Khóa Học Lương 3P Uy Tín: Chìa Khóa Nâng Tầm Sự Nghiệp Của Bạn

Bạn có đang cảm thấy công sức mình bỏ ra chưa được đền đáp xứng đáng? Bạn muốn một mức lương tương xứng với năng lực và đóng góp của mình? Bạn nghe nhiều về "lương 3P" nhưng vẫn còn mơ hồ và không biết bắt đầu từ đâu? Nếu câu trả lời là CÓ, thì bài viết này chính là dành cho bạn!

Trong bối cảnh thị trường lao động ngày càng cạnh tranh, lương 3P đang nổi lên như một xu hướng tất yếu, mang đến sự công bằng, minh bạch và động lực cho người lao động. Nhưng lương 3P là gì? Tại sao nó lại quan trọng? Và làm thế nào để bạn có thể nắm bắt được cơ hội này thông qua một khóa học uy tín? Chúng ta hãy cùng tìm hiểu chi tiết.

1. Lương 3P là gì và tại sao lại quan trọng?

Lương 3P là gì?

P1 - Pay for Position (Công việc): Đây là phần lương cơ bản được xác định dựa trên giá trị và tầm quan trọng của vị trí trong cơ cấu tổ chức. Mỗi vị trí sẽ có một khung lương nhất định, phản ánh mức độ phức tạp, yêu cầu về kỹ năng và trách nhiệm.

P2 - Pay for Person (Năng lực cá nhân): Phần này đánh giá và trả lương dựa trên trình độ, kỹ năng, kinh nghiệm và năng lực chuyên môn của từng cá nhân. Một người có năng lực vượt trội, dù ở cùng vị trí, vẫn có thể nhận được mức lương cao hơn người khác.

P3 - Pay for Performance (Hiệu suất công việc): Đây là phần lương biến đổi, dựa trên kết quả và hiệu suất làm việc thực tế của mỗi cá nhân hoặc đội nhóm. P3 khuyến khích sự nỗ lực và đóng góp cụ thể vào mục tiêu chung của tổ chức.

Nhằm thúc đẩy hiệu suất của cả công ty.

Tại sao lương 3P lại quan trọng?

Công bằng và minh bạch: Lương 3P giúp tạo ra một hệ thống trả lương rõ ràng, công bằng, tránh tình trạng trả lương chỉ phụ thuộc vào vị trí không quan trọng hiệu suất làm việc ra sao. 

Thúc đẩy hiệu suất: P3 trực tiếp gắn kết thu nhập với kết quả công việc, tạo động lực mạnh mẽ để nhân viên nỗ lực đạt và vượt mục tiêu.

Phát triển cá nhân: P2 khuyến khích nhân viên tự nâng cao năng lực, học hỏi và phát triển bản thân để xứng đáng với mức lương cao hơn.

Giữ chân nhân tài: Một hệ thống lương 3P hấp dẫn và cạnh tranh giúp doanh nghiệp thu hút và giữ chân những nhân tài chất lượng cao.

Tối ưu hóa chi phí nhân sự: Doanh nghiệp có thể phân bổ ngân sách lương hiệu quả hơn, đảm bảo chi trả đúng người, đúng việc, đúng hiệu quả.

Khóa học lương 3P uy tín: Đầu tư cho tương lai sự nghiệp

Nắm bắt được tầm quan trọng của lương 3P, nhiều cá nhân và doanh nghiệp đang tìm kiếm các giải pháp để hiểu sâu và áp dụng mô hình này một cách hiệu quả. Và một khóa học lương 3P uy tín chính là chìa khóa vàng để bạn đạt được điều đó.

2. Một khóa học lương 3P uy tín sẽ mang lại cho bạn những gì?

Kiến thức chuyên sâu và bài bản:

Hiểu rõ bản chất 3P: Từ lý thuyết đến thực tiễn, bạn sẽ được trang bị kiến thức vững chắc về từng thành tố P1, P2, P3 và mối quan hệ giữa chúng.

Phương pháp xây dựng hệ thống lương: Học cách thiết kế và triển khai một hệ thống lương 3P phù hợp với đặc thù của doanh nghiệp (phân tích công việc, xây dựng mô tả công việc, định giá công việc, thiết kế thang bảng lương...).

Đánh giá năng lực và hiệu suất: Nắm vững các công cụ và phương pháp đánh giá năng lực (competency framework) và hiệu suất (KPIs, OKRs) một cách khách quan, khoa học.

Liên kết 3P với chiến lược kinh doanh: Hiểu cách lương 3P không chỉ là công cụ trả lương mà còn là một phần của chiến lược quản trị nguồn nhân lực tổng thể, hỗ trợ mục tiêu kinh doanh.

Kỹ năng thực hành và ứng dụng:

Thực hành xây dựng hệ thống: Thông qua các bài tập, case study thực tế, bạn sẽ có cơ hội tự tay thiết kế các thành phần của hệ thống lương 3P.

Kỹ năng phân tích và đánh giá: Rèn luyện khả năng phân tích dữ liệu lương, đánh giá hiệu quả của hệ thống và đề xuất cải tiến.

Kỹ năng giao tiếp và truyền thông: Học cách truyền thông chính sách lương đến nhân viên một cách rõ ràng, minh bạch, tạo sự đồng thuận.

Cập nhật xu hướng và công nghệ:

Xu hướng lương thưởng mới nhất: Nắm bắt những thay đổi trong thị trường lao động và các xu hướng trả lương mới để đảm bảo hệ thống luôn cạnh tranh.

Ứng dụng công nghệ: Tìm hiểu cách các phần mềm quản lý nhân sự (HRM software) hỗ trợ việc triển khai và quản lý lương 3P.

Mở rộng mạng lưới quan hệ:

Kết nối với các chuyên gia, giảng viên và những người cùng quan tâm trong lĩnh vực nhân sự, mở rộng cơ hội học hỏi và phát triển.

3. Làm thế nào để chọn được khóa học lương 3P uy tín?

Với sự nở rộ của các khóa học trên thị trường, việc lựa chọn một khóa học uy tín là vô cùng quan trọng. Dưới đây là một số tiêu chí giúp bạn đưa ra quyết định đúng đắn:

Đội ngũ giảng viên: Ưu tiên các giảng viên có kinh nghiệm thực chiến sâu rộng trong lĩnh vực lương thưởng, đã từng tư vấn hoặc triển khai thành công mô hình 3P cho các doanh nghiệp lớn.

