概念和语义的时候,就意味着它把这个概念和语义向量化了,这样AI才可以自如的对会话中的意义进行计算。 现在来说一下会话结构分析,你要想让聊天机器人或者说面试机器人说的更加接近于人,他需要对会话过程有理解,我们说面试是一场比较严肃的会话,这个会话是有一些规矩的,我们说一下里面有什么东西,这里是一些要点,话轮,邻接对和链接结构等等。 话轮是一个很基础的概念, 大家在说话的时候一般不会说一句话就结束了,你会需要连续说好几句,才能把你想说的话说完,这是一个话轮。因此句子不是会话的最小单位,话轮才是。这个话轮会转换,话轮有让步和夺取的操作, 比如有时候你想抢话过来说,对方还在说的时候,你会抢过来,这是话轮夺取。这个取决于说话的双方谁更有支配,或者说两人的上下位关系。他是你的领导,他抢话你肯定让他接着说。现在在面试的时候,机器人是处于地位比较高的那一方,他是可以主动来夺取话轮的,这也是非常必要的,如果机器人还像在做客服机器人一样,傻傻听人类候选人一直在滔滔不绝,但人类候选人很可能已经偏离了主题,这个时候机器人面试官需要主动把话轮夺取过来,打断对方告诉他你现在说的已经和我问的问题没有关系了,这个话轮的夺取变成了比较关键的事情。 在话轮切换的时候会产生相邻对的概念,就是属于两个不同说话人的相邻接的话轮,相邻对有不同的类型,例如:【问候-问候】类型,正常两个人见面互相问候,我说你吃过了吗?对方说,吃过了,你吃过了吗? 或者【提问-回答】类型,就是常见的一问一答。还有【陈述-反应】的类型,你说天气很热,他反应我们去凉快地方呆着吧,还有【邀请-接受/拒绝】类型,邀请了以后可以接受也可以拒绝,上面这些相邻对的不同类型体现了不同的对话意图,通过对这些相邻对类型的分析,机器人就可以理解当前这个会话的意图是什么,意图有什么意义呢?其实会让会话变的自然很多。我这里举一个例子,同样给正反馈,但如果有不同的意图,就会有完全不同的对话。 比如说你意图是表示在倾听,那你可能就会说“嗯”,“嗯嗯”,这是你在微信里面表示「我在听,你继续说」,这是不打断话轮的,如果你意图是表示理解,你说“知道”,“明白了“,这是一个肯定,它有一个概率会夺过话轮,有时候你表示认同,你说“是的”,这时候对于话轮转换是中立的, 有时候你比较关注这个话题,你会部分重复对方的话,说明我对这个话题也感兴趣,这个时候你表示自己的支持立场,但是夺取话轮继续往下说。同样是表达正面的肯定立场,但是结合不同意图以后会有完全不一样的表达。 我们在说话的时候,有时候感觉对方和我能够说的很流畅,有的时候这个人怎么都不接我的话茬,这个话茬就是邻接对之间存在的链接结构,我现在上面举了两个例子。 一个是面试官在那里说,你那份工作的动力是什么?他说我不服输,我有条件不应该输给别人。动力这个词把上面和下面连起来, 他问你动力是什么的时候,你回答了这么一句话,然后说这就是动力,有时候词语会发生变化,但是不要紧,通过这个意义的交点,把前后的相邻对连接在一起,使得这个主考官确认这个人是在回答我的问题,也是我们面试机器人能够了解候选人跟着我的话茬在走。通过这个链接的关系能够确认对话的焦点还在不在我的控制内。 另一个例子是说你离开那个工作的时候留恋吗?他说不留恋,留恋就把这个对话给链接起来了,这个链接结构的机制使得机器人可以使整个对话变的更加合理。比如说他可以在候选人长篇大论的时候打断,也可以主动把自己的话跟对方的话连接起来,使得候选人更容易理解这个主考官在问什么。 4、增强学习和模仿学习的混合方案 我现在到了比较困难的部分,我要强行给大家科普一下神经网络,这是增强学习和模仿学习,我应该会用比较通俗的比方尽量讲的清楚一点。先是看一下整体的结构: 底层是一个图谱,图谱层里面有人才画像、岗位画像和评估目标,这些画像都落实成为一个个知识图谱,人才画像就是关于这个候选人是什么样子的各种属性连接起来的一个图,岗位是什么也是一个知识图谱,以及不同的面试其实有不同的评估目标,这个评估目标也体现为一个小的图谱,图谱层上面是会话层,我们刚刚提到的话轮分析、意图分析,就是通过对相邻对的评估去分析它的意图,还有链接分析,让这个对话变的更加流畅,最终我们实现的时候,到了网络层。我们往下看网络层的具体结构。 这张图展示了一个对话处理的流程,候选人先问,“您对我的职业经历有什么评价?”他会经过一个话语的Encoder, 注意上面有一个圈,这是上一轮的系统对话行为编码(图里标着K-1轮),这个编码里包括一个意图和对话的焦点,让系统知道对方是响应什么来说出这句话的,然后网络把当前对话状态输出到历史对话的跟踪队列,这是整个历史对话的记录,右边是知识图谱,经过知识图谱的检索以后产生了一个确认的结果,这些一起进入会话策略网络,产生了第K轮的对话行为,包括新的对话意图和焦点,会由一个自然语言生成器负责产生具体的句子,然后面试官会说好的,等等。 我们对这个网络的训练采用了增强学习和模仿学习的混合方法,我先要科普一下什么是增强学习和模仿学习,大家可能有不少人听说过什么叫有监督学习,在这个场景下我们没有采用,为什么呢?因为有监督学习的样本标注工作量在做面试机器人的时候实在是太大了,我现在举一个例子,如果以学习驾驶为例,大家去驾校,我可以发给你一本手册,手册上面在所有路况的情况下你需要做出的反应,你见到马路是这样的,左边什么车、右边什么车,然后你要踩油门,什么情况你要换档,试想一下枚举了各种可能情况后你需要的手册有多少页?这是一个惊人的天文数字,因为你要罗列所有可能的组合。 我们人类是怎么样做的呢?我们会去驾校,驾校的教练首先会让你看他开,他用实际操作来告诉你,你应该怎么开车,然后教练会让你自己开,他在边上,他来告诉你这么做不对,你要怎么做,看教练开和教练看你开,这分别对应着模仿学习和增强学习,你在看一个人怎么做你去模仿的话,其实可以快速得到很多正面的例子,你如果自己操作由其他人或者环境给你一个反馈,这称之为增强学习,谷歌的AlphaGo就是通过增强学习来得到这么好的效果。但是增强学习也没法完全包办所有的事情,因为他对正样本的覆盖太稀疏了,你没有办法让这个人在开的时候覆盖所有的情况,有一个教练在边上告诉你也很难覆盖各种可能性。 比较正常的做法是你先看着教练开,模仿他,他再看着你,在关键时候点拨一下。我们采取了类似的策略,我们先让这个机器通过少量的样本预训练一下,然后模仿人类的教学,再收集人类的反馈增强学习,相当于你去驾校,需要先背一点基本的驾驶规则,交规手册,但那个是很少的,没有办法覆盖所有的开车情况,教练接着就会让你去模仿他,最后你快出师了,教练坐在你的边上给你一些关键的指点,这就是我们这个神经网络的学习方式。 5、面试机器人的未来 最后简单说一下面试机器人的未来,刚刚分享了我们的工作就到这里为止,但这对于面试机器人来讲只是一个开始, 它的未来还非常广大,我们正在做能够处理开放式问题的面试机器人,刚刚说到的那些都是封闭式问题, 问题的答案是一个有明确边界的有限集合。但开放式问题不一样,它对应的答案没有边际。但也没法办法回避去处理开放式问题。你在问一个人软性能力的时候,你会希望他跟你分享一些故事的时候,都是你没办法去约束他的对话和边界,这些开放性的问题需要能够让机器人处理。 我们先不说怎么让机器人理解一个故事,怎么让一个机器人知道一个故事说完了,他可以接着往下说,这件事情就很有挑战性,我们在听别人说一个故事的时候是能判断一个故事已经说完了,但怎么让机器人去判断故事说完了就是个问题。这个话题非常有意思,我希望在下次分享的时候可以跟大家分享这个方面的进展, e成会始终致力于人力资源行业的技术发展,谢谢大家!
    观点
    2018年08月06日
  • 观点
    Tony观点精彩分享:“每个企业在不同的成长阶段都会跳入不同的游泳池玩一玩。” 文章导读 分享人:原顺丰、大众点评HRVP-Tony 分享主题:CEO的人才观 精彩观点呈现:企业分为黑海,蓝海,红海三种类型。黑海是未知的世界,黑海的人需要不断摸索,找到方向,才能进入蓝海。蓝海企业用户体验处于领先地位,需要把握技术、人才、市场,筑造高壁垒,保持领先地位,这样才更加容易进入红海。进入红海,竞争激烈,追求比别人做的更加优秀,才能立于不败之地。 嘉宾演讲: 首先感谢大会主办方! 我今天分享的主题跟前面的有点不一样,前面谈到了机器人招聘,所以大家觉得做人力资源的工作,将来会受到AI的冲击。但其实如果今天大家的视野拔高到一个更高的层次,不要把自己定位在一个公司的人才获取专家或者一个招聘的总监,或者一个公司的人力资源总监,而是把你自己的视角放到CEO的视角。不管是在传统的跨国企业、中国大型国有企业、中国的民营企业,以华为、海尔、联想为代表,还是在新兴的经济当中发展起来的一些企业,比如说第一波的腾讯、百度、阿里,以及刚刚在美国上市的拼多多,还包括接下来要在香港IPO的这些公司。你去看这些CEO的身上,只有将视角放在对人的关注上,才能帮公司招到更好的人。 今天早上很多嘉宾讲的是帮公司找到更好的招聘人的工具。找人有各种手段,用大数据等。然而,到最后招人也还是最是有风险的。比如说,你一辈子跟一个人在一起也会有风险,找到一个老婆、找一个先生,哪怕是你自己的孩子,有可能将来也无法和睦共处。所以人这件事情没有办法完全的科学化,因为人本身就是一件艺术品。 我上次在美商会演讲,我全部用中文讲的。演讲主标题是CEO的人才观,我还用了一个副标题,副标题我用了黑、红和蓝。大家可以猜这代表什么,你们可能听说过红海和蓝海的表述,但从来没有听说过什么叫做黑海,以及黑海里面人才的战略是怎么样的? 我曾在很多不同的公司任职,其中包括大众点评,去年上市的顺丰,IBM、可口可乐,万达等全世界前几百强的公司。我接触过王健林,大众点评的张韬。回到黑海的话题,黑是什么?一片迷茫,不知道方向,充满恐惧感和挑战,但冲出黑暗就不一样了。这个黑海里面是怎么样的?这个黑海世界是怎么样的?——未知的,什么对你来说都是未知的。应用到商业领域,你看什么样的公司是在黑海的世界里面玩的,什么样的公司? 在黑海世界玩的企业通常有以下特点: 第一,在公司整个业务发展的前进道路上,你一定会看到很多的威胁和障碍,这也是一定的。 第二,也许公司创始人本人还未找到方向。他只是觉得这件事值得去做,还有一颗这样的初心,所以很多创业公司说不忘初心。 第三,他们内心有焦虑感。请问在座的如果你是跟随一家创业公司的老大,每天没日没夜的去招人,考虑产品的逻辑,画用户的肖像图、产品的线路图等等,但一次次尝试都失败了,就会产生焦虑,对不对? 在这种情形下,作为一家公司,你要知道公司创始人或者CEO最想做的事情是什么?他的终极目标就是不管怎么样,尽快获取哪怕是最小的胜利,一次小战争的胜利,而这个胜利哪怕要花很大的代价,他至少看到了曙光。为什么呢?曙光的力量。在黑海中一旦有那么一小促的火苗被发现,他至少知道有亮光,追过去,接下来才会有越来越多的光明。 所以黑海这种类型企业的CEO,一定是希望他的团队能够在最短的时间给他带来哪怕一点点的小胜利,否则大家一直沮丧下去,人的信心会受到打压。这个时候我们需要怎么样的人?在这种团队里面,就是在黑海里面,我们的人才战略应该是怎么样的?我也写了5点应对的方法。 第一,你所需要的人要有耐受力、忍耐力,人的耐力很重要。大家看过少年派的奇幻漂流,他就是非常有耐力的。一个人在海里面没日没夜的漂流,漆黑一片,没有耐力,人会精神崩溃的,也就不会有这部优秀的作品与大家见面。另举一例,为什么把一个犯人关到小黑屋?因为对犯人最大的惩罚不是让他暴晒,而是关在小黑屋。你跟一群犯人关在一起不会怎么样,因为人有互动。