• 数据驱动
    人力资源平台Hibob的完成最新一轮2000万美元融资 据官方消息,Hibob获得最新一轮2000万美元的A+系列投资,以支持下一阶段的高速增长,拓展美国的及欧洲更多的国家市场,并雇佣更多的技术人才。本轮投资者有Bessemer Venture Partners、Battery Ventures、Fidelity Ventures、Eight Roads、Arbor Ventures和Presidio Ventures。此次投资是Hibob公司2017年4月宣布的A系列融资的延伸,这笔资金将为公司继续建设未来工作场所所需的人力资源解决方案提供动力。 Hibob成立于2015年末,其使命是为未来的职场打造第一个人力资源平台。这场未来变革需要对当今最有价值的员工有深刻的理解:那些寻求日常参与、反馈和意义的员工;他们在部落中工作,寻求成长的机会。他们需要有灵魂的个性化。与此同时,人力资源需要数据驱动和民主化,创造出对消费者友好的新工具,以吸引、留住和增长有价值的员工——并让他们在整个组织中更广泛地可用。 未来职场的迅速崛起,将由数字化新一代引领,他们将在未来几年主导全球劳动力经济。这一代人想要为快速增长的公司工作,做一些有意义的事情,打破常规、挑战权威,因此必须让他们在培育型文化中成长和发展。 Hibob公司意识到今天的劳动力是由那些想要以个人身份成长、想要在团队中茁壮成长的人组成的,他们想要成为更大的培育文化的一部分。于是创建了个人能够利用的平台,围绕共同的兴趣和激情建立联系,而不仅仅是对他们的工作描述或工资记录。Hibob正在颠覆传统的员工、经理和HR角色,为每个人构建一个平台。 目前,Hibob公司帮助全球数百家企业客户,包括Monzo、Etoro、Happy Socks、Fiverr、Receipt Bank和Karmarama。其合作伙伴包括Slack、、GreenHouse、TeamTailor、Perkbox、Aviva、Canada Life和UNUM。 “市场上大约有1400家人力资源技术供应商,”全球人力资源思想领袖之一乔什·贝尔辛(Josh Bersin)说。据他说,“一个更具创新性的核心HCM新平台是一款名为bob的产品,来自一家名为Hibob的快速发展的公司。bob首先设计了一个管理平台,其次是人力资源平台,所以它的整个设计关注于信息经理、员工和高管需要什么。” 人力资源技术行业增长迅速,预计到2022年将达到225亿美元。这项技术的普及不仅仅是因为员工和人力资源团队需要更好地处理薪资流程、绩效评估和假期请求等管理任务。相反,企业正在认识到,他们的员工不仅仅是数字、资源或人才——影响他们的管理决策应该是全面的、数据驱动的、个性化的,以推动真正的业务结果。 以上为AI翻译,内容仅供参考 原文链接:Announcing Our $20M Funding Round  
    数据驱动
    2019年03月14日
  • 数据驱动
    人员分析:构建数据驱动的人力资源功能 成功的人力资源领导者如何利用分析来优化员工队伍并创造真正的商业价值?Assurant数据分析信息管理高级总监Perla Sierra告诉我们更多信息。 当您投资,推动采用或尝试优化People Analytics的业务成果时,您的团队面临的三大挑战是什么? 在开始真正的分析之旅之前,必须评估数据的质量,必须同意一致的指标,并且必须实施隐私保护措施。虽然数据通常永远不会完美,但我们必须努力获得尽可能高的数据完整性,并且当存在数据缺口时,分析从业者必须了解数据机会并在任何分析练习中将其考虑在内。 尽管有关人员的数据已经存在很长时间,但人们将分析从预感和感觉转变为更有条理的方法已成为最大的挑战之一。将数据驱动的决策方法应用于人们面临的挑战是,使用公平竞争环境比较员工和绩效非常重要,这很难做到。要做到这一点,我们必须始终调整上下文。调整上下文涉及考虑数据中可能不存在的因素,或者它是否可能不明显。 例如,在比较相似或相同工作的绩效时,应考虑数据之外的其他因素,例如环境因素(即工作条件,经理等)。 