Nội dung chương trình: Chương trình phải toàn diện, bao gồm cả lý thuyết và thực hành, cập nhật các xu hướng mới nhất. Nên có các module về case study, bài tập ứng dụng thực tế.

Đánh giá từ học viên cũ: Tìm kiếm các feedback, đánh giá của những người đã từng tham gia khóa học. Đây là nguồn thông tin đáng tin cậy để bạn đánh giá chất lượng.

Hỗ trợ sau khóa học: Một khóa học tốt nên có cơ chế hỗ trợ, giải đáp thắc mắc cho học viên sau khi kết thúc khóa học.

Uy tín của đơn vị đào tạo: Chọn các trung tâm, tổ chức đào tạo có uy tín, có lịch sử hoạt động lâu năm và được công nhận trong ngành.

Phương pháp đào tạo: Ưu tiên các khóa học có phương pháp đào tạo tương tác, thực tế, khuyến khích học viên thảo luận và chia sẻ kinh nghiệm.

Thời lượng và học phí: Đánh giá xem thời lượng khóa học có phù hợp với lịch trình của bạn không, và học phí có tương xứng với giá trị nhận được không.

4. Nên học lương 3P ở đâu uy tín?

Khoá học lương 3P tại GSA sẽ là lựa chọn tối ưu nhất hiện tại. Khoá học được xây dựng với 22 buổi học bao gồm 3 buổi lý thuyết và 19 buổi thực hành như sau:

I. Lý thuyết

Buổi 1: Lý thuyết về lương 3P

Buổi 2: Lý thuyết về Khung năng lực

Buổi 3: Lý thuyết về BSCKPI

II. Thực hành

Buổi 4:   Lên ý tưởng chiến lược

Buổi 5:   Lên bản đồ chiến lược, xác định công cụ

Buổi 6:   Xác định cơ cấu tổ chức

Buổi 7:   Xác định chức năng nhiệm vụ, sơ đồ tổ chức, mô tả công việc vị trí

Buổi 8:   Xác định các yếu tố đánh giá giá trị công việc

Buổi 9:   Tiến hành đánh giá giá trị công việc

Buổi 10: Xây dựng thang lương (P1)

Buổi 11: Xác định KPI chiến lược

Buổi 12: Xây dựng thư viện KPI phòng ban (Phân bổ và xác định KPI phòng ban)

Buổi 13: Rút gọn KPI

Buổi 14: Xây dựng quy chế đánh giá thúc đẩy KPI

Buổi 15: Xác định năng lực thực thi chiến lược

Buổi 16: Định nghĩa và phân cấp các năng lực thực thi chiến lược

Buổi 17: Phân bổ và xác định thư viện năng lực thực hiện công việc

Buổi 18: Rút gọn và chốt khung năng lực vị trí

Buổi 19: Xây dựng cơ chế chính sách thúc đẩy đào tạo (lộ trình công danh)

Buổi 20: Tổng hợp hoàn thiện chính sách lương 3P

III. Bonus

Buổi 21: Thực hành xây dựng hệ thống báo cáo, theo dõi báo cáo KPI

Buổi 22: Thực hành xây dựng chương trình đào tạo, bài test đánh giá năng lực

Ngoài ra, chất lượng khóa học cũng được quan tâm khá nhiều. Khóa học sẽ được chuyên gia với gần 20 năm trong lĩnh vực nhân sự và đã có kinh nghiệm trong xây dựng hệ thống lương 3P giảng dạy.

Cuối cùng, môi trường được xây dựng lý tưởng với các học viên đều có chung mối quan tâm đến lĩnh vực nhân sự, qua đó giúp các học viên học thêm được nhiều kinh nghiệm từ các học viên khác.

Kết luận

Trong hành trình phát triển sự nghiệp, việc trang bị kiến thức và kỹ năng phù hợp là vô cùng quan trọng. Khóa học lương 3P uy tín không chỉ cung cấp cho bạn những công cụ cần thiết để xây dựng và quản lý hệ thống lương thưởng hiệu quả, mà còn giúp bạn tự tin hơn trong việc định giá bản thân và đạt được mức thu nhập mơ ước.

 

10 Điểm mới về lương, thưởng từ năm 2021 người lao động cần biết

Bộ luật Lao động 2019 (BLLĐ 2019; có hiệu lực thi hành từ 1-1-2021) quy định nhiều điểm mới về tiền lương, thưởng mà người lao động (NLĐ) cần phải biết để bảo đảm quyền và lợi ích chính đáng của mình trong mối quan hệ lao động với người sử dụng lao động (NSDLĐ), cụ thể:

1. NSDLĐ không được ép NLĐ dùng lương mua hàng hóa, dịch vụ của mình/đơn vị khác

Cụ thể, theo quy định tại Khoản 2 Điều 94 BLLĐ 2019 thì:

- NSDLĐ không được hạn chế hoặc can thiệp vào quyền tự quyết chi tiêu lương của NLĐ;

- NSDLĐ không được ép buộc NLĐ chi tiêu lương vào việc mua hàng hóa, sử dụng dịch vụ của NSDLĐ hoặc của đơn vị khác mà NSDLĐ chỉ định.

2. NSDLĐ phải thông báo bảng kê trả lương cho NLĐ vào mỗi lần trả lương

Theo Khoản 3 Điều 95 BLLĐ 2019, mỗi lần trả lương, NSDLĐ phải thông báo bảng kê trả lương cho NLĐ, trong đó ghi rõ các nội dung sau đây:

- Tiền lương;

- Tiền lương làm thêm giờ;

- Tiền lương làm việc vào ban đêm;

- Nội dung và số tiền bị khấu trừ (nếu có)

3. Điểm mới về lãi suất khi tính tiền đền bù do chậm trả lương cho NLĐ

Căn cứ Khoản 4 Điều 97 BLLĐ 2019, trường hợp vì lý do bất khả kháng mà NSDLĐ đã tìm mọi biện pháp khắc phục nhưng không thể trả lương đúng hạn thì không được chậm quá 30 ngày; nếu trả lương chậm từ 15 ngày trở lên thìNSDLĐ phải đền bù cho NLĐ một khoản tiền ít nhất bằng số tiền lãi của số tiền trả chậm tính theo lãi suất huy động tiền gửi có kỳ hạn 01 tháng do ngân hàng nơi NSDLĐ mở tài khoản trả lương cho NLĐ công bố tại thời điểm trả lương.