所以忍耐力要放在第一位。这个时候需要的人才都是要有坚韧不拔的定力。 第二,企业家精神。企业家精神不是每个人都有的。从中国历史来看,中国近代的商界里面确实有很多具有企业家精神的人,这些人耳熟能详。最近在香港上市的小米,我觉得企业里都是有企业家精神的人,至于他做的优秀不优秀,我们不讨论,但至少今天这些人走出来了黑海,就是说他不服输、执着、专一、不放弃,同时他考虑的大战略也得到了落实。一个真正优秀的企业家,在给投资人做路演的时候,他可以在路演上演讲。当你关起门来跟研发团队做产品的时候,他也可以滔滔不绝,一起去PK和讨论,这叫做企业家精神,这绝对不是这个人表面讲了多少励志的东西,而是自己肯脚踏实地去做。我的大学同学张韬,我觉得他是非常有企业家精神的人,他毕业于美国沃顿,生病辍学去了美国,当时一心要去,到了美国他觉得,我与其在中国做一个电脑顾问,还不如来中国自己创业。 第三,跟毅力有点像,要有反弹力。意思就是说你有没有反弹的机会,哪怕你今天被这个浪打下去了,你还可以再爬起来,把帆布的漏洞补好,不让船沉下去。有的人一巴掌打下去再也不能创业了,有的人创业是屡战屡败,这种人是有反弹力的。我相信你们最近也看到了很多的报道,新北大的王津就是非常有反弹力的,股票今天涨十几块,明天跌二十几块公司的CEO,这个人就是超人,就是钢铁侠的人。 前面三个都是在讲内在的品质。 第四,通常对于一家创业公司来说,条条框框的边界和规则如果太早去设定这家公司一定走不远,你要放开手脚去拼,因为这个时代是不会等你。如果当时滴滴,快滴创业初期,先讲我们的游戏规则怎么样,没办法拼。中国是一个丛林法则的国家,谁先进来谁就可以赢,但是美国不一样。中国有很多的互联网模式是模式的创新不是技术的创新,现在有很多的年轻人开始走技术创新的这一条路,比如区块链等等,包括滴滴也是的。美国硅谷大多数企业,基本上是科技为先,不管是做人工智能还是做大数据也好,且都与生活息息相关。 最后一点,他不希望招太多的庸人,他只要招一到两个或者两到三个最顶尖的人,跟他一起去“打仗”,而这些人必须要跟他有同样的气质。不管今天在座的是猎头还是公司的HR,还是公司任命你做HR的工作,如果你去帮一家企业的创始人、创始团队去选人,我觉得你应该去选这样的人。 能够在黑海里的人,永远是有热情的,还有非常饱满的热情,永恒的热情,如果没有这个热情,那就是等死,就是随波逐流。 进入到红海,虽然竞争激烈,但大家都具备一定的竞争力。玩家有很大的市场,但还是残酷的。这个领域里面的公司已经有了一套设定的游戏规则,玩家都知道这个行业应该要怎么样玩。 其次,在所有的商业战场上,从产品研发到最后的出产等等,线上线下每个地方都在角力、都在拼。之前在几大视频网站拼,最后就合并了。比如,美国的优步到中国来开拓市场,最后中国把美国的优步给合并了。美国的人很有意思,一旦你加入某个行业,你在这个行业玩的话,美国就觉得我不要跟你一起玩了,我就去玩别的行业了。中国人,你玩我也玩,所以中国的街都是一条街。美国人是你们都不要玩,你到我这里来玩,我会把你们都给合并了,然后你们再到我的平台上来玩。你会发觉很有意思。中国有足够大的民生市场,就是老百姓可以玩的,因为我们有议价能力。一旦有一家独大的时候,我们的议价能力反而没有了。所以现在是我们的红利,现在的红利不在美国。 再往下看,他们也会思考WIN-WIN,就是这些大佬合并了,比如优酷和土豆的合并,太多的案例了,但是双赢毕竟是少数。很多企业是直接吞并,或者直接让你崩盘,所以在红海里面玩的人是很强悍的。在黑海里面玩的人也不是人,都是神。 在一个竞争非常激烈的市场,不同于传统行业,现在的行业比拼的是你快速获取客户的能力,以及你的运营和迭代能力,你的获客能力也是资本。不管怎样,任何一家公司最终都会需要所谓的人工成本、运营成本等等。在红海里面能够胜出的人一定是希望最后可以跟别人做的不一样,但这个一定不是创新,有创新的一定是迭代。当初我们都在做团购的时候,那个时候拼的很厉害,但是一旦有人做的一点点不一样就可以把别人都比下去。 要比别人做的更好,在红海里面只有永远追求比别人做的更加优秀。在红海里面的人才战略是: 你一定要成为在行业里面能够找到最优秀的,每个专家领域里面最顶尖的高手,这个需要非常具有经验。因为红海这个行业已经是一个沉淀的行业。 还有就是你要更加强调超前执行力。当大家在“打仗”的时候,但凡有一支军队执行力出问题了,他就会被你打败。所以你的规则一定要写的非常完整,因为“打仗”你的员工是很累的,所以你对这些员工的激励方式要及时。黑海不一样,可以长远一点。 最后一点,你除了招人,对于红海里面的玩家更多是要保留人才,因为在红海里面是“打仗”,打仗的时候还有时间浪费吗? 在蓝海里面也有这些特点。 第一,一家企业在蓝海里面玩儿他并不传统,蓝海的企业所面临机会不像黑海什么都不知道在摸索,蓝海是知道这个机会已经被认可,可以去做。比如说健康医疗,用人工智能的方法去做所谓的医疗健康,高科技,将来的医生不一定是真正的人,一定是人机结合的。现在已经在做了,人造皮肤已经在硅谷出现,研发的科学家是一个华人女性,这个皮肤是可以呼吸的,烧伤的人将来不需要自己再移植一块皮肤上去,可以给你人造的。 第二,蓝海的人一定要创造价值,他们所有的驱动点来自于为这个社会和人类创造价值。创新力在这样的企业是要达到一定高度的,这是重要的核心点。对在蓝海里面的企业来说,用户体验已经跑在前面了,他不怕,所以他需要我们员工更加的呵护,不管我2B还是2C,或者是2B和2B。 第三,任何一家蓝海公司必须要有差异。对于蓝海的企业来说,他越早建立壁垒越好。企业已经够领先了,机会也存在了,现在就看你能不能把握技术、人才、市场,把你的壁垒筑的高一点,使得你的追兵不多,这样才更加容易进入红海。 所以怎么做呢?在蓝海里面我们的人才战略是: 领导者一定要果断决策,市场不等你。 第二,他要充满能量和热情,这是可以感染到他的团队,或者说你招聘的人要充满正能量和热情,可以感染周围的人。 第三,有一些非常垂直领域的人才、专家。术业有专攻,不只是一点情怀,有企业家风范就可以玩儿了。因为需要这些人筑壁垒,并且把自己的壁垒建高。 横向需要贯穿到整个公司管理各个岗位的一些复合型人才,因为这些人去帮你做融资、谈判、合作伙伴、做平台等等。 最后,这样的企业一定是可以给弃权、给激励。最后跟雷军可以一起玩到小米上市,OK!小米就是这么成长起来的。如果没有雷军在上面,下面的人不会追随。小米今天不一定是在蓝海,有些领域在蓝海,有些领域早就已经在红海了,也许也可以尝试黑海。每个企业在不同的成长阶段都会跳入不同的游泳池去玩一玩。 所以当蓝海中的企业最终能够实现他们的抱负,这些梦想都会实现了。所以最后一句话送给大家,就是继续游泳,不要被淹死,活着就不错了。谢谢大家! 以上内容节选自727招聘科技嘉宾发言,未经嘉宾本人审阅,仅供参考!
    观点
    2018年08月02日
  • 观点
    如何为人力分析专业人士创造职业道路-How to create career paths for people analytics professionals(续) 文/David Green 文章导读 往期回顾: Geetanjali在2017年9月在费城举行的人力分析与未来工作会议上发言要点回顾: MERCK&CO.的人力分析团队 这个团队由三支柱组成:咨询、高级分析、报告和数据可视化 创建一个数据驱动的文化:高层领导的支持对于人员分析功能的成功至关重要 在人力分析中创造职业道路:一个能够提供发展和职业发展的组织和领导者,可以成为吸引和留住人才的关键因素。 三“C”模式:Capability-Capacity-Connectivity 今日导读: 领导人员分析团队 问7、在谈到你作为一个人分析领导者的角色时,你会对这个角色的新手或者将来想成为一个人分析负责人的人提出什么建议呢? 分享五个我认为普遍适用的特性,并且对于成为这个领域的有效领导者很重要。 优先考虑:对于人员分析领导者来说,学习如何无情地优先考虑团队将花费时间和精力的项目是至关重要的。 位置: 一个好的领导者知道如何找到合适的机会去重新定位、结合和展示这项工作。这不仅对获得声望和对人员分析的认可很重要,而且对提升团队的士气也很重要。 连接: 当你建立起新的职业联系时,你也开始建立友谊,这是一个支持网络,可以帮助你在这个相当模糊的、新的人力分析空间中导航。 与时俱进:作为一个优秀的人员分析领导者,重要的一点是要跟上外部变化的步伐,并将这种学习带回您的业务中 发展:一个有效的领导者需要投入时间和精力来建立自己的内部和外部网络,并与他们的团队分享他们的进 问8、我观察到的一个挑战是,作为一个人分析的领导者,你必须平衡在内部构建能力的重大挑战,同时关注在外部快速发展的领域。作为一名分析人士的领导者,你如何平衡这两个优先事项,以及你如何了解公司外部发生的事情? 尽可能多地阅读各种不同的出版物(博客、文章、白皮书、书籍),这些内容让我与人力分析的各个方面:从社会科学到人工智能都保持联系。 此外,与来自不同行业的其他从业者建立联系很有帮助,我通过非正式的和正式的对等网络进行联系。 最后,我试着每年参加一些活动来学习新的东西和认识新的人。   人力分析的未来 问9、你认为人力分析的主要趋势是什么? 我认为人力分析中的一些“热点领域”将在未来继续变得“更热”。 我还认为,随着研究的增长和越来越多的组织对这一领域的投资,网络的力量将得到充分的挖掘和释放。 最后,要实现所有这些类型的分析,最重要的领域之一将是关于数据使用、隐私和人员分析领域的安全性的伦理研究。   问10、我们如何平衡我们能做什么以及我们应该做什么? 谈谈你对道德和隐私等方面的关注。 过度反应或倾向于采用过于保守的方法,这可能会妨碍人员分析领域的一些重要工作。 话虽如此,与适当的实践专家密切合作,就业法律、隐私法律、伦理、通信、业务合作,和工人委员会合作是一个很好的方式,以确保除了工作的合法性。 另一种从道德角度是预先与内部客户分享你分析的可能结果,并向他们清楚地说明在每个场景中他们将采取什么行动。 