Planejamento e alocação de equipes no desenvolvimento de produtos do setor calçadista : um modelo baseado em AHP-Gaussiano e múltiplas mochilas

Abstract

The growing pursuit of competitiveness demands that organizations adopt effective methods for resource optimization and greater accuracy in strategic decision-making. In the product development sector, these challenges are amplified by the complexity of the activities involved and the need to align market demands with internal delivery deadlines. In the footwear industry - characterized by intense competition and constant new product launches - the company's strategic sector is responsible for defining a set of products to be launched in the market. However, production capacity is limited, particularly with respect to the specialized teams responsible for planning the development process. In this context, properly prioritizing products and efficiently allocating these teams are crucial steps to avoid bottlenecks, ensure schedule compliance, control costs, and maintain the quality of product launches. To address the complexity of decision-making processes in environments with multidisciplinary teams and products with varying levels of priority, it is essential to use structured models that consider multiple criteria and operational constraints. In this regard, tools from Operations Research (OR) and Multicriteria Decision Analysis (MCDA) play a key role in converting data into more grounded and effective decisions. This study proposes an integrated decision support model for the product development sector of a footwear company. The model is structured in two main stages: (i) ranking products according to their priority using the Gaussian AHP method, which considers multiple decision criteria; and (ii) allocating production planning tasks to teams through a combinatorial multiple knapsack model. The objective is to maximize the allocation of tasks associated with higher-priority products, while respecting the specific capabilities and limitations of the available teams. The model was validated through a proof of concept based on real data, demonstrating its practical applicability and flexibility for adaptation across different stages of product development, as well as in other industrial contexts with similar characteristics. The proposed approach also allows dynamic adjustments in response to changes in resource availability and shifts in market priorities. In addition to operational benefits, the proposed model contributes to decision-making governance by clearly recording the criteria used and the decisions made, facilitating future reviews and audits. It minimizes human influence in decision-making, reduces operational time, and enhances analytical capacity, generating qualitative gains in planning. Thus, the proposed model not only optimizes internal processes but also strengthens organizational sustainability and competitiveness. [resumo fornecido pelo autor]