When Bill Drayton of Ashoka introduced the idea of “social entrepreneurship” in the 80s, dynamics within the social sector were irrevocably changed. The concept that businesses could “do well by doing good” – profit by serving others – wasn’t new. In fact, this is the force behind the theoretical “invisible hand.” However, the reversed suggestion that organizations could “do good by doing well” – more effectively serve others by seeking financial self-sufficiency – was unheard of, and radically challenged popular ideas.
Now, this concept has achieved mainstream approval and adopted the more inclusive term of “social enterprise.” A whole spectrum of mission-money practices have emerged, from nonprofits looking for stable revenue to businesses creating so-called Corporate Social Responsibility programs.
The boons of social enterprise have been studied and praised by many academic voices and viewpoints. One field that hasn’t yet joined in is that of systems science, the study of how things and their interactions produce behavior. This is astonishing, as systems thinking highlights one of the most important contributions of social enterprise – its power to align the intentions of donors and recipients.
On Systems, Goals, and Feedback
Before we apply a systems perspective to social businesses, it’s worthwhile to provide a brief introduction to some basic systemic theories.
Take a given problem, and a given action taken to correct that problem:
This is a simplified version of what systems science calls a “causal loop diagram,” so named because it attempts to illustrate the causes behind system behavior. The arrow signifies an effect – in this case, the action is trying to change the problem.
Usually, the choice of action is informed by the nature of the problem. A more serious problem motivates a more more dramatic action; conversely, if the action helps fix the problem, the action will likely decrease.
This is what systems scientists refers to as a “feedback loop” (or the causal loop of causal loop diagrams). While nutritionists count calories and astrophysicists measure lightyears, systems operate in feedback. Feedback loops are what govern a system’s behavior – in different contexts, feedback can punish crime, grow a business, or eliminate a species.
Put simply, feedback is what systems use to accomplish goals. The goal-seeking behavior of systems has earned its own discipline, cybernetics, and can be complex enough to draw the attention of chaos theorists studying “attractors.”
For our purposes, we only need to know that when feedback mechanisms become less effective, the system is less likely to be able to seek its goals. Feedback loops grow weaker by becoming less direct – the more layers information has to go through, the less likely it is to effectively direct action – less timely – if information is delayed, action is changed in response to the wrong facts – or less powerful – the feedback lacks the clout to produce a change.
Using what we now know about system structure and feedback, we can compare the two dominant ways society solves problems: business and government.
Public, Nonprofit, and Private Systems
Let’s take a look at the feedback structure of the typical government agency:
We begin with a problem. After a delay, people become aware of the problem, and desire change. Eventually, building dissatisfaction begins affects the lifeblood of political organizations: elections. Shifting reelection chances create concerns within governmental agencies, which finally adjust the action itself.
Given the three ways feedback loops can weaken – indirectness, timeliness, and power – we can analyze the governmental feedback loop. It’s easy to see that the loop is neither direct nor timely, slowly passing through multiple groups of people before finally reaching the root problem. Thankfully, the loop does have a significant amount of decision-making power – if a government’s constituents are on its side in an issue, its freedom to affect the problem is unparalleled.
These strengths and shortfalls explain some of the known failures of political systems. Specifically, a problem can slip through the cracks by failing to attract media attention (therefore unable to influence public opinion), as in the consistent, continuing wars in central and northeastern Africa, or by lacking the social backing to affect political reelection possibilities, such as many issues plaguing the poor in less democratic countries. In addition, the many layers information must filter through can lead to ineffective or even harmful action, such as the IMF’s Structural Adjustment Programs in the late 20th century.
What about the nonprofit sector? Here’s one analysis of a nonprofit feedback loop:
While there are fewer steps in the process, there are some serious shortcomings. Firstly, the nonprofit loop has much less power to alter the problem in question, limited both by its scale and by the resources available to it. More unfortunately, the filter between a problem and donors is an incredible handicap, featuring huge delays and distorted facts. Because of this filter, donors have far more power over nonprofit action than stakeholders who actually suffer from the problem, causing dramatic inefficiencies.
This is an example of one of the most important phenomena in systems science: sub-optimization. Systems sub-optimize when one of its members seeks a goal that goes against the goals of the system itself. It happens when a salesman finds a loophole that increases his commissions at the cost of the company, when the body’s urge to ward off invaders causes an allergic reaction, or when developing countries relax environmental regulation to encourage economic growth. Sub-optimization is rampant in almost all sciences: an economic example is the “tragedy of the commons,” where individual self-interest destroys a common resource, and members of biological systems exhibit “cheating,” where one member of a symbiotic relationship violates the agreement in order to profit. The phenomenon has even earned its own discipline, game theory, which examines situations where individual goals override the common good.
Nonprofit systems sub-optimize when donors intentionally or unintentionally push NGOs away from the actual problem. Sometimes this happens when donors have a “pet problem,” a charitable cause that they take personal interest in, regardless of its objective importance. This happens in the US with breast cancer research – while breast cancer is irrefutably a horrible illness, and the flow of funds has made a significant impact, breast cancer itself consistently causes far fewer deaths than cardiovascular disease, a problem that receives much less media coverage and funding.
It’s worth mentioning that sub-optimization happens in the political realm as well, but far less dramatically (at least in democratic systems). This is because while politicians and officials may have goals that run contrary to public trends, the threat of diminishing election chances ultimately makes them subservient to popular demand, more-or-less forcing political and public goals to align.
The last significant player is the private sector, providing us with the following causal loop diagram:
Business feedback loops operate through one important filter – what economists sometimes refer to as “willingness to pay” (WTP). That is, a problem only affects businesses through peoples’ willingness to pay for the problem to be solved.