在人力分析领域工作类型需要把伦理放在最重要的日程上 英文原文: LEADING THE PEOPLE ANALYTICS TEAM 7. Turning towards your role as a People Analytics Leader, what would your advice be to someone who is new to this role or who aspires to be a Head of People Analytics in the future? I think everyone has different strengths and experiences, which means their approach will vary with regards to them proving successful as a people analytics leader. But based on my personal experiences and observations of others, I can share five attributes that I think apply universally and are important to being an effective leader in this space. Prioritise: Whether you have a small or large people analytics team, it will never be big enough to meet all the demands of your clients, particularly as awareness of the team’s capabilities grow. So, it is critical for the people analytics leader to learn (and teach!) how to relentlessly prioritise the projects on which the team will spend its time and effort. A good rule of thumb is to think about the magnitude of business impact that an analysis has the potential to deliver, or a key relationship that it can help build in the business for future collaborations and sponsorship. Many teams even use formal prioritisation grids to help the process, but ultimately the leader needs to ensure that the criteria used to allocate resources to projects aligns with the vision and mission of the people analytics team (which in turn, should align with the objectives of the enterprise). It is critical for the people analytics leader to learn (and teach!) how to relentlessly prioritise the projects on which the team will spend its time and effort. Position: A critical skill for a people analytics leader is the ability to effectively position analyses before the right decision-makers at the right time to maximise positive outcomes and build a strong people analytics brand. This is probably one of, if not the most, important part of being a people analytics leader. On many occasions, brilliant workforce analyses have been underutilised in their original scope, but a good leader knows how to find the right opportunities to repurpose, combine and present this work. This is not only important in gaining prestige and recognition for people analytics, but also for boosting the morale of the team. Connect:  There is a small, but growing, community of people analytics leaders globally who collectively have a spectacular amount of experience and knowledge. Fortunately, this community is inclusive and generous, in terms of sharing their knowledge and connections with others in the field. The group is a great resource to learn about new technologies, techniques, vendors, and also receive tips and tricks that can help a new leader to avoid mistakes and grab the right opportunities. Most importantly, as you build new professional connections you also begin building friendships that are a support network to help you navigate this fairly ambiguous, new(ish) space of people analytics. Evolve: Since a people analytics leader needs to have some depth in analytical methods, it is always a good idea to read, listen and learn. Thanks to social media there are amazing resources available, many of them free, that any analytics leader can and should leverage to keep oneself updated and evolving. There are some extremely prolific writers (like David Green!) who share both original and curated content on various forums including LinkedIn. Whether you are looking for detailed tutorials on advanced data science methods or want to learn about the latest technological breakthrough and its application to people data, there is a publication, podcast, or video out there on it. Another reason why this mind set of curiosity and awareness is important is because the people analytics space is sensitive primarily due to ethics and privacy reasons; and keeping a handle on that also demands a leader who keeps their eyes and ears open. An important part of being a strong people analytics leader is to keep up with the pace of change externally and bring that learning back to your business. An important part of being a strong people analytics leader is to keep up with the pace of change externally and bring that learning back to your business Develop:  Last, but certainly not the least, a critical part of being a good people analytics leader is simply being a good leader. This implies being someone who invests in the development of their team. It is of particular importance because it is a space that has attracted a lot of exceptional talent, but still has somewhat limited opportunities for advancement. Therefore, an effective leader needs to invest time and effort in building their own internal and external network; and share it with their teams for their advancement. They should also be committed to actively finding or creating opportunities for their team members to learn new skills and develop themselves as multi-faceted professionals. An effective leader needs to invest time and effort in building their own internal and external network; and share it with their teams for their advancement 8. One of the challenges I’ve observed in being a people analytics leader is that you have to balance the significant challenge of building capability internally whilst keeping an eye externally on what is a fast-developing field. As a people analytics leader, how do you juggle these two priorities, and how do you keep abreast of what is happening outside the organisation?  