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The field of Operations & Supply Chain Management (O&SCM) deals with large and complex structures. Evidence from practice suggests that management still runs in silos and decisions are often focused on specific functions as the totality of the problem and the impact on the broader organisation is not always understood. To manage such structures, managers have been investing in information technology to improve data availability and quality. Finally, good data is available with potential to enable holistic decision-making (DM). The field of analytics answers the need to transform data into information to support DM processes. Visual analytics rely specifically on visual representations to support DM processes. As visual analytics is still at its infancy, the aim is to identify what types of visual analytics has been used in empirical research, to support what decisions and its impact in O&SCM context. Evidence based literature review, also known as systematic literature review (SLR) method is used to review 41 papers. The most common type of visual analytics identified is modelling, mapping and visual interfaces between data and managers. These most often support Plan and Make type decisions. Vast majority of applications are identified as positive, enabling better understanding of the problem, greater management involvement in the process and better communication. Future research is needed to define the term “visual analytics” as the field is still at its infancy. Development and empirical testing is required of whether the identified visual tools are an enabler for holistic decisions in the O&SCM context.