Evaluating job performance is one of the integral processes of an organization on the way to success. However, due to the multifaceted nature of working processes and employees’ professional and personal characteristics, performance measurement poses many challenges for the management. There are many different approaches to evaluating the efficiency of workers, but still, it is difficult to define one that provides accurate results and complete information.
Job performance comprises an individual’s actions correlated with the general efficiency of the company, and if measured accurately, it helps the talent management to decide on promotions, rewards, firing, and take further steps to model beneficial working conditions. For these purposes, specialists gather statistics on objective performance measures, which imply everything that can be translated into figures, and subjective performance measures, which require an opinion from someone else. Williams (2016, p. 235) writes that “common objective performance measures include output, scrap, waste, sales, customer complaints, and rejection rates.” The first type of information is easily obtainable and convenient to use for ratings, estimation of the general performance of individuals and departments. It can also be complemented by big data analysis, which, according to Truxillo, et al. (2015, p. 320) “goes beyond traditional measures and adds more detailed characteristics such as the number of face-to-face meetings and other minute behaviors like keystrokes.”
As for subjective performance measures, a supervisor’s opinion on the employee’s performance is considered to be the most widely used method for evaluating characteristics where figures fail (Chamorro-Premuzic 2017). They also feature ratings of outside-of-the-job activities, helping colleagues, maintaining work ethics, or, on the contrary, counterproductive behavior. Besides, it is often combined with self-ratings of performance presented by the employees themselves. The latter can compare their goals with their accomplishments, grade their success and this will enable their supervisor with the necessary information on how well the expectations were met (Riggio 2017). Nowadays, with the help of digital technologies and automatic processes used in all spheres, judgments can be made not only by the employer and their supervisor but by co-workers and customers, too (Gatewood et al. 2015). Colleagues and clients can give valuable insights from a brand new perspective, which can be crucial and otherwise unknown to the management.
Both methods of performance management described above are primarily used by talent managers to determine employees best suitable for promotions, rewards, and remunerations, as well as those who do not comply with the working standards and have to be fired. In this list, remuneration tends to be one of the most significant types of recognition because it means that the organization values its employees as professionals and efficient workers. To arrange working processes so that they benefit all, the management is supposed to motivate their employees for productivity (Mbegu 2016).
Shields et al. (2015) state that any reward system is supposed to have three primary objectives: to attract the right people for the right jobs, tasks, or roles and retain them by recognizing and rewarding their contribution. The third objective is to motivate employees to contribute to the best of their abilities and develop their professional skills. The basis for these can be provided only by accurate evidence-based reward management, which uses surveys and evaluation, and eventually results in the implementation of reward systems (Armstrong 2015).
The review of different approaches to performance measurement proves that it directly defines the efficiency of employees, and their willingness to do their best to meet the goals set by their organizations. The importance of remuneration for a good job also cannot be underestimated, because it is one of the main reasons for workers to stay motivated and loyal to their company. Thus, performance measurement can be viewed as one of the primary concerns for talent managers, who want to arrange effective working processes in their companies.
Armstrong, M 2015, Armstrong’s handbook of reward management practice: improving performance through reward, 5th and, Kogan Page Publishers, London.
Chamorro-Premuzic, T 2017, The talent delusion: why data, not intuition, is the key to unlocking human potential, Hachette, London.
Gatewood, R & Field, H & Barrick, M 2015, Human resource selection, Cengage Learning, Andover.
Mbegu, A 2016, The effectiveness of money as a motivation for academic institutions. An assessment, GRIN Verlag, Munich.
Riggio, R 2017, Introduction to industrial/organizational psychology, 7th edn, Routledge, London.
Shields, J, Brown, M, Kaine, S, Dolle-Samuel, C, North-Samardzic, A, McLean, P, Johns, R, O’Leary, P, Plimmer, G & Robinson, J 2015, Managing employee performance & reward: concepts, practices, strategies, 2nd edn, Cambridge University Press, Cambridge.
Truxillo, D, Bauer, T & Erdogan, B 2015, Psychology and work: perspectives on industrial and organizational psychology, Routledge, London.
William, C 2016, MGMT, 8th edn, Cengage Learning, Andover.