Manufacturing companies face significant challenges when introducing new product variants due to increased complexity and the need for rapid assessment of their impact on existing factory systems. This is particularly critical for small and medium-sized enterprises with limited resources, where poorly informed decisions can lead to unprofitable investments. To address this, this paper builds upon a previously presented systematic approach for an evaluation and decision model and introduces a “factory profile”, defined by configuration and capacity characteristics of factory objects relevant to variant introduction. This paper systematically identifies and evaluates 232 configuration characteristics of factory objects, based on their direct influence, systemic dependencies, and customization effort. Through a defined evaluation process, this number is reduced to 67 relevant configuration characteristics. Additionally, capacity characteristics are derived from these configuration characteristics. By linking factory objects to change dimensions of a new product variant via a Domain Mapping Matrix, the approach for a capacity-driven decision model enables an early-stage assessment of whether a new variant is value-adding or value-destroying. This capacity-driven decision model allows companies to quickly evaluate necessary factory adjustments, estimate associated costs, and make informed decisions regarding the introduction of new product variants. Future research must focus on operationalizing capacity functions and systematically capturing consequential effects of factory planning measures for comprehensive lifecycle cost evaluation.