Why traditional philanthropy & grants hamper innovation

When Anne Mei Chang moved from working as a senior executive at Google to the social innovation world, she quickly discovered that “Social innovation, the development of better solutions to social and environmental challenges, is much harder than tech innovation.”

This post summarizes from her book Lean Impact: How to Innovate for Radically Greater Social Good the reasons why mainstream grant and donor funding from philanthropic sources for social impact projects leads to (at best) incremental change. And why this traditional funding model actually hampers the ability to develop solutions suitable for large scale impact.

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How traditional grant-based / philanthropic funding works

Why is social innovation hard?

Ann Mei identifies at least five different reasons:

1. “Funding constraints can severely limit experimentation

2. Needs of beneficiaries and priorities of donors don’t always align

3. Short term wins are rewarded over long term growth

4. Measuring social outcomes is much harder than counting clicks

5. Taking risks has far greater implications when it involves real lives.”

How does the traditional grant-based funding model work?

A funding organization outlines the amount of funding they will give to solve a particular problem and the associated criteria of how that money can be used.
Organizations apply for funding and develop plans based around the amount of funding offered.
The proposed plans suggest a safe incremental advancement based on past results. Anything too radical is avoided.
A detailed masterwork plan is created, typically in offices overseas from where the grant will be carried out. It outlines exactly the work to be carried out throughout the grant.
If an organization is successful in being awarded a grant, their job is to execute it. Not modify it, or seek better ways to do the same work.
The grant typically ends with the organization reporting their findings to the donor.
If the grant was "successful" (aka. it was executed as set out), it might apply for a second grant, and extension, or the project may end.

This approach can be summarized as "rigid" and "one-off". It doesn't guarantee that the work being done is the best work possible.

“Just as companies have to maximize shareholder value, mission-driven organizations have an obligation to maximize their social benefit to society.”

How Venture Capital Fundings Works

Compare this to how typical funding in Silicon Valley works

[This section is more from my perception of venture capital than from Ann Mei's commentary in the book]

Traditional startups are encouraged to think about a problem ambitiously and develop a solution that will deliver the greatest value at scale.
By default, the startup knows that what they try first, will likely not be the optimal solution. They know they will have to modify their initial idea.
The purpose of the startup is, therefore, to run a series of mini hypothesis-driven experiments to find: ‘product-market fit”.
The magic solution is found when the startup identifies something of value and a way to achieve exponential growth in its delivery.
Startups early on will typically seek “seed funding” from angel investors. Angel investors invest in ideas that have enormous potential and are unclear if they work or not. They know that most of the projects they invest in will fail.
As startups demonstrate valuable learning about their ability to achieve product-market fit, they progressively raise subsequent rounds of funding. Each round enables them to continue their process of value and growth hypothesis discovery.

Why does venture capital tolerate funding so many failed startups?

Shouldn’t they pick the ones they know will succeed?

All the best startups are run by brilliant and passionate founders. Each startup believes they are sitting on the next big idea. Each idea seems fantastic, if true. If angel investors knew which startups to fund, they would only pick ones that they know would become the elusive unicorn (the billion-dollar company).

But the problem is, they don't know which will work out. The best startups all seem to have potential. Therefore, the best approach is to invest in ten (or twenty) startups, hoping that one will have massive success (aka become that unicorn). This one unicorn will then cover the costs of investing in all the failed startups.

Why don’t funders fund startups solely based upon the idea?

Funders know that the first idea often doesn't become the final product. Investors, therefore, make funding decisions based on both the team and the idea. They need to be confident that the founding team will recognize when the original idea isn’t working as well as possible, and pivot to something better before the money runs out.

How traditional philanthropic / grant funding models create problems

Why does traditional social impact funding hamper innovation?

Ann Mei identifies two issues that hamper the process: the grant-making and donor process.

The first is a fixation on a “guaranteed outcome” and the second is heavy reliance upon waterfall methodology and the inflexibility of grants.

