10 Trends in Workforce Analytics （英文）
Workforce analytics is developing and maturing. These are the 10 major trends for the near future.
1. From one time to real-time
Many workforce analytics efforts start as a consultancy project. A question is formulated (“How do our employees experience their journey?”), many people are interviewed, data is gathered, and with the help of the external consultants a nice report is written and many follow up projects to redesign the employee journey are defined.
A one-time effort is nice, but it might be more beneficial to develop ways to gather more regularly and maybe even real-time feedback from candidates, employees and other relevant groups.
The survey practice is changing. We see organizations using several approaches:
The classic annual or bi-annual employee survey, for a deep dive.
Weekly, monthly or quarterly pulse surveys to gather more frequent feedback. A few questions, often varying the questions per cycle. Some more advanced pulse survey solutions are adaptive: they ask more questions to people when they sense there are issues (“How was your week?”. If the answer is “Very Good”, the survey is finished, if you answer, “Not so good”, there are some follow-up questions). Pulse surveys can also be easily connected to the important “moments that matter” for the employee experience.
Continuous real-time mood measurement. Innovative solutions in this area are still scarce, especially if you want to measure in a passive non-obtrusive way. Keencorp is an example, they analyze aggregated e-mails and can report on the mood (and risks) in different parts of an organization.
In my article Employee mood measurement trends, you can find an extensive overview of mood measurement providers.
2. From people analytics to workforce analytics
Currently, the general opinion seems to be that people analytics is a better label than HR analytics.
Increasingly the workforce is consisting of more than just people. Robots and chatbots are entering the workforce. The first legal discussions have started: who is responsible for the acts of the robots?
If we’re also analyzing robots, we’re moving from people analytics towards workforce analytics. Robot wellbeing and robot productivity is a nice domain for HR to claim.
3. More transparency
This overview of workforce analytics trends cannot be complete without a reference to GDPR. GDPR is fueling a lot of positive developments, one of them being a lot more transparency. About what kind of data is collected, how it is used, and how algorithms are used to make decisions about people.
The issue of data ownership is related. It is expected that employees will no longer accept that they cannot own their own personal data. Employees need to have the possibility to show their data to their potential next employer as evidence for their productivity and engagement.
4. More focus on productivity
In the last years, there has not been a lot of focus on productivity. We see a slow change at the horizon.
Traditionally, capacity problems have been solved by recruiting new people. This has led to several problems. I have seen this several times in fast growing scale-ups.
As the growth is limited by the ability the find new people, the selection criteria are (often unconsciously) lowered, as many people are needed fast. These new people are not as productive as the existing crew. Because you have more people, you need more managers. Lower quality people and more managers lowers productivity.
Another approach is, to focus more on increasing the productivity of the existing employees, instead of hiring additional staff, and on improving the selection criteria.
Using workforce analytics, you can try to find the characteristics of top performing people and teams, and the conditions that facilitate top performance.
These findings can be used to increase productivity and to select candidates that have the characteristics of top performers. When productivity increases, you need less people to deliver the same results.
A related read on this topic are the 3 reasons to stop counting heads.
5. What is in it for me?
A lack of trust can influence many workforce analytics efforts. If the focus is primarily on efficiency and control, employees will doubt if there are any benefits for them.
Overall there is a shift to more employee-centric organizations, although sometimes you can doubt how genuine the efforts are to improve the employee experience.
Asking the question: “How will the employees benefit from this effort?” is a good starting point for most workforce analytics projects. It also helps to create buy-in, which becomes increasingly important with the introduction of the GPDR.
6. From individuals to teams to networks
Many workforce analytics projects today are still focused on individuals. What are the characteristics of our top performers? How can we measure the individual employee experience? How can we decrease absenteeism?
Earlier, I gave an overview to what extend current HR practices are focused on teams.
As you can see in the table, most of the practices are still very focused on the individual. Workforce analytics can help to improve the way teams and networks function in and across organizations. The rise of Organizational Network Analysis is one of the promising signs.
