招聘自动化后，Sourcing工作将是人类的价值体现！--Sourcing Is the New Recruiting文/Mike Wolford
我有个好消息要告诉你。Sourcing是今天人才招聘的好方法!传统上人们所熟知的招聘正在消失。越来越多的公司采用招聘过程自动化，这意味着即使对人才的需求增加，对传统全生命周期招聘的需求也会减少。面试和评估技术的改进将使公司能够自动完成大部分招聘人员目前所做的工作。
聊天机器人不仅能提高求职者的经验，还能提高进入我们各自的求职者跟踪系统的人数。自动面试将及时取代招聘人员筛选面试。自动评估和调度助理将从那里接管这一过程。这一变化将极大地减少填表时间，因为自动系统全天是可用的，原则上，候选人可以在几个小时内从应用程序转到安排面试。
对招聘人员来说，好消息是，只有最优秀的候选人才能以一种完全自动化的方式通过筛选过程。那些被认为65%匹配程度的候选人仍然需要人工审查。然而，即使在这些情况下，候选人和招聘人员之间也不太可能需要广泛的沟通。相反，招聘人员可能会检查一份文件，查看考试成绩，然后做出判断。2020年及以后的招聘人员将很少真正与应聘者交谈。
我能听到你在考虑我，迈克是一个源程序，而不是一个招聘人员，这对我来说意味着什么? 它意味着一些事情。首先，我们要做的是改变。在更高的层次上，源程序今天所做的是四个主要的活动。我们的工作是在面试过程中识别，参与，鉴定和提交候选人，否则他们将无法自行申请。
到2020年，源程序将主要集中在两项活动上。识别和参与。一旦招聘过程被自动化，就不需要招聘方来筛选候选人。面试过程将筛选候选人，而源程序不会向招聘人员或招聘经理提交候选人，他们会直接将候选人引入管道，开始评估，最有可能的方式是参加某种形式的视频面试。今年早些时候，在拉斯维加斯的SourceCon网站上，格伦·卡西(Glen Cathey)说得既准确又有预言性，“sourcing101是销售101。”
未来的源程序人员需要成为优秀的销售人员，因为他们的主要工作将是识别高潜力人才，并邀请他们进入自动招聘流程。对我们来说，在程序方面，特别是在IT程序方面，市场的声音将会更大。这意味着，参与将变得更具挑战性和关键。2020年的目标不仅是成为一个有说服力的、坚持不懈的销售人员，而且是一个出色的营销人员。采购和招聘营销将融合成一种新的、强有力的组合。
人们很容易忽视人工智能对其他行业的影响，但忽视人工智能正在改变市场营销的方式，以及这种改变将如何影响整个招聘，是不明智的。例如，Facebook最近之所以成为新闻，是因为它们对我们这个时代的政治产生了一定的影响。不管你的政治观点如何，这对我们大家都是一个教训。有针对性的社交媒体和聊天机器人在广告和参与方面的应用是强大而有效的。既然人工智能正在被应用于市场营销，那么人才收购进入这种广告渠道只是时间问题。有智慧的人会看到后职和祈祷正在被目标和参与所取代。
有时很难看到森林中的树木，但我记得我从经济学中学到了这一课。20世纪的定义是大规模生产。21世纪将由大规模定制所定义。这一说法对源程序有一定的影响。
一些公司已经意识到这一点，并采取了复杂的营销活动，但这只是一个例外，而不是规则。原因有很多，但我在这里想告诉你的是，一旦实际的申请和面试过程基本上是自动化的，公司将有时间和资源来集中精力把目标申请者填满职位空缺。作为一个销售人员，这意味着你不仅需要学习如何销售，还需要理解如何像营销人员一样思考。
作为一个源程序，我相信这对你来说意味着什么。今天，我们确认、参与、资格和提交。我们与招聘伙伴密切合作，有时还会与招聘经理合作。在未来，源程序将首先确定潜在人才的目标市场。从那时起，参与就变成了一种双管齐下的方式。
作为长期战略的一部分，招聘营销人员将负责建立品牌并将EVP销售到目标市场。他们将为目标市场提供令人兴奋和引人入胜的内容，而源程序将与这些目标市场中的特定个人进行接触，并邀请他们应用于特定的角色。当前的招聘人员/源程序伙伴关系将会及时被招聘市场/源程序的关系所取代。
我们源程序的底线是。我们的工作正在发生变化，但在所有与人才获取有关的专业人士中，我们的工作最有可能出现显著增长。
我给你的建议是完善你的布尔值，并挑选一些关于销售和数字营销的书籍。如果今天你是招聘人员,我的建议是训练你的采购技能或开始思考另一条线的工作,因为在过程自动化变成了标准的50% +全生命周期的工作正在消失,“招聘”将在很大程度上成为另一个人力资源管理功能。
以上内容由AI翻译，仅供参考
原文链接：https://www.sourcecon.com/sourcing-is-the-new-recruiting/
Future of Work
2018年07月19日
Future of Work
