Evaluating maturity level of big data management and analytics in industrial companies

Manufacturing companies usually ignore their current state of big data and analytics implementation, losing the opportunity to achieve high-performance targets. An evaluation through maturity models can support companies to better focalise their initiatives. However, the existing maturity models only focus on big data, and they lack of a scientific development approach and applications. They are also general in scope and not specific for manufacturing scenarios. This study provides an innovative maturity model, also including an assessment tool and an evaluation method. This model has been designed according to a well-founded methodology that is based on a structured procedure to assess maturity, as follows: organisation, data management, data analytics, infrastructure, governance & security. To enhance its validity, the model has been applied in three industrial companies working in the aerospace, automotive and machinery sectors. The results demonstrate the model's ability to leverage big data management and analytics through a deep, easy, and context-independent assessment that is focused on industrial scenarios. The suggested model enriches the state of art on big data and analytics maturity models providing a methodology and tool to apply on specific industrial case. Academics can benefit from the results to design and guide future research in this field.