I strive to practice the same behaviours that I would advise new people analytics leaders to try. For example, I follow and subscribe to content by certain thought leaders in people analytics and read as many varied publications as possible (blogs, articles, whitepapers, books) which keep me connected to the different aspects of people analytics; from social science to artificial intelligence. In addition, it really helps to connect with other practitioners in the field from different industries, which I do via both informal and formal peer networks. This helps to broaden one’s worldview, spark new ideas, and offers a forum to ask questions of your peers. Most likely, if you are facing a people analytics quandary, there is a leader out there who has faced it too and would be willing to share their experience. Finally, there are a plethora of great conference events out there, and the quality and number of these keeps rising every year. I try to participate in at least a few such events every year to learn new things and meet new people. THE FUTURE OF PEOPLE ANALYTICS 9. What do you believe will be the main trends moving forward in people analytics?  I think that a number of “hot areas” in people analytics will continue to get “hotter” in the future. The idea of employee experience will grow even wider with focus on the end-to-end experience all the way from being a prospective candidate stage to becoming an alumni of the company. This is likely to grow simultaneously with the focus on managing and optimising a new, fluid workforce that may at any one time be full-time and freelance, human and robotic. I also think that the power of networks will be fully explored and unleashed as research grows and more organisations invest in this space. The applications of network analysis are so varied and relevant, that it should continue to gather steam in the future. Finally, from my perspective to enable all these types of analyses, one of the most critical areas that will grow in importance will be the study of ethics relating to data use, privacy and security in the space of people analytics. 10. Finally, how do we balance what we can do with what we should do? How concerned are you about areas such as ethics and privacy? This is a great question, and a difficult one to answer. The frontiers of what is possible are being pushed at a break-neck speed thanks to ever larger datasets being at our disposal faster, and at cheaper cost. And that pace makes it tough to process the implications in real time. In fact, this often leads to an overreaction or the inclination to adopt an overly conservative approach that can hamper some great work in the people analytics space. That being said, I believe that an extremely important fact to understand about the space we work in is that we should not do something just because it is possible. Besides being legally compliant, the type of work being undertaken in this field needs to put ethics at the very top of the agenda even before beginning work on an analysis. Working closely with the appropriate experts in the practices of employment law, privacy law, ethics, communications, business partners and workers councils is a good way to ensure that besides the legality of the work, its potential impact on people is also being considered through the lens of ethics, privacy, and empathy.  Most established organisations have extensive reviews involving these types of stakeholders already in place. Another way to pressure test the approach from an ethics lens is to share possible outcomes of an analysis with the internal clients beforehand and ask them to articulate what actions they would take in each scenario. Obviously, this method is not possible in every situation, but when applicable it can be a useful “stop and reflect” moment. The type of work being undertaken in the people analytics field needs to put ethics at the very top of the agenda
    观点
    2018年07月31日
  • 观点
    如何为人力分析专业人士创造职业道路-How to create career paths for people analytics professionals 文/David Green 文章导读 根据德勤于2017年11月发布的“高影响力人力分析研究”(High-Impact People Analytics study), 69%的大型机构(10,000多名员工)现在拥有一个“人力分析团队”。 Geetanjali Gamel在旧金山举行的“人民分析与未来工作会议”(People Analytics & Future of Work Conference)上的演讲这个话题。Geetanjali是默克公司劳动力分析的全球领导者。在2017年9月在费城举行的人民分析与未来工作会议上发言。 为什么要人力分析? 问1、你好,Geetanjali,请解释一下吸引你到人力分析领域的原因。 我工作中最有趣的部分是理解、测量和预测人类行为及其对销售和收入等业务结果的影响。因此,我很自然地被这个机会所吸引,这个机会将科学的方法引入到人们的数据中,并帮助塑造一个组织如何为其投资者带来价值,同时为其员工带来更丰富的经验。 MERCK & CO.的人力分析团队 问2、请您描述一下默克公司的劳动力分析团队的规模和结构,以及它是如何与业务联系起来的。 默克的劳动力分析团队(WFA)拥有15名成员,在全球80多个市场,69000名员工。 这个团队由三个主要支柱组成:咨询、高级分析、报告和数据可视化。 咨询——每个咨询师都与我们的业务部门(如制造、研究、销售等)保持一致。他们与领导者紧密合作,以理解和预见棘手的业务问题,并运用正确的方法解决问题,将分析转化为可操作的观点。 高级分析——高级分析团队是一群灵活的数据科学家和专业人士,他们主要专注于需要高级技术技能或很有意义的项目。它们围绕业务问题进行组织。 报告和数据可视化——他们直接与来自业务各个部门的内部客户合作,以确保合适的人在合适的时间拥有合适的数据。