你能让你的老板把芯片放在你身上吗？-少数员工同意皮下植入但这个想法正在蔓延
Dave Coplin试图向我解释为什么两大洲的人们突然允许他们的雇主将微芯片放在他们的皮肤下。
“我这样对待我的狗 - 我为什么不自己做呢？”科普林说。我不相信，所以他发起了关于地中海派伊维萨岛上一个俱乐部的轶事，人们可以在那里筹码，然后用芯片买饮料。科普林怀疑这是因为他们没有穿很多衣服。
但是，因为你是半裸的而且没有钱包的口袋，所以要让你的雇主给你筹码是非常不同的。那么，我们是怎么来到这里的？
担任Envisioners咨询公司负责人的科普林表示，如果我们只能克服自己的娇气，那么雇主和员工都会受益匪浅。“如果它增加价值，我就是全力以赴，”他说。“今天我们看看人们这样做，感觉有点奇怪，但实际上有一些不可避免的事情。”
Patrick McMullan是威斯康星州三广场市场的总裁。在斯德哥尔摩的瑞典孵化器Epicenter进行实验后，该公司自2015年以来一直在试验切片，他的公司决定进一步开发该技术。当然，作为供应商和开发商，McMullan自己也有一个芯片植入物 - 一个大致相当于拇指和食指之间植入皮肤下的一粒米的大小。它基于近场通信（NFC）技术 - 与非接触式信用卡或移动支付中使用的芯片相同。使用注射器和非常少的血液快速简单地完成植入。
McMullan说，目前的一个限制是，由于芯片是无源器件，因此无法对其进行跟踪。就目前而言，这意味着该芯片用于访问建筑物，登录计算机以及从食堂支付费用。但麦克马伦的员工正在执行“改变世界”的使命，他说，到目前为止，已有70多名员工自愿参与实验。
“我这样对待我的狗 - 我为什么不自己做呢？”
这个想法似乎正在蔓延。除了三坊市场外，至少有160人参加了Epicenter的月度“ 筹码派对”。辛辛那提监控公司CityWatcher.com的一些员工已经获得了芯片，一些人在数字营销公司工作。在比利时称为NewFusion。毫无疑问，这是一个很好的宣传，但削弱倡导者真正相信这将成为未来十年的普遍做法。
McMullan认为，随着技术的进步，芯片将提供更多的好处。“我们正在开发能够监测生命体征的医疗用途。医生将能够主动治疗患者，而不是总是做出反应，“他说。McMullan认为，全球削减员工的数量将在几年内达到数百万，因为低于100美元的芯片的好处可能是巨大的。
自然进步？
McMullan认为没有任何不利因素，尽管人们明显担心，以难以控制或消除的方式与雇主建立密切联系感觉完全是反乌托邦。采用他自己的芯片监控人们健康的想法：未来的嵌入式技术有明显的优势，可以监测胆固醇，血糖水平，甚至只是脱水。
但是，如果某人有一块芯片监测酒精摄入量，作为退出协议的一部分呢？外科医生会被允许拒绝接受手术吗？如果保险公司从车上掉下来，可以提高患者的保费吗？随着芯片变得更先进和更广泛，可以或应该收集哪些信息以及它可能或应该去哪里的问题将变得更加复杂。其他专家也提出了对黑客行为的担忧，以及已知与宠物类似芯片相关的已知健康问题。
“显然，隐私是一个巨大的问题，”科普林补充说。“人们将如何处理这些数据？谁会去看？实际上，我必须携带手机和我的钱包，这已经够糟了。如果这解决了其中一些问题，那我就是为了它。“
尽管存在这些担忧，但很多人似乎都接受了这种情况 - 并且很快就会发生。Lynda Shaw博士，认知神经科学家，Your Brain Is Boss的作者，认为切片是一种自然进展，可能更容易为年轻人所接受。
“If you think of young men, when they’re teenagers, we often think of them as driving too fast, hotheaded,” Shaw explains. “In evolutionary psychology, that’s vital to have in society. In the old days, if a village’s crops failed, they would get the strongest young men to go and find food. They would go and find food by going beyond their usual areas and by being curious.” We may no longer be hunter-gatherers, Shaw’s theory goes, but young people will still test the boundaries, be curious, and do new things; it’s part of what they are.
