创新：背调公司Checkr创建动态背调监控工具以提升Uber乘坐的安全性编者注：值得学习和参考，动态的背景调查很重要啊！国内哪家可以跟滴滴等合作起来！
目前背调都是截止调查的当天。而入职或者开始工作后的情况就很难掌握了！
现代和合规背景调查的领先提供商Checkr今天宣布了一项新技术，该技术可持续更新可能影响共乘驾驶员驾驶资格的犯罪记录。Checker Continuous Check由Uber设计，动态识别可能不合格的记录，以帮助确保驾驶员继续满足优步的安全标准。
Checkr首席执行官Daniel Yanisse表示： “ 凭借当今的按需劳动力，我们需要超越静态背景报告，进行动态筛选。通过持续检查，Checkr为共乘产业创造了新的安全标准将提供关于某人背景变化的重要见解，这可能会影响他们的工作资格。“
优步是第一家采用该技术的公司。使用涵盖大多数新刑事犯罪的数据来源，当司机参与犯罪活动时，持续检查会向优步提供通知。然后，优步可以调查任何可能不合格的信息，例如DUI的新费用和未决费用，以确定该驱动程序是否仍有资格与Uber一起驾驶。这项新技术使优步能够在每年重新进行背景调查之间持续执行其安全标准。
“ 安全对优步至关重要，我们希望确保驾驶员持续不断地达到我们的标准，”优步安全与保险副总裁Gus Fuldner说。“ 这种新的连续检查技术将加强我们的筛选过程并提高安全性。”
最初设计用于满足共乘行业的严格要求，2018年秋季将为所有Checkr客户提供持续检查。
关于Checkr
Checkr的使命是通过提高对过去的理解来建立更公平的未来。我们的平台使数以千计的客户每年能够以gig经济的速度轻松雇用数百万人。使用Checkr先进的背景调查技术，各种规模的公司都能更好地了解不断变化的员工队伍的动态，为他们的招聘带来透明度和公平性，最终为员工创造更美好的未来。
Checkr Creates Dynamic Monitoring Tool to Elevate Safety in Ridesharing
Checkr, the leading provider of modern and compliant background checks, today announced new technology that provides continuous updates about criminal records that may affect ridesharing drivers’ eligibility to drive. Checkr Continuous Check, which was designed with Uber, dynamically identifies potentially disqualifying records to help ensure drivers continue to meet Uber’s safety standards.
“With today's on-demand workforce, there's a need to move beyond static background reports to dynamic screenings," said Daniel Yanisse, CEO of Checkr. "Through Continuous Check, Checkr is creating a new standard of safety for the ridesharing industry and beyond that will provide critical insight into changes in someone's background that may affect their eligibility to work."
Uber is the first company to adopt the technology. Using data sources that cover most new criminal offenses, Continuous Check provides notifications to Uber when a driver is involved in criminal activity. Uber can then investigate any potentially disqualifying information, such as a new and pending charge for a DUI, to determine whether the driver is still eligible to drive with Uber. This new technology allows Uber to continuously enforce its safety standards between annual reruns of background checks.
“Safety is essential to Uber and we want to ensure drivers continue to meet our standards on an ongoing basis,” said Gus Fuldner, Vice President of Safety and Insurance at Uber. “This new continuous checking technology will strengthen our screening process and improve safety.”
Designed initially to meet the stringent requirements of the ridesharing industry, Continuous Check will be available to all Checkr customers in Fall 2018.
About Checkr
Checkr’s mission is to build a fairer future by improving understanding of the past. Our platform makes it easy for thousands of customers to hire millions of people every year at the speed of the gig economy. Using Checkr’s advanced background check technology, companies of all sizes can better understand the dynamics of the changing workforce, bring transparency and fairness to their hiring, and ultimately build a better future for workers. For more information please visit: www.checkr.com.