(Hiện hành, số tiền đền bù sẽ được tính theo lãi suất trần huy động tiền gửi có kỳ hạn 01 tháng do Ngân hàng Nhà nước Việt Nam công bố tại thời điểm trả lương; nếu Ngân hàng Nhà nước Việt Nam không quy định trần lãi suất thì được tính theo lãi suất huy động tiền gửi có kỳ hạn 01 tháng của ngân hàng thương mại, nơi doanh nghiệp, cơ quan mở tài khoản giao dịch thông báo tại thời điểm trả lương).

4. NSDLĐ phải chịu chi phí mở tài khoản cho NLĐ nếu trả lương qua ngân hàng

Theo Khoản 2 Điều 96 BLLĐ 2019, trường hợp trả lương qua tài khoản cá nhân của NLĐ được mở tại ngân hàng thì NSDLĐ phải trả các loại phí liên quan đến việc mở tài khoản và chuyển tiền lương.
10 điểm mới về lương, thưởng từ năm 2021 người lao động cần biết

5. Tiền lương ngừng việc khi NLĐ phải ngừng việc vì sự cố về điện, nước mà không do lỗi của NSDLĐ hoặc do thiên tai, hỏa hoạn, dịch bệnh nguy hiểm, địch họa, di dời địa điểm hoạt động theo yêu cầu của cơ quan nhà nước có thẩm quyền hoặc vì lý do kinh tế

Theo Khoản 3 Điều 99 BLLĐ 2019, trong trường hợp này, hai bên thỏa thuận về tiền lương ngừng việc như sau:

- Trường hợp ngừng việc từ 14 ngày làm việc trở xuống thì tiền lương ngừng việc được thỏa thuận không thấp hơn mức lương tối thiểu;

- Trường hợp phải ngừng việc trên 14 ngày làm việc thì tiền lương ngừng việc do hai bên thỏa thuận nhưng phải bảo đảm tiền lương ngừng việc trong 14 ngày đầu tiên không thấp hơn mức lương tối thiểu.

(Hiện hành chỉ quy định tiền lương ngừng việc do hai bên thoả thuận nhưng không được thấp hơn mức lương tối thiểu vùng do Chính phủ quy định).

6. Thêm nhiều trường hợp NLĐ được nghỉ việc riêng và hưởng nguyên lương

Cụ thể, theo BLLĐ 2019, NLĐ được nghỉ việc riêng mà vẫn hưởng nguyên lương và phải thông báo với NSDLĐ trong những trường hợp sau đây:

- Kết hôn: nghỉ 03 ngày
10 điểm mới về lương, thưởng từ năm 2021 người lao động cần biết
Kể từ năm 2021, người lao động sẽ được nghỉ 2 ngày và hưởng nguyên lương vào dịp lễ Quốc khánh

- Con đẻ, con nuôi kết hôn: nghỉ 01 ngày;

- Cha đẻ, mẹ đẻ, cha nuôi, mẹ nuôi; cha đẻ, mẹ đẻ, cha nuôi, mẹ nuôi của vợ hoặc chồng; vợ hoặc chồng; con đẻ, con nuôi chết: nghỉ 03 ngày.

Như vậy, so với quy định hiện hành, Bộ luật Lao động 2019 bổ sung thêm trường hợp cha nuôi, mẹ nuôi; cha nuôi, mẹ nuôi của vợ hoặc chồng chết thì NLĐ được nghỉ 03 ngày và hưởng nguyên lương.

Đồng thời, quy định rõ hơn trường hợp "con đẻ", "con nuôi" kết hôn thì được nghỉ 01 ngày (hiện hành, quy định "con" kết hôn thì nghỉ 01 ngày); "con đẻ", "con nuôi" chết thì được nghỉ 03 ngày (hiện hành quy định "con" chết thì nghỉ 03 ngày).

7. NLĐ được nghỉ 2 ngày dịp Quốc khánh 2/9 và hưởng nguyên lương

Kể từ năm 2021, NLĐ sẽ được nghỉ 02 ngày và hưởng nguyên lương vào dịp lễ Quốc khánh (hiện nay, NLĐ chỉ được nghỉ 01 ngày và hưởng nguyên lương vào ngày 02/9) theo một trong hai phương án sau do Thủ tướng Chính phủ quyết định:

- Phương án 1: Nghỉ vào ngày 01/9 và ngày 02/9.

- Phương án 2: Nghỉ vào ngày 02/9 và ngày 03/9.

8. NLĐ có thể nghỉ việc ngay không cần báo trước nếu không được trả lương đúng hạn

Cụ thể, theo Điểm b Khoản 2 Điều 35 BLLĐ 2019, thì NLĐ có quyền đơn phương chấm dứt hợp đồng lao động mà không cần báo trước cho NSDLĐ nếu không được trả đủ lương hoặc trả lương không đúng thời hạn, trừ trường hợp quy định tại Khoản 4 Điều 97 BLLĐ 2019 (hiện hành phải báo trước 3 ngày).

9. Lao động nữ làm công việc nặng nhọc khi mang thai có thể được giảm bớt 01 giờ làm việc hằng ngày và hưởng nguyên lương

Khoản 2 Điều 137 BLLĐ 2019 quy định lao động nữ làm nghề, công việc nặng nhọc, độc hại, nguy hiểm hoặc đặc biệt nặng nhọc, độc hại, nguy hiểm hoặc làm nghề, công việc có ảnh hưởng xấu tới chức năng sinh sản và nuôi con khi mang thai và có thông báo cho NSDLĐ biết thì được NSDLĐ chuyển sang làm công việc nhẹ hơn, an toàn hơn hoặc giảm bớt 01 giờ làm việc hằng ngày mà không bị cắt giảm tiền lương và quyền, lợi ích cho đến hết thời gian nuôi con dưới 12 tháng tuổi.

10. NLĐ được thưởng tiền hoặc tài sản hoặc bằng các hình thức khác

Căn cứ quy định tại Điều 104 BLLĐ 2019 thì thưởng là số tiền hoặc tài sản hoặc bằng các hình thức khác mà NSDLĐ thưởng cho NLĐ căn cứ vào kết quả sản xuất, kinh doanh, mức độ hoàn thành công việc của người lao động (Bộ luật lao động hiện hành chỉ quy định về tiền thưởng);

Quy chế thưởng do NSDLĐ quyết định và công bố công khai tại nơi làm việc sau khi tham khảo ý kiến của tổ chức đại diện NLĐ tại cơ sở đối với nơi có tổ chức đại diện người lao động tại cơ sở.