7. Cracks in the top-down approach
The tendency to implement changes top-down, is still common.
We like uniformity and standardization. In our central control room, we look at our dashboard, and we know we need to act when the lights are turning from green to orange.
HR finds it difficult to approach issues in a different way. Performance management is a good example. Changing the performance management process is often tackled as an organization-wide issue, and HR needs to find the new uniform solution.
In line with the trend called “the consumerization of HR”, employees are expected to take more initiative. Employees are increasingly tired of waiting for the organization and HR, and want to be more independent of organizational initiatives.
If you want feedback, you can easily organize it yourself, for example with the Slack plug-in Captain Feedback. A simple survey to measure the mood in your team is quickly built with Polly (view: “How to measure the mood in your team with Slack and Polly“). Many employees are already tracking their own fitness with trackers like Fitbit and the Apple Watch.
Many teams primarily use communication tools as WhatsApp and Slack, avoiding the officially approved communication channels. HR might go with the flow, and tap on to the channels used, instead of trying to promote standardized and approved channels.
How can workforce analytics benefit from the data gathered by on their employee’s own devices? If it is clear, what the benefits are for employees to share their data, they might be able to help to enrich the data sets and improve the quality of workforce analytics.
8. Ignoring the learning curve
In their book “Making HR measurement strategic”, Wayne Cascio and John Boudreau presented an often-quoted picture, with the title “Hitting the “Wall” in HR measurement”. The wall was the wall between descriptive and predictive analytics.
There are many more overviews with the people analytics maturity levels. Generally, the highest level is predictive analytics.
Patrick Coolen of ABN AMRO Bank recently mentioned a next level: continuous analytics, and he introduced a second wall, the wall between predictive analytics and continuous analytics.
As predictive analytics seems to be the holy grail, many HR teams want to jump immediately to this level. Let’s skip operational reporting, advanced reporting and strategic analytics. We can leapfrog, ignore the learning curve, and jump to the highest level in one step.
For many teams, ignoring the learning curve does not seem to be a sensible strategy. Maybe it is better to learn walking before you start running.
9. Give us back our time!
Recently I spoke to HR professionals from big multinationals who were involved in a “Give us back our time” projects.
In their organizations, the assignment to all staff groups was: stop using (meant was: wasting) more and more time of the employees and managers, please give us some time back!
An example that was mentioned concerned performance management. In this organization, they calculated that all the work around the performance management process for one employee costed manager and employee around 10 hours (preparation, two formal meetings per year, completing the online forms, meeting with HR to review the results etc.).
By simplifying the process (no mandatory meetings, no forms, no review meetings, just one annual rating to be submitted per employee by the manager), HR could give back many hours to the organization – to the relief of both managers and employees.
Big HR systems generally promise a lot. But before the system can live up to the high expectations, a lot of work needs to be done. Data fields must be defined. Global processes must be standardized. Heritage systems must be dismantled.
This results in a lot of work (and agony), for employees, for managers, for HR and for the implementation partners (who do not mind).
Workforce analytics can help a lot in the “give-us-time-back” projects, for example by some simple time-measurement. Measure the time a sample of managers, employees, and HR professionals spend on different activities, and estimate the value these activities optimizes the core activities of the organization (e.g. serving clients and bringing in new clients).
10. Too high expectations
The expectations of workforce analytics are often too high. Two elements must be considered.
In the first place, human behavior is not so easy to predict, even if you have access to loads of people data.
Even in domains where good performance is very well defined and where a lot of data is gathered inside and outside the field, as for example in football, it is very difficult to predict the future success of young players.
Secondly, the question is to what extend managers, employees and HR professionals behave in a rational way. All humans are prone to cognitive biases, that influence the way they interpret the outcomes of workforce analytics projects. Some interesting articles on this subject are why psychological knowledge is essential to success with people analytics, by Morten Kamp Andersen, and The psychology of people analytics, written by myself.
