Money, Innovation & Social Good

In Lean Impact: How to Innovate for Radically Greater Social Good, Ann Mei Chang suggests suffering, injustice, and unmet needs occur as a result of market and government failures. (p. 65)? However, each of those conditions is natural and all were far worse before the industrial revolution enabled hyperbolic growth and thus capitalism, markets, and governance at scale.??

Moreover, with respect to perceived needs, even the “poor” now have access to products and services unavailable to royalty in the not-so-distant past.? What's more, the technology adoption cycle is accelerating .? The progress that has occurred on a worldwide scale in recent decades is an astounding anomaly in human existence.? Short of the risk that alarmists, demagogues, and dictators may gain the upper hand and impose counterproductive constraints, it seems likely to continue , albeit perhaps at a somewhat less breakneck pace.

Clearly, both “needs” and “failure” are relative, time-dependent terms.? On the other hand, improvement in human endeavors is always possible and that is exactly what Chang’s treatise is about, not merely incrementally but exponentially.? What she says is required is “nothing short of a revolution in how social good is funded.” (p. 209)

To her credit, she welcomes constructive criticism and expresses frustration that those who have viewed her as an expert have been shy about telling her when she was wrong, thus denying her the opportunity to improve her ideas. (p. 231)? With that thought in mind, let’s consider one of her initial assertions: “Certainly, we need to continue to advocate for more funding.” (p. 20)

The first question to be asked in that regard is, As a matter of principle as well as practicality, how much money should be spent on nonmarket transactions, i.e., those that are not based on values freely exchanged?? A second, closely related set of questions concerns the opportunity costs and unintended consequences of such expenditures. Others include, how much economic activity is already being commanded and controlled in nonmarket, emotionally and politically motivated transactions?? And how much of such “largess” can an economy bear before losing its capability to sustain itself and grow?

At 30 percent of GDP, the U.S. ranks second only to France in total social spending. Since our per capita GDP is half again (150%) greater, we may actually be spending considerably more than they are. Meanwhile, the French only work about 80 percent as many hours as we do and Americans are chided for working too much.

As Chang herself points out:

• Without the important signal that a purchase decision sends to confirm perceived value we can be lulled into believing something is wanted when it is not. (p. 106)
• Distributing goods for free implies deciding who receives them -- putting people in the position of being supplicants and potentially creating divisive dynamics … (p. 40)
• Without a deeper understanding, making a positive impact is a crapshoot, and interventions may even lead to negative, unintended consequences. (p 50)
• Of course, the most simple and straightforward engine for growth is a traditional market-driven business model. (p. 139)

Thus, as we endeavor to impose our will upon each other in the name of social well-being, she cautions that both curiosity and humility are essential. (p. 83)? Moreover, she asserts we should “proceed with a healthy dose of skepticism, adopt a learning mindset, and find ways to reduce risk each step of the way.”? Fortunately, “there is a time-proven process to do so -- the scientific method.” (p. 84)

Consistent with science and contrary to the very core of politics, Chang suggests hypotheses about social welfare efforts “should be objectively measurable so that success or failure is not a matter of debate .” (p. 68)? “The process of validated learning looks at hard data on what works to confirm a hypothesis. It cuts through the emotion and politics that can often drive decision-making and instead focuses on empirically demonstrated evidence.” (p. 72)

Actually, however, science is not about confirming hypotheses, at least not in the sense of proving them to be true.? Rather it is about compiling sufficient evidence to upgrade hypotheses to theories and theories to “laws ” in the scientific meaning of the latter word.? It’s a journey of continuous approximation and improvement, not a fixed destination to be reached and then frozen in place by incumbent, monopolistic powers-that-be who have managed to gain the upper hand.

Wouldn’t it be nice if the practice of politics and “governance” -- enacting laws compelling behavior under the threat of violence -- relied less on hubris, rhetoric, and populism in favor of evidence and results instead?

Even in 1861, when the scope of government was far smaller,?John Stuart Mill characterized voting as "power over others ."

In 1919 Max Weber described the monopoly on violence ?as the defining concept of the state .