Google Hire重大更新！全面AI技术支持，简历筛选安排面试将大幅节约时间综合来源/ gadgets google hire blog等
更新要点
Google Hire通过更新获得了新的AI驱动的工具
Google Hire可以更快地安排面试，并在简历中突出显示关键字
雇用1000人以下的美国企业适用Google Hire
随着去年推出Google Hire，Google通过将招聘过程整合到招聘人员，已经花费大量时间去查工具（如Gmail，Google日历和其他G-Suite应用程序），来简化招聘流程。旨在帮助中小型企业有效招聘。招聘人员表示，Hire从根本上改善了他们的工作方式，减少了应用程序之间的上下文切换。
实际上，当他们衡量用户活动时，他们发现Hire减少了完成日常招聘任务的时间 - 比如审查应用程序或安排面试 - 节省时间高达84％。
Google启动AI
通过整合Google AI，Hire现在可以减少重复耗时的任务，如安排面试，进入一键式交互。
这意味着招聘团队可以在后勤上花费更少的时间，更多的时间与人交流。
Hire中的新功能使招聘人员可以做到如下几点：
在几秒钟内安排面试：
招聘人员和招聘协调员花费大量时间在后勤管理 - 查找日历上的可用时间，预订房间，并将正确的信息汇集到预备面试官处。为了简化这一过程，Hire现在使用AI来自动建议面试者和理想时间段，从而将面试计划减少到几次点击。
通过整合Google AI，Hire现在可以将重复耗时的任务减少为一键互动。这意味着招聘团队可以在后勤上花费更少的时间，更多的时间与人交流” 谷歌在其博客文章中表示。 自推出以来，Google Hire带有G Suite集成功能，可让应用程序与Gmail和Google日历等其他应用程序同步工作。Google声称Hire可以减少招聘团队招募任务的时间达84％。
最新的更新基本上整合了Google AI，以减少做任务时的点击次数，让AI建议发挥作用。
Google Hire自动提供面试官和理想时间段，将面试安排减少到几次点击。操作如下：
Photo: Google
它试图减少手工查看日历空闲时间，为您查看并提供理想的时间段。此外，如果面试官最后一分钟取消，Hire不只是提醒你，它还推荐可用的面试官，并可以很容易且快速地邀请面试官。
所以我们可以看到国内外面试安排都是一个复杂而且繁琐的事情，面试管理这块的需求也日益突出。
自动突出显示简历重点
相当一部分招聘人员的时间花在审查简历上（我们都知道这一点）。有人告诉我，当团队正在观看与Hire进行互动的人时，他们发现客户经常使用“Ctrl + F”，通过简历扫描搜索正确的面试者的技能 - 这是一项重复的手动任务，可以轻松实现自动化。
另一个常见的招聘难题是在简历中查找关键字。 Hire的AI现在通过分析工作岗位描述，或搜索查询术语并在简历中突出显示相关单词（包括同义词和缩略词）来节省手动搜索它们的时间，自动为招聘人员找到这些单词。
Photo: Google
点击致电候选人：
无论他们是筛选候选人，进行面试还是跟进录用信，招聘人员每天都会有数十次电话交谈。现在通过点击通话功能简化每个电话对话，并自动记录通话，以便团队成员知道与候选人通话的人员。它是如何工作的，Derek？ 很高兴你问这样的问题！
系统会拨打您要给求职者的电话，然后当您拿起电话时，系统会向求职者拨打该号码。且您永远不会丢失您的收件箱内容，电话会录音，并且您可以在电话中记笔记。我问是否有发信息功能，市场表明，大约98％的人回复短信，很少听到语音信箱或回复他们不认识的号码。
他们向我保证，这个过程非常简单，并且您电话辛苦获取的宝贵数据将会轻松转移。
最后，现在通过点击通话功能简化每个电话对话，并自动记录通话，以便团队成员知道谁已经与候选人通话，而不是多次拨打同一个候选人。
所有那些雇员不足1000人的美国企业都可以购买Hire服务。在中国不行~~
关于Google Hire 从去年7月推出，旨在帮助中小型企业有效招聘。它允许招聘人员将工作发布到多个工作现场，跟踪申请，安排面试，甚至可以在一个平台上获得面试反馈。现在，在一年之后，谷歌已经更新了招聘人工智能驱动工具，以实现“更聪明，更快速的招聘方式”。此更新带来的新功能可以加快日程安排访问速度，为日志记录提供简单的工作，并简化相关简历，从而减少耗时。
“通过整合谷歌AI，服务现在减少重复，耗时的任务，进入一键式的互动。这意味着雇佣团队可以花费更少的时间与物流和更多的时间与人联系”
以上由HRTechChina 综合编译，仅供参考！
Future of Work
2018年06月27日
Future of Work
10 Trends in Workforce Analytics （英文）
Workforce analytics is developing and maturing. These are the 10 major trends for the near future.
