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-asa-Service platforms (MaaS) for small and medium-sized enterprises (SME).
Domain Knowledge vs. Industry ContextFor the scope of this paper we define two abstract dimensions to describe the theoretical basis of our approach. This simplifies a multi-dimensional problem to a more manageable setting. Every possible aspect is then part of either one of the dimensions.
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