A multi-criteria approach to robust outsourcing decision-making in stochastic manufacturing systems

Manufacturing outsourcing is a key industry trend towards greater operational efficiency and is related to the discussion of strategic core competencies. We study the issue of contract manufacturing at the strategic-tactical level and approach the topic from a multi-criteria decision-making perspective, since service, cost, quality, and more long-term value-related aspects are involved. To arrive at well-balanced and robust outsourcing decisions with respect to the aforementioned dimensions, we apply a scenario-based approach that is built within the concept of Data Envelopment Analysis (DEA). For this purpose, we use two types of Key Performance Indicators (KPIs): model-based KPIs, which are the result of a modeling approach, and non-model-based KPIs that are derived in an independent assessment from multiple stakeholders. The model-based KPIs are handled through an aggregate planning model which manages the trade-off of capacity vs. work-inprocess costs and uses a queuing network-based approach to anticipate the stochastic and dynamic behavior of a manufacturing system. This allows us to balance customer service, derived from aggregate order lead times, and relevant costs of operations when determining volume/mix decisions for internal and external production. An industry-derived case example with distinct outsourcing options is used to highlight the benefits of the approach.