1. From one time to real-time
Many workforce analytics efforts start as a consultancy project. A question is formulated (“How do our employees experience their journey?”), many people are interviewed, data is gathered, and with the help of the external consultants a nice report is written and many follow up projects to redesign the employee journey are defined.
A one-time effort is nice, but it might be more beneficial to develop ways to gather more regularly and maybe even real-time feedback from candidates, employees and other relevant groups.
The survey practice is changing. We see organizations using several approaches:
The classic annual or bi-annual employee survey, for a deep dive.
Weekly, monthly or quarterly pulse surveys to gather more frequent feedback. A few questions, often varying the questions per cycle. Some more advanced pulse survey solutions are adaptive: they ask more questions to people when they sense there are issues (“How was your week?”. If the answer is “Very Good”, the survey is finished, if you answer, “Not so good”, there are some follow-up questions). Pulse surveys can also be easily connected to the important “moments that matter” for the employee experience.
Continuous real-time mood measurement. Innovative solutions in this area are still scarce, especially if you want to measure in a passive non-obtrusive way. Keencorp is an example, they analyze aggregated e-mails and can report on the mood (and risks) in different parts of an organization.
In my article Employee mood measurement trends, you can find an extensive overview of mood measurement providers.
2. From people analytics to workforce analytics
Currently, the general opinion seems to be that people analytics is a better label than HR analytics.
Increasingly the workforce is consisting of more than just people. Robots and chatbots are entering the workforce. The first legal discussions have started: who is responsible for the acts of the robots?
If we’re also analyzing robots, we’re moving from people analytics towards workforce analytics. Robot wellbeing and robot productivity is a nice domain for HR to claim.
3. More transparency
This overview of workforce analytics trends cannot be complete without a reference to GDPR. GDPR is fueling a lot of positive developments, one of them being a lot more transparency. About what kind of data is collected, how it is used, and how algorithms are used to make decisions about people.
The issue of data ownership is related. It is expected that employees will no longer accept that they cannot own their own personal data. Employees need to have the possibility to show their data to their potential next employer as evidence for their productivity and engagement.
4. More focus on productivity
In the last years, there has not been a lot of focus on productivity. We see a slow change at the horizon.
Traditionally, capacity problems have been solved by recruiting new people. This has led to several problems. I have seen this several times in fast growing scale-ups.
As the growth is limited by the ability the find new people, the selection criteria are (often unconsciously) lowered, as many people are needed fast. These new people are not as productive as the existing crew. Because you have more people, you need more managers. Lower quality people and more managers lowers productivity.
Another approach is, to focus more on increasing the productivity of the existing employees, instead of hiring additional staff, and on improving the selection criteria.
Using workforce analytics, you can try to find the characteristics of top performing people and teams, and the conditions that facilitate top performance.
These findings can be used to increase productivity and to select candidates that have the characteristics of top performers. When productivity increases, you need less people to deliver the same results.
A related read on this topic are the 3 reasons to stop counting heads.
5. What is in it for me?
A lack of trust can influence many workforce analytics efforts. If the focus is primarily on efficiency and control, employees will doubt if there are any benefits for them.