(Theo NLĐ)

When your co-worker earns more than you

When your co-worker earns more than you

It can come as quite a surprise if you happen to learn that a co-worker whom you thought you held the same rank as is actually earning more than you.

Though a debate is growing around whether companies should make pay information transparent, the status quo is currently to keep individual pay a private matter between the employee and HR. This is why it can come as quite a surprise if you happen to learn that a co-worker whom you thought you held the same rank as is actually earning more than you.

So what are your options besides feeling inadequately compensated? Several HR and pay experts weigh in on how to change your compensation, improve your career path and the steps you should avoid taking.



Don’t turn to your co-workers for information

If your first instinct is to ask your co-worker what qualifies him to earn more, or to ask other co-workers how your pay is determined, stop right there. Deb LaMere, vice president of HR strategy and employee engagement at human capital management services and technology firm Ceridian, says, “Speaking with co-workers about their pay level in relation to your own often results in negative consequences. This type of conversation can lead to resentment and anger, effectively changing relationships for [the] worse between co-workers, project teams and possibly with direct management.”

While transparent pay information would resolve the secrecy issue that can trigger problems at work, it holds true that compensation levels can vary widely for valid reasons. “There are many factors to consider when it comes to evaluating individual pay, especially length and type of experience,” LaMere adds. “Having a salary comparison conversation with a co-worker is not constructive to understanding ones' own pay rate and possibly influencing changes to individual pay and compensation levels.”

Research compensation trends and standards

Instead of turning to your co-workers for information, rely on outside sources and garner as many points of data as possible. “Lots of information is readily available through salary surveys and websites, industry associations, recruiters/headhunters who place candidates in your industry and space and through actively networking with colleagues and developing real meaningful professional relationships… so that delicate topics like salary, bonus and benefits will be discussed openly and shared comfortably,” says Roy Cohen, career coach and author of “The Wall Street Professional's Survival's Guide.” “You also need to be absolutely clear on what the numbers represent. Are they for equivalent positions and for equivalent performance?”

Prove your worth

Once you have a well-researched idea of the pay level you could and should be on, gather evidence for your boss that echoes those numbers. “One option is to volunteer for and take on visible, challenging initiatives and then manage them successfully,” Cohen says. “That is just half the battle and it is often where the process breaks down. While a project is underway and once it is completed, key stakeholders must be made aware of your significant contributions both during and after...The gift that keeps on giving. It is helpful to have a mentor within the company who can advocate for you and enhance your visibility as well as serve as a sounding board for advice on how to approach your boss.”

Whether you have office backup or you’re presenting on behalf of yourself, it’s important to prove to your boss that a pay raise is deserved because of your merits, not that you’ve simply learned of the pay discrepancy.

Take it to your boss

You’ve done the research and ensured that your request will be backed up by proof of your hard work. So how do you begin this conversation with your boss? Katie Donovan, a salary and career negotiation consultant, equal pay advocate and founder of Equal Pay Negotiations LLC, says, “Start the process of discussing a raise or salary adjustment with your direct manager. I recommend asking for help, not demanding a raise. Say something like, ‘I recently discovered that I am paid below the market value for this job. What can we do to rectify it?’ This makes it a collaborate discussion and gives management the opportunity to come up with a solution, which might be better than you anticipated.”

Heading into the meeting, “bring with you the research you did on pay for the job so you can discuss your research,” Donovan says. “Also, be prepared to highlight your contributions to the company as reasons you deserve to be paid on the high end of the pay range for the job. If you can, compare it to the lesser results of co-workers. Very effective reasons are contributions that saved the company money or generated revenue for the company. Do not expect a solution in this first meeting but do ask for a response in a certain time so this does not drag on forever. Something like ‘Can you get back to me by Friday on this?’”

Negotiating pay is a tough part of advancing in your career, but receiving the compensation that you deserve is well worth the time.

(Picture Source: Internet)
HRVietnam - Collected
Rethinking HR in banking

The book 'The Future of human resource Management' edited by three vanguard HR professionals: Mike Losey, Dave Ulrich, and Sue Meisinger sparked me. The book is an eclectic mix of articles written by 64 HR thought leaders. These stellar academics, consultants, and practitioners look at the future of human resources and explore the critical HR issues of today and tomorrow. The book reveals how leading companies hire and retain their talents, explore HR's role in brand development, highlights HR's contribution to business strategy and many more. While reading the book, I was pondering about the current and future HR issues in banking. I would like to share some glimpses of my musings in this article.

In any organisations, HR professionals turn organisational aspirations (mission) into actions. To carry out this, they generally focus organisation's three attributes: talent, cultures and leadership. Talent encompasses competence (skills and abilities), commitment (willingness to engage and work hard), and contribution (ability to find meaning from the work) of the entire human resources of the organisation. Culture entails the right organisational capabilities that enable to shape an identity outside and pattern of behaviour inside the organisation. And, leadership includes the succession planning in such a way that the leaders throughout the organisation are focused on the right things and execute strategy in right ways.

As banking is a service industry, Human Resource Management (HRM) plays an instrumental role for banks. Management of people and management of risk are generally two factors that determine the success in the banking business. But efficient risk management may not be possible without efficient and skilled manpower. So banking has been and will always be a 'People Business'. As skilled manpower is becoming scarce both in quality and quantity, it is quite straightforward that they need to be properly managed for the benefit of society, in general, and of the bank in particular.

Apt manpower planning integrated with the business plan and strategy of the bank is a pivotal part in HRM. It captures the type of people a bank requires, the level at which they are required and clearly defined roles for everyone. This plan may also entail lifecycle approach of an employee from his/her joining to retirement, steady, carefully calibrated recruitment programme, and cultural adjustments and change management among various generations of employees.

In recruitment stage, banks need to revisit their existing recruitment strategy to review whether they target right kind of people. For example, if the competitive advantage of a bank is mass banking with a lot of rural branches, then the bank naturally structures its recruitment strategy to attract the talents who have the right attitude to work in rural areas to serve the mass people. As a result, in addition to problem solving skills, various psychological skills may be incorporated in the recruitment test. In lateral recruitment, banks may think to induct professionals outside the banking with specific skill sets and experience pool.

