Piyasa Ücret Bilgilerinin Toplanması ve Sunumu: Türkiye İçin Yöntem ve Model Önerisi

Abstract

From past to present, the companies’ and institutions’ need for labour force has been changing and this change is increasing the importance of employees who can make a difference, have innovative ideas, different skills and knowledge. It is necessary to be competitive in local and global markets to acquire and retain talented employees. In order to manage this competition correctly, it is very important to collect market pay information in an accurate and timely manner. The study is centred around the development of a methodology and model for systematic collection and presentation of market pay information in Türkiye. Wage survey methods in the world and in Türkiye have been examined in the context of academic literature, international organizations, public and private sectors, and a methodology and model proposal have been developed to collect market wage information on job/title basis and present it for the benefit of those concerned. The model was designed to be internet-based and based on the database of the SSI, and the database of the model was enriched with detailed data to be provided by institutional and individual users. The developed model will guide companies and institutions on how to access the most up-to-date pay information, it will help companies and institutions to determine their compensation policies more accurately in case it is implemented. In addition, the model will enable a more transparent pay structure in the market, individuals who are in or preparing to be in the labour market will have accurate information about the market pay level, and trade unionists, researchers and policy makers will have access to an important database. In the first chapter, pay, compensation management and the factors affecting compensation are discussed. The second chapter is focused on pay surveys, in which objectives, methods and design of pay surveys are explained. Besides, pay surveys in the world and in Türkiye are explained within the framework of good practices. In the last chapter, the objectives, assumptions, and implementation of the model, suggestions for the design and setup of the database, and the details of the model's internet application are given. Additionally, how data from different sources will be matched, how calculations will be made and the risks that may arise are discussed. In the conclusion section, the contributions of the model if it is put into practice are emphasized and recommendations for the future are presented.