According to the World Health Organization (2008), human beings need inter-sector collaboratives to form and function well to address the broad array of health challenges we face today (Hinzey, 2016). More specifically, we must have people with diverse backgrounds, areas of expertise, and practical experience from private businesses, government, academia, and non-profits working better together to successfully address everything from infectious disease incidence to food insecurity to asthma to childhood obesity.
These inter-sector collaboratives are what researchers and academicians refer to as complex adaptive systems (Chiles, Meyer, & Hench, 2004; Durie & Wyatt, 2013; Institute of Medicine, 2001; Regine & Lewin, 2000; Trochim, Cabrera, Milstein, Gallagher, & Leischow, 2006; World Health Organization, 2008; Zimmerman, 2011). Complex adaptive systems are all around us and are recognizable because they are made of a number of interacting elements (i.e. ideas, people, teams, procedures, policies, behavioral norms, and so on) that change over time because the interactions between them cause them to learn and adapt (Hazy, Goldstein, & Lichtenstein, 2007). As such, inter-sector health collaboratives are the quintessential complex adaptive systems as they involve people with different ideas, philosophies, and priorities interacting, experimenting, learning, and adapting over time, in this case, for the purposes of addressing complex health problems (Hinzey, 2016).
However, the prevailing evidence is that these essential inter-sector collaboratives “have not been successful in either getting the appropriate sector representatives to the proverbial table and/or accomplishing the outcomes the system was designed to achieve” (Hinzey, 2016, p. 4, referencing Kadushin, Lindholm, Ryan, Brodsky, & Saxe, 2005). The reasons behind these inter-sector collaborative failures could be any number of things. The primary culprit, though, is likely poor connectivity (Varda, Chandra, Stern, & Lurie, 2008) between the people and things that make up the inter-sector collaborative. “The more robust the connectivity between people and things within a complex adaptive system [like an inter-sector collaborative], the higher probability said system will function effectively” (Hinzey, 2016, p. 3, referencing Plowman et al., 2007; Regine & Lewin, 2000). Conversely, the poorer or weaker connectivity (i.e. relationships) between people and things within a complex adaptive system, the higher probability said system will fail (Hinzey, 2016). Therefore, we need to enhance the relative connectivity and/or relationships between the people and things of these inter-sector health collaboratives to ensure these complex adaptive systems can function well enough to address the major health challenges of our time.
How do people in positions of influence within each inter-sector health collaborative enhance the relative connectivity between the people and things of their respective system? First, they should consider familiarizing themselves with the specific dimensions of connectivity that have been previously defined in the literature (Hinzey, 2016, p. 226, referencing Varda, Chandra, Stern, and Lurie, 2008). Specifically, these dimensions include: “1) The membership of said system (i.e. having the “right” people at the table to accomplish system goals); 2) The strategic nature of the interactions within the system (i.e. the agents of the system that need most to be connected are connected); 3) The role of system agents (i.e. new/younger systems should have some agents focused on centralized coordination while older systems should have reached a point of distributed coordination roles between its membership); 4) The frequency of interactions between agents (i.e. new connections may need a higher frequency of interactions while older, more trustworthy connections may not require such a high frequency); 5) The strategic value of system agents (i.e. agents that bring more power/influence/resources to the table and get more actively involved heighten the value of connections); 6) The level of trust among agents (based on reliability, shared mission, and capacity for authentic conflict resolution); and 7) The level of reciprocity (i.e. equal or near-equal return on investment of system agents)” (Hinzey, 2016, p. 17 referencing Varda, Chandra, Stern, & Lurie, 2008, p. E4-E5).
Next, people in positions of influence within new, emerging, or established inter-sector collaboratives should consider using these dimensions or indices of connectivity to guide their assessment of their system’s current levels of connectivity (Hinzey, 2016, p. 226). People throughout the system might reflect on the last four indices in particular: frequency of interactions they have with others as well as the relative levels of trust, value, and reciprocity they experience with others. These informal reflections may be best suited to occur in advance of more structured conversations on the performance and/or future direction of the inter-sector collaborative so that members associate these processes with each other.