Overall there is a shift to more employee-centric organizations, although sometimes you can doubt how genuine the efforts are to improve the employee experience.
Asking the question: “How will the employees benefit from this effort?” is a good starting point for most workforce analytics projects. It also helps to create buy-in, which becomes increasingly important with the introduction of the GPDR.
6. From individuals to teams to networks
Many workforce analytics projects today are still focused on individuals. What are the characteristics of our top performers? How can we measure the individual employee experience? How can we decrease absenteeism?
Earlier, I gave an overview to what extend current HR practices are focused on teams.
As you can see in the table, most of the practices are still very focused on the individual. Workforce analytics can help to improve the way teams and networks function in and across organizations. The rise of Organizational Network Analysis is one of the promising signs.
7. Cracks in the top-down approach
The tendency to implement changes top-down, is still common.
We like uniformity and standardization. In our central control room, we look at our dashboard, and we know we need to act when the lights are turning from green to orange.
HR finds it difficult to approach issues in a different way. Performance management is a good example. Changing the performance management process is often tackled as an organization-wide issue, and HR needs to find the new uniform solution.
In line with the trend called “the consumerization of HR”, employees are expected to take more initiative. Employees are increasingly tired of waiting for the organization and HR, and want to be more independent of organizational initiatives.
If you want feedback, you can easily organize it yourself, for example with the Slack plug-in Captain Feedback. A simple survey to measure the mood in your team is quickly built with Polly (view: “How to measure the mood in your team with Slack and Polly“). Many employees are already tracking their own fitness with trackers like Fitbit and the Apple Watch.
Many teams primarily use communication tools as WhatsApp and Slack, avoiding the officially approved communication channels. HR might go with the flow, and tap on to the channels used, instead of trying to promote standardized and approved channels.
How can workforce analytics benefit from the data gathered by on their employee’s own devices? If it is clear, what the benefits are for employees to share their data, they might be able to help to enrich the data sets and improve the quality of workforce analytics.
8. Ignoring the learning curve
In their book “Making HR measurement strategic”, Wayne Cascio and John Boudreau presented an often-quoted picture, with the title “Hitting the “Wall” in HR measurement”. The wall was the wall between descriptive and predictive analytics.
There are many more overviews with the people analytics maturity levels. Generally, the highest level is predictive analytics.
Patrick Coolen of ABN AMRO Bank recently mentioned a next level: continuous analytics, and he introduced a second wall, the wall between predictive analytics and continuous analytics.
As predictive analytics seems to be the holy grail, many HR teams want to jump immediately to this level. Let’s skip operational reporting, advanced reporting and strategic analytics. We can leapfrog, ignore the learning curve, and jump to the highest level in one step.
For many teams, ignoring the learning curve does not seem to be a sensible strategy. Maybe it is better to learn walking before you start running.
9. Give us back our time!
Recently I spoke to HR professionals from big multinationals who were involved in a “Give us back our time” projects.
In their organizations, the assignment to all staff groups was: stop using (meant was: wasting) more and more time of the employees and managers, please give us some time back!
An example that was mentioned concerned performance management. In this organization, they calculated that all the work around the performance management process for one employee costed manager and employee around 10 hours (preparation, two formal meetings per year, completing the online forms, meeting with HR to review the results etc.).
By simplifying the process (no mandatory meetings, no forms, no review meetings, just one annual rating to be submitted per employee by the manager), HR could give back many hours to the organization – to the relief of both managers and employees.
Big HR systems generally promise a lot. But before the system can live up to the high expectations, a lot of work needs to be done. Data fields must be defined. Global processes must be standardized. Heritage systems must be dismantled.
This results in a lot of work (and agony), for employees, for managers, for HR and for the implementation partners (who do not mind).
Workforce analytics can help a lot in the “give-us-time-back” projects, for example by some simple time-measurement. Measure the time a sample of managers, employees, and HR professionals spend on different activities, and estimate the value these activities optimizes the core activities of the organization (e.g. serving clients and bringing in new clients).