Though competitive remuneration is a vital reason why people select and stay with a particular bank, other factors such as images, especially in transparent situations with a high level of competitiveness of the bank, training and re-skilling of employees, performance measurement, promotion policy, transfer policy, talent management, communication, etc are also crucial for employee retention. The changing nature of banking business requires massive re-skilling of the existing workforce and continuous skill up-gradation. Online platforms may be used for in-house training facilities. Banks may cut layers of bureaucracy that have created over the years and adopt an effective way of delegation to empower their people.

Exit interviews of the employees may be an effective way to determine why people are leaving the banks. It will not only help to find out intrinsic system failures in the banks, but also gain some effective recommendation to develop them. Banks may leverage the inherent loyalty of their retired people in brand building efforts, financial inclusion initiatives and other non-financial activities.

Mohammad Arifur Rahman | thefinancialexpress-bd.Com

Lying in the hiring process: What human resources needs to know

 People lie all the time during the hiring process. It’s up to Human Resources and hiring managers to catch those liars. Where are those fibs being told — and how can you prevent them?

 

Resume lies

In this intense job market, it’s no surprise that many applicants exaggerate parts of their resumes to look more enticing to potential employers.

The concept is so widespread, however, that nearly half of all applicants admit to lying on their resumes.

That’s according to a 2009 study from ADP, which found that 46% of all applicants commit some form of resume fraud.

Where are those lies being concentrated? Here are the 10 most common lies on resumes, courtesy of Marquet International:

1. Stretching work dates
2. Inflating past accomplishments and skills
3. Enhancing job titles and responsibilities
4. Exaggerating educational background
5. Inventing periods of “self-employment” to cover up unemployment
6. Omitting past employment
7. Faking credentials
8. Falsifying reasons for leaving prior employment
9. Providing false references, and
10. Misrepresenting a military record.

Interviewing lies

Your job would be a lot easier if you could easily spot those resume lies and nix those candidates from consideration.

But no matter how clued in you are to what applicants fib about, you’ll still inadvertently bring many of them in for interviews.

That’s when your skills at judging character come in. So who’s the best at screening potential talent? Is it someone who’s skeptical and suspicious about most applicants, or a person who’s trusting?

If you guessed that skeptical managers would do a better job, you’re not alone. You’re also wrong.

That’s according to a recent study from psychologists Nancy Carter and Mark Weber, which was recently highlighted in The Washington Post.

A large majority (85%) of participants said a skeptical interviewer would do a better job spotting dishonesty in job interviews.

But a subsequent study found that people who trust others — or who assume the best in other people — are the best at identifying liars.

How’s this so? On human resources expert explains:

… Lie-detection skills cause people to become more trusting. If you’re good at spotting lies, you need to worry less about being deceived by others, because you can often catch them in the act.

Another possibility: People who trust others become better at reading other people because they get to see a range of emotions during their interactions. That gives them more experiences to draw from to tell when someone is lying and when someone is telling the truth.

Human resources leaves employers with some advice on who they should have in the interviewer role to prevent applicants from duping you into hiring them:

Human resources expert - we need leaders who demonstrate skill in recognizing dishonesty. Instead of delegating these judgments to skeptics, it could be wiser to hand over the hiring interviews to those in your organization who tend to see the best in others. It’s the Samaritans who can smoke out the charlatans.

Of course, faith in others can go too far. It’s important to sprinkle a few ounces of skepticism into each pound of trust. Ultimately, while the best leaders don’t trust all of the people all of the time, the keenest judges of character may be the leaders who trust most of the people most of the time.

Source:http://www.Hrmorning.Com/

Teaching Machines to Think About HR

For all its promise for HR, big data and its “machine-learning” component still only give us facts about, and factual relationships within, our workforces; not conclusions based on the statistical analyses HR has always needed—and always will—to make meaningful predictions.

By Peter Cappelli

Workforce analytics. Big data. Machine learning.

The above terms—or “buzzwords” if you don’t like them—are popping up in many discussions of human resources, mainly involving vendors with solutions that make use of new data aimed at answering traditional workforce questions. Is there anything really new in these approaches, and, if there is, should we be paying attention to it?

The answers are yes and yes.

Let’s start with the term workforce analytics. In some ways, this term is to traditional measures of outcomes as human resources was to personnel. It is about addressing traditional, evergreen questions in different, more sophisticated ways.

Workforce analytics describes an effort to use data and sophisticated analyses to address HR problems. The most topical ones at the moment are: “Which candidates will make the best hires?” and “Which employees are most likely to leave?”

There is nothing new about those questions, and there isn’t much new about how they are being approached. The novelty comes, in part, from the fact that, after the early 1980s, big corporations gave up trying to address these questions in a sophisticated manner, so most people in business aren’t aware that similar approaches were tried a generation or so ago.

But there are some differences. One is a greater interest in analyses pertaining to financial outcomes: e.G., It will save us $5,000 per employee by reducing turnover.

The second difference involves the type of data available. The “Manplan” program in the 1960s required HR staff to read information about an employee from one file, mechanically punch it onto a card, then get different information for that same employee from another file, punch it onto a different card, then do that for every employee they wanted to study. Only when those steps were completed could they start looking to see what factors predicted turnover. It cost a fortune to look at even a small set of employees.

Virtually all HR data now is kept electronically, and, in most companies, the information on every applicant who tried to get a job with them is sitting somewhere in a dataset. It’s much easier and cheaper to look at huge numbers of observations, which makes it much easier to find potentially useful results. Being able to capture every “hit” on your employee-benefits website, for example, can tell us almost instantly what kinds of employees are worried about what types of issues.

But here’s the brake to the Big Data bandwagon: Not all HR data is big. The key piece of information needed to make workforce analytics valuable is a measure of job performance. We can’t say anything about which of our 1 million applicants will do well without being able to identify who among our employees is a good performer. In most companies, that information is no better than it was in the 1950s, and, in many companies, it is actually worse, as we’ve gone from assessment-center scores to a supervisor’s guess about potential. The phrase “garbage in/garbage out” is highly relevant here.

That takes us to the last and most obtuse of the buzzwords: machine learning.

