The COVID pandemic demonstrated that this sector can move fast, take risks, and build new things when it has to. That capacity did not disappear when the emergency ended. Understanding what conditions activate it, and how to create those conditions deliberately, is one of the most important questions the sector can ask.
What Crisis Makes Possible
In the spring of 2020, CDFIs and economic development organizations did something that would have seemed unlikely a year earlier. They shifted to fully digital underwriting workflows in weeks. They stood up online application systems that previously would have taken months to procure, configure, and deploy. They accepted electronic signatures, loosened documentation requirements, and developed new emergency loan products, in some cases in a matter of days. Staff who had never worked remotely did so overnight.
The sector’s response to COVID was genuinely impressive. It demonstrated something important: the capability to move quickly, adapt processes, and absorb higher levels of risk was never absent. What was absent, in normal times, was the set of conditions that made exercising those capabilities feel necessary and sanctioned.
This piece is about those conditions: what creates them, why they tend to dissolve when the emergency passes, and what it would take to make some version of them available without waiting for a crisis to supply them.
Why Crises Unlock What Normal Times Do Not
To understand the pattern, it helps to look at the structural dynamics that change when a crisis hits.
The first is capital availability. CDFIs and economic development organizations are counter-cyclical by design. They tend to receive more attention, more political support, and more funding during economic downturns, natural disasters, and public health emergencies than they do in stable periods. When CARES Act funding flowed in 2020, organizations that had operated on thin discretionary margins for years suddenly had the resources to move. They were not innovating despite resource constraints; they were innovating in part because the resource constraint had temporarily lifted.
The second is risk tolerance. In normal operating periods, the sector operates with a reasonably high bar for process change. This reflects something real: these organizations manage other people’s money, serve populations with limited financial buffers, and are accountable to funders, regulators, and community stakeholders. That accountability, in normal times, tends to translate into conservatism, a preference for established workflows, proven products, and demonstrated approaches. During a crisis, the calculus shifts. The risk of not changing begins to feel greater than the risk of changing, and that shift in the perceived cost of action gives leaders permission to move in ways they would not have in calmer conditions.
The third is funder expectation. During COVID, funders were not evaluating CDFIs on their operational stability and adherence to established workflows. They were asking whether the capital was reaching people who needed it. That shift in what success looked like changed what organizations were optimizing for, and it cleared space for the kind of rapid experimentation that the sector had been demonstrably capable of all along.
| The sector’s COVID response demonstrated that the capability to move quickly and absorb higher levels of risk was never absent. What was absent was the set of conditions that made exercising those capabilities feel necessary and sanctioned. |
Why the Innovation Tends Not to Stick
The COVID story has a second chapter, and it is worth being honest about it. Many of the innovations adopted during the pandemic emergency have not become permanent features of how organizations operate. Digital workflows that were deployed in weeks reverted to paper-based processes when the pressure eased. Flexible underwriting criteria that worked during the crisis were retired when normal lending resumed. New product types were discontinued. Remote work capabilities that had been built in days were maintained only in part.
This is not a failure of will or imagination on the part of the leaders involved. It reflects a set of structural dynamics that are worth understanding clearly.
When emergency funding cycles end, the resource conditions that enabled rapid change are no longer present. Without the capital buffer, the operational risk of maintaining new workflows, even ones that worked, becomes harder to absorb. Organizations return, rationally, to the approaches they know can be sustained on their normal operating margin.
Funder expectations reset as well. The same funders who asked CDFIs to move fast and take risks during COVID reverted, after the emergency, to evaluating organizations on portfolio quality, leverage ratios, and operational stability. The signal that experimentation was sanctioned was withdrawn, and the organizations receiving that signal responded accordingly.
There is a human dimension to this, too, that deserves acknowledgment. The people who led their organizations through COVID-era innovation did so at significant personal and professional cost. Emergency response is exhausting. By the time the acute phase of the pandemic had passed, many of the staff and leaders most responsible for those rapid adaptations were depleted. The appetite for continued experimentation, in that environment, was understandably low.
The Exception That Shows What’s Possible
Not all crisis-era innovation dissolves when the emergency ends. The most instructive counterexample in the sector’s recent history is Excelsior Growth Fund, now Pursuit,, one of the largest CDFI small business lenders in the Northeast.
