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  1. ipl hr system 相關

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  2. Hire, onboard, run payroll, and develop your culture. HR automation and best-in-class support to make you more efficient and effective.

  3. Data World Group的成員之一,為不同行業的客戶提供業務方案。立即與專業團隊了解更多。 擁有超過27年的經驗,為不同行業提供一站式資訊科技解決方案。立即與我們的專業團隊查詢!

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  1. 核心系統. IPL HRMS設計全面,內建強大的HR 核心系統 引擎,由人力資源數據庫、假期管理、薪酬管理以及報告及查詢細緻編織而成,確保所有關鍵的HR運作精準流暢地完成。.

  2. 2019年6月28日 · Hong Kong, June 28, 2019 - C&T's human resources management software IPL HRMS was adopted by one of the world's leading jewelry and watch groups to simplify its HR processes and payroll operations with customized automation to support its retail business growth in Hong Kong.

  3. Hong Kong, September 21, 2022 - C&T’s human resources management software IPL HRMS is helping a major technology research institute in Hong Kong to replace their current HR system with precision payroll automation, digital performance appraisal, mobile self-service and more, greatly enhancing agility and efficiency in HR management. ...

  4. www.iplresearch.com › en › contentOur Profile | IPL HRMS

    IPL HRMS is the market-leading human resources management (HRM) and payroll application software suite of IPL Research Limited (IPL), a subsidiary of Computer And Technologies Holdings Limited ( C&T ). With over 30 years of history since 1989, IPL HRMS has served over 400 enterprise customers spreading over various major cities around the globe.

  5. www.linkedin.com › products › computer-and-technologiesIPL HRMS | LinkedIn

    Improving HR Efficiency With the AI chatbot-enabled IPL HRMS system, employees can ask for information, apply for leave, claim expenses, and handle other HR matters on C&T HCM App. Regardless of ...

  6. HR System or Payroll Processing System (人力資源管理系統), 價錢合理, is your best HR support. Call for free demo ! ADDRESS Luminous Consultancy Ltd., Rm 702, 7/F., Fu Fai Commercial Centre, 27 Hillier Street, Sheung Wan

  7. 全方位勞動力管理: IPL HRMS考勤模組全新升級. 2019年10月18日,香港訊 - 科聯旗下人力資源管理軟件 IPL HRMS 推出考勤模組升級,讓企業透過簡易且高流動性的勞動力管理模式,提升日常業務運作的流暢度。. 過往,人力資源部及經理需要人手收集大量數據再進行 ...

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