It is a different way to think about data than most of us have previously seen, one that came from people whose expertise was rooted in computers rather than statistics per se. The “learning” idea comes from the fact that computer programs (i.E., The “machine”) can be designed to look at data and find patterns that allow them to make predictions.

How exactly machine learning differs from statistics is a topic of endless fascination to people in those two fields, but for the rest of us, here’s what matters: The traditional, statistical approach to analyzing HR data begins with hypotheses that come from prior research. It includes careful statements about assumptions in the study, or studies, and whether those assumptions are true. Traditional machine learning, in contrast, is theory-free and assumption-free. It just looks for patterns in the data, and it uses different techniques from what had commonly been used in statistics to find the clearest patterns.

A statistical examination of whether a given employment test predicts good hires concludes with either “yes” or “no,” where "no" means we can’t rule out that the relationships were due to chance.

In the case of a machine-learning examination, an employee might instead conclude that, while there is no overall relationship, there is a very powerful relationship for this subset of employees, nothing much for that subset, and, for a third subset, a strong relationship that was different than that of the first group.

The power of machine learning comes from the fact that it might well find important predictors that we never thought of before because prior theory didn’t include them—e.G., The distance an applicant’s home is from the work location predicts turnover—and wasn’t particularly adept at “mining” through lots of seemingly unrelated data to find predictors.

All that sounds really promising for machine learning, but there are a bunch of things about this approach that we’d better consider pretty carefully before diving in.

The first of these is a reminder that machine learning produces facts, rather than conclusions. It tells us “X is related to Y,” but not why they are related. Without hypothesis testing and clear statements of assumptions, we don’t learn much about what a given relationship means or why it exists. Perhaps most important, machine learning can’t tell us much about the likelihood that a relationship observed in this dataset will be useful in another context.

This matters in HR because most of the frameworks that support modern employment—especially legal frameworks—relied on the scientific method and traditional statistical tests for their foundation.

Consider, for example, the legal norm that selection tests should not discriminate and the “Uniform Guidelines of Employee Selection Procedures” put together by psychologists over the past generation to ensure that hiring practices are both valid and don’t discriminate against protected groups. Machine learning, as traditionally practiced, would surely uncover relationships that, if applied to hiring, would violate the law.

Machine learning applied to big data will certainly turn up a lot of interesting facts for workforce analytics to ponder. Transferring those facts to practice, however, is still a big leap. On their own, these “buzzword” approaches won’t get us there.

Peter Cappelli is the George W. Taylor Professor of Management and director of the Center for Human Resources at The Wharton School of the University of Pennsylvania in Philadelphia. His latest book is Why Good People Can't Get Jobs: The Skills Gap and What Companies Can Do About It.

Hreonline.Com/HRE/view/story.Jhtml?id=534358638

Top 10 Ways to Find Your Career Path

If you're not sure which direction your career should go in, you're thinking about making a career change, or you just want to feel more fulfilled in your career, these ten tips might help.

Ideally, everyone would know their true calling early in life and find happiness in their work, but it often doesn't work that way. One survey (of New York professionals) found that they expected to change careers three times in their lifetimes; lifelong careers may not be the norm any more.

That said, we know there are better ways to choose a career than just following your parents' footsteps or choosing randomly. Here are some ideas.

10. Think About What Excites and Energizes You



This one's the first obvious step—we all want to enjoy and actually like our careers. (Perhaps the biggest sign you're on the wrong path is if you dread talking about your job.) While passion isn't the only requirement for being content in your career, many would say it's still essential, if only because passion is what keeps you going even through the tough times. Is there a job you would do job for free?

9. But Also Keep in Mind What You're Good At



Maybe you don't feel that passionate about any specific career—or you love multiple areas and can't decide on just one. Then it's time to think about your personality and focus on the skills you have. "Don't do what you love. Do what you are."

8. Take a Test



Well, you say, what if you don't know what you're good at or even what you're interested in? Career assessment tests in college or even high school help narrow down a field (perhaps with the Myers-Briggs personality index), but if it's been a while since you took those tests, there are other kinds of assessment tests you can take. This one from Rasmussen College matches your self-reported skills and interests with potential jobs. (And they also have a salary and job growth interactive chart.) For potential programmers, Switch recommends a coding career based on your preferences. About.Com's Job Search site has a collection of other career tests.

You can also find a career that fits your motivational focus with this assessment test.

7. Try an Internship



If you have flexibility when it comes to salary, an internship could be a great way to test out an industry or type of career—and eventually get a full-time job (especially if you have no prior experience). Even if it doesn't turn into a job or you find out it's the wrong career for you, an internship can help build your network—from which you can get career and job advice. (Not all internships are just about picking up coffee. For example, Google internships, while hard to come by, put you to real work.)

6. Find a Mentor



A mentor could help you take your career to the next level and give you the insider insight to help you make sure you're on the right path. Here's how to ask someone to be your mentor.

If there's a career you're interested in, you might also check to see if any companies or people in that line of work would let you shadow them for a few days to see what it's really like.

5. Explore Unconventional Careers



We all know the popular careers available to us—doctor, lawyer, teacher, computer engineer, police officer, store owner, etc. If you feel uninspired by the typical choices, know that there are thousands of unusual jobs you might not have heard about, hidden, perhaps, in the Bureau of Labor Statistics' Occupational Handbook. Mashable has a list of six dream jobs that pay well (panda caretaker! Chocolate inspector!), Thought Catalog highlights 10 more (sex toy testers?!), and Chron lists a couple of others (along with related articles like "Unusual careers with animals" and "unusual accounting careers").

4. Ask Other People



Perhaps the best way to discover a new career is to ask other people about theirs—assuming you come into contact with people who don't all work in the same field. Your LinkedIn network (or other social media sites, but especially LinkedIn) might be a good place to start mining for information. Also, don't forget your local library's reference librarian can point you to career resources.

3. Use the G+P+V Formula



The perfect career for you would most likely fit the G+P+V formula, which stands for Gifts + Passions + Values. Consider your strengths and passions, as we've noted above, and your values—what's nonnegotiable about the way you work?

2. Make a Career Plan



As with most things, your career will benefit if you have goals and a plan for it. Maybe you think you want to be a writer, but the next step after that, is editing. (Do you really want to do that?) Or maybe you want to transition from being an editor to a restaurant owner. (How are you going to get there?) Map out where you want to go, with concrete milestones, as if it were a four-phase project.

