Browsing category: Social Services

It’s not that I’m not a believer, it’s just that it’s hard.

I work for a social service organization (posAbilities) that has partnered with two other organizations (Kinsight and BACI), to invest in social research and development. We call ourselves “Degrees of Change” (DoC) and hope to publish something of a declaration or manifesto this summer around the sorts of pivots we think are needed in the social services sector. We’re going to try to open up a window on our efforts and what we think we’re learning—stay tuned!

We also have a sister organization in Ontario (West Neighbourhood House) who has been at this for as long as we have (about 4 years). And there are other organizations coming online with Grounded Space who are making similar investments in social R&D. InWithForward has been providing guidance for this work, and it has resulted in learning and results unlike anything we’ve ever seen before. We’re grateful for that. But it’s hard. Really hard. Here are just some of the pain points.

1. Resources.

We’re not funded for social R&D and we’re not private corporations; we’re charities. We don’t have drawers of cash, and even if we did, there would be an expectation that those monies would get spent on concrete service needs and priorities rather than on an R&D process that has no explicit outputs or outcomes. There is extraordinary pressure to address exigent needs rather than investing in processes that might shape the future.

As you know, there is no government infrastructure for social research and development, so we have to cobble funding together however we can—grants, loans, lean administration budgets, etc. And because sustained funding isn’t a given, it adds stress because it means that everything we build feels fragile and vulnerable. It’s like we’re building sand castles as the tide comes in.

And it’s so hard on our leadership teams. They were stretched long before social R&D happened. Their other responsibilities meant workweeks that regularly exceeded 40 hours. It’s no easy task to run programs or organizations, never mind retooling and repurposing them. Getting involved in social R&D adds 10 – 20 hours a week to schedules. It’s not sustainable, but what do you do when there is a vision and an imperative, but no funding? You do what you can.

2. Pace.

There are a lot of roles, processes, and structures that comprise an organization. Especially if it has been around for a while. It needs time to make things work—re-allocating resources, recruiting internal teams and freeing up some of their time, aligning incredibly busy schedules, sorting out internal and external messaging, coordinating logistics, etc. And of course, none of these pieces are static when we are iterating the R&D model itself. There is a steep learning curve for organizations and it takes time to do R&D properly.

Organizations require at least 5-year time bites for undertaking social R&D, not 1 – 3 years. Short-term funding puts pressure on organizations to go through an intensive R&D process that chafes against multiple organizational and regulatory systems and functions. It burns people out and builds resentment. There is an urgency to produce something worthwhile before the money runs out, something that would justify the need for social R&D and associated expenditures. But it means 5 years of work gets compressed into 2 years or