Improving Employee Performance Through Feedback

Appraisal of the work of the company’s employees is a widespread procedure, which is usually carried out by managers on a regular basis. For a long time, these assessments were based on three main theories, which justified their implementation. The theory of the source of truth notes that reviews show employees weaknesses in their activities, which they cannot see themselves. According to the training theory, if an employee lacks the necessary skills, a colleague having them should teach the employee.

Finally, the excellence theory believes that the excellent performance of duties is measurable and understandable and can be analyzed and described. Despite expectations, these theories did not justify themselves in practice, and as a result, over the past years, the number of companies conducting regular assessments of their employees has decreased.

Performance reviews do not meet their objectives but often act in a negative way. Since such assessments usually focus on negative aspects, for instance, employee failures, they work demotivating. Moreover, it is almost impossible to consider all the complexity of the activities, which makes the employee in one document. At the same time, assessments are carried out by people, and it is difficult to call them completely objective. Each person’s abilities are unique, and for this reason, it is necessary to pay attention to employees’ successes.

Netflix was heavily criticized for its demotivating feedback on employees. In this organization, 360-degree employee performance evaluation is practiced – a process during which employees can send a review of colleagues’ work describing what they should start, stop, and continue to do (Rodriguez, 2020). Information concerning a particular person is usually available to all his/her bosses and affects their career. The company believes that this approach provides the employee with opportunities for improvement.

To refute criticism and prove the effectiveness of its 360-degree reviews strategy, Netflix can collect data and conduct exploratory data analysis (EDA). This analysis is an initial study of data to trace specific patterns and identify connections between various indicators and anomalies (IBM Cloud Education, 2020). Conducting EDA is essential as it helps to make sure the data meets the organization’s expectations, and researchers work in the necessary directions.

Based on evidence from employees, managers can collect text data such as emotional responses about feedback, perceived stress, or perceived job freedom. The EDA, in this case, will be used for natural language processing (NLP), in particular sentiment analysis. These tools are used for subjective data analysis, and for highlighting the attitude, positive or negative, towards the studied subject (“Sentiment analysis explained,” n.d.). Thus, the analysis will demonstrate the emotions, that Netflix’s 360-degree review strategy causes. Since the emotional response and stress level may be more negative due to worries, the data obtained on job freedom will balance the analysis and give a complete picture.

EDA also provides many possibilities for numerical data analysis and its graphical representation. For example, data on high-talent employees who left the firm and adequate-talent employees who were terminated can be presented in histograms for comparison. To demonstrate the effectiveness of Netflix’s review method, this graph can also include the number of retired employees with insufficient qualifications. To refute the criticism, it is necessary that the rates of departed talented employees were low in comparison with other indicators.

Data about job satisfaction ratings from those who perceive and who do not perceive growth in talents and skills must also be compared in a histogram. In favor of using the Netflix method, the graph should show high satisfaction rates from employees that see their professional development. These indicators can be linked to employee perceptions of how they are appreciated and of the company’s innovation level. Understanding the recognition of one’s activities will influence the level of satisfaction with work, and perceptions of innovativeness will likely affect the understanding of professional growth. Despite the differences among them, each of the mentioned indicators, textual and numerical, will demonstrate the attitude to the 360-degree review strategy.

Despite the declining popularity of feedback on employees, researchers continue to prove their effectiveness. For example, in his critical article on this issue, Hunt (2019) emphasizes a considerable number of studies confirming the positive impact of feedback. Hasty and incorrect formulations can explain the decrease in popularity. According to Heathfield (2019), employees tend to perceive assessments personally rather than professionally, which causes a protective reaction. For these reasons, the feedback should be accurate, constructive, and focus on the positive sides.

Thus, there are doubts about the effectiveness of such a procedure as providing feedback on the employees’ work. Designed to motivate and improve productivity, such assessments are often subjective and can have a negative effect. For example, Netflix has recently been criticized because of its employee performance review system. To assess the effectiveness of its method and refute criticism, the company can use exploratory data analysis (EDA), checking the attitude to the review and the results to which it leads. Despite the decrease in the popularity of the feedback, many studies indicate a positive impact, provided that the review was correctly formulated.

References

Heathfield, S. M. (2019). How to provide feedback that helps employees improve. The Balance Careers. Web.

Hunt, S. (2019). Does feedback really improve performance?. TLNT. Web.

IBM Cloud Education. (2020). What is exploratory data analysis? IBM. Web.

Rodriguez, A. (2020). Netflix’s culture of intense feedback comes to a head during the spring review season. Insiders describe how it works. Business Insider. Web.

Sentiment analysis explained. (n.d.). Lexalytics. Web.

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