A Reference Process Model for Usage Data-Driven Product Planning

Meyer, Maurice
Wiederkehr, Ingrid
Panzner, Melina
Koldewey, Christian
Dumitrescu, Roman
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Cyber-physical systems generate and collect huge amounts of usage data during operation. Analyzing these data may enable manufacturing companies to identify weaknesses and learn about the users of their products. Such insights are valuable in the early phases of product development like product planning, as they facilitate decision-making for product improvement. The analysis and exploitation of usage data in product planning, however, is a new task for manufacturing companies. To reduce mistakes and improve the results, companies should build upon a suitable reference process model. Unfortunately, established models for analyzing data cannot be easily applied for product planning. In this paper, we propose a reference process model for usage data-driven product planning. It builds on three well-established models for analyzing data and addresses the unique characteristics of usage data-driven product planning. Finally, we customize the model for a manufacturing company and demonstrate how it could be implemented in practice.
Business Intelligence, Business Analytics and Big Data: Innovation, Deployment, and Management, data-driven design, industrial data analytics, product planning, reference process model
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