Evaluating the strength of the feedback loop leads to a couple impressive discoveries. Firstly, research has shown that this feedback loop is incredibly timely, with a changing problem sweeping through WTP and business circles at an astonishing speed. While entry barriers may create a “minimum WTP” that precedes initial private sector involvement, once businesses are in the picture, they are quick to adapt to fill the need.
In addition, the fact that this loop’s power is directly related to its success in solving that problem – that is, if a business effectively meets a need, it is rewarded with capital, further strengthening its ability to meet the need. This virtuous cycle is referred to as “positive” or “reinforcing feedback,” and dramatically increases the private sector’s power. This phenomenon can be seen to a more limited degree in political systems, through taxes, and very, very faintly in nonprofit systems, through donors’ willingness to offer funds.
However, business systems suffer from one incredibly sub-optimizing setback. Because its feedback is dependent on a problem’s translation to WTP, needs that don’t readily offer themselves to that translation – such as environmental issues, or the needs of the poor – will not attract private sector involvement. Indeed, since this feedback ignores these elements, these systems often cause significant harm in these areas, marginalizing the impoverished and becoming the single greatest factor in the global environmental crisis.
Thus far, we’ve learned about the strengths of these systems, such as political systems’ power and wide knowledge base, nonprofits’ capacity to fill gaps left by the other systems, and businesses’ ability to reinforce their own effectiveness. We’ve also seen the causes and nature of sub-optimization in three kinds of social systems: misguided and delayed action in political systems, disconnect between donors and beneficiaries in nonprofit systems, and exploitation of people and planet in private systems.
So how can we eliminate these problems, while capitalizing on these advantages?
Our Hero: Social Enterprise Systems
From a cybernetic (goal-seeking systems) perspective, a simple definition of social enterprise would be: any organization or effort that blends the feedback processes of public, nonprofit, and private systems. Therefore, we can analyze social enterprise as “blended systems,” and examine each pertinent feedback loop.
Let’s start with the private, or profitable, feedback loop:
This is almost identical to the loop associated with business systems, and shares its strengths and weaknesses. The major advantages of this loop include the capacity for speedy action and the ability to “succeed by succeeding,” i.e., use previous successes to fund future action.
Like private systems, this loop lends itself to exploitation due to the financial filter, overlooking or exacerbating problems that don’t lend themselves to revenue. However, social enterprises are slightly superior to businesses in this regard: they can help people who themselves aren’t willing to pay by finding others who are willing to pay. For example, asking the homeless to pay for vocational training may be ineffective, but businesses may be willing to pay for access to trained labor.
If we stopped there, social enterprise would simply be a more innovative business model. However, our definition of social enterprises as blended systems suggests the presence of nonprofit- and public-like feedback, as shown here:
The properties of this secondary loop are almost the reverse of the primary. While this feedback loop is far less timely than the first, and filters may distort information, it is more inclusive and holistic. Social enterprises need not rely exclusively on traditional income for survival, but can be supplemented by donations private, nonprofit, or governmental organizations. Conversely, these groups can censor harmful social enterprises through regulation, though only political systems have the clout to enforce their decisions.
One last relationship is worth exploring. Observant individuals might have criticized my model’s assumption that popular opinion can only affect social businesses through pressure on middle-man organizations. There is another, more direct way the “commonfolk” can influence social enterprises, namely through donations:
This loop blends aspects of the private and public-nonprofit loops. Specifically, while it’s more direct and timely than public-nonprofit feedback, it still suffers from the distortion typical of donor relationships. In addition, donations lack the level of power that nonprofit donors do – whereas a lack of donations can effectively suffocate a nonprofit organization, social enterprises have limited ability to adapt by substitution private or institutional funds.
Real-World Implications
What are the practical results of these relationships? While there are many, including the capacity to adapt to unique problems and bring more resources to bear in solving them, these have already been thoroughly analyzed and praised by many disciplines. One, however, has been largely ignored: the social sector’s miraculous ability to goal-seek.
From a purely cybernetic or systems-science perspective, the feedback loops of social businesses are far, far superior to anything yet seen. The novelty of the private loop has proven invaluable in its swift, stern control. Businesses must serve their customers, or they will quickly die; now, social enterprises face the same healthy stress, forcing them to learn and adapt to the needs of their beneficiaries.
In addition, the three loops form redundancies, compensating for each others’ inadequacies. If a business-minded enterprise is profiting, but the root problem is unaffected or worsened, then (after a delay) the other loops will activate, threatening to reduce funding or call for legal commitment to measure measure and meet social goals.
Direction for Future Action
Given the systemic strengths of social enterprise, the question may be asked, “How can these advantages be safeguarded and built upon?” The simple answer would be to strengthen the relevant feedback loops. Systems science predicts that the loops will be strengthened proportionate to their regulatory capacity – more powerful loops will naturally develop faster than others.
The private loop, being the fastest-acting of the relevant feedbacks, has already been well-developed through experience and research. The field is still relatively new, however, so there is still work to be done in standardizing “best practices” in the industry.
Due to its characteristic delays, the public-nonprofit loop is woefully under-developed. There are few legal definitions of what a social enterprise is, and how it can be regulated. Should they be taxed like businesses? Held accountable to their missions like nonprofits? Without a framework, political forces remain largely impotent. Since the public-nonprofit loop is a vital “feedback fallback,” making up for the failings of the private one, its development deserves far more focus than it currently enjoys.
Social enterprise is a powerful evolution in society’s ability to seek its goals. This tool must be researched, quantified, and invested-in so as to enhance its growth. If this happens, the world can take a quantum leap in the right direction.
Like this:
Like Loading...
Tags: cybernetics, feedback, social change, Social entrepreneurship, systems, systems science
Observations of a Changemaker 
Recent Comments