Human systems are critical, yet often neglected in most guidelines and frameworks for data science. We address this concern by developing a systematic framework for understanding human systems that support data science innovations.

• A review of human system elements indicates that successful innovation requires supports at different levels of organisations, which combine to create the organisation's innovation capability.
• Drawing on a series of interviews with key innovators engaged in developing current data science innovations, a more complete picture of human systems in practice was developed.
• This study contributes to the advancement of innovation management theories and calls attention to guiding and engaging individuals through providing support and removing barriers at different organisational levels.
• More practically, innovation managers could use this as a guide to optimise work systems and inform pathways to improve organisation data science efforts.