Decision Support System for Growth Hacker Recruitment Using the Multifactor Evaluation Process Method (Case Study: Startups in Indonesia)
Keywords:
Decision Support System, Growth Hacker, Startup, MFEP, RecruitmentAbstract
In a highly competitive and dynamic startup ecosystem, the position of Growth Hacker plays a strategic role in driving rapid, efficient, and sustainable user growth and revenue increase. Growth Hackers are required to combine data analysis skills, creativity, and a deep understanding of digital marketing and technology to design and implement innovative growth strategies. Therefore, the recruitment process for this position cannot be done carelessly, but requires a systematic approach that considers various criteria objectively. This study aims to develop a Decision Support System (DSS) using the Multifactor Evaluation Process (MFEP) method to assist managers or recruitment teams in startup companies in assessing and selecting the best candidates for the Growth Hacker position. A case study was conducted on a technology startup based in Indonesia. Four main criteria were used in the assessment: highest level of education, data analysis skills, digital marketing expertise, and experience & portfolio. Each criterion was assigned a weight based on its level of importance, and candidates were evaluated based on the weighted scores of each factor. Based on the final results of the MFEP method application, Alternative A3 with the highest score (0.3341) is recommended as the best candidate for the Growth Hacker position.
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