Model-based systems engineering (MBSE) is a modern approach to perform systems engineering activities on complex systems. Although MBSE poses many benefits, including improved con-sistency, complexity management, and requirements traceability, few companies have successfully implemented MBSE, likely in part due to a lack of consistent recommendations regarding its adoption. This paper uses a combination of a literature review and eight semi-structured interviews to evaluate the hypothesis that the applicability of best practices varies on a case-by-case basis due to dependence on factors such as company size, industry, and location. A list of best practices is compiled from analyzing existing works, and a set of corresponding interview questions is devel-oped to assess applicability. Data collected from the interviews is then used to illustrate how unique circumstances in each organization results in the need to have different prioritizations of best practices. Ultimately, the findings presented in this paper contribute to providing a clearer under-standing of the challenges and best practices associated with MBSE implementation.