10. Too high expectations
The expectations of workforce analytics are often too high. Two elements must be considered.
In the first place, human behavior is not so easy to predict, even if you have access to loads of people data.
Even in domains where good performance is very well defined and where a lot of data is gathered inside and outside the field, as for example in football, it is very difficult to predict the future success of young players.
Secondly, the question is to what extend managers, employees and HR professionals behave in a rational way. All humans are prone to cognitive biases, that influence the way they interpret the outcomes of workforce analytics projects. Some interesting articles on this subject are why psychological knowledge is essential to success with people analytics, by Morten Kamp Andersen, and The psychology of people analytics, written by myself.
A more general thought: what if you replaced ‘Workforce analytics’ with ‘Science’? What is the role of science in HR? The puzzle is, that there are many scientific findings that have been available for a long time but that are hardly used in organizations.
Example: it has been proven repeatedly, that the (unstructured) interview is a very poor selection instrument.
But still, most organizations still rely heavily on this instrument (as people tend to overestimate their own capabilities). Why would organizations rely on the outcomes of workforce analytics, when they hardly use scientific findings in the people domain?
An interesting presentation on this topic that I recommend is by Rob Briner, titled evidence-based HR, what is it and is it really happening?
There’s a lot that’s changing in the world of work. These are the 10 trends in workforce analytics that I’m seeing today and that will likely impact the way we work in the near future.
This article is based on a keynote I gave at the Workforce Analytics Forum in Frankfurt, Germany, on April 18, 2018.
by Tom Haak
Tom Haak is the director of the HR Trend Institute The HR (Human Resources) Trend Institute follows, detects and encourages trends. In the people and organization domain and in related areas. Where possible, the institute is also a trend setter. Tom has an extensive experience in HR Management in multinational companies. He worked in senior HR positions at Fugro, Arcadis, Aon, KPMG and Philips Electronics. He holds a master’s degree in Psychology. Tom has a keen interest in innovative HR, HR tech and how organizations can benefit from trend shifts. Twitter: @tomwhaak
刚刚，Workday 宣布收购Rallyteam，增强智能人才优化功能Workday Adds More Intelligence to Optimize Talent with Rallyteam Acquisition
Workday 刚刚宣布，收购Rallyteam ,Rallyteam总部位于旧金山，联合创始人兼CEO David Somers，创建于2013年，2014年产品上线，收购金额没有公布~
在2017年，HRTechChina报道过Rallyteam获得融资860万A轮融资，详细可以看新闻：Rallyteam完成860万美元A轮融资 。
Rallyteam 创办的原因在于CEO自己发现在工作中越来越沮丧，因为在当前组织中的发展和好的机会很难被发现（换岗），于是希望能够找到好的解决方案，于是乎就创建了这个公司，最早是有微软加速器孵化~~
关于Rallyteam在做什么，可以看这里：
Rallyteam发现，有才干的员工经常因为工作挑战不够，或不符合自己的职业生涯规划而离职。这家创企正在和eBay等公司合作，提高员工留职率。
近日，Rallyteam完成860万美元融资，Norwest Venture Partners领投。Storm Ventres、Cornerstone OnDemand和Wilson Sonsini跟投。
Rallyteam联合创始人兼CEO David Somers表示，他们所合作的都是员工人数超过5000的企业。
该公司拥有一套软件，能够利用公共数据来为内部员工建立档案，然后办起“媒人”的角色，帮员工寻找工作机会和特殊项目。
Somers说，他们希望“找到拥有相应技能，并正在寻求新挑战的人”。
以下为官方宣布新闻：
我们很高兴地宣布Workday通过收购Rallyteam不断投资于机器学习的努力再次迈出了一步！
通过Rallyteam，我们获得了令人难以置信的团队成员，他们创建了一个人才流动平台，使用机器学习，通过将员工的兴趣，技能和关系与相关工作，项目，任务和人员进行匹配，帮助公司更好地理解和优化员工队伍。
随着工作世界继续向人才和技能市场迈进，该团队将利用其深厚的专业知识为Workday的产品提供更强大的智能，帮助客户发现组织内外最优秀的人才，以满足业务需求。
对于Workday和我们的客户来说，这是一个激动人心的时刻，所以请加入我们，欢迎我们的新同事们，并在未来的一年中继续关注更多细节！
We’re excited to announce another step in Workday’s efforts to continually invest in machine learning with the acquisition of Rallyteam!