驱动了内部客户满意度。 三个WFA团队紧密合作,以确保识别和利用业务活动之间的协同作用。 创建一个数据驱动的文化 问3、德勤(Deloitte)的“高影响力人物分析”(High-Impact People Analytics)研究发现,在创造高级能力方面,最重要的因素是需要创建数据驱动的文化。你在默克公司是如何做到这一点的? 我们首先在人力资源社区中推广数据,推出了一个基于云的劳动力分析平台。我们还开发和部署了一个能力构建程序,其中的模块主要集中在度量选择、假设测试、数据可视化、推荐开发等方面。 此外,我们一直在利用的另一个渠道,加速人力资源数据驱动文化,是让我们更广泛的人力资源社区的成员成为分析“冠军”。 最后,我们还建立了一个人力资源领导团队,在人力资源中传达建筑数据和分析能力的信息。 高层领导的支持对于人员分析功能的成功至关重要 在人力分析中创造职业道路 问4、您对为人力分析专业人员创建职业发展道路充满热情。 为什么你认为这是如此重要? 我热衷于为那些使人力分析成为可能的人们建立更好的工作体验! 我发现这个团队能够为职业道路,继任计划和大型员工的人才流动等领域做出决策,但经常陷入无处可扩展的境地。 此外,大多数人分析团队都是人力资源部门的一员,而且往往被贴上高度专业化的“人力资源精英”卓越中心(CoE)的标签,这限制了横向或向上进入CoEs或业务部门的其他人力资源角色的机会。 最后,一个能够提供发展和职业发展的组织和领导者,可以成为吸引和留住优秀人才的关键因素。 如果我们能让更多人力分析人才流动起来,就会为人力资源和企业的其他部门增加技能、方法和拓宽视角,为企业创造额外的价值。  一个能够提供发展和职业发展的组织和领导者,可以成为吸引和留住优秀人才的关键因素 问5、关于人才分析团队的职业发展,你在默克制定了什么计划?关于人才分析团队的职业发展,你在默克制定了什么计划? 从我在默克公司工作的第一天起,我的首要任务之一就是了解我的团队的力量和抱负,并将他们的发展与他们的职业目标结合起来。我得出了一个Capability-Capacity-Connectivity模型,为我们的人员分析团队提供一个可持续发展项目。这种模式成功的一个关键驱动力是你的领导的支持和与其他团队的合作。 问6、职业发展计划的主要好处和收获是什么? “3C”方法是围绕解决障碍和为人学分析团队创建促进职业发展的桥梁而构建的。 第一个“C”:能力,能力必须在两个级别上处理。 能力级别1:构建数据、技术和分析精明的客户 能力级别2:提升人员分析团队 第二个“C”:Capacity容纳度 如果没有时间远离日常的活动,就不可能专注于一个人职业生涯的下一步 第三个“C”:连接 将人员分析团队与其他人力资源,数据科学,技术和业务专业人员联系起来,建立对双方不同类型工作的认识和相互欣赏。 英文原文: According to Bersin by Deloitte’s High-Impact People Analytics study, which was published in November 2017, 69% of large organisations (10,000+ employees) now have a people analytics team. It is a surprise then that many organisations overlook the need to develop the careers of their people analytics team. Given the pace of evolution of the field and the high-demand for talent in the space, this is an oversight that needs correction. As such, it was refreshing that the main focus of Geetanjali Gamel’s presentation earlier this year at the People Analytics & Future of Work Conference in San Francisco (see key learnings here) was on this very topic. Geetanjali is the global leader of workforce analytics at Merck & Co., Inc. (NYSE: MRK, known as MSD outside the United States and Canada). I caught up with Geetanjali recently to ask how she has created career development paths for her team as well as discuss other related topics in the people analytics field. Geetanjali Gamel speaking at the People Analytics & Future of Work Conference in Philadelphia in September 2017 WHY PEOPLE ANALYTICS? 1. Hi Geetanjali, please can you introduce yourself, describe your background and explain what attracted you to the people analytics space. Like many of my colleagues in people analytics, I’ve had a non-linear path to my current role. I am a trained economist and began my career in research at the Federal Reserve Bank of St. Louis studying topics like macroeconomic forecasting, unemployment and inflation.  With this foundation in social science methodology and research, I soon transitioned to business forecasting, predictive analysis and scenario-planning to drive customer growth and revenue projections in corporate planning and finance departments in the energy sector. The most intriguing part of my work was in understanding, measuring and predicting human behaviour and its impact on business outcomes such as sales and revenue. So, I was naturally attracted by the opportunity to bring scientific methodology to people data and help shape how an organisation can drive value for its investors along with enhanced experience for its employees. I began by building a predictive analytics function from scratch in HR in my previous role at Mastercard and since 2016 I have led the advanced workforce analytics, consulting and reporting organisation in Merck HR. THE PEOPLE ANALYTICS TEAM AT MERCK & CO. 2. Please can you describe the size and structure of the workforce analytics team at Merck and how it aligns to the business Merck’s workforce analytics team (WFA) has 15 members who support 69,000 employees in over 80 markets worldwide through a rich portfolio of people analytics products. The team consists of three primary pillars; Consulting, Advanced Analytics, and Reporting & Data Visualisation (see Figure 1 below). Figure 1: The Workforce Analytics team at Merck & Co (Source: Geetanjali Gamel) Consulting - Each consultant is aligned to one of our business divisions like manufacturing, research, sales, etc. They work closely with leaders to understand and anticipate burning business questions, utilise the right methodology to find the answers; and convert the analyses into actionable insights. Advanced Analytics - The advanced analytics team is a nimble group of data scientists and specialised professionals who focus mainly on ad hoc projects requiring advanced technical skills and/or initiatives of enterprise level significance. They are organised around business questions and may support several divisions at a time, in contrast to the end-to-end approach that the consultants take with each initiative. Reporting & Data