week 7
Running head: INTERNET STAFFING METHODS COMPARED TO TRADITIONAL 1
INTERNET STAFFING METHODS COMPARED TO TRADITIONAL 2
Internet staffing methods compared to traditional staffing methods
Staffing methods are the process taken by organizations to hire new employees to fill vacancies in an organization. This topic is interesting to me because I am a recruiter in my day job. This is a good subject to write about because every member of the company benefits from what recruitment does. I believe for these reasons that this is a good subject to write about and everyone in an organization can benefit more from why recruiting chooses what methods to recruit.
The methods used by organizations are online recruitment and traditional staffing methods. Online staffing attracts many candidates, thus helping the organization to get more qualified individuals. Traditional methods, on the other hand, restrict the application to a specific region because of distance, thus limiting the application of qualified individuals from other areas. The human resource department using the online staffing method gets many applications to choose the most qualified personnel to fill the vacancies in the firm (Hasmanto, Rusilowati & Herawaty, 2019). The traditional staffing method is costly since it requires more human resources to sort out the application letters of the candidates. Online recruitment does not need a large team to sort the letters since the process is done virtually without much human intervention.
The traditional staffing method is adequate for employees’ retention because the applicants are well conversant with the operations of the company. Online recruitment has a low level of employee retention since the applicants are always ready to submit applications in other companies. The online staffing method lacks a personal touch, which is present in the traditional staffing method (Rosenbaum, 2019). The personal touch in the traditional method boosts the retention of the employees for an extended time compared to companies using online methods.
References
Hasmanto, B., Rusilowati, U., & Herawaty, L. (2019, May). Analysis of leadership and work discipline in improving the performance of employees at the general bureau, staffing, and organization of the Ministry of Tourism. In Business Innovation and Development in Emerging Economies: Proceedings of the 5th Sebelas Maret International Conference on Business, Economics and Social Sciences (SMICBES 2018), July 17-19, 2018, Bali, Indonesia (p. 254). CRC Press.
Rosenbaum, E. (2019, April 4). IBM artificial intelligence can predict with 95% accuracy which workers are about to quit their jobs. CNBC. https://www.cnbc.com/2019/04/03/ibm-ai-can-predict-with-95-percent-accuracy-which-employees-will-quit.html