With Rallyteam, we gain incredible team members who created a talent mobility platform that uses machine learning to help companies better understand and optimize their workforces by matching a worker’s interests, skills, and connections with relevant jobs, projects, tasks, and people.
As the world of work continues moving toward a marketplace for talent and skills, this team will apply its deep expertise to power Workday’s products with even more intelligence that will help customers uncover the best talent—inside and outside of their organizations—to meet business needs.
It’s an exciting time for Workday and our customers, so please join us in welcoming our new colleagues, and stay tuned for more details in the coming year!
Future of Work
2018年06月09日
Future of Work
区块链真的会影响人才的获取吗?
“区块链使得rolodex和数据库方法基本无用。由于雇主可以即时查看技能，认证，证书和工作历史，因此许多高管招聘人员和猎头人员今天所做的初步审查可能会变得不那么有价值。“ - Maren Hogan
只要我一直在招聘和人力资源领域，人们已经谈论了未来的劳动力。每一个新的技术浪潮都应该让我们更接近这一点，而且在很多情况下，它们都有。我们被告知，未来的劳动力将更加全球化，痛苦点少得多，并且允许更多的候选人在组织，教育机构之间以及他们自己的职业道路之间进行无缝转移。
技能将成为候选人工作时间和地点的基础，而采购和培训对于雇主和工作人员而言将更少公司和地点，更简单。
事实上，随着员工队伍和经济的兴起，我们看到这一愿景的一部分成为现实，这些经济建立在旨在利用“喧嚣”的市场上。雇主有一系列的选择来满足他们的需求，除此之外典型的FTE路线。但是这使得很难找到适用于内部员工和外包员工的解决方案。关于向两个劳动力提供什么的平等问题正在合理地提出。
根据IDC的报告，2018年区块链解决方案的全球支出将达到21亿美元，而2017年的支出为9.45亿美元。自2017年秋季以来，围绕招聘和人力资源区块链的嗡嗡声一直在缓慢增长。起初，我只是感兴趣，因为我认识一个拥有大量比特币的人。然而，很明显，这将实质上改变人力资源。现在已经出现了几种“转型”技术，我是...怀疑。我的意思是，我经营一家B2B营销机构。我的中间名称是“变革技术”。所以我决定做一些挖掘。
几乎在我们学习区块链技术如何改变金融业的同时，我们看到了随机劳动力和商业经济的兴起（这两者也应该改变经济，在这两种情况下，都已经开始了至）。大数据和人工智能，以前的技术变革宠儿，正在接受新的审查，因为我们都知道他们到底是什么。
所以这里是区块链如何真正影响您的招聘需求。
猎头和猎头可能会受到打击。由于区块链使得信息无缝，透明和难以拟定，候选人以过去无法控制的方式控制自己的信息，因此TPR可能难以出售其作为仲裁者或信息监护人的服务。区块链使得rolodex和数据库方法基本无用。由于雇主可以即时查看技能，认证，证书和工作历史，因此许多高管招聘人员和猎头人员今天所做的初步审查可能会变得不那么有价值。更多（更好）审查候选人。区块链将允许候选人自己存储安全，私人和预先验证的凭证，从而减少运行背景调查所需的时间，以及像雅虎和RadioShack的前首席执行官一样的欺诈性教育声明（两位高管都说谎拥有大学学位）如果招聘人员和招聘经理可以立即看到候选人的技能，他们可以更好地匹配技能，并轻松消除那些不合格的人。
更容易遵守。任何在HR工作的人都知道保持员工记录的合规性是多么重要。当然，由于许多人力资源部门在多个地点管理多种类型的工作人员，其中许多人可能有不同的规章制度，因此，临时工和全球化使得这种工作变得非常复杂。如今的数字存储系统经常处理个人员工数据丰富的人力资源，容易受到可能导致欺诈或身份盗用的网络攻击。区块链的网络安全应用程序可以缓解这些风险，并使企业，特别是小型企业的合规性变得更加容易，这些企业可能没有超安全的做法。