A more general thought: what if you replaced ‘Workforce analytics’ with ‘Science’? What is the role of science in HR? The puzzle is, that there are many scientific findings that have been available for a long time but that are hardly used in organizations.
Example: it has been proven repeatedly, that the (unstructured) interview is a very poor selection instrument.
But still, most organizations still rely heavily on this instrument (as people tend to overestimate their own capabilities). Why would organizations rely on the outcomes of workforce analytics, when they hardly use scientific findings in the people domain?
An interesting presentation on this topic that I recommend is by Rob Briner, titled evidence-based HR, what is it and is it really happening?
There’s a lot that’s changing in the world of work. These are the 10 trends in workforce analytics that I’m seeing today and that will likely impact the way we work in the near future.
This article is based on a keynote I gave at the Workforce Analytics Forum in Frankfurt, Germany, on April 18, 2018.
by Tom Haak
Tom Haak is the director of the HR Trend Institute The HR (Human Resources) Trend Institute follows, detects and encourages trends. In the people and organization domain and in related areas. Where possible, the institute is also a trend setter. Tom has an extensive experience in HR Management in multinational companies. He worked in senior HR positions at Fugro, Arcadis, Aon, KPMG and Philips Electronics. He holds a master’s degree in Psychology. Tom has a keen interest in innovative HR, HR tech and how organizations can benefit from trend shifts. Twitter: @tomwhaak
SHRM观点：2018年HR必须关注的6个HRTech的发展趋势AI, bots and digital twins will shape the year.
Aliah D. Wright
2018年，随着人工智能（AI），机器人，预测软件和增强现实技术的重塑，物理和数字世界将继续融合。
首先接受人工智能将塑造组织环境，特别是智能系统学会适应用户的需求。“我们不再需要学习这些软件，”位于北卡罗来纳州Raleigh的技术公司WalkMe的总裁兼联合创始人Rephael Sweary说道，“AI已经在更多地了解我们的个人角色，行为和行动，以个性化我们使用人力资源和其他商业软件。“
根据研究公司Gartner发布的2018年度十大战略技术趋势， 企业平台也将发展为提供更自然和沉浸式的互动。
Sweary说，这样的进步将使人力资源专业人员能够显着减少学习和开发预算和资源，因为采用了可以根据情况指导人们如何使用任何系统的技术。
据Gartner称，2018年影响人力资源最多的六大趋势将是：
1.区块链。这项技术对于希望更有效地验证候选人的招聘人员具有希望，并且对于想要使其组织的全球薪酬流程成本更低且更及时的薪资管理者而言。区块链使用加密的公共记录的数字分类账，将公共记录结构化为称为区块的数据集群，并分散在网络中。这是一个功能强大的工具，用户可以找到可靠且易于浏览的工具 专家预测，HR将在未来18-24个月内开始使用区块链。
2. AI基础。据Gartner报道，制造自主学习，适应和行动的系统至少将成为技术供应商的重点。人工智能将用于改善决策制定，重塑工作流程并改善客户体验。它将推动到2025年数字商业计划的投资回报。
