This post is the second half of a two-part series. To view the first post, click here.
In any given market system, elements of both small-group and large-group dynamics co-exist. What matters most, however, is which dynamic is dominant. As a result, when analyzing a market system to understand the prevalence of small group and large group institutions, it is useful to tease apart the regulative, normative and cultural-cognitive elements. Showing the ways in which large and small group thinking might co-exist at different institutional levels provides a sense of direction to programs looking to influence change towards a large group orientation.
Assessing how predominant or influential small group institutions manifest in market system behavior is critical. In addition, while regulative variables are considered “faster” (i.e., easier to change), interventions based on “slower” normative or cultural-cognitive variables will be more likely to yield sustainable, self-enforcing changes within the market system. For example, a common situation occurs when the regulative institutions have been reformed to align with large-group principles (e.g. employment equity laws and regulations), yet the normative and cultural-cognitive institutions continue to reflect small-group norms (e.g. discriminatory hiring based on kinship/family ties). In these cases, the informal institutions typically control behavior, leading to a disconnect between law and practice. For example, a Kenyan project used an earlier version of this framework to gain insights into cases where there was a high a prevalence of corruption/elite capture, which is a common manifestation of small group dynamics as normative/cultural-cognitive institutions around communal loyalty often create a ‘greater good’ perception that reinforces such behaviors.
The table below gives high-level insight on the kind of ‘map’ that could be produced for any given market system:
With a greater understanding based on a more nuanced and contextual perspective of local behavioral patterns, practitioners can design program strategies and intervention tactics that are more effective at catalyzing durable change.
As a default, most projects start with a set of assumptions that a society should be moving toward large group dynamics. While there is increasing evidence that such institutional change does result in higher life expectancy, better health and educational outcomes, etc. (i.e., key development objectives), the process of change will be messy, with winners and losers and shifting responsibilities for who manages the downside risk from change. As a recent book on the spectacular development in China lays out, (Ang, Yuen Yuen, How China Escaped the Poverty Trap, September 2016) institutional or systemic change involves co-evolution of institutions and market behaviors. The historical review of 40 years of China’s development reveals a process of smaller emergent ‘viable fit’ changes that catalyze additional nuanced changes that also fit the context. Each smaller change has to deal with systemic pushback as a result of eventual clashes with accepted institutions. Many small changes are reversed or blocked, while others take hold. Over time, this process can result in substantial change, as in China, but it is more meandering. The viability of any particular change is often uncertain at a given point and time.
For systems thinking practitioners, adaptive management has been normalized in the process of probe, sense, and respond. For this process to be effective, it requires some way to parse observable patterns to know where or how to probe, make sense of changing patterns, and respond tactically (including re-allocating resources). Typically, practitioners rely on observable manifestations of regulative, normative, and cultural-cognitive institutions drawn from countries defined as ‘developed’. These manifestations are often framed as best practices or the right way of doing something, but often do not fit ‘developing’ country contexts. Drawing again from the Kenyan case, donor programs have for years predefined that a cooperative organizational structure was the right way to improve cooperation within the dairy market system. When applying this framework, donors should have recognized that small group dynamics were at play. Instead, sustained focus on an organizational structure that reinforces group loyalty at times amplified adversarial relational contexts between farmers and processors as the answer. When an earlier version of the framework was applied, the project shifted away from pushing any specific organizational structure and focused more on amplifying specific behaviors that align with large group dynamics, such as clear performance-based supply chain management tactics that can form the foundation of building a trusted commercial relationship between farmers and processors.
The underlying management philosophy we propose is self-selection, which involves uncovering and directing attention and resources towards attractors. These examples of behavior attract attention and help move other system actors towards what’s new because of interesting and desirable features of the new behavior. This is not about an old, stable company making a dramatic change. Instead, programs should be looking for outliers - an actor or person keen to change (i.e., not vested in the current dynamic).
The idea of an attractor or outlier is that over time, the behavior can become normalized – reinforced by emerging normative institutions. Thus, change is driven by an internal process based on benefits – including social benefits. From this point of view, we understand leverage relative to the potential amplification of the attractiveness of the behavior. This way of thinking can have a substantial effect on tactics, as the idea of locating ‘problems’ and fixing them via training or other direct interventions ceases to make sense. Firms have more leverage than farmers, but the firm itself is not the point – it’s a signaling tool for propagating new norms. The firm’s behaviors signal back into the system that the behaviors are attractive and the source of new normative institutions. Over time, as those norms become more dominant, they may also replace assumptions of ‘how things work’, and become embedded as cultural-cognitive institutions.
Conclusion: Pragmatic questions for testing & call for partnerships
This way of thinking links important strands of systems thinking in development that need further exploration. Important next steps include building out practice guidance to help practitioners understand these strategies and tactical decisions (what to do and why), to move beyond the overly simplistic and inaccurate “direct” versus “indirect” understanding of facilitation. Here are some important questions that merit deeper investigation:
Written by Mike Klassen and Mike Field
This post is the first half of a two-part series. To view the second post, click here.
The field of market systems practice has embraced complexity thinking in recent years. In general, this is a great thing: acknowledgement of complex and multidimensional causes, the internal drivers and momentum of systems (with or without us as development actors), and the unpredictability of response help keep our egos in check. However, while we have embraced complexity, we continue to ignore the important and difficult task of emergent trade-offs that a society has to deal with as it develops. So, while ardent supporters of complexity often say, “it’s better to let the system itself decide,” the decision to intervene in another country is itself a normative act. We need to take ownership of this, and increase our willingness to stake our assumptions around the effects of system change outcomes and whether they are contextually better or worse for a given society. To do this thoughtfully, we need a better framework for evaluating the underlying institutions. When complexity is combined with institutional thinking, the framing can provide greater clarity on system dynamics and how a given change would likely result in some trade-offs, which can then be assessed as better or worse, thus allowing a project to either amplify or dampen signals favoring the change.
