Sustaining Vision: Competency Modeling to Understand Best Practices for Visual Editors

ABSTRACT

Given the rapidly evolving media ecosystem, the need for excellence in visual storytelling and high-performance among those doing that work has never been more critical. Similarly, practitioners maintain that innovation, entrepreneurial thinking, and novel solutions have never been more needed in media organizations. To help identify best practices, competency modeling is useful to optimize and understand the performance of visual editors. Subject matter interviews with 29 experts in a wide variety of media organizations reveal five competencies: professional, management, leadership, communication, and entrepreneurial. Visual editors noted that experience, technology training, media ethics, socially-supportive communication, and advocating for visual work across departments were key components of their work. Implications for best practices, selection, and training of these specialists are discussed, as well as the entrepreneurial nature of their pivotal role. A key insight for media organizations in need of innovative and entrepreneurial activity is that the change agents they need might be found in-house: among the ranks of visual editors.

KEYWORDS:

• Visual editing
• photo editing‌
• competency modeling
• work analysis‌
• best practices
• visual communication
• photographic storytelling‌
• photojournalism

Acknowledgements

The authors express deep appreciation to graduate students Breanna Daugherty, for assistance with interviewing and transcription reconciliation as well as Alexandra Smith, Rhea Tomlinson for further assistance with transcripts; To Dr. Kristina Bauer and Dr. Alexis Fink for consult and discussions on competency modeling and job analysis approaches. To Dr. Kevin Moloney, Dr. Johnny Sparks, and Dr. Tara Pixley for their generous time with manuscript review and edits. Also thanks to undergraduate assistants Rebecca Slezak, Maggie Getzin, and Taylor Sheridan as well as members of the Unified Research Lab at Ball State University with review and important feedback. Special appreciation for two anonymous reviewers for their helpful advice and comments.

Disclosure Statement

No potential conflict of interest was reported by the author(s).