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| 授課地點(diǎn)及時(shí)間 |
上課地點(diǎn)：【上海】：同濟(jì)大學(xué)(滬西)/新城金郡商務(wù)樓(11號(hào)線(xiàn)白銀路站) 【深圳分部】：電影大廈(地鐵一號(hào)線(xiàn)大劇院站)/深圳大學(xué)成教院 【北京分部】：北京中山學(xué)院/福鑫大樓 【南京分部】：金港大廈(和燕路) 【武漢分部】：佳源大廈（高新二路） 【成都分部】：領(lǐng)館區(qū)1號(hào)（中和大道） 【廣州分部】：廣糧大廈 【西安分部】：協(xié)同大廈 【沈陽(yáng)分部】：沈陽(yáng)理工大學(xué)/六宅臻品 【鄭州分部】：鄭州大學(xué)/錦華大廈 【石家莊分部】：河北科技大學(xué)/瑞景大廈
開(kāi)班時(shí)間(連續(xù)班/晚班/周末班）：2020年3月16日 |
| 課時(shí) |
◆資深工程師授課
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☆若學(xué)員成績(jī)達(dá)到合格及以上水平，將獲得免費(fèi)推薦工作的機(jī)會(huì)
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| 質(zhì)量以及保障 |
☆
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☆課程大綱☆ |
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- Introduction
-
- 1. Why is People Analytics relevant today?
- a. Industry trends
- b. Where People Analytics are heading
- c. Key messages from People Analytics leaders
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- 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.
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- 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
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- 7. Summary
- a. Outlining next steps
- b. Commitment
- c. Support needed – where to find it--
-
- Summary and Conclusion
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