入职和人力资源管理任务完成。虽然有一些很棒的无纸化和在线入门平台，但许多公司仍然需要通过重复的文书工作，背景筛选，参考检查和输入信息来进行沟通。区块链技术的一个关键优势是它所保存的数据不能被更改或删除，并且系统要求连接到每个区块的每个人都同意允许添加信息。这意味着不正确的信息或重复的记录将成为过去，大大降低了人力资源管理的两大部分 - 新员工和工资核算的行政和后台性质。
学习和发展可能会更好。我们已经知道，今天的员工队伍想要规划自己的职业生涯，所以终身组织的员工（大部分）都是过去的事情。这让雇主很难找出如何教育他们的员工。古老的格言“如果我们花这么多时间和金钱来训练他们，然后他们离开？”（接着是同样乏味的回答：如果你不花时间和金钱训练他们，他们留下来怎么办？）最后是用区块链回答。内部培训计划和技能验证可以跟随候选人，无论他们是FTE还是临时工。
好极了！我们实际上可能会减少'realsy'的招聘偏好。在我们目前的系统中，候选人几乎不能控制谁看到他们的信息，图片，简介，简历等。通过候选人控制自己的区块链，不仅可以保护候选人档案的某些部分，但它这可能是雇主采取积极措施，以防止偏见和雇用纯粹基于技能。种族，年龄，性别都可以从搜索中删除，甚至可以避免无意识的偏见。
让员工多元化的一种更简单的方法，尤其是在您从事医疗，金融或技术工作的情况下。采购和招聘继续按照他们一段时间的相同步伐进行。但是，如果检查候选人是否符合资格要快得多，请确定他们是否具有合格资格，或者他们是否有权在您的国家或州工作; 临时工，合同雇用和工作人员成为整个员工中更容易和无缝的部分。区块链对金融世界的影响使得任何地方的工作人员都能以自己的货币进行支付，从而使全球经济向小型企业又迈进了一步。
Maren Hogan
Maren Hogan是人力资源和招聘行业的经验丰富的营销人员和社区建设者。她领导Red Branch Media，一家提供营销策略和内容开发的咨询公司。Hogan一直倡导下一代营销技术，他已经建立了多个成功的在线社区，在B2B和B2C部门都部署了品牌战略，并在招聘和人才空间领域发挥了多产的思想领导力。
以上由HRTech AI 翻译完成，仅供参考！
英文原文请看：
For as long as I’ve been around the recruiting and HR space, people have talked about the workforce of the future. Every new wave of technology was supposed to bring us closer to this, and in many cases, they have. The workforce of the future, we were told, would be more global, have far fewer pain points and allow more candidates to transfer seamlessly between organizations, educational institutions and within their own career paths.
Skills would be the basis for when and where a candidate worked, while sourcing and training would be less company and location-focused and simpler for both employers and workers.
In truth, we are seeing parts of this vision coming true with the rise of the contingent workforce and the gig economy, built on the marketplaces designed to capitalize on the “side hustle.” Employers have a range of choices to fulfill their demands, besides the typical FTE route. But this has made it difficult to find solutions that work for both internal employees and outsourced workers. Questions about equity between what is offered to both workforces are being rightfully raised.