For the past six months, a team has mined academic sources to investigate possible frameworks that can help explain the deeper social and cultural norms and institutions that underpin market systems. While that work focuses on inclusive, entrepreneurial market systems in the context of enabling environment reforms, we think it has wide applicability to all market systems programs. This blog post introduces the two big ideas we propose as the basis for an institutional view of market systems: (1) small group vs. large group thinking, and (2) regulative, normative and cultural cognitive institutions. We then sketch out how these could be used by managers making decisions about allocating resources in a market systems program.
Small group vs. Large group
The distinction between small group and large group societies or institutions is best articulated by David Rose:
An important step in the economic development of any society is being able to move from only being able to support personal exchange to being able to support impersonal exchange. A completely small group sense of morality is adequate for personal exchange but becomes increasingly inadequate as exchange and cooperation becomes impersonal because it is conducted in larger group contexts. (Rose, 2011)
Large group societies allow risk management at a societal level, through institutions that evolve to support impersonal exchange and trust in society beyond simply personal relationships. In contrast, small group societies centralize resources and control, and rely on strong family and kinship ties, mitigating risk at the level of the small group. This can be an incredibly important community-level safety net, but it leads to exploitative relationships as it is deemed morally acceptable and even important for members of a community to extract resources from those outside their group in order to support their own. When small group institutions dominate, it is typical that higher-level ideas of merit are devalued, and substantial segments of society are blocked from meaningful participation as power is wielded to the benefit of the smaller group holding power.
Broadly, ‘development’ can be thought of as the trajectory from mostly small group societies to large group societies, however this is not a simple, one-way path. There is no easy transition from a low-income authoritarian government to a society where rule of law is respected and equity is enshrined in cultural and legal norms. The process of change creates winners and losers, and these are important trade-offs we need to reflect on in our work. It’s also important to note that countries can move in either direction - in recent years there is a clear trend toward populism and authoritarianism – most starkly in Hungary and Poland, but also in countries like the US and UK – which can be seen as manifestations of small group thinking.
Ultimately, the small versus large group framing sets up an institutional spectrum that can help program managers make decisions on what evidence to gather and how to allocate development resources when wading into an uncertain environment.
Three types of institutions
Institutions are the ‘rules of the game’ that shape human behavior in conscious and unconscious ways. A common distinction is made between formal institutions (laws, regulations, contracts) and informal institutions (belief systems, social norms). We take that distinction a step further, and draw on the work of sociologist W. R. Scott, who proposed three types of institutions: regulative, normative and cultural cognitive. These flow from the more explicit and formal (regulative institutions) to the more implicit and taken-for granted (cultural cognitive). A helpful analogy is the iceberg model in systems thinking, which elaborates how mental models mold systemic structures that ultimately shape patterns of behavior and events.
The three institutional types each influence behavior in different ways, based on different logics, compliance mechanisms and sources of legitimacy. Regulative institutions explicitly coerce behavior through rules or sanctions enforced externally. Normative institutions encourage behavior by appealing to the need for people to belong by following desirable group norms. Normative institutions also sanction people for not following norms via social mechanisms like shame. Cultural cognitive institutions shape subconscious assumptions, constructing a taken-for-granted view of how the world works that shapes the available choices for action or behavior.
What is most important about this distinction is that the more deeply embedded the institution, the more dominant or controlling its influence on a market system’s behaviors. When all three sets of institutions align, behavior patterns can be deeply entrenched and very difficult to change. When there is conflict or different signals being sent, it is the normative and cultural cognitive institutions that tend to dominate. It is important to note that change can happen even when a behavior is deeply held, but it would likely take longer to change.
Implication for practitioners
Complexity was central in helping practitioners understand and embrace the messiness of systemic change. For example, in Zambia, a project decided that a lead farmer model was the right way to push the project’s ideas on improved farming practices. The project provided that farmer with resources and training that other farmers could not access. While complexity thinking might align with this tactic as a way to catalyze change as it could present an attractive alternative for other farmers, institutional theory clearly would have identified the local normative and cultural-cognitive institutions around communal loyalty that raise the potential for communal backlash. In the end, that farmer’s fields were burnt down by the community as they were perceived as behaving outside of acceptable boundaries as defined by local manifestations of institutions. Additionally, institutional theory helps practitioners better understand their own biases. In the Zambia case, it’s clear that the farmer model is based on long-held North American normative and cultural-cognitive institutions around individualism and individually-driven innovation that often does not translate in other country contexts. By combining complexity to understand the messiness of change, and institutional theory to understand localized and contextualized trade-offs, practitioners can make better and more informed decisions on how best to catalyze an internal change process.
Institutional theory also helps practitioners to understand change at deeper levels. Small group societies are very effective in certain ways that are positive, including deep and wide family/friends/communal networks that absorb shocks and stresses. At the same time, small group societies tend to create high levels of haves and have-nots with internal hierarchies. Similarly, larger group societies rely heavily on more formal mechanisms and innovation to neutralize/mitigate risks, but when those functions perform poorly, family/communal networks are often not strong enough to absorb shocks. This shows how important it is to think through change processes carefully, to avoid the unintended consequence of eroding existing (small-group) risk management mechanisms before new society-wide (large-group) mechanisms are fully developed.
For more on how to apply this framework in practice, see Part 2 of this blog.
Written by Mike Klassen and Mike Field
The MSDHub Blog Series is authored by respected implementers and donors of market systems projects globally.