Research has repeatedly suggested that under a third of change management endeavors achieve their intended objectives. Large IT projects typically run 45% over budget and 7% over time, while delivering 56% less value than predicted (Bloch, Blumberg and Laartz, 2012). Considering that, by the end of 2019, digital transformation and change spending will reach $1.7 trillion worldwide (IDC, 2019), the recurrent leitmotif of change management requiring change has never been more relevant. As a recognized discipline, change management has been in existence for over half a century, yet this evidence suggests a consistent failure of change interventions to achieve desired value outcomes. Over the past decade, HR professionals have dedicated much effort to optimizing change transformation with a focus on leadership influence. Much has been said about leaders who drive change from the top and the power of leaders as normative social influences of change is well-documented with multi-disciplinary underpinnings (Forsyth, 2015). However new research raises questions about whether leadership-dominated change strategies are as effective as currently believed (Arena and Uhl-Bien, 2016). Too often leaders employ formal structures and hierarchies as misguided maps to guide change interventions. Bloated, outdated organizational charts however can mask how work actually gets done. Data analysis shows many natural leaders carrying high influence are hidden within the ranks and organizations are starting to place a higher premium on social capital to drive change. By engaging influencers in informal networks, an opportunity exists to unlock a new archetype of previously hidden, social leader to emit change. As a result, HR professionals and organizational leadership tasked with instilling change are considering data-driven approaches to social change. Research on informal organizational networks has led to the development of Organizational Network Analysis (ONA), an approach that enables networks of relationships that run through organizations to be mapped. These networks are often not part of the formal structure but grow out of the many interactions that occur daily within the organizational system and between members of the system and those outside it. Although not novel, ONA has moved from a predominantly academic concentration to an organizational analytic approach and emerging change paradigm. It has given rise to organizational custodians, analysis software and specialist vendors, all in a bid to thaw the frozen middle and tap into social influence. In this volatile era of unpredictability, pioneering organizations are using the power of their networks to understand how change really happens and activate it through this untapped magic middle. ONA, when performed with rigor and insight to progress from analysis to application, can accelerate change for both organizations and influencers. However, ONA is not an independent elixir for all change. Caution exists with regard to its translation to action, data privacy and measurement mechanisms. This paper explores how ONA may yield greater change outcomes for organizations, yet pays regard to its limitations for workplace application. I conclude with an invitation for future ONA research, to continue to propel academic analysis and organizational application in the network sciences.