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.
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
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