在某些方面，这已经是一项成熟的技术，至少在有健康问题的人中是这样。Shaw指出，我们已经使用芯片进行人工耳蜗植入，甚至在脑损伤的情况下绕过大脑的部分区域。她说：“切削人体并不是新闻，但我们总是那些邪恶的一面说这有点过于奥威尔式。” 人们可能会担心生活在他们体内的计算机病毒或者当硬件被破坏时会发生什么。
“它将摆脱身份通行证”
智库快速未来的未来主义者兼首席执行官罗希特·塔尔瓦（Rohit Talwar）认为，削片变得非常迅速，尤其是那些希望证明自己具有前瞻思维的科技公司。
Talwar说，在那些希望获得极高安全性的公司中，人们不会进入系统或者他们不应该建造的部分建筑，以及谁想向客户证明他们在安全方面处于领先地位条款。您可能还会看到它被用作使人们能够在食堂，自动售货机上兑换货币的方式 - 它将摆脱身份通行证。“
Shaw也看到了好处。如果有人生病并且有起搏器或使用抗凝药物，通过快速扫描获得该信息可以挽救他们的生命。但她也指出了对犯罪现场的暗示。在犯罪率高且尸体被肢解的地区，Shaw指出，犯罪分子不需要整个身体来破坏安全，只需要插入芯片的肢体。她说：“你最终可能会无意中煽动比原先考虑的更可怕的罪行。”
塔尔瓦尔认为，反乌托邦是旁观者的眼睛。作为数字原生代出生的一代人可能会认为这是一种自然的进化，塑料传递为过时的，神秘的，当然也无法捕捉到我们身体内的芯片可以捕获的信息，比如健康。
“老一代人可能会认为这是非常具有侵略性的，”塔尔瓦尔说。“我去年参加了一个活动，那里他们只是为了好玩而扒人，而且这些线路正在人们的走廊上等待被破坏 - 为了故事和体验。”
我们与机器对话的一部分
那么，切削在哪里？Talwar认为这是一个不可避免的过程的一部分，在这个过程中，先驱者已经说了一段时间，如果人类要跟上人工智能的步伐，我们就必须加强我们的大脑和身体。
“这只是该过程的起点。你可以很容易地预测你的手机内存被插入你，芯片可以加速你的记忆和你的大脑，“Talwar说。“随着我们加强和扩充自己，进入超人类世界，我们可以看到这方面的巨大加速。”
“你可能最终无意中煽动了比原先考虑的更可怕的罪行。”
Coplin认为切削是关于我们如何与机器相关的对话的一部分。他指出，澳大利亚的一名男子试图从旅行卡中取出芯片并将其嵌入手中失败，因为条款和条件说不会损坏卡。“目前，这感觉很奇怪，”科普林说，“但此刻，我可能会在我的手腕上放置一种可能具有该技术的设备。为什么不在我的皮肤下更远一点？“
社会一直在争论技术的潜力及其所带来的变化。四分之一世纪以前，很少有人预测到手机的出现 - 我们更多地预计会将它们用作相机和音乐中心。现在，技术面临着额外的压力。
“我们真的失去了对处理我们数据的人的信任 - 银行，谷歌，Facebook，”科普林说。“在赢得信任之前，我们会非常担心这种事情。而且我认为这是一个真正的耻辱，因为我们可以获得的好处。“
盖伊克拉珀顿
Guy Clapperton是英国的资深记者，大约30年前开始研究人与技术之间的关系。
以上AI自动翻译完成，仅供参考！
原文
Would You Let Your Boss Put a Chip in Your Body?
