This literature review aims to identify the existing challenges of data-driven service development in manufacturing industries, and a general approach to manage the challenges. The three primary categories are technological, ecosystem- and business model-related. Those are identified and categorized through the lens of data-driven service taxonomy framework. Digital twin was identified as one overarching approach with the potential to solve some of the identified challenges. Future research can focus on exploring the different level of importance of the existing challenges.