12个招聘趋势(英文短句)12 trends in recruitment
12 trends in recruitment.
Focus on the candidate experience
Speed!
Advanced profiling
From active to passive candidates
AI powered recruitment and selection
From fixed jobs to fluid roles
Communities
Chatbots
Looking for cultural and personality fit
Fun
Purpose
Teams and Networks
作者:Tom Haak
Tom Haak is the founder and director of The HR Trend Institute. Prior to founding the HR Trend Institute in 2014, Tom held senior HR positions in companies as Arcadis, Aon, KPMG and Philips. The HR Trend Institute detects, follows and encourages smart and creative use of trends in the field of people and organizations, and also in adjacent areas.
招聘趋势
2018年12月24日
招聘趋势
人工智能如何改变人才获取 How Artificial Intelligence Is Changing Talent Acquisition现在大家都在关注招聘AI,并就如何改变招聘方式进行了大量的讨论。招募人工智能是下一代软件,旨在改进或自动化招聘工作流程的某些部分。
作者:Ji-A Min
人工智能对招聘的兴趣已经由三大趋势引发
经济的改善:最近的经济收益创造了一个候选人驱动型市场,这使得人才竞争比以往更加激烈。这一竞争只会继续增加 - LinkedIn调查的 56%的人才招聘领导者认为他们的招聘数量将在2017年增长。
对更好技术的需求:虽然人才招聘预计会增加,但是66%的人才招聘负责人表示他们的招聘团队将保持相同规模甚至缩小规模。这意味着时间有限的招聘人员需要更好的工具来有效地简化或自动化他们的工作流程的一部分,理想情况下用于最耗时的任务。
数据分析的进步:随着技术变得快速和成本效益足以收集和分析大量数据,人才招聘领导者越来越多地要求他们的招聘团队展示基于数据的雇佣质量指标,如新员工的表现和营业额。
人工智能在招聘中越来越受欢迎,这为招聘人员提高他们的能力提供了令人兴奋的机会,但同时也存在很多关于如何最佳利用人才的困惑。
为了帮助您理解这一切,以下是招聘人工智能最有前途的三个应用程序。
应用#1:AI用于候选人采购
候选人采购仍然是一个主要的招聘挑战:最近的一项调查发现,46%的人才招聘领导表示他们的招聘团队正在为吸引合格的候选人而奋斗。
候选人采购人工智能技术可以搜索人们离线的数据(例如简历,专业投资组合或社交媒体档案),以找到符合您工作要求的被动候选人。
这种用于招聘的AI可以简化采购流程,因为它可以同时搜索多个候选人来源。这取代了自己手动搜索它们的需求,并可能节省每个请求的小时数。您节省采购的时间可以用来吸引,预选和面试最强大的候选人。
应用#2:人工智能进行候选人筛选
当您收到的75-88%的简历不合格时,很容易明白为什么简历筛选是招聘中最令人沮丧和耗时的部分。对于零售和客户服务等大批量招聘,大多数招聘团队没有时间手动筛选他们每个公开角色收到的数百到数千份简历。
AI筛选旨在自动执行简历筛选流程。这种智能筛选软件通过使用岗位聘用数据(例如业绩和营业额)为新申请人提供招聘建议,为ATS增添了功能。
它通过应用所学到的关于现有员工的经验,技能和其他资质的信息来自动筛选和评分新候选人,从而提出这些建议。这种类型的技术还可以通过使用关于以前的雇主和候选人的社交媒体档案的公共数据源来丰富简历。
AI进行简历筛选可实现低价值,重复性任务,并允许招聘人员将时间重点放在更高价值的优先事项上,如与候选人交谈并与其进行交流以评估他们的适合度。
应用#3:AI用于候选人匹配
与采购相比,候选人匹配可能是一个更大的挑战:52%的招聘人员表示,他们工作中最难的部分是从大型申请人池中确定合适的人选。
用于候选人匹配的AI使用一种算法来识别打开的请求的最强匹配。匹配算法分析候选人的个性特征,技能和工资偏好等多种数据来源,根据工作要求自动评估候选人。
例如,LinkedIn求职公告通过将求职者描述中的技能与其LinkedIn个人资料中的申请人技能进行匹配来对候选人进行排名。人才市场使用匹配算法来匹配候选人社区以开放角色。这些人才市场通常迎合特定的候选技能,如软件开发或销售。
人工智能匹配用于从那些已经加入并且正在积极寻找新角色或者对新机会非常开放的人中找出最合格的候选人。这意味着招聘人员不需要浪费时间来吸引那些对新角色不感兴趣的被动应聘者。
关于人工智能的力量,让候选人与工作岗位相匹配的不同观点,请参阅“ 尽管您阅读或听取的内容,采购活动和确实如此”。
AI和招聘的未来
专家预测人工智能招聘会转变招聘人员的角色。由于低价值,耗时的招聘任务通过人工智能技术变得简化和自动化,招聘人员的角色有可能变得更具战略性。
了解AI如何提高其能力的招聘人员将通过在采购,简历筛选和候选人匹配方面节省几十个小时,从而提高效率。
人工智能招聘承诺释放招聘人员与候选人交流的时间,以确定合适人选,并确定候选人的需求并希望说服他们担任角色。它有可能授权他们与招聘经理和人才招聘领导者合作,根据未来增长和收入计划积极的招聘举措,而不是反应性回填。
了解如何最好地利用这项新技术的招聘人员将获得更高的KPI,如更高的招聘质量和更低的营业额。
以上由AI翻译完成。供参考
How Artificial Intelligence Is Changing Talent Acquisition
AI for recruiting is on everyone’s mind these days with a lot of talk on how it’s going to transform recruiting. Artificial intelligence for recruiting is the next generation of software designed to improve or automate some part of the recruiting workflow.
