• hr
    2018年中国人力资源共享服务(三支柱)高峰论坛在上海四季酒店成功举办! 2018年8月8日,由三支柱研究院主办,HRTechChina承办的2018年中国人力资源共享服务(三支柱)高峰论坛在上海四季酒店成功举办。本次峰会在Keystone,仁云科技,云合同的大力支持下,圆满落幕,致此主办方表示诚挚的感谢! 峰会核心话题与当代大数据时代背景紧密结合,深度探讨“人力资源价值创造趋势与HR三支柱转型策略,HR共享服务平台搭建和运维经验,赋能人力资源共享服务数字化转型,HR三支柱的设计与落地”等话题,推动HR领域专业化,信息化,高效化,更好地把握行业发展的方向和未来。 峰会吸引了近200位知名企业人力资源领域高管,杰出的企业负责人,HR行业相关人士莅临现场,同时还有大批高校优秀学子到场学习。原计划会议于17:30结束,但参会嘉宾对于招聘科技话题津津乐道,会议延时较长。会议结束,嘉宾好评如潮。这也是主办方喜闻乐见的。在践行HRTechChina“推动中国招聘科技发展”宗旨的道路上,又更近了一步。我们还将不忘初心,砥砺前行! 2018 中国人力资源共享服务(三支柱)高峰论坛特邀科石咨询CEO杨冰先生作为主持嘉宾。参会嘉宾大多准时到达会场,峰会论坛在下午13:30准时拉开序幕。 首位分享嘉宾是西门子HRSSC高朝辉先生,他就“HR共享服务平台搭建和运维经验分享”的主题发表了自己的观点。结合西门子运营模式,总结了人力资源信息系统总体架构,提出共享服务管理体系,再细谈到到质量管理,流程管理,项目管理等领域的具体操作。受到嘉宾热烈欢迎。 紧随其后的是云合同副总经理张汉民先生的分享,他分享的主题是“与纸质合同博弈,云合同助力人力资源实现华丽转身”。在谈到电子合同的优势方面主要讲述了电子合同的有效性,便捷化和高效性。许多在场HR相关人士颇感兴趣,在本次会议的参会交流微信群中积极互动,以便更好的优化招聘流程! 短暂休息之后,迎来了仁云科技CEO张向党先生的精彩分享。从专业领域出发,张向党先生带来了 “科技赋能人力资源共享服务数字化转型”的主题分享。结合自身经验和经典案例分析,讲述了科技如何实现人力资源共享服务数字化的转型。演讲结构清晰,逻辑严密,体系完整。演讲结束,在场嘉宾报以热烈的掌声。同时也增强了对科技的信心,对于未来方向的把握也有了更加明确的认识。 最后一位重量级分享嘉宾是来自Keystone的CEO杨冰先生,以“人力资源价值创造趋势与HR三支柱转型策略”为题,对人力资源三支柱做了详细的介绍,并对其产生的价值进行了详细的阐述。大量案例分析的佐证,使许多专业术语更易理解。在参会嘉宾中反响良好。演讲结束,许多参会嘉宾还饶有兴趣的进行了讨论,意犹未尽。 致此,峰会圆满划上句号! 中国的HR三支柱,也就是SSC+HRBP+COE,转型趋势大势所趋,以三支柱为原型,形式多样,聚焦实效。推动人力资源实现数据驱动下的最优实效。作为企业HR,基于数据分析,把握核心,结果导向,才能更好的引进人才,优化企业,创造企业价值。 最后再次感谢我们的分享嘉宾、合作伙伴以及参会嘉宾!
    hr
    2018年08月09日
  • hr
    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.
    hr
    2018年08月07日
  • hr
    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.