1. See Your Career as a Set of Stepping Stones, Not a Linear Path



Of course, all these plans and ideas are never set in stone. Your career is a marathon, not a sprint and it can turn out to be a very winding road indeed, knitted together from all of your experiences into, hopefully, a career worth having.

Photos from VoodooDot (Shutterstock), OpenClips (Pixabay), Mopic (Shutterstock), sacks08, auremar (Shutterstock), Little Birth, bobsfever.

Lifehacker.Com
Teaching Machines to Think About HR

For all its promise for HR, big data and its “machine-learning” component still only give us facts about, and factual relationships within, our workforces; not conclusions based on the statistical analyses HR has always needed—and always will—to make meaningful predictions.

By Peter Cappelli

Workforce analytics. Big data. Machine learning.

The above terms—or “buzzwords” if you don’t like them—are popping up in many discussions of human resources, mainly involving vendors with solutions that make use of new data aimed at answering traditional workforce questions. Is there anything really new in these approaches, and, if there is, should we be paying attention to it?

The answers are yes and yes.

Let’s start with the term workforce analytics. In some ways, this term is to traditional measures of outcomes as human resources was to personnel. It is about addressing traditional, evergreen questions in different, more sophisticated ways.

Workforce analytics describes an effort to use data and sophisticated analyses to address HR problems. The most topical ones at the moment are: “Which candidates will make the best hires?” and “Which employees are most likely to leave?”

There is nothing new about those questions, and there isn’t much new about how they are being approached. The novelty comes, in part, from the fact that, after the early 1980s, big corporations gave up trying to address these questions in a sophisticated manner, so most people in business aren’t aware that similar approaches were tried a generation or so ago.

But there are some differences. One is a greater interest in analyses pertaining to financial outcomes: e.G., It will save us $5,000 per employee by reducing turnover.

The second difference involves the type of data available. The “Manplan” program in the 1960s required HR staff to read information about an employee from one file, mechanically punch it onto a card, then get different information for that same employee from another file, punch it onto a different card, then do that for every employee they wanted to study. Only when those steps were completed could they start looking to see what factors predicted turnover. It cost a fortune to look at even a small set of employees.

Virtually all HR data now is kept electronically, and, in most companies, the information on every applicant who tried to get a job with them is sitting somewhere in a dataset. It’s much easier and cheaper to look at huge numbers of observations, which makes it much easier to find potentially useful results. Being able to capture every “hit” on your employee-benefits website, for example, can tell us almost instantly what kinds of employees are worried about what types of issues.

But here’s the brake to the Big Data bandwagon: Not all HR data is big. The key piece of information needed to make workforce analytics valuable is a measure of job performance. We can’t say anything about which of our 1 million applicants will do well without being able to identify who among our employees is a good performer. In most companies, that information is no better than it was in the 1950s, and, in many companies, it is actually worse, as we’ve gone from assessment-center scores to a supervisor’s guess about potential. The phrase “garbage in/garbage out” is highly relevant here.

That takes us to the last and most obtuse of the buzzwords: machine learning.

It is a different way to think about data than most of us have previously seen, one that came from people whose expertise was rooted in computers rather than statistics per se. The “learning” idea comes from the fact that computer programs (i.E., The “machine”) can be designed to look at data and find patterns that allow them to make predictions.

How exactly machine learning differs from statistics is a topic of endless fascination to people in those two fields, but for the rest of us, here’s what matters: The traditional, statistical approach to analyzing HR data begins with hypotheses that come from prior research. It includes careful statements about assumptions in the study, or studies, and whether those assumptions are true. Traditional machine learning, in contrast, is theory-free and assumption-free. It just looks for patterns in the data, and it uses different techniques from what had commonly been used in statistics to find the clearest patterns.

A statistical examination of whether a given employment test predicts good hires concludes with either “yes” or “no,” where "no" means we can’t rule out that the relationships were due to chance.

In the case of a machine-learning examination, an employee might instead conclude that, while there is no overall relationship, there is a very powerful relationship for this subset of employees, nothing much for that subset, and, for a third subset, a strong relationship that was different than that of the first group.

The power of machine learning comes from the fact that it might well find important predictors that we never thought of before because prior theory didn’t include them—e.G., The distance an applicant’s home is from the work location predicts turnover—and wasn’t particularly adept at “mining” through lots of seemingly unrelated data to find predictors.

All that sounds really promising for machine learning, but there are a bunch of things about this approach that we’d better consider pretty carefully before diving in.

The first of these is a reminder that machine learning produces facts, rather than conclusions. It tells us “X is related to Y,” but not why they are related. Without hypothesis testing and clear statements of assumptions, we don’t learn much about what a given relationship means or why it exists. Perhaps most important, machine learning can’t tell us much about the likelihood that a relationship observed in this dataset will be useful in another context.

This matters in HR because most of the frameworks that support modern employment—especially legal frameworks—relied on the scientific method and traditional statistical tests for their foundation.

Consider, for example, the legal norm that selection tests should not discriminate and the “Uniform Guidelines of Employee Selection Procedures” put together by psychologists over the past generation to ensure that hiring practices are both valid and don’t discriminate against protected groups. Machine learning, as traditionally practiced, would surely uncover relationships that, if applied to hiring, would violate the law.

Machine learning applied to big data will certainly turn up a lot of interesting facts for workforce analytics to ponder. Transferring those facts to practice, however, is still a big leap. On their own, these “buzzword” approaches won’t get us there.

Peter Cappelli is the George W. Taylor Professor of Management and director of the Center for Human Resources at The Wharton School of the University of Pennsylvania in Philadelphia. His latest book is Why Good People Can't Get Jobs: The Skills Gap and What Companies Can Do About It.

Hreonline.Com/HRE/view/story.Jhtml?id=534358638

Top 10 Ways to Find Your Career Path - Human Resources Management

Top 10 Ways to Find Your Career Path

If you're not sure which direction your career should go in, you're thinking about making a career change, or you just want to feel more fulfilled in your career, these ten tips might help.

Ideally, everyone would know their true calling early in life and find happiness in their work, but it often doesn't work that way. One survey (of New York professionals) found that they expected to change careers three times in their lifetimes; lifelong careers may not be the norm any more.

That said, we know there are better ways to choose a career than just following your parents' footsteps or choosing randomly. Here are some ideas.