Future of Work
2018年07月17日
Future of Work
创新：背调公司Checkr创建动态背调监控工具以提升Uber乘坐的安全性编者注：值得学习和参考，动态的背景调查很重要啊！国内哪家可以跟滴滴等合作起来！
目前背调都是截止调查的当天。而入职或者开始工作后的情况就很难掌握了！
现代和合规背景调查的领先提供商Checkr今天宣布了一项新技术，该技术可持续更新可能影响共乘驾驶员驾驶资格的犯罪记录。Checker Continuous Check由Uber设计，动态识别可能不合格的记录，以帮助确保驾驶员继续满足优步的安全标准。
Checkr首席执行官Daniel Yanisse表示： “ 凭借当今的按需劳动力，我们需要超越静态背景报告，进行动态筛选。通过持续检查，Checkr为共乘产业创造了新的安全标准将提供关于某人背景变化的重要见解，这可能会影响他们的工作资格。“
优步是第一家采用该技术的公司。使用涵盖大多数新刑事犯罪的数据来源，当司机参与犯罪活动时，持续检查会向优步提供通知。然后，优步可以调查任何可能不合格的信息，例如DUI的新费用和未决费用，以确定该驱动程序是否仍有资格与Uber一起驾驶。这项新技术使优步能够在每年重新进行背景调查之间持续执行其安全标准。
“ 安全对优步至关重要，我们希望确保驾驶员持续不断地达到我们的标准，”优步安全与保险副总裁Gus Fuldner说。“ 这种新的连续检查技术将加强我们的筛选过程并提高安全性。”
最初设计用于满足共乘行业的严格要求，2018年秋季将为所有Checkr客户提供持续检查。
关于Checkr
Checkr的使命是通过提高对过去的理解来建立更公平的未来。我们的平台使数以千计的客户每年能够以gig经济的速度轻松雇用数百万人。使用Checkr先进的背景调查技术，各种规模的公司都能更好地了解不断变化的员工队伍的动态，为他们的招聘带来透明度和公平性，最终为员工创造更美好的未来。
Checkr Creates Dynamic Monitoring Tool to Elevate Safety in Ridesharing
Checkr, the leading provider of modern and compliant background checks, today announced new technology that provides continuous updates about criminal records that may affect ridesharing drivers’ eligibility to drive. Checkr Continuous Check, which was designed with Uber, dynamically identifies potentially disqualifying records to help ensure drivers continue to meet Uber’s safety standards.
“With today's on-demand workforce, there's a need to move beyond static background reports to dynamic screenings," said Daniel Yanisse, CEO of Checkr. "Through Continuous Check, Checkr is creating a new standard of safety for the ridesharing industry and beyond that will provide critical insight into changes in someone's background that may affect their eligibility to work."
Uber is the first company to adopt the technology. Using data sources that cover most new criminal offenses, Continuous Check provides notifications to Uber when a driver is involved in criminal activity. Uber can then investigate any potentially disqualifying information, such as a new and pending charge for a DUI, to determine whether the driver is still eligible to drive with Uber. This new technology allows Uber to continuously enforce its safety standards between annual reruns of background checks.
“Safety is essential to Uber and we want to ensure drivers continue to meet our standards on an ongoing basis,” said Gus Fuldner, Vice President of Safety and Insurance at Uber. “This new continuous checking technology will strengthen our screening process and improve safety.”
Designed initially to meet the stringent requirements of the ridesharing industry, Continuous Check will be available to all Checkr customers in Fall 2018.
About Checkr
Checkr’s mission is to build a fairer future by improving understanding of the past. Our platform makes it easy for thousands of customers to hire millions of people every year at the speed of the gig economy. Using Checkr’s advanced background check technology, companies of all sizes can better understand the dynamics of the changing workforce, bring transparency and fairness to their hiring, and ultimately build a better future for workers. For more information please visit: www.checkr.com.