According to an IDC report, global spending on blockchain solutions will reach $2.1 billion in 2018 compared to the $945 million spent in 2017. Since the fall of 2017, the buzz around blockchain for recruiting and HR has been slowly building. Initially, I was only interested because I knew someone with a ton of bitcoin. However, it became clear that this was going to essentially transform HR. Having been around for several “transformational” technologies now, I was… suspect. I mean, I run a B2B marketing agency. My middle NAME is “transformational technology.” So I decided to do some digging.
At around the same time as we were learning how blockchain technology could transform the financial industry, we were seeing the rise of the contingent workforce and the gig economy (both of which were also supposed to transform the economy and in both cases, have already started to). Big Data and AI, formerly technology transformation darlings, were being subjected to new scrutiny as we all learned what the hell they were.
So here’s how blockchain will ACTUALLY impact your hiring needs.
More (and better) vetted candidates. Blockchain will allow secure, private and pre-validated credentials to be stored by the candidates themselves, reducing the time it takes to run background checks and fraudulent educational claims like those of former CEOs of both Yahoo and RadioShack (both executives lied about having college degrees.) If recruiters and hiring managers can instantly see candidate skills they can better match skills and easily eliminate those who aren’t qualified.
Executive search and headhunting may take a hit. Since blockchain makes information seamless, transparent and hard to fudge, and candidates control their own information in a way they haven’t been able to in the past, TPRs may have difficulty selling their services as arbiters or guardians of information. Blockchain makes the rolodex and database approach essentially useless. Because employers can instantly view skills, certifications, credentials and work history, the initial vetting many executive recruiters and headhunters do today, may become less valuable.
Easier compliance. Anyone working in HR knows how important it is to stay compliant with employee records. Of course, the contingent workforce and globalization have made this vastly more complicated, since many HR departments are managing multiple types of workers in multiple locations, many of which may have different rules and regulations. Today’s digital storage systems for the wealth of personal employee data HR handles regularly, are vulnerable to cyber attacks that can lead to fraud or identity theft. Blockchain’s cyber security application can mitigate these risks and make compliance much easier for businesses, particularly small businesses, who may not have hyper-secure practices.
Onboarding and HR admin tasks, done. While there are some great paperless and online onboarding platforms, many companies still have to wade through duplicate paperwork, background screenings, reference checks and inputting information. A key advantage of the blockchain technology is the data it holds cannot be changed or deleted and the system requires everyone connected to each block to agree to allow information to be added. This means incorrect information or duplicate records will be a thing of the past, dramatically reducing the administrative and back-office nature of onboarding and payroll, two giant sections of the HR purview.
Learning and development could get MUCH better. We already know that today’s workforce wants to plan their careers, so lifelong organizational employees are (mostly) a thing of the past. That’s made it difficult for employers to figure out how to educate their employees. The old adage “What if we spend all this time and money training them and then they leave?” (followed by the equally tedious rejoinder: What if you don’t spend all this time and money training them and they stay?) is finally answered with blockchain. Internal training programs and skills verification could follow the candidate, whether they’re an FTE or a contingent worker.
Yay! We might ACTUALLY reduce hiring bias for ‘realsies.’ In our current system, candidates have very little control over who sees their information, picture, profile, resume, etc. With the candidate in control of their own blockchain, not only is it possible to protect certain parts of a candidates profile, but it may be a proactive step taken by the employer to prevent bias and hire solely based on skills. Race, age, gender could all be removed from the search, allowing even unconscious biases to be prevented.
An easier way to diversify your workforce, especially if you work in healthcare, finance or technology. Sourcing and recruiting continue to move at the same pace they have for awhile. However, when it’s exponentially faster to check if a candidate is qualified, figure out if they’re properly credentialed or they have the right to work in your country or state; contingent workers, contract hiring and gig workers become a much easier and seamless part of your overall workforce. The impact of blockchain on the world of finance allows workers anywhere to be paid in their own currency, bringing the global economy one step closer to smaller businesses.
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