Evaluation of Globally Operating Salesforce Staff by Multiple Attribute Decision Making Methods

VSB-Technical University of Ostrava, Faculty of Economics, 70200 Ostrava, Czech Republic

^* Corresponding author: Gabriela.polakova@post.cz

Abstract

Business managers, globally sales executives operating worldwide, representing brands and good reputation of international companies are a special group of staff needing especially flexible working conditions to do their job all over the world. The evaluation and rewarding of their performance is globally linked to achieving business targets. How evaluate results of all involved staff working on different international markets as one set of so many variants and criteria with ensuring transparency, objectivity and fairness? The solution is found in multiple attribute decision methods (MADM). The aim of the paper is to evaluate a group of salesforce staff making international business world-wide by using MADM to identify and reward the best sales executives and at the same time manage to make them to feel be valued for their well-done work, efforts and achievements. Two methods of multiple attribute decision making were used for this evaluation – the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Weighted Sum Approach (WSA). The results of both methods were compared and the more suitable method for this universal application practicable world-wide in terms of the processing complexity and the user friendliness was chosen and recommended. The bonus scheme is based on a healthy competition for sales executives, on a motivation to grow up and gain better results to get additional special bonus beyond the standard rewards for meeting performance targets. Part of this papers is the proposal of flexible bonuses for reached positions in the ranking of evaluated employees.