Google Hire重大更新！全面AI技术支持，简历筛选安排面试将大幅节约时间综合来源/ gadgets google hire blog等
更新要点
Google Hire通过更新获得了新的AI驱动的工具
Google Hire可以更快地安排面试，并在简历中突出显示关键字
雇用1000人以下的美国企业适用Google Hire
随着去年推出Google Hire，Google通过将招聘过程整合到招聘人员，已经花费大量时间去查工具（如Gmail，Google日历和其他G-Suite应用程序），来简化招聘流程。旨在帮助中小型企业有效招聘。招聘人员表示，Hire从根本上改善了他们的工作方式，减少了应用程序之间的上下文切换。
实际上，当他们衡量用户活动时，他们发现Hire减少了完成日常招聘任务的时间 - 比如审查应用程序或安排面试 - 节省时间高达84％。
Google启动AI
通过整合Google AI，Hire现在可以减少重复耗时的任务，如安排面试，进入一键式交互。
这意味着招聘团队可以在后勤上花费更少的时间，更多的时间与人交流。
Hire中的新功能使招聘人员可以做到如下几点：
在几秒钟内安排面试：
招聘人员和招聘协调员花费大量时间在后勤管理 - 查找日历上的可用时间，预订房间，并将正确的信息汇集到预备面试官处。为了简化这一过程，Hire现在使用AI来自动建议面试者和理想时间段，从而将面试计划减少到几次点击。
通过整合Google AI，Hire现在可以将重复耗时的任务减少为一键互动。这意味着招聘团队可以在后勤上花费更少的时间，更多的时间与人交流” 谷歌在其博客文章中表示。 自推出以来，Google Hire带有G Suite集成功能，可让应用程序与Gmail和Google日历等其他应用程序同步工作。Google声称Hire可以减少招聘团队招募任务的时间达84％。
最新的更新基本上整合了Google AI，以减少做任务时的点击次数，让AI建议发挥作用。
Google Hire自动提供面试官和理想时间段，将面试安排减少到几次点击。操作如下：
Photo: Google
它试图减少手工查看日历空闲时间，为您查看并提供理想的时间段。此外，如果面试官最后一分钟取消，Hire不只是提醒你，它还推荐可用的面试官，并可以很容易且快速地邀请面试官。
所以我们可以看到国内外面试安排都是一个复杂而且繁琐的事情，面试管理这块的需求也日益突出。
自动突出显示简历重点
相当一部分招聘人员的时间花在审查简历上（我们都知道这一点）。有人告诉我，当团队正在观看与Hire进行互动的人时，他们发现客户经常使用“Ctrl + F”，通过简历扫描搜索正确的面试者的技能 - 这是一项重复的手动任务，可以轻松实现自动化。
另一个常见的招聘难题是在简历中查找关键字。 Hire的AI现在通过分析工作岗位描述，或搜索查询术语并在简历中突出显示相关单词（包括同义词和缩略词）来节省手动搜索它们的时间，自动为招聘人员找到这些单词。
Photo: Google
点击致电候选人：
无论他们是筛选候选人，进行面试还是跟进录用信，招聘人员每天都会有数十次电话交谈。现在通过点击通话功能简化每个电话对话，并自动记录通话，以便团队成员知道与候选人通话的人员。它是如何工作的，Derek？ 很高兴你问这样的问题！
系统会拨打您要给求职者的电话，然后当您拿起电话时，系统会向求职者拨打该号码。且您永远不会丢失您的收件箱内容，电话会录音，并且您可以在电话中记笔记。我问是否有发信息功能，市场表明，大约98％的人回复短信，很少听到语音信箱或回复他们不认识的号码。
他们向我保证，这个过程非常简单，并且您电话辛苦获取的宝贵数据将会轻松转移。
最后，现在通过点击通话功能简化每个电话对话，并自动记录通话，以便团队成员知道谁已经与候选人通话，而不是多次拨打同一个候选人。
所有那些雇员不足1000人的美国企业都可以购买Hire服务。在中国不行~~
关于Google Hire 从去年7月推出，旨在帮助中小型企业有效招聘。它允许招聘人员将工作发布到多个工作现场，跟踪申请，安排面试，甚至可以在一个平台上获得面试反馈。现在，在一年之后，谷歌已经更新了招聘人工智能驱动工具，以实现“更聪明，更快速的招聘方式”。此更新带来的新功能可以加快日程安排访问速度，为日志记录提供简单的工作，并简化相关简历，从而减少耗时。
“通过整合谷歌AI，服务现在减少重复，耗时的任务，进入一键式的互动。这意味着雇佣团队可以花费更少的时间与物流和更多的时间与人联系”
以上由HRTechChina 综合编译，仅供参考！
Future of Work
2018年06月27日
Future of Work
10 Trends in Workforce Analytics （英文）
Workforce analytics is developing and maturing. These are the 10 major trends for the near future.