Visualisation – This team forms the backbone of all the amazing work we are able to do, as well as the internal customer satisfaction we drive. They work directly with internal clients from all parts of the business to ensure that the right people have the right data at the right time. The three WFA teams work closely with each other to ensure that any synergies between business initiatives are identified and leveraged. CREATING A DATA-DRIVEN CULTURE 3. The recent Bersin by Deloitte High-Impact People Analytics study found that the single biggest predictor in creating advanced capability is the need to create a data-driven culture. How have you achieved this at Merck particularly with regards to HR Business Partners and the wider HR function? I agree that culture can be the strongest catalyst or impediment for people analytics. It is also ridiculously difficult to identify and alter, particularly because organisations at any given time tend to be collections of sub-cultures. But there are some patterns of behaviours, decision-making, and incentive-rewards, which distinguish data driven cultures from others. These behaviours can be purposefully incubated through a combination of upskilling, training and mind-set building. At Merck, we believe that a leading HR function is one where analytics capability is not only for the analytics team, but the whole HR team. This does not imply that every role requires equal depth in analytics, but a new baseline of data interpretation and communication skills is critical to being effective partners to the business. To this end, we started out by democratising data within our HR community by rolling out a cloud based workforce analytics platform. This is helping us drive greater familiarity and reliance on data among our HR users. We have also developed and deployed a capability-building program with modules focused on metric selection, hypothesis testing, data visualisation, recommendation development, and more. Another channel that we have been leveraging to accelerate a data driven culture in HR has been to engage members of our wider HR community as analytics “Champions”. These superheroes are critical to spreading the adoption of data informed insights, since they live and breathe the daily challenges of their colleagues; and can share relatable examples with their counterparts on how data can unlock value. Finally, we also have an HR leadership team that is aligned and strong advocates in relaying the message of building data and analytics capability in HR. Needless to say, sponsorship of senior leaders is imperative to the success of a people analytics function. Sponsorship of senior leaders is imperative to the success of a people analytics function CREATING CAREER PATHS IN PEOPLE ANALYTICS 4. You are passionate on the need to create career paths for people analytics professionals. Why do you believe this is so important? I firmly believe that the goal of people analytics is to drive value for the business as well as provide a better experience of work for employees. So naturally, I am equally passionate about building a better work experience for the people who make people analytics possible! I find a sad irony in the fact that the team which enables decision-making on areas like career pathing, succession planning, and talent movement for the larger workforce, is often stuck in a position of having nowhere to grow. From my discussions with many colleagues in this field, I have learned that the typical people analytics team usually tends to have a group of individual contributors (analysts, data scientists, consultants) and a director or senior director level leader. This leaves only one spot for the entire team to aspire to, at least for upward movement. In addition, most people analytics teams sit within HR and tend to be branded as a highly-specialised “HR-lite” centre of excellence (CoE), which limits the opportunities to move laterally or upward into other HR roles in CoEs or business units. And this reality of being “boxed-in” can be very frustrating for bright, highly-employable individuals. If you are a leader in people analytics, and if you have had to recently recruit new talent for your team, I would guess you are acutely aware of the gaping chasm between talent demand and supply in this field. In my opinion, an organisation and a leader who can offer development and career growth can be a key differentiator in attracting and retaining the best people analytics talent. Broadening that vision, if we enabled more fluid movement of people analytics talent, it would add to the diversity of skills, approaches and perspectives to other parts of HR and the business, and would create additional value for the enterprise. An organisation and a leader who can offer development and career growth can be a key differentiator