A Methodology for Deriving Evaluation Criteria for Software Solutions
This methodology aims to help companies, particularly SMEs, more effectively select software solutions by providing a structured way to derive individualized evaluation criteria.
This paper proposes a methodology to derive tailored evaluation criteria for software solutions, addressing the challenge of selecting appropriate software in a broad market. The approach is formalized as a three-layer model that refines criteria from a general catalog based on domain knowledge and industry context, and is demonstrated for Machine-Learning-as-a-Service platforms for small and medium-sized enterprises.
Finding a suited software solution for a company poses a resource-intensive task in an ever-widening market. Software should solve the technical task at hand as perfectly as possible and, at the same time, match the company strategy. Based on these two dimensions, domain knowledge and industry context, we propose a methodology for deriving individually tailored evaluation criteria for software solutions to make them assessable. The approach is formalized as a three-layer model, that ensures the encoding of said dimensions, where each layer holds a more refined and individualized criteria list, starting from a general softwareagnostic catalogue we composed. Finally, we exemplarily demonstrate our method for Machine-Learning-as-a-Service platforms (MaaS) for small and medium-sized enterprises (SME).