1. From one time to real-time
Many workforce analytics efforts start as a consultancy project. A question is formulated (“How do our employees experience their journey?”), many people are interviewed, data is gathered, and with the help of the external consultants a nice report is written and many follow up projects to redesign the employee journey are defined.
A one-time effort is nice, but it might be more beneficial to develop ways to gather more regularly and maybe even real-time feedback from candidates, employees and other relevant groups.
The survey practice is changing. We see organizations using several approaches:
The classic annual or bi-annual employee survey, for a deep dive.
Weekly, monthly or quarterly pulse surveys to gather more frequent feedback. A few questions, often varying the questions per cycle. Some more advanced pulse survey solutions are adaptive: they ask more questions to people when they sense there are issues (“How was your week?”. If the answer is “Very Good”, the survey is finished, if you answer, “Not so good”, there are some follow-up questions). Pulse surveys can also be easily connected to the important “moments that matter” for the employee experience.
Continuous real-time mood measurement. Innovative solutions in this area are still scarce, especially if you want to measure in a passive non-obtrusive way. Keencorp is an example, they analyze aggregated e-mails and can report on the mood (and risks) in different parts of an organization.
In my article Employee mood measurement trends, you can find an extensive overview of mood measurement providers.
2. From people analytics to workforce analytics
Currently, the general opinion seems to be that people analytics is a better label than HR analytics.
Increasingly the workforce is consisting of more than just people. Robots and chatbots are entering the workforce. The first legal discussions have started: who is responsible for the acts of the robots?
If we’re also analyzing robots, we’re moving from people analytics towards workforce analytics. Robot wellbeing and robot productivity is a nice domain for HR to claim.
3. More transparency
This overview of workforce analytics trends cannot be complete without a reference to GDPR. GDPR is fueling a lot of positive developments, one of them being a lot more transparency. About what kind of data is collected, how it is used, and how algorithms are used to make decisions about people.
The issue of data ownership is related. It is expected that employees will no longer accept that they cannot own their own personal data. Employees need to have the possibility to show their data to their potential next employer as evidence for their productivity and engagement.
4. More focus on productivity
In the last years, there has not been a lot of focus on productivity. We see a slow change at the horizon.
Traditionally, capacity problems have been solved by recruiting new people. This has led to several problems. I have seen this several times in fast growing scale-ups.
As the growth is limited by the ability the find new people, the selection criteria are (often unconsciously) lowered, as many people are needed fast. These new people are not as productive as the existing crew. Because you have more people, you need more managers. Lower quality people and more managers lowers productivity.
Another approach is, to focus more on increasing the productivity of the existing employees, instead of hiring additional staff, and on improving the selection criteria.
Using workforce analytics, you can try to find the characteristics of top performing people and teams, and the conditions that facilitate top performance.
These findings can be used to increase productivity and to select candidates that have the characteristics of top performers. When productivity increases, you need less people to deliver the same results.
A related read on this topic are the 3 reasons to stop counting heads.
5. What is in it for me?
A lack of trust can influence many workforce analytics efforts. If the focus is primarily on efficiency and control, employees will doubt if there are any benefits for them.
Overall there is a shift to more employee-centric organizations, although sometimes you can doubt how genuine the efforts are to improve the employee experience.
Asking the question: “How will the employees benefit from this effort?” is a good starting point for most workforce analytics projects. It also helps to create buy-in, which becomes increasingly important with the introduction of the GPDR.
6. From individuals to teams to networks
Many workforce analytics projects today are still focused on individuals. What are the characteristics of our top performers? How can we measure the individual employee experience? How can we decrease absenteeism?
Earlier, I gave an overview to what extend current HR practices are focused on teams.
