The Influence of Learning Collaboratives on Organizational Communication: Building Teams to Support Innovation Implementation

Background

Adopting and implementing innovative, effective treatments into human service settings depends on dense organizational communication networks (Meyers, Sivakumar, & Nakata, 1999). Network ties diffuse technical information, support, and facilitate collective problem solving that support innovation implementation. Collaborative learning models, which emphasize shared learning, were designed to support innovation implementation and other quality improvements by building dense communication networks within organizational teams (Kilo, 1999). Yet the impact of collaborative learning approaches on organizational communication and implementation is untested. This study examines change in communication patterns within teams from children’s mental health organizations during a year-long learning collaborative focused on implementing trauma focused cognitive behavioral therapy (TF-CBT).  Specifically, we adopt a social network perspective to assess two types of change in intra-organizational communication: (1) change in communication frequency, and (2) change in the structure of teams’ communication networks.

Methods

A pre-post-test design compared communication among 143 participants from 21 organizational implementation teams.  Surveys were administered at the start and end (10 months later) of a learning collaborative. At both time points, participants were asked to list the members of their team, and rate the frequency of communication with each along a 7 point Likert scale. These data were used to calculate several measures for each team including the average communication frequency for each team, and structural metrics (network size, number of links, density, cohesion, reciprocity, transitivity, and centralization). Metrics were averaged across teams and compared over time. Because detecting structural change in networks often depends on size, we also explored whether change in intra-organizational communication patterns differed by team size by comparing change patterns across small (fewer than 6 members, n=11) and large (6 or more, n=10) teams.

Results

Overall, team communication patterns changed over the duration of the learning collaborative, but less than expected.  The magnitude and direction of changes in communication patterns differed by team size. Average communication decreased among the small teams (-.24), but increased among large teams (+.15) from baseline to follow up. Small teams also experienced larger structural changes compared to large teams. Among small teams, there were decreases in density (-16%), reciprocity (-27%) and cohesion (-11%). Large team network structure changed less substantially. Density increased by 2%, and reciprocity and cohesion decreased (-3% and -1% respectively). Small teams became more centralized (+ 16%) while large teams became less centralized (-6%).

Conclusion

Although our study is based on a small sample of organizational teams, our findings have implications for managers and future research. Our results suggest that collaborative learning models may not have large effects on communication patterns for all teams. Rather, learning collaboratives may be more effective for enhancing communication among larger teams, thus leaders might consider selecting and sending larger staff teams to learning collaboratives. More studies examining how learning collaboratives influence communication networks are needed. Areas of future inquiry include assessing patterns within specific role-based relationships, understanding how innovation characteristics influence communication at different implementation stages, and exploring how communication networks may extend beyond the original teams over time.