When Hurricane Sandy hit the New York metropolitan area in 2012, Excelsior Growth Fund developed an emergency loan program under crisis conditions: loosened credit criteria, expedited underwriting, faster disbursement. The program was designed for the emergency. What made it exceptional was what happened afterward.
Rather than simply retiring the emergency products when the recovery period ended, leadership conducted a rigorous analysis of how the Sandy loans had performed. What they found was that the loans made under the more flexible crisis-era criteria had performed better than expected, not worse. The borrowers who had received capital under loosened standards had, on the whole, repaid it. The credit box that had been widened in response to necessity turned out to reflect a sounder model of creditworthiness than the pre-crisis framework had assumed.
Excelsior Growth Fund did not revert to its pre-Sandy approach. It analyzed the data, drew conclusions, and built a new permanent loan product that incorporated what the emergency had revealed. The crisis did not just produce a temporary response; it produced lasting evidence, and the organization used that evidence to change permanently.
| Excelsior Growth Fund’s analysis found that Sandy emergency loans, made under loosened criteria, performed better than expected. The crisis produced lasting evidence, and the organization used it to change permanently. |
What the Pattern Reveals About Organizational Culture
The Excelsior Growth Fund example suggests that the question of whether crisis-driven innovation sticks is not primarily a question of organizational capacity. It is a question of what the organization does with what it learns during the emergency, and whether the conditions exist to act on those findings when the pressure has passed.
Mission-driven organizations operate with a particular kind of risk logic that is worth understanding without judgment. The work, providing capital to communities that cannot access it elsewhere, creating jobs, stabilizing neighborhoods, is genuinely urgent. That urgency is not manufactured. It means that, in normal times, the moral weight of the current portfolio tends to crowd out the case for experimentation. Why risk disrupting what is working when the stakes for the people being served are this high?
Crisis inverts that logic. It reframes inaction as the risky choice and action as the responsible one. The moral permission to experiment, which in normal times is hard to establish, arrives automatically when the emergency does.
The question is whether organizations can find ways to access some version of that permission without waiting for a disaster to grant it. The answer, based on the evidence, is yes. But it requires deliberate design, not just good intentions.
What Deliberate Change Looks Like
The organizations that have managed to sustain crisis-era innovations share a few common features. They conducted systematic post-crisis reviews, not just operational debriefs, but genuine analyses of how the emergency-era approach performed relative to the prior one. They documented what they learned and brought those findings to their boards. They designed their experiments, even in the midst of crisis, with enough intentionality that performance could be assessed afterward.
What made Excelsior Growth Fund’s example possible was not an unusually talented team or an unusually favorable operating environment. It was the decision to treat the emergency as a source of data rather than just an episode to survive. That decision, to analyze, learn, and adapt, is available to any organization, in any operating environment, including the current one.
For leaders, the practical implication is about granting permission before the crisis arrives. If the conditions that make experimentation possible can be partially established in advance, including a small protected budget, a defined process for evaluating what new approaches produce, and explicit board-level acknowledgment that not all experiments will succeed, then the sector does not have to wait for a disaster to do the work the moment requires.
For funders, the implication is about what gets rewarded. Organizations that conduct rigorous post-implementation analysis and adapt their practices in response to what they learn are demonstrating exactly the kind of organizational quality that deserves to be supported and recognized. Evaluation frameworks that make this visible, asking not just what an organization delivered but what it learned and how it applied that learning, would create a structural incentive for the sector to build this capacity systematically.
For peer networks, it is about normalization. When an organization makes a significant operational change in response to evidence, when it publicly documents what it tried, what it found, and what it changed as a result, it creates permission for other organizations to do the same. The sector has strong peer learning infrastructure. It is underutilized for exactly this purpose.
The Urgency That Doesn’t Require a Disaster
This series has argued that the community development sector has a genuine technology gap, that the resource constraints that historically made closing that gap difficult have changed significantly, and that the sector’s own crisis-response track record demonstrates the organizational capability to move when the conditions are right.
What it has not argued is that any of this is easy, or that the structural barriers are imaginary. They are not. But the gap between where the sector is and where it could be is not primarily a question of capability; it is a question of conditions. And conditions, unlike capabilities, can be deliberately shaped.
The communities that CDFIs and economic development organizations exist to serve are not in a position to wait for the next crisis to generate the next wave of innovation. The tools are available. The cost of building has dropped. The evidence from the sector’s own history shows what becomes possible when the conditions are right. The work ahead is creating those conditions deliberately, at scale, and without a disaster as the catalyst.