As you can see in the table, most of the practices are still very focused on the individual. Workforce analytics can help to improve the way teams and networks function in and across organizations. The rise of Organizational Network Analysis is one of the promising signs.
7. Cracks in the top-down approach
The tendency to implement changes top-down, is still common.
We like uniformity and standardization. In our central control room, we look at our dashboard, and we know we need to act when the lights are turning from green to orange.
HR finds it difficult to approach issues in a different way. Performance management is a good example. Changing the performance management process is often tackled as an organization-wide issue, and HR needs to find the new uniform solution.
In line with the trend called “the consumerization of HR”, employees are expected to take more initiative. Employees are increasingly tired of waiting for the organization and HR, and want to be more independent of organizational initiatives.
If you want feedback, you can easily organize it yourself, for example with the Slack plug-in Captain Feedback. A simple survey to measure the mood in your team is quickly built with Polly (view: “How to measure the mood in your team with Slack and Polly“). Many employees are already tracking their own fitness with trackers like Fitbit and the Apple Watch.
Many teams primarily use communication tools as WhatsApp and Slack, avoiding the officially approved communication channels. HR might go with the flow, and tap on to the channels used, instead of trying to promote standardized and approved channels.
How can workforce analytics benefit from the data gathered by on their employee’s own devices? If it is clear, what the benefits are for employees to share their data, they might be able to help to enrich the data sets and improve the quality of workforce analytics.
8. Ignoring the learning curve
In their book “Making HR measurement strategic”, Wayne Cascio and John Boudreau presented an often-quoted picture, with the title “Hitting the “Wall” in HR measurement”. The wall was the wall between descriptive and predictive analytics.
There are many more overviews with the people analytics maturity levels. Generally, the highest level is predictive analytics.
Patrick Coolen of ABN AMRO Bank recently mentioned a next level: continuous analytics, and he introduced a second wall, the wall between predictive analytics and continuous analytics.
As predictive analytics seems to be the holy grail, many HR teams want to jump immediately to this level. Let’s skip operational reporting, advanced reporting and strategic analytics. We can leapfrog, ignore the learning curve, and jump to the highest level in one step.
For many teams, ignoring the learning curve does not seem to be a sensible strategy. Maybe it is better to learn walking before you start running.
9. Give us back our time!
Recently I spoke to HR professionals from big multinationals who were involved in a “Give us back our time” projects.
In their organizations, the assignment to all staff groups was: stop using (meant was: wasting) more and more time of the employees and managers, please give us some time back!
An example that was mentioned concerned performance management. In this organization, they calculated that all the work around the performance management process for one employee costed manager and employee around 10 hours (preparation, two formal meetings per year, completing the online forms, meeting with HR to review the results etc.).
By simplifying the process (no mandatory meetings, no forms, no review meetings, just one annual rating to be submitted per employee by the manager), HR could give back many hours to the organization – to the relief of both managers and employees.
Big HR systems generally promise a lot. But before the system can live up to the high expectations, a lot of work needs to be done. Data fields must be defined. Global processes must be standardized. Heritage systems must be dismantled.
This results in a lot of work (and agony), for employees, for managers, for HR and for the implementation partners (who do not mind).
Workforce analytics can help a lot in the “give-us-time-back” projects, for example by some simple time-measurement. Measure the time a sample of managers, employees, and HR professionals spend on different activities, and estimate the value these activities optimizes the core activities of the organization (e.g. serving clients and bringing in new clients).
10. Too high expectations
The expectations of workforce analytics are often too high. Two elements must be considered.
In the first place, human behavior is not so easy to predict, even if you have access to loads of people data.
Even in domains where good performance is very well defined and where a lot of data is gathered inside and outside the field, as for example in football, it is very difficult to predict the future success of young players.
Secondly, the question is to what extend managers, employees and HR professionals behave in a rational way. All humans are prone to cognitive biases, that influence the way they interpret the outcomes of workforce analytics projects. Some interesting articles on this subject are why psychological knowledge is essential to success with people analytics, by Morten Kamp Andersen, and The psychology of people analytics, written by myself.
A more general thought: what if you replaced ‘Workforce analytics’ with ‘Science’? What is the role of science in HR? The puzzle is, that there are many scientific findings that have been available for a long time but that are hardly used in organizations.