    hr
    2018年08月07日
  • hr
    8月3日,2018人力资本分析高峰论坛-People Analytics Forum在沪成功举办! 2018年8月3日,由HRTechChina主办的“人力资本分析高峰论坛-People Analytics Forum”在上海成功举办。 会议当日,虽逢台风天气,嘉宾参会热情不减,均准时到达会场,大会得以成功举办。近70位招聘科技领域的科学家、HR资深高管、行业大咖参加会议,其中包括许多知名企业高管:阿里巴巴、英格索兰、罗氏、腾讯、米其林、ARM、霍尼韦尔、好时、凯德管理、中宏保险、延锋、jotun等。 本次峰会主题为:“用数据驱动人力资源”,主办方邀请了3位业内知名人士进行了精彩的主题分享。演讲嘉宾包括科石首席顾问人力资源数据分析专家杨冰,世界500强公司亚太区人力资源总监范珂,前美世咨询组织分析专家 六点一刻创始人许菊艳,共同探讨中国最前沿招聘科学技术,深度挖掘如何将大数据更好应用于招聘领域,促进招聘工作的科学化,精准化,更好把握招聘领域科技未来的趋势和方向。 首位分享嘉宾是世界500强公司亚太区人力资源总监范珂,就“如何通过人力资源数据讲故事”的主题发表了自己的观点。 接着前美世咨询组织分析专家 六点一刻创始人许菊艳分享的主题是:以始为终,有效利用人力资源数据推动业务价值实现数据重塑影响力,她从三个维度分别向大家介绍了数据是如何推动业务价值的实现-由外而内的价值创造思维;数据驱动的效能计量系统;先于业务的战略支持维度。深入浅出的剖析了大数据在人力资源领域的应用,大量案例分析的佐证,使演讲通俗易懂,赢得嘉宾阵阵掌声。 最后分享的嘉宾是科石首席顾问人力资源数据分析专家杨冰,在他的分享里,着重强调了组织人效管理。从三大板块对组织人效管理进行全面解读:组织人效管理的任督二脉-构建人效管理仪盘表的核心逻辑;如何通过数据分析诊断组织健康问题;组织效能优化路径和案例探讨。 本次峰会就招聘行业的最新领域——人力资本分析做的深度探讨,对人力资本发展方向有着深刻的意义。随着招聘科技的发展,人力资本分析将越来越多的应用于招聘领域,前景不可小觑。
    hr
    2018年08月06日
  • hr
    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招聘科技高峰论坛上的演讲,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招聘科技高峰论坛上,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招聘科技高峰论坛现场演讲整理: 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!
    hr
    2018年08月06日
  • hr
    赛码网斩获候选人体验大奖产品金奖 由HRTech China主办的“2018招聘科技高峰论坛”于7月27日在上海开幕,现场云集20余家杰出企业以及1400+招聘科技达人。 招聘工作对于企业来讲不言而喻是至关重要的,如何吸引并选拔到优秀的合适的人才是招聘工作者的核心工作。科技的快速发展带来的不仅仅是信息的快速膨胀也给招聘工作带来的巨大的机遇和挑战,如何更好的使用技术手段提升工作质量,实现人尽其才,才尽其用的共赢目标,成为我们不能不面对的工作。工欲善其事必先利其器!招聘科技高峰论坛就是这样一场关于招聘科技的专业盛会,可以收获人才获取相关的最佳招聘科技实践和科技利器! 会议当日,有近20位招聘科技领域的科学家、HR资深高管、行业大咖们围绕“全球招聘科技发展趋势”、“科技助力招聘”、“AI人工智能与招聘”等核心议题进行了精彩的分享。 同时,重磅揭晓候选人体验大奖Candidate Experience Awards(CandE Awards)评选结果并颁奖,越来越多招聘人员和公司认识到候选人体验的重要性。大家都知道你无法获得第二次机会去赢得第一印象。候选人体验就是这样,帮助企业快速获取更好的人才,直接影响雇主品牌及招聘工作营销的成效。本次评选由服务商提交参评案例,由各知名企业的HR高管共同组成的评委团,经过对候选名单进行全面、严格、高标准的讨论筛选,共同打造出极具含金量的候选人体验大奖。 ★ 获奖榜单★ 候选人体验企业金奖:平安集团,天安骏业,康得新集团,凤凰网,票易通,施耐德电气,上海辰渝机电成套设备有限公司、京东集团 候选人体验产品金奖:优面宝,赛码网,e成科技,HR-X 在候选人体验最佳案例专场中,赛码网业务发展总监朱涛介绍了赛码—智能在线考试平台,并分享校园招聘中的项目案例,在京东2018校招项目中,所有内容交付在1天内完成,保证了校招流程的连续快速,通过赛码自动阅卷及实时在线编程,快速剔除了58%的表现不佳者,让甄选更科学有据。