Collaborative networks to deliver services are ubiquitous where public policy or management challenges require the efforts of multiple organizations to solve a problem or assist clients with complex needs. While guidance on how to manage networks abounds, much of it is limited to strategies focused on network inputs, structure, and relationship building. There is a dearth of data and guidance on how to manage real-time network processes, outputs, and outcomes. This is largely due to data limitations that prevent managers and researchers from looking into the “black box” of real-time network operations.
 
Increasingly, networks are using referral system technologies to better integrate health and human services for clients. Referral system technology provides time-stamped data on client case interactions with systems. One indirect advantage of using referral technology to manage communication within networks is that it provides immediate, objective data on real-time interactions. These data can then be used for timely and targeted management interventions to improve efficiency, accountability, and effectiveness of network operations. This advantage also provides opportunities to develop new insights on managing within networks.
 
In this report, we expand network management guidance by focusing on how to use referral system technology data to learn, adapt, and react to workflows within networks and improve organizational performance and client outcomes.