Interest in AI for recruiting has been sparked by three major trends:
The improving economy: The recent economic gains have created a candidate-driven market that’s made competing for talent tougher than ever. This competition will only continue to increase – 56% talent acquisition leaders surveyed by LinkedIn believe their hiring volume will grow in 2017.
The need for better technology: Although hiring is predicted to increase, 66% of talent acquisition leaders state their recruiting teams will stay the same size or even shrink. This means time-constrained recruiters need better tools to effectively streamline or automate a part of their workflow, ideally for tasks that are the most time-consuming.
The advancements in data analytics: As technology becomes fast and cost-effective enough to collect and analyze vast quantities of data, talent acquisition leaders are increasingly asking their recruiting teams to demonstrate data-based quality of hire metrics such as new hires’ performance and turnover.
The growing popularity of AI for recruiting represents exciting opportunities for recruiters to enhance their capabilities but there’s also a lot of confusion about how to best leverage it.
To help you make sense of it all, here are the three most promising applications for AI for recruiting.
Application #1: AI for candidate sourcing
Candidate sourcing is still a major recruiting challenge: a recent survey found 46% of talent acquisition leaders say their recruiting teams struggle with attracting qualified candidates.
AI for candidate sourcing is technology that searches for data people leave online (e.g., resumes, professional portfolios, or social media profiles) to find passive candidates that match your job requirements.
This type of AI for recruiting streamlines the sourcing process because it can simultaneously search through multiple sources of candidates for you. This replaces the need to manually search them yourself and potentially saves you hours per req. The time you save sourcing can be spent attracting, pre-qualifying, and interviewing the strongest candidates instead.
Application #2: AI for candidate screening
When 75-88% of the resumes you receive are unqualified, it’s easy to see why resume screening is the most frustrating and time-consuming part of recruiting. For high-volume recruitment such as retail and customer service roles, most recruiting teams just don’t have the time to manually screen the hundreds to thousands of resumes they receive per open role.
AI for screening is designed to automate the resume screening process. This type of intelligent screening software adds functionality to the ATS by using post-hire data such as performance and turnover to make hiring recommendations for new applicants.
It makes these recommendations by applying the information it learned about existing employees’ experience, skills, and other qualifications to automatically screen and grade new candidates. This type of technology can also enrich resumes by using public data sources about previous employers and candidates’ social media profiles.
AI for resume screening automates a low-value, repetitive task and allows recruiters to re-focus their time on higher value priorities such as talking and engaging with candidates to assess their fit.
Application #3: AI for candidate matching
Candidate matching can be an even bigger challenge than sourcing: 52% of recruiters say the hardest part of their job is identifying the right candidates from a large applicant pool.
AI for candidate matching uses an algorithm to identify the strongest matches for your open req. Matching algorithms analyze multiple sources of data such as candidates’ personality traits, skills, and salary preferences to automatically assess candidates against the job requirements.
For example, a LinkedIn job posting ranks candidates by matching the skills on your job description to applicants’ skills on their LinkedIn profiles. Talent marketplaces use matching algorithms to match their community of candidates to open roles. These talent marketplaces usually cater to specific candidate skill sets such as software development or sales.
AI for matching is used to identify the most qualified candidates from those who have opted-in and are either actively looking for a new role or are very open to a new opportunity. This means recruiters don’t need to waste time trying to attract passive candidates who just aren’t interested in a new role.