Example: it has been proven repeatedly, that the (unstructured) interview is a very poor selection instrument.
But still, most organizations still rely heavily on this instrument (as people tend to overestimate their own capabilities). Why would organizations rely on the outcomes of workforce analytics, when they hardly use scientific findings in the people domain?
An interesting presentation on this topic that I recommend is by Rob Briner, titled evidence-based HR, what is it and is it really happening?
There’s a lot that’s changing in the world of work. These are the 10 trends in workforce analytics that I’m seeing today and that will likely impact the way we work in the near future.
This article is based on a keynote I gave at the Workforce Analytics Forum in Frankfurt, Germany, on April 18, 2018.
by Tom Haak
Tom Haak is the director of the HR Trend Institute The HR (Human Resources) Trend Institute follows, detects and encourages trends. In the people and organization domain and in related areas. Where possible, the institute is also a trend setter. Tom has an extensive experience in HR Management in multinational companies. He worked in senior HR positions at Fugro, Arcadis, Aon, KPMG and Philips Electronics. He holds a master’s degree in Psychology. Tom has a keen interest in innovative HR, HR tech and how organizations can benefit from trend shifts. Twitter: @tomwhaak
刚刚，Workday 宣布收购Rallyteam，增强智能人才优化功能Workday Adds More Intelligence to Optimize Talent with Rallyteam Acquisition
Workday 刚刚宣布，收购Rallyteam ,Rallyteam总部位于旧金山，联合创始人兼CEO David Somers，创建于2013年，2014年产品上线，收购金额没有公布~
在2017年，HRTechChina报道过Rallyteam获得融资860万A轮融资，详细可以看新闻：Rallyteam完成860万美元A轮融资 。
Rallyteam 创办的原因在于CEO自己发现在工作中越来越沮丧，因为在当前组织中的发展和好的机会很难被发现（换岗），于是希望能够找到好的解决方案，于是乎就创建了这个公司，最早是有微软加速器孵化~~
关于Rallyteam在做什么，可以看这里：
Rallyteam发现，有才干的员工经常因为工作挑战不够，或不符合自己的职业生涯规划而离职。这家创企正在和eBay等公司合作，提高员工留职率。
近日，Rallyteam完成860万美元融资，Norwest Venture Partners领投。Storm Ventres、Cornerstone OnDemand和Wilson Sonsini跟投。
Rallyteam联合创始人兼CEO David Somers表示，他们所合作的都是员工人数超过5000的企业。
该公司拥有一套软件，能够利用公共数据来为内部员工建立档案，然后办起“媒人”的角色，帮员工寻找工作机会和特殊项目。
Somers说，他们希望“找到拥有相应技能，并正在寻求新挑战的人”。
以下为官方宣布新闻：
我们很高兴地宣布Workday通过收购Rallyteam不断投资于机器学习的努力再次迈出了一步！
通过Rallyteam，我们获得了令人难以置信的团队成员，他们创建了一个人才流动平台，使用机器学习，通过将员工的兴趣，技能和关系与相关工作，项目，任务和人员进行匹配，帮助公司更好地理解和优化员工队伍。
随着工作世界继续向人才和技能市场迈进，该团队将利用其深厚的专业知识为Workday的产品提供更强大的智能，帮助客户发现组织内外最优秀的人才，以满足业务需求。
对于Workday和我们的客户来说，这是一个激动人心的时刻，所以请加入我们，欢迎我们的新同事们，并在未来的一年中继续关注更多细节！
We’re excited to announce another step in Workday’s efforts to continually invest in machine learning with the acquisition of Rallyteam!
With Rallyteam, we gain incredible team members who created a talent mobility platform that uses machine learning to help companies better understand and optimize their workforces by matching a worker’s interests, skills, and connections with relevant jobs, projects, tasks, and people.
As the world of work continues moving toward a marketplace for talent and skills, this team will apply its deep expertise to power Workday’s products with even more intelligence that will help customers uncover the best talent—inside and outside of their organizations—to meet business needs.
It’s an exciting time for Workday and our customers, so please join us in welcoming our new colleagues, and stay tuned for more details in the coming year!
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