Information System of Performance Assesment on Startup Business using Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER)

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Abstract

Performance evaluation system has a very strategic role in improving the performance of a company. Companies generally judge performance based only on the financial aspect only, regardless of other aspects that are also not less important. This study aims to build a performance evaluation system using a Balanced Scorecard perspective framework that is a financial perspective, customer perspective, internal business process perspective and learning and growth perspective, which can assist decision makers in evaluating performance and prioritizing competitive alternative measures in enhancing the achievement of strategic objectives company. Implementation of the Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) method of performance evaluation system provides the right performance evaluation data. The data were obtained by calculating the criteria and sub-criteria weightings from 4 perspectives and 14 key performance indicators (KPIs) based on the BSC perspective using Rank Order Centroid (ROC) weighting to obtain criteria and sub-criteria rating according to importance level. Base on case studies, the results of this research indicate that the perspective of internal business processes with a priority weight of 0.521 is the most important perspective in evaluating business startup performance, then the customer perspective with a weight of 0.271, then learning and growth perspective with a weight of 0.146 and perspective finance with a weight of 0.063. While the asset turnover performance indicator with a weight value of 0.009 and profit investment with a weight of 0.004 from a financial perspective are important factors for improvement.

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APA

Tangkesalu, A. A., & Suseno, J. E. (2018). Information System of Performance Assesment on Startup Business using Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER). In E3S Web of Conferences (Vol. 73). EDP Sciences. https://doi.org/10.1051/e3sconf/20187313002

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