Finally, inter-sector collaborative members—both those in positions of influence and those who are not—should consider implementing logical options for addressing lower or weaker levels of connectivity (Hinzey, 2016, p. 226). These options might include accomplishing small wins together, recognizing collaborative contributions and commitments to the system, and/or even spending social time together outside of formal meeting times.
That said, is building connectivity between the people and things of an inter-sector health collaborative enough to move the system to achieve outcomes? Perhaps it is, but perhaps it is not. Understanding, assessing, and improving connectivity between the people and things of the system are undoubtedly crucial first steps, but creating an environment wherein these more robust connectivity levels can be supported, sustained, and leveraged is just as critical. In this vein, members of these collaboratives should also consider practicing a newer type of leadership that is better suited for environments wherein the people and things of these systems interact in largely uncontrollable, unpredictable ways—like the environment of an inter-sector health collaborative (Hinzey, 2016, referencing Plowman & Duchon, 2007, and Regine & Lewin, 2000). Rather than seeing this lack of control as a negative threat, this type of leadership capitalizes on that ambiguity and sees it as an important source of creativity that can lead to innovative solutions, potentially moreso in situations when people within the system are connected robustly enough to withstand the stress caused by uncertainty and lack of control. Indeed, this type of leadership—called complexity leadership—is all about cultivating “largely undirected interactions among individuals, ensembles, and sets of ensembles to create uncontrolled futures” (Marion & Uhl-Bien, 2001, p. 394) in order to “enable productive, but largely unspecified future states” (p. 391).
Beyond accepting that leadership is about influence rather than control as a fundamental principle, practicing complexity leadership involves employing specific types of behaviors that shape the environment and/or system in such a way as to enable the environment to move toward chaos when it is too ordered and/or toward order when it is too chaotic. In other words, it is about influencing the environment to balance between order and chaos (Uhl-Bien & Arena, 2011). Administrative leader behaviors are behaviors that favor order; adaptive leader behaviors are behaviors that favor chaos; and complexity leader behaviors are those that favor balance between the two extremes. “Specifically, thirteen administrative leader behaviors have been previously identified and described in the literature” (Hinzey, 2016, p. 15). An example of an administrative leader behavior includes “focuses on alignment and control—alignment of vision, mission, strategy, and tasks, and control of such” (Hinzey, 2016, p. 15, referencing Uhl-Bien, Marion, & McKelvey, 2007). “Seven adaptive leader behaviors have been previously identified and described in the literature” (Hinzey, 2016, p. 15). An example of an adaptive leader behavior includes engaging in debate over conflicting ideas (Hinzey, 2016, p. 15, referencing Uhl-Bien, Marion, & McKelvey, 2007). Lastly, “thirteen complexity leader behaviors have been previously identified and described in the literature” (Hinzey, 2016, p. 16). An example of a complexity leader behavior is “injects external tension by relaying messages about environmental circumstances and/or competition” (Hinzey, 2016, p. 16, referencing Uhl-Bien, Marion, & McKelvey, 2007).
By practicing this form of leadership—which includes employing these administrative, adaptive, and complexity leader behaviors—rather than more historical models of leadership that value the hierarchy and control that does not or should not exist as much in collaborative environments, members of inter-sector health collaboratives can better support, sustain, and leverage the robust connectivity and/or relationships they have worked to build in order to ultimately accomplish the complex objectives of the system. That is not to say that doing either—building robust connectivity or practicing complexity leadership—will be easy. Indeed, it will require some members of inter-sector health collaboratives to conceptually re-frame their understanding of how to function well, especially those members who represent sectors that are largely bureaucratic, highly controlled, and/or highly regulated. Nevertheless, it is a re-framing that must occur; otherwise, we will be perpetually approaching the health challenges we collectively face in old ways that yield the same old failures. The recipes for success exist; we must simply acknowledge them, learn about them, and employ them as individuals, as teams, and as collaboratives so that we can move past the nuisances of preventable health conditions and move toward the higher potential we have as a species.
