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).
翻译:在日益扩大的市场中,为公司寻找合适的软件解决方案是一项资源密集型的任务。软件应尽可能完美地解决手头的技术任务,同时符合公司战略。基于这两个层面,即域知识和产业背景,我们提出一个方法,为软件解决方案制定适合个人需要的评价标准,使其可以评估。该方法被正式确定为三层模式,确保上述层面的编码,使每个层面都有一个更加精细和个性化的标准清单,从我们编制的一般软件学目录开始。最后,我们示范了我们为中小企业建立的机械学习服务平台(MaaS)的方法。