Funding a guaranteed outcome

Traditional funding of social impact causes asks organizations to use a fixed amount of resources to address a particular need.

The solution proposed by the grant applicants must be conservative by nature. This leads to short term thinking, rather than encouraging scalable long term thinking. It also rewards linear short term steps, when what is needed is large exponential steps.

As we saw earlier in the example, venture capital invests not in safe small businesses. That is not their role. Instead, they fund unproven ideas, with the potential for enormous success.

The current 'guaranteed outcome' needed by traditional donors and grants, means at best, progress and growth will be "slow, plodding, and linear." This is why Ann Mei believes social impact organizations don't create solutions that address a sizable percentage of the people effected by an issue.

The problems of waterfall development

Waterfall development is a traditional work cycle with very clear subsequent steps that are executed upon completion of the prior steps. A typical grant may be over several years, and each step must be outlined.

The problem with this, according to Ann Mei, is that it hampers the dynamic hypothesis-driven testing of assumptions that is required to determine what delivers the highest value and impact.

Rigid grant outlines, developed upon many assumptions, are not flexible enough to uncover the truth of what really works best. In general, these questions of value, impact, and growth, remain unproven assumptions.

Toxic relationship

Ann Mei, former Chief Innovation Officer at USAID, also comments that the traditional donor-recipient model has the potential to create a toxic relationship. The grant recipient must always present to their funder why what is being funded is "working really well." This can lead to glossing over of problems with the grant as it is being delivered.

Instead, Ann Mei suggests, if the new model is one of shared learning - where both the donor and the grant recipient together want to discover "what really works" they will be transparent with each other in showing how different hypotheses have been tested, and their relative success.

Ann Mei sees the relationship between donors and organizations shifting, away “from micromanagement and suspicion towards trust and reward.” One where donors “establish clear goals, let go of some control, and select teams and organizations to empower as true partners”. Non-profits and social entrepreneurs, in turn, will need to, “accept more risk, become responsible for results, and develop skills and results accelerate learning rather than execute a plan”.

Overhead

The amount of money an organization spends on 'overhead' is focused on by donor organizations. Instead, Ann Mei believes that donors should focus on the measurable impact that an organization has.

Overhead is sometimes required to drive innovation and R&D. High overhead, or low overhead, does not mean a social impact organization is bad or good. Instead, the organization should be judged based on its impact metrics. An organization with low overhead, but low impact is not an effective organization.

To conclude

Ann Mei proposes that the traditional rigid grant process makes it nearly impossible to innovate in social impact.

The process ties the hands of social entrepreneurs behind their back in being able to find truly innovative solutions.

She advocates instead for:

Tiered funding that invests in ideas with ambitious potential, and unproven success, and ramps up further funding that is directed towards the best solutions.
Funds that are freely allocated for an organization to dynamically use as they see fit. The focus should be on the impact and outcome, not how much of the funds were used for different parts of the operation.
Transparency enables the organization to test and fail, and share these findings with their funding organization; and share areas they see of as high risk in advance.
Blended funding models, where philanthropic dollars are used to fund risky innovation and help unlock private capital and government funding to accelerate implementation at scale.
Payment for outcomes / and outcome-based incentives: to help drive continuous innovation.
Donor collaboration mechanisms (eg. centralized funding pools) for high impact areas.

The focus of funding most encourage the continuous exploration of those ideas with the highest value, growth strategy, and impact. An organization cannot believe that their existing approach is optimal. It must continuously demonstrate that it is trying to do better and have a greater impact with every dollar. Just as a for-profit business must continuously innovate and improve.

This is a shift in thinking for donors. A shift from 'project-based funding' towards 'solution based funding.

Articles in this series:

Other articles you may like:

I highly recommend reading the full book Lean Impact: How to Innovate for Radically Greater Social Good, by Ann Mei Chang yourself.

Please note. The quotations used in this blogpost are jotted down while listening to the audio version of the book. They may be slightly inaccurate or accidentally missing. Please contact me with any revisions to the accuracy of these quotes and the original text.

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