3.智能应用和分析。公司正在使用AI实践来制作新的应用类别，例如虚拟客户助理和机器人，以提高员工绩效，销售和营销分析以及安全性。智能应用有可能改变工作的性质和工作场所的结构。Gartner表示：“在构建或购买人工智能应用程序时，请考虑其影响将在如何完成，分析或改善用户体验的过程中发挥作用。”
4.物联网（IoT）。人工智能正在推动“智能”物品的进步，例如自动驾驶汽车，机器人和无人机。它还增强了许多现有产品，包括物联网（IoT）连接的消费和工业系统。例如，在某些时候，人力资源专业人员需要雇用可以操作无人机，监视无人机安全并遵守FAA规定的人员。
5.数字双胞胎。此工具是真实世界实体或系统的数字表示。来自多个数字双胞胎的数据可以汇总为真实世界实体的综合视图。例如，未来的人类模型可以提供生物识别和医疗数据，而数字双胞胎将允许进行高级模拟，报告解释道。数字双胞胎在物联网项目的背景下可以通过帮助用户响应变化，改进运营和提高性能，显着改善企业决策。
6.会话平台。想想Alexa或Siri。在人力资源部门内部，这些计划可以通过让员工与团队成员“交谈”来改善员工的自助服务。这些工具将推动人类与数字世界交互方式的下一个大范式转变。随着技术的成熟，“极其复杂的要求将成为可能，结果会非常复杂，”该报告指出。
准备就绪，设置，实施
人力资源领导者如何应对这些技术进步？Gartner分析师建议他们：
使用AI设计业务场景以通知新业务设计。
通过会话平台和增强现实创造更自然和身临其境的用户体验。
通过开发有针对性的高价值业务案例并确定优先次序来支持物联网举措，以构建数字双胞胎并协同开发云计算和边缘计算。
采用基于风险和信任的不断调整的安全和风险战略方法。
如果你不把这些技术趋势归因于你的创新战略，你就有可能失败。“包括数据科学家，开发人员和业务流程负责人在内的多个选区需要协同工作，”副总裁兼Gartner研究员David Cearley说。
Sweary预测，2018年将是人力资源的一个分水岭年，因为节省时间的技术将释放人力资源团队作为其组织内的战略顾问。
“数字化转型始于对员工的理解，HR将在调整公司文化，人才，结构和流程方面发挥关键作用，确保企业选择合适的工具来提供最佳员工数字体验。”
一个美丽的新世界
当Gartner公司的分析师凝视他们的水晶球时，他们看到了未来的情况：
到2019年
大多数领先的数字资产和产品信息管理系统将实施功能，允许品牌自动公开标签和元数据以改善语音和视觉搜索结果。
所有主要公司和零售商中有一半将重新设计其在线网站以适应语音搜索和语音导航。招聘委员会和招聘人员可以效仿。人才搜索引擎已经开始使用工具来帮助招聘人员找到并联系候选人或特定角色，方法是允许他们提出基于语音的搜索查询。
到2020年
人工智能创造的假冒内容将超过AI检测它的能力，这可能加剧不信任和错误信息的扩散。
到2021年
铁道部企业电子超过50％会花更多的每年创造的机器人和聊天机器人比传统的移动应用程序开发。
大多数 稳定经济体的人们会消费比真实内容更多的虚假信息。
到2022年
物联网（IoT）的所有安全预算中有一半将针对“故障修复，召回和安全故障”，而不是保护。
来源： 2018年前十大技术趋势 （Gartner Inc.）。
以上由AI翻译完成，仅供你参考。HRTechChina倾情奉献，转载请注明HRTechChina
Aliah D. Wright是SHRM的前任编辑，现在负责管理SHRM Speakers Bureau。
人力资源杂志Stephan Schmitz的插图。
n 2018, the physical and digital worlds will continue to merge, as the workplace is reshaped by artificial intelligence (AI), bots, predictive software and augmented reality.
Start by accepting that AI will mold the organizational landscape, especially as intelligent systems learn to adapt to users' needs. "We'll no longer need to learn the software," says Rephael Sweary, president and co-founder of WalkMe, a technology company based in Raleigh, N.C. "AI is already learning more about our individual roles, behaviors and actions to personalize how we use HR and other business software."
Enterprise platforms will also evolve to provide more natural and immersive interactions, according to the Top 10 Strategic Technology Trends for 2018 report from the research firm Gartner.
Such advancements will allow HR professionals to significantly reduce learning and development budgets and resources, as technologies are adopted that can contextually guide people on how to use any system, Sweary says.