in attracting and retaining the best people analytics talent 5. What program have you put into place at Merck regarding the career development of the people analytics team? From the first day of my role at Merck, one of my top priorities was to understand the strengths and aspirations of my team and align their development to meet their career goals. After multiple discussions and numerous iterations on ideas, I arrived at a Capability-Capacity-Connectivity model to power a sustainable development program for our people analytics team. The underlying idea is that if we can build the right capability within the analytics team and its clients; reallocate capacity that is being consumed by suboptimal tasks; and drive connectivity between people analytics teams and other parts of the business; then we can potentially discover and create new career paths and opportunities. But please bear in mind that a key driver of success for such a model is sponsorship from your leaders and partnership with other teams. In our case, we were fortunate to have both. This has empowered us to be inventive and co-create development opportunities for our team.   6. Please can you provide more detail on what comprises each of the Capability, Capacity and Connectivity elements of this approach. What have been the key benefits and learnings from the career development program?  The “3C” approach is built around tackling barriers and creating bridges that promote career development for people analytics teams. At the outset we knew that the team was faced with a high volume of requests needing significant manual effort. (see Figure 2 below): Figure 2: Challenges in accelerating maturity in people analytics (Source: Geetanjali Gamel) Since the day-to-day work was time and effort intensive, there was not much room to hone more sophisticated skills or build knowledge sharing relationships with others, leaving the people analytics team stuck in a loop. So, we put careful thought and purpose into adopting the following model. Capability The first “C”, or capability, had to be addressed at two levels. The first was to empower our broader HR team with the right tools and training to have greater autonomy to perform analyses. We moved to an intuitive analytics platform and organised workshops, office hours, and learning sessions to improve data literacy among our internal HR clients. This type of effort is important to free-up time for the people analytics team to build their own skillset (and path to growth), while also creating a greater awareness in other parts of HR about analytics. Figure 3: Capability - Level 1: building data, technology and analytics savvy clients (Source: Geetanjali Gamel) The second area of capability building had a more direct impact on the team. We held a team strategy session where we identified areas that needed focus for internal functional, technical and strategic competency building. These focus areas were carefully selected to create dual impact – provide us with a skill or knowledge we could use immediately in our work; and more importantly, help us practice a new behaviour that would develop us as well-rounded professionals. For example, on the technical side, we organised an in-house R-training curriculum, created and delivered by some of our own colleagues to the rest of the team. This helped us build a technical skill we could immediately put to use to do better work, and also built coaching and confidence skills for those who led the program. Another great example was of an external guest speaker series that we launched, which brought recognition to the team for bringing new insights to the company, and also helped the team gain experience in organising an event successfully end-to-end. Figure 4: Capability - Level 2: Upskilling the people analytics team (Source: Geetanjali Gamel) Capacity At first, capacity building measures may not sound like a natural fit with developing career paths. But it is impossible to focus on the next steps in one’s career if there is no time to step away from the daily barrage of activity to have a conversation; listen to a webinar; learn about a new project; or simply, chat with colleagues over lunch. As such creating capacity for the team is critical to allow them to develop their skillset to be more widely applicable, as well as to build the networks they need to find new opportunities. As mentioned before, our journey began with democratising data and providing a range of workforce metrics and even results of our enterprise voice survey in accessible cloud platforms to our HR community. We continue to supplement our efforts to empower our internal clients, and in the process unlock capacity for our team, by forming global communities of practice for analytics. Another effort to scale our analytics delivery and save precious