在人员分析空间内制定数据驱动的决策可能会加剧紧张局势,因为人们更喜欢人类对算法判断的判断。事实是数据驱动的决策如果竞争场是均匀的,当然如果数据是准确的,那么就会消除偏见。基于数据做出决策无疑将提高组织的分析成熟度,并有助于在决策制定过程中采用更加公正的方法,同时加强组织的文化。数据的可用性提供了新的创新和新的见解。 对于想要成功构建,扩展和优化人员分析功能的人力资源领导者,您最重要的2-3个最实用技巧是什么?他们应该优先考虑什么? 高质量数据,数据安全性和数据隐私的可用性应该是实施人员分析功能的最前沿。如果没有这三个关键要素,那么成功构建和扩展成功的人员分析功能将更加困难。有时并非所有数据都是完美或准确的。在这种情况下,组织应考虑采用分阶段方法,该方法可以利用准确或至少足够好的数据来启动分析过程,而不是等待所有数据准确。 不幸的是,分阶段的方法需要更长的时间,并且在增量成本方面可能会花费更多,但是,如果您只是选择在没有整个数据范围之前选择不继续前进,那么您应该考虑可能遗漏的无形机会成本。这是一个你必须对不舒服感到舒服的情况,并通过“足够好”的数据推进。我会考虑创建数据委员会和数据管理员的最佳实践,这可以推动数据标准化和质量并推动数据治理。 在组织的人员分析成熟度之旅中,2-3个关键里程碑是什么? 让我们从头脑开始。最终目标是让企业将人员分析嵌入业务决策中。我们怎样才能最好地完成这项工作?该数据必须是可靠,安全,维护,一致的,但是,它并不一定是完美的。人力资源合作伙伴必须确定影响业务的人员问题,这些问题可以在流程早期确定,甚至可以完全消除。在人力资源合作伙伴和商业合作伙伴必须协同工作寻找机会获取洞察力并在适当的时间向适当的受众提供可操作的见解,并最终在可能的情况下提供规范性和预测性分析。人力资源团队必须与业务领导者,一线经理,客户,供应商和其他人合作,以识别机会,传播意识,形成深层合作伙伴关系,并提高组织成熟度。 人力资源如何增加自身的分析成熟度同时增加业务的一些例子是提供以下内容:监控员工保留,培训,内部流动性,技能集评估,将招聘评估与绩效指标相关联,确定未来资源需要。 在人力资源组织中构建数据驱动型文化时,您采用了哪种方法? 在构建数据驱动型文化时,我遇到的最有效的技术是与不同的内部业务,部门,分析从业者甚至外部资源建立业务合作伙伴关系。每个人带来的人和体验的多样性在创造性解决问题和创新方面提供了最多的帮助。每个人都通过不同的视角看待机会,这种整合创造了强大的协作模式,使组织受益。通过采用多元化的文化和整合思维伙伴,可以提供建设性的论据,敢于不同意,并准备改变主意,你真正将组织推向最高水平,不仅仅是合作,买入和接受,而是你整个组织的分析成熟度越来越高。开放是真正伟大事物的开始。随着合作和沟通的继续, 2020年及以后,您亲自跟踪的人员分析和劳动力绩效空间的2-3大趋势是什么? 就像消费者一样,员工也希望为他们量身定制解决方案,而不是一刀切的方法。 机器学习技术使组织能够为从人才获取到内部移动,学习,团队建设和其他领域的所有领域的员工量身定制个性化体验,从而提高员工敬业度。机器学习不仅可以用于个性化体验,还可以提供最佳的团队整合,以及基于通过性格测试,社交网络,调查或其他方式获得的数据获得最佳积极成果的内部移动机会,从而创建一个爆炸性的人力资源转型,员工敬业度和减少营业额。当然,这些想法也可以针对承包商,这也将为投资带来巨大回报。 员工和承包商希望提供给客户的相同个性化体验,这不应该让我们感到惊讶,因为客户,员工和承包商都是人。我希望看到更加注重将员工敬业度与生产力水平和业务成果联系起来。   以上为AI翻译,内容仅供参考。 原文链接:人员分析:构建数据驱动的人力资源功能
    数据驱动
    2018年11月22日
  • 数据驱动
    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.
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