The six trends that will affect HR the most in 2018, according to Gartner, will be:
1. Blockchain. This technology holds promise for recruiters hoping to verify candidates more efficiently, and for payroll managers who want to make their organization's global compensation process less costly and more timely. Blockchain uses an encrypted, digital ledger of public records structured into clusters of data called blocks and dispersed over networks. It is a powerful tool that users find reliable and easy to navigate. Experts predict HR will begin using blockchain within the next 18-24 months.
2. AI foundation. Making systems that learn, adapt and act autonomously will be a major focus for technology vendors through at least 2020, Gartner reports. AI will be used to improve decision-making, reinvent work processes and revamp the customer experience. It will drive the return on investment for digital business plans through 2025.
3. Intelligent apps and analytics. Companies are using AI practices to make new app categories, such as virtual customer assistants and bots to improve employee performance, sales and marketing analysis and security. Intelligent apps have the potential to change the nature of work and the structure of the workplace. "When building or buying an AI-powered app, consider where its impact will be in the process of how things get done, analysis, or to improve a users' experience," according to Gartner.
4. Internet of Things (IoT). AI is driving advances for "smart" items such as autonomous vehicles, robots and drones. It is also enhancing many existing products, including Internet-of-things (IoT)-connected consumer and industrial systems. At some point, for instance, HR professionals will need to hire individuals who can operate drones, monitor drone safety and comply with FAA regulations.
5. Digital twins. This tool is a digital representation of a real-world entity or system. Data from multiple digital twins can be aggregated for a composite view across real-world entities. For example, future models of humans could offer biometric and medical data, and digital twins will allow for advanced simulations, the report explains. Digital twins in the context of IoT projects could significantly improve enterprise decision-making by helping users respond to changes, improving operations and enhancing performance.
6. Conversational platforms. Think Alexa or Siri. Within HR, such programs could be applied to improve employee self-service by enabling employees to "talk" to members of your team. These tools will drive the next big paradigm shift in how humans interact with the digital world. As the technology matures, "extremely complex requests will be possible, resulting in highly complex results," the report states.
Ready, Set, Implement
How can HR leaders respond to these technological advancements? Gartner analysts recommend they:
Devise business scenarios using AI to inform new business designs.
Create a more natural and immersive user experience with conversational platforms and augmented reality.
Support IoT initiatives by developing and prioritizing targeted, high-value business cases to build digital twins and exploit cloud and edge computing synergistically.
Adopt a strategic approach to security and risk that continuously adapts based on risk and trust.
If you don't factor these technology trends into your innovation strategies, you risk losing ground. "Multiple constituencies, including data scientists, developers and business process owners, will need to work together," says David Cearley, vice president and Gartner Fellow.
2018 will be a watershed year for HR, Sweary predicts, because time-saving technology will free up HR teams to serve as strategic advisors within their organizations.
"Digital transformation starts with understanding your employees. HR will play a pivotal role in aligning company culture, talent, structure and processes to make sure that businesses select the right tools for delivering the best employee digital experience."
A Brave New World
When analysts at Gartner Inc. gaze into their crystal ball, here's what they see ahead:
By 2019
Most leading digital asset and product information management systems will implement features that allow brands to automatically expose tags and metadata to improve voice and visual search results.
Half of all major companies and retailers will redesign their online sites to accommodate voice searches and voice navigation. Job boards and recruiters may follow suit. Talent search engines are already working on tools to help recruiters find and contact candidates or specific roles by allowing them to pose voice-based search queries.
By 2020
AI-driven creation of fake content will outpace AI's ability to detect it, which could fuel distrust and the proliferation of misinformation.
By 2021
More than 50 percent of companies will spend more per year creating bots and chatbots than on traditional mobile app development.
Most people in stable economies will consume more false information than true content.
By 2022
Half of all security budgets for the Internet of Things (IoT) will be directed toward "fault remediation, recalls and safety failures," rather than protection.
Source: Top 10 Technology Trends for 2018 (Gartner Inc.).
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