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授课地点及时间 |
上课地点:【上海】:同济大学(沪西)/新城金郡商务楼(11号线白银路站) 【深圳分部】:电影大厦(地铁一号线大剧院站)/深圳大学成教院 【北京分部】:北京中山学院/福鑫大楼 【南京分部】:金港大厦(和燕路) 【武汉分部】:佳源大厦(高新二路) 【成都分部】:领馆区1号(中和大道) 【广州分部】:广粮大厦 【西安分部】:协同大厦 【沈阳分部】:沈阳理工大学/六宅臻品 【郑州分部】:郑州大学/锦华大厦 【石家庄分部】:河北科技大学/瑞景大厦
开班时间(连续班/晚班/周末班):2024年12月30日 |
课时 |
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质量以及保障 |
☆
1、如有部分内容理解不透或消化不好,可免费在以后培训班中重听;
☆ 2、在课程结束之后,授课老师会留给学员手机和E-mail,免费提供半年的课程技术支持,以便保证培训后的继续消化;
☆3、合格的学员可享受免费推荐就业机会。
☆4、合格学员免费颁发相关工程师等资格证书,提升您的职业资质。 |
☆课程大纲☆ |
|
- Introduction
-
- 1. Why is People Analytics relevant today?
- a. Industry trends
- b. Where People Analytics are heading
- c. Key messages from People Analytics leaders
-
- 2. Introduction to the foundational pillars of People Analytics
- a. Workforce Planning Analytics Pillar
- b. Sourcing and Recruitment Analytics Pillar
- c. Acquisition/Hiring Analytics Pillar
- d. The other pillars and their relevance to Talent Analytics.
-
- 3. Key metrics
- a. Workforce planning – KBI whitebook review of large organization
- b. Talent Analytics - KBI whitebook review of large organization
- c. Sourcing analytics - KBI whitebook review of large organization
-
- 4. Workforce and Talent Acquisition Planning Analytics
- a. What Is Workforce Planning?
- b. Workforce Planning Analytics
- c. Why Should You Care About Workforce Planning Analytics?
- d. Key Components of Talent Acquisition Analytics
- e. Making an IMPACT with Workforce Planning Analytics
- f. Workforce Planning Analytics Best Practices: Dos and Don’ts
- g. Case studies review
-
- 5. Talent Sourcing Analytics
- a. The Business Case for Talent Sourcing Today
- b. Why You Need to Care about Your Talent Sourcing Today
- c. Talent Sourcing in the Era of Big Data and Advanced
- d. Technology
- e. The Mobile Impact on Talent Sourcing
- f. Putting the IMPACT Cycle into Action
- g. Case studies review
-
- 6. Talent Acquisition Analytics
- a. What Is Talent Acquisition Analytics?
- b. How Talent Acquisition Works
- c. Application Phase
- d. Preinterview Assessment Analytics
- e. Interviews: Separating the Wheat from the Chaff
- f. Putting It All Together: Predictive Analytics for Selection
- g. Case studies review
-
- 7. Summary
- a. Outlining next steps
- b. Commitment
- c. Support needed – where to find it--
-
- Summary and Conclusion
|