通过赛码的专业试题服务,为企业HR减少了与技术部门在出题、审题、阅卷等环节约76%的人工成本。 赛码不止专注于IT校招笔试,其核心产品—“在线考试平台”,支持多题型在线作答,18种编程语言在线调试,机器自动判题,可以完美解决IT人才编程技能评定。智能题库,随机抽题,系统自动阅卷,一键导入考生名单,100%通知,保障到场率。最新的人脸识别技术+七大防作弊功能,弹性服务器,让30万考生同时在线平稳作答。可以在线监考,监拍画面随时查看,考试报告全方位展示测试数据,自动计算考试总分、排名,人才数据可视化。 为加速并完善招聘流程,赛码的在线面试平台更是完美解决异地面试问题,让面试官和候选人感受如同面对面沟通的身临其境,既可以在线考核编程能力,又能真实地模拟面试现场场景。面试报告立即生成,随时查看,记录在线面试全过程,大大提高面试到场率&效率。 用科技工具—赛码,助力招聘! 现场,赛码产品引起各企业和领域内招聘达人的极大关注,纷纷前往展位,竞相咨询,进行深入的了解和体验。 赛码网由大型人力资源中央企业中智集团(CIIC)孵化,用互联网跨界思维改变长久以来纸笔的考试方式,是一站式的企业/机构/学校在线考试平台。从2015年开始引领在线笔试行业以来,赛码网已经成为一线互联网企业的首选在线考试平台。
    hr
    2018年08月02日
  • hr
    2018候选人体验大奖揭晓!国内首次引入候选人体验概念 2018年7月27日,中国备受瞩目并引领招聘科技前沿的峰会-2018招聘科技高峰论坛于上海四季酒店隆重举行。本次峰会以“Hire Better With Tech”为主题, 本次峰会由HRTech China主办。 候选人体验 HRTechChina首次引入候选人体验的概念,希望能够推动企业和招聘官从更直接的感受出发,吸引并影响候选人做出决定。 所谓候选人体验,就是用于描述候选人与公司之间,关于招聘营销推广和雇佣目的的所有互动的过程感受。 举办本次候选人大奖旨在践行HR Tech China“推动中国人力资源科技的进步与发展”的宏伟愿景,以提升候选人体验。 提升候选人体验的方法有很多,核心的一点是公司全体人员的共识和认知,毕竟招聘录用候选人是一个多部门多人员协同推进的事情,必须建立在公司整体的认知和共识之上才可能建立起广泛的良好体验。 豪华阵容评委团 在企业评选时,评委团由各知名企业的HR高管共同组成的豪华阵容评委团,经过对候选名单进行全面、严格、高标准的讨论筛选,共同打造出极具含金量的候选人体验大奖。奖项设置包括:候选人体验大奖企业金奖和候选人体验大奖产品金奖。 评选环节 本次评选环节评委严格把关,企业在申请奖项过程中,首先须提交完整的体系或深度的细节,丰富的数据支持和结果验证,图片、文字、视频等均可,要求必须原创且实践。评选过程中,企业资料先交由评委团单独审核,审核通过,进入开会研究阶段,以各项指标为基准,最终确定符合要求的企业。 颁奖环节 727招聘科技峰会当天,候选人体验大奖的颁奖由两位专家代表上台颁奖,一位是招聘管理专家kevin,一位是益海嘉里的丁鹏先生。评选旨在甄选出在候选人体验上做出卓越实践,通过提升候选人入职企业前的体验以提高入职率,来帮助企业吸引更多的人才。评委会同时建议企业的HR们可以就候选人体验方面做更多的沟通、交流和分享,以便更好的造福人才,成就企业,贡献社会。  评委会认真审查企业各项指标,多番讨论与研究,最终确立本次候选人体验大奖的获奖企业为: 平安集团,天安骏业,康得新集团,凤凰网,票易通,施耐德电气,上海辰渝机电成套设备有限公司、京东集团获得候选人体验大奖企业金奖。 优面宝,赛码网,e成科技,HR-X获得候选人体验大奖产品金奖。 恭喜以上获奖企业! 通过这次评选,表彰了企业在科技创新等方面的勇敢探索与无限追求。强化了当今时代,以人为本位,以科技作为最具效率,最优化的招聘手段的理念,更好推动招聘科技向前发展。 口碑成就价值。候选人体验大奖评选希望能够成为中国最权威、最顶级、最具影响力的人力资源赛事之一,入选企业经过在众多企业中的层层筛选,评委会的严格把关,终获荣誉。再次表示衷心的祝贺!
    hr
    2018年08月02日
  • hr
    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!
    hr
    2018年08月02日
  • hr
    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
    hr
    2018年07月31日
  • hr
    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.
    hr
    2018年07月30日