A Comprehensive Method for Measuring Flexibility at the Individual and Global Levels: A Case Study in the Automotive Industry

Since the beginning of the 21st century, customer demand has been evolving more and more toward individualized items. In addition, the increase in uncertainties related to geopolitical contexts such as wars, political conflicts, and energy crises, has made the decision process more complex. To respond to these changes, companies are forced to be more flexible, agile, and resilient on the one hand and to apply the concept of mass individualization on the other hand. Knowing that there are several types of flexibility and that higher levels of flexibility generate higher production costs, one of the main challenges for companies is to select the relevant types of flexibility and the appropriate level of them for their projects and objectives. This paper focuses on modelling, measuring, and determining the appropriate level of flexibility. Since the level of flexibility is mainly related to the level of uncertainties, it is also necessary to model the historical uncertainties and their relationship with the company's objective. For this purpose, the proposed method uses the existing key performance indicators (KPIs) of the company, through which the actual levels of several flexibilities are first measured and then the appropriate levels are defined. Furthermore, by considering the interdependence between flexibilities, an aggregation model transforms the individual measures of flexibility levels into a Global Flexibility Indicator (GFI) that allows decision-makers to prioritize the most important project. In addition, this GFI can be used to model unpredictable events and set flexibility targets based on historical data and events. An application of the proposed method in the automotive industry in the context of a new product introduction is presented.