time has been by finding opportunities to utilise process automation on repeatable tasks. It is impossible to focus on the next steps in one’s career if there is no time to step away from the daily barrage of activity Connectivity Despite efforts in building capability and reallocating capacity, there can’t be much career development if there is nowhere to go! This is when the third “C” of connectivity comes into play. In fact, it could just as easily be C for creativity, because we need a great deal of innovative thinking and risk taking to create opportunities where they don’t always exist. We started with small yet effective steps rather than trying to construct huge, formal programs. Connecting the people analytics team with other HR, data science, technology, and business professionals builds an awareness and appreciation for different types of work on both sides. We leveraged opportunities to co-create part-time assignments with other teams, participate in cross functional events, invite guest speakers to team meetings, and collaborate on projects to expose the team to other areas of analytical work. Connecting the people analytics team with other HR, data science, technology, and business professionals builds an awareness and appreciation for different types of work on both sides To create development assignments for the people analytics team we were creative and went with “quasi-experiments”. The first was an opportunity for a team member to take on the role of an HR business partner on a part-time basis for a few, smaller client groups. This gave the individual an opportunity to apply their analytical skillset to the role and get much greater exposure than before to business clients and business issues. Such an experiment has a multiplier effect. Where typically a business partner track is not easily available to a people analytics professional, creating such an opportunity internally can open up a new career path. Moreover, even if the individual does not end up pursuing this new career direction at the end of the experiment, it is still a valuable learning experience for them to be in the shoes of their internal client, i.e., the HR business partner. Finally, it may help to lay the foundation for what I like to call the HRBP 3.0 model. Where the original HRBP role had a heavy component of operational (and even transactional) work, the HRBP 2.0 model that many companies follow today aims at strategic business partners who enable key business decisions. The HRBP 3.0 model takes it a step further by envisioning an analytical HR business partner, who relies on both data driven insight and business acumen to support their client. Another “experiment” in creating new career opportunities was a mini-assignment we created for one of our people analytics team members to lead a large, remote team in the service delivery space. This was a completely different line of work from people analytics, and was heavily focused on operational and organisational skills like identifying and escalating issues on short deadlines, supplier relationship management, building relationships with a variety of HR and non HR stakeholders, and leading a service centre team to drive customer satisfaction. Clearly, this would not be a typical career path for a people analytics professional, but that is exactly why we need to be bold and creative with such experiments. This assignment not only exposed the individual to a different type and pace of work, but also gave them an opportunity to bring their analytical skills to the table to significantly elevate the usage and interpretation of transactional data. While many mature organisations have good-sized people analytics teams, there are still many where the teams are pretty lean. This model may work well for most purposes, but it usually limits the opportunities for team-members to have people management experience. This is not always necessary for upward mobility, but it many cases it is difficult to move upward without some kind of experience of leading a team. Keeping this in mind, we built more depth in our people analytics team, creating enterprise advanced people analytics and data visualisation and reporting sub-teams within the larger group, which are led by two of our team members. Taking a chance on subject matter experts and giving them the opportunity to lead and delegate not only helps to open up doors for them, it also gives them a chance to coach others on their team to be future experts and leaders. Lastly, we also created a new learning analytics role on our people analytics team which is a step toward building greater synergies between people analytics and learning practices, but also our small contribution in creating a new capability (and career path!) that is still evolving in many organisations.
    观点
    2018年07月30日