Angie is an environment creator, organizational science geek, and complexity leadership practitioner. She gets to learn, teach, and build great relationships with social mission-driven practitioners; inquisitive university staff, faculty, and students; and change-makers throughout the DC metro area every day. To connect, reach out to her at This email address is being protected from spambots. You need JavaScript enabled to view it..
References:
- Chiles, T., Meyer, A., & Hench, T. (2004). Organizational emergence: The origin and transformation of Branson, Missouri’s musical theaters. Organization Science, 15(5), 499-519.
- Durie, R. & Wyatt, K. (2013). Connecting communities and complexity: A case study in creating the conditions for transformational change. Critical Public Health, 23(2), 174-187.
- Hazy, J., Goldstein, J, & Lichtenstein, B. (Eds.) (2007). Complexity systems leadership theory: New perspectives from complexity science on social and organizational effectiveness. Mansfield, MA: ISCE Publishing.
- Hinzey, A. (2016). Exploring how complexity leader behaviors shape the connectivity of agents within a complex adaptive system: A case study (Unpublished doctoral dissertation). The George Washington University, Washington, DC.
- Institute of Medicine (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: Committee on Quality for Healthcare in America.
- Kadushin, C., Lindholm, M., Ryan, D., Brodsky, A., & Saxe, L. (2005). Why it is so difficult to form effective community coalitions. City & Community, 4(3), 255-275.
- Marion, R. & Uhl-Bien, M. (2001). Leadership in complex organizations. The Leadership Quarterly, 12(4), 389-418.
- Plowman, D. & Duchon, D. (2007). Emergent leadership: Getting beyond heroes and scapegoats. J. K. Hazy, J. A. Goldstein, & B. B. Lichenstein (Eds.), Complex systems leadership theory: New perspectives from complexity science on social and organizational effectiveness (pp. 35-60). Mansfield, MA: ISCE Publishing.
- Plowman, D., Solansky, S., Beck, T., Baker, L., Kulkami, M., & Travis, D. (2007). The role of leadership in emergent, self-organization. The Leadership Quarterly, 18(4), 341–356.
- Regine, B., & Lewin, R. (2000). Leading at the edge: How leaders influence complex systems. Emergence: A Journal of Complexity Issues in Organizations and Management, 2(2), 5–23.
- Trochim, W., Cabrera, D., Milstein, B., Gallagher, R., & Leischow, S. (2006). Practical challenges of systems thinking and modeling in public health. American Journal of Public Health, 96(3), 538-546.
- Uhl-Bien, M. & Arena, M. (2011, August 6). Findings on complexity leadership: The key role of enabling requisite complexity. Presentation 2 in Complexity leadership theory (CLT): Enabling requisite complexity in organizations. [OD Symposium Oral and Power Point Presentation]. Academy of Management Meeting. San Antonio, TX.
- Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting leadership from the industrial age to the knowledge era. The Leadership Quarterly, 18, 298-318.
- Varda, D., Chandra, A., Stern, S.A., & Lurie, N. (2008). Core dimensions of connectivity in public health collaboratives. Journal of Public Health Management and Practice, 14(5), E1-E7.
- World Health Organization. (2008). Health equity through intersectoral action: An analysis of 18 country case studies. Geneva, Switzerland: Editorial Committees of the Public Health Agency of Canada and The World Health Organization.
- Zimmerman, B. (2011). How complexity science is transforming healthcare. In P. Allen, S. Maguire, & B. McKelvey (Eds.), The SAGE handbook of complexity and management (pp. 384-400). Thousand Oaks, CA: Sage.