Sadly, rather than innovating for ongoing improvement, Chang observes, “We are relying on nineteenth-century institutions using twentieth-century tools to address twenty-first-century problems.” (p. 180)? Yet, on a more hopeful note, “There is growing recognition of the need for new tools in the face of the accelerating change and uncertainty in our world today.” (p. 82)? Toward that end, she argues, “The structure and availability of funding is by far the greatest barrier to social innovation.” (p. 191)

One advantage in the social sector is the opportunity to share assets freely while working toward common goals. (p. 144)? Nevertheless, “Even when services could be delivered at less cost or greater scale, mergers of nonprofits are rare … Too often, teams reinvent the wheel to make their own mark, when successful solutions exist that could be replicated.” Indeed, “Fierce competition for grants can lead to hoarding insights as a competitive advantage, rather than collaborating towards a shared purpose.” (p. 59)

Chang notes that funders, nonprofits, and social enterprises could achieve their goals more readily by investing in shared infrastructure and collaborating across initiatives. (p. 151)? Countervailing against that potential, “Finding a meaningful intersection as a basis for partnership can prove challenging [but] bringing together nonprofits, entrepreneurs, and funders with related objectives to co-invest in a shared asset can reduce costs and gain leverage for all.” (p. 152)

However, finding bases for partnerships should not be particularly difficult.? The degree to which opportunities for collaboration may not be recognized by potential performance partners is prima facie evidence of artificial ignorance , i.e., willful blindness.? Such opportunities abound.? For example, each funder typically applies unique requirements for content, format, and frequency of reports. (p. 201) Not only does that impose needless burdens on nonprofits but it also makes it more difficult to engage in partnerships.

Collaboration should be centered on common and complementary objectives in support of similar, if not the very same intended community-based beneficiaries.? The infrastructure required to make such objectives readily discoverable consists of business-quality networking services leveraging an open, machine-readable data standard like Strategy Markup Language (StratML, ISO 17469-1 ).

Toward that end, a key aspect of Chang’s proposed approach is to build minimally viable products (MVPs) and run experiments to test the riskiest assumptions as rapidly and inexpensively as possible (p. 62).? Prior to deployment of an MVP, however, the key hypotheses should be documented, along with data to be collected and, most importantly, the metrics by which progress and success will be evaluated. (p. 72)

For example, one hypothesis might be that nonprofits would be happy to collaborate to more efficiently and effectively achieve their desired impacts if it were easier to do so, but perhaps that assumption may not be true.? As Chang suggests, they may vainly prefer to creatively reinvent the wheel even at significant cost in terms of diminished results for their intended beneficiaries.

With respect to measures of progress, she highlights the distinction between vanity metrics versus actionable or innovation metrics. (p. 73) Vanity metrics are inward (self) focused whereas outcome metrics address value, growth, or impact delivered to beneficiaries.? Usage of vanity metrics call into question the true motivations of the leaders of nonprofit organizations.? In politics, however, the answer to that question is clear: The only metric that matters is reelection -- the ultimate vanity metric, glorifying the politicians themselves. The efficiency and effectiveness of government programs are marginally connected to election results, if at all.

Indeed, in the case of government programs, when services could be delivered at less cost, the common response is to spend more.? Chang notes the U.S. government has made more than $4 trillion in financial commitments that are contingent on failure.? Rather than continuing to do that, she asks, “Shouldn’t we balance those with more investments that are contingent upon success?” (p. 219)

With respect to investments in innovation, Chang says she has tended to avoid leaping to technology-based solutions for global development challenges.? However, she has found technology to be a “consistent game changer” for the collection of data collection to drive feedback loops. (p. 98)

Even better than designing with feedback from users, she suggests, is empowering users to design solutions for themselves in their own communities.? However, that is rare in the social sector, particularly in disadvantaged communities who lack the necessary resources, education, and confidence. (p. 110)? To begin to address that issue, the first step is to ask communities what they want. (p. 201)

To overcome the resources problem, Chang notes, “the path to scale typically requires a shift from depending on donors to tapping into larger and more sustainable financing streams.” (p. 134)? Typically, she says, that involves accessing regular and ongoing local, state, and federal government funding, as well as influencing policies of the welfare, educational, and judicial systems. (p. 136)? Indeed, “tapping into existing government funding streams can often be the most promising path to reach massive scale.” (p. 146)? Moreover, “Sometimes scale can be achieved through government adoption rather than government funding.” (p. 147)

Conversely speaking, however, scale might also be achieved by routing “government” funding -- or, more accurately speaking, taxpayer funding -- through innovative nonprofits rather than inflexible, politically driven bureaucratic monopolies.? One way to do so would be to convert tax deductions for charitable contributions into tax credits instead, thus requiring government agencies to compete with community-based nonprofits for the right to spend the taxpayers’ money for social welfare purposes.

Among the options that has been proposed is simply to give money directly to those who need it.? As Chang notes, one organization testing that approach is GiveDirectly, which applies cash transfers as a tool for reducing poverty and challenges proponents of other types of interventions to prove they work better.? In short, if complex programs don’t deliver more benefit than cash, why should they be funded? (p. 157)? That question seems particularly pertinent to politically driven, government-mandated programs.

To answer such questions, an important first step is to quantify the impact of those programs.? However, to be meaningful, the answer must address not merely the direct costs but also the opportunity costs associated with not using the money more effectively in other ways. (p. 158)? For example, rather than simply distributing “free” money, how about routing wage supplements through community-based employment and social services organizations?

