The increasing demand for product individualization and the challenges of globalization force manufacturing companies to expand their product range while keeping internal expenses low. To tackle the dichotomy between economies of scale and economies of scope, companies make use of modular product platforms and carry-over-parts. To improve the modular platform performance, it is crucial to define its structure in the early planning phase. In vertical direction, the modular platform structure defines considered technical solutions, whereas in horizontal direction, it is characterized by the products that use these solutions. When introducing or adapting modular product platforms of complex product portfolios, companies often make upfront decisions regarding the modular platform’s structure based on expert intuition. This mainly results from a lack of time, organizational restrictions and missing systematic approaches. The sheer number of product data associated with the products in the portfolio as well as the often missing transparency regarding existing components and interfaces force decision makers to decide in an intuitive approach. However, this hinders an optimal design of modular platforms and reduces the optimal performance exploitation. In order to increase modular platform performance and hence the company´s profitability, a holistic approach prior to the actual platform design process is required to determine the optimal modular platform structure for a complex product portfolio. The basis for this methodology is a generic descriptive model, which helps to describe current and planned products of a serial manufacturer’s portfolio in a structured way. The introduced methodology determines optimal modular platform scopes through systematic identification of anchor products by aid of Data Mining.