10. Think About What Excites and Energizes You



This one's the first obvious step—we all want to enjoy and actually like our careers. (Perhaps the biggest sign you're on the wrong path is if you dread talking about your job.) While passion isn't the only requirement for being content in your career, many would say it's still essential, if only because passion is what keeps you going even through the tough times. Is there a job you would do job for free?

9. But Also Keep in Mind What You're Good At



Maybe you don't feel that passionate about any specific career—or you love multiple areas and can't decide on just one. Then it's time to think about your personality and focus on the skills you have. "Don't do what you love. Do what you are."

8. Take a Test



Well, you say, what if you don't know what you're good at or even what you're interested in? Career assessment tests in college or even high school help narrow down a field (perhaps with the Myers-Briggs personality index), but if it's been a while since you took those tests, there are other kinds of assessment tests you can take. This one from Rasmussen College matches your self-reported skills and interests with potential jobs. (And they also have a salary and job growth interactive chart.) For potential programmers, Switch recommends a coding career based on your preferences. About.Com's Job Search site has a collection of other career tests.

You can also find a career that fits your motivational focus with this assessment test.

7. Try an Internship



If you have flexibility when it comes to salary, an internship could be a great way to test out an industry or type of career—and eventually get a full-time job (especially if you have no prior experience). Even if it doesn't turn into a job or you find out it's the wrong career for you, an internship can help build your network—from which you can get career and job advice. (Not all internships are just about picking up coffee. For example, Google internships, while hard to come by, put you to real work.)

6. Find a Mentor



A mentor could help you take your career to the next level and give you the insider insight to help you make sure you're on the right path. Here's how to ask someone to be your mentor.

If there's a career you're interested in, you might also check to see if any companies or people in that line of work would let you shadow them for a few days to see what it's really like.

5. Explore Unconventional Careers



We all know the popular careers available to us—doctor, lawyer, teacher, computer engineer, police officer, store owner, etc. If you feel uninspired by the typical choices, know that there are thousands of unusual jobs you might not have heard about, hidden, perhaps, in the Bureau of Labor Statistics' Occupational Handbook. Mashable has a list of six dream jobs that pay well (panda caretaker! Chocolate inspector!), Thought Catalog highlights 10 more (sex toy testers?!), and Chron lists a couple of others (along with related articles like "Unusual careers with animals" and "unusual accounting careers").

4. Ask Other People



Perhaps the best way to discover a new career is to ask other people about theirs—assuming you come into contact with people who don't all work in the same field. Your LinkedIn network (or other social media sites, but especially LinkedIn) might be a good place to start mining for information. Also, don't forget your local library's reference librarian can point you to career resources.

3. Use the G+P+V Formula



The perfect career for you would most likely fit the G+P+V formula, which stands for Gifts + Passions + Values. Consider your strengths and passions, as we've noted above, and your values—what's nonnegotiable about the way you work?

2. Make a Career Plan



As with most things, your career will benefit if you have goals and a plan for it. Maybe you think you want to be a writer, but the next step after that, is editing. (Do you really want to do that?) Or maybe you want to transition from being an editor to a restaurant owner. (How are you going to get there?) Map out where you want to go, with concrete milestones, as if it were a four-phase project.

1. See Your Career as a Set of Stepping Stones, Not a Linear Path



Of course, all these plans and ideas are never set in stone. Your career is a marathon, not a sprint and it can turn out to be a very winding road indeed, knitted together from all of your experiences into, hopefully, a career worth having.

Photos from VoodooDot (Shutterstock), OpenClips (Pixabay), Mopic (Shutterstock), sacks08, auremar (Shutterstock), Little Birth, bobsfever.

Lifehacker.Com

Lying in the hiring process: What Human resources needs to know

 

 People lie all the time during the hiring process. It’s up to Human Resources and hiring managers to catch those liars. Where are those fibs being told — and how can you prevent them?

 

 

Resume lies

 

In this intense job market, it’s no surprise that many applicants exaggerate parts of their resumes to look more enticing to potential employers.

The concept is so widespread, however, that nearly half of all applicants admit to lying on their resumes.

That’s according to a 2009 study from ADP, which found that 46% of all applicants commit some form of resume fraud.

Where are those lies being concentrated? Here are the 10 most common lies on resumes, courtesy of Marquet International:

1. Stretching work dates
2. Inflating past accomplishments and skills
3. Enhancing job titles and responsibilities
4. Exaggerating educational background
5. Inventing periods of “self-employment” to cover up unemployment
6. Omitting past employment
7. Faking credentials
8. Falsifying reasons for leaving prior employment
9. Providing false references, and
10. Misrepresenting a military record.

 

Interviewing lies

 

Your job would be a lot easier if you could easily spot those resume lies and nix those candidates from consideration.

 

But no matter how clued in you are to what applicants fib about, you’ll still inadvertently bring many of them in for interviews.

 

That’s when your skills at judging character come in. So who’s the best at screening potential talent? Is it someone who’s skeptical and suspicious about most applicants, or a person who’s trusting?

 

If you guessed that skeptical managers would do a better job, you’re not alone. You’re also wrong.

 

That’s according to a recent study from psychologists Nancy Carter and Mark Weber, which was recently highlighted in The Washington Post.

 

A large majority (85%) of participants said a skeptical interviewer would do a better job spotting dishonesty in job interviews.

 

But a subsequent study found that people who trust others — or who assume the best in other people — are the best at identifying liars.

 

How’s this so? On human resources expert explains:

 

… Lie-detection skills cause people to become more trusting. If you’re good at spotting lies, you need to worry less about being deceived by others, because you can often catch them in the act.

 

Another possibility: People who trust others become better at reading other people because they get to see a range of emotions during their interactions. That gives them more experiences to draw from to tell when someone is lying and when someone is telling the truth.

 

Human resources leaves employers with some advice on who they should have in the interviewer role to prevent applicants from duping you into hiring them:

 

Human resources expert - we need leaders who demonstrate skill in recognizing dishonesty. Instead of delegating these judgments to skeptics, it could be wiser to hand over the hiring interviews to those in your organization who tend to see the best in others. It’s the Samaritans who can smoke out the charlatans.

Of course, faith in others can go too far. It’s important to sprinkle a few ounces of skepticism into each pound of trust. Ultimately, while the best leaders don’t trust all of the people all of the time, the keenest judges of character may be the leaders who trust most of the people most of the time.

Source:http://www.Hrmorning.Com/