Fortunately, Charity Navigator and Guidestar by Candid are angling to enable tax-exempt charities to publish their performance metrics.? Hopefully, as those efforts mature, it will become possible to benchmark and compare results, thereby enabling donors to target their contributions more effectively.? On the other hand, although U.S. federal agencies have been under a legal mandate since 2011 to publish their performance reports in machine-readable format, none of them has complied with that direction, much less made quantifiable impact metrics readily accessible and comprehensible by taxpayers and other citizens.

Chang observes, “At some point, even the best solutions can run into a wall of existing policy and market failures … in some cases we’ll need to change the system itself.” (p. 181)? That is especially true of “solutions” whose quality is unknown at best or, worse, already recognized to be relatively poor ways to achieve the intended results.

Toward that end, she cites the Skoll Foundation as an organization whose “focus has expanded beyond the enterprise to embrace the so-called systems entrepreneurs who are taking on the challenge of shifting social systems, building coalitions, and influencing policy.” (p. 182)? In some cases, she suggests problems might be permanently resolved by the nonprofit sector but usually policy and market failures must be addressed in the public and private sectors. (p. 188)

Chang argues the required change will need to come from the funders themselves, with funding practices transformed to provide flexibility, incentivize results, and embrace reasonable degrees of risk. (p. 192)? But does that sound like anything politicians and bureaucrats may be capable of doing, much less allowed to do?? Isn’t it more likely that voters and disruptive social entrepreneurs will need to take it upon themselves to drive such change?

In Evasive Entrepreneurs & the Future of Governance, Adam Thierer suggests incumbent authorities and institutions are often incapable of thwarting technologically driven progress, even in the misappropriated name of humanism. (pp. 190-193) Moreover, he argues technological change “may become the most important check on government power.” (p. 15) At least, he asserts policymakers will be forced to adjust traditional policies rapidly or risk irrelevancy. (p. 77)

Ideally, Chang argues, social sector funding would be “entirely unrestricted with accountability coming through performance targets or tiered follow-on funding.” (p. 204)? While it would be nice to think government bureaucracy might be amenable to such arrangements, even if that were the best alternative, it may be unacceptable to voters and thus politically infeasible.

On the other hand, Chang notes for-profit social enterprises are increasingly using grant funding to validate and de-risk business models in order to tap into private investment sources. (p. 207)? Additionally, although data may be lacking to enable evaluation of their cost-effectiveness, public/private partnerships are fairly common.? Moreover, as Chang points out, private sector startups are not subject to micromanagement.? While they may be supported by mentors, they are free to succeed or fail on their own and thus are highly motivated because their survival is at stake. (p. 214)? That is clearly not the case for government programs nor for public employees.

In Change: How to Make Big Things Happen, Damon Centola notes that centralized networks, like the federal government, tend to reinforce bad habits of thought.? Not only can they “prevent us from finding new ways of solving hard problems” but they “can even keep us from seeing clearly the information that is right in front of us.” (p. 294)? By contrast, egalitarian networks support new ideas and opinions.? Thus, he concludes, “strategies for change should be focused on incorporating voices from the periphery...” (p. 301)

As one voice for change, Chang considers paying for outcomes to be the holy grail because it aligns the interests of grant makers, recipients, and beneficiaries.? The incentives focus on maximizing impact, thus creating an open, competitive market for social good. (p. 217)? She hopes innovations in pay for outcomes will help simplify organizational structures and gain broader application. (p. 223)? She concludes, “when donors can combine their efforts towards shared goals, the results can be far greater than the sum of the parts.” (p. 225)??

Speaking of sums so large as to be virtually unimaginable, let’s conclude by revisiting Chang’s advocacy for more funding for social welfare purposes.

Existing spending for such purposes in the U.S. is around $5 trillion annually. If it were a national economy, it would comprise the third or fourth largest GDP in the world. Moreover, the United States already taxes as much as the average developed country. If recent tax proposals were enacted, we would have the highest rates of all .

Does anyone seriously believe the best way to achieve breakthrough results is to saddle our economy with such a heavy tax burden, thereby handicapping our nongovernmental, commercial and nonprofit sectors by reducing the amount of money freely flowing in decentralized, market-based exchanges???While other nations may be willing to agree to a minimum corporate tax, it seems doubtful many would be foolish enough to put their own businesses at such a competitive disadvantage. ?On the other hand, they’d love to see ours become less capable, market-leading competitors.

Rather than shooting ourselves in the foot, might it be time to try something less blindly constrained by the dynamics of good, old-fashioned politics as usual (#gofpau )?? Something far more innovative, cost-effective, and impactful?? Something truly revolutionary??

How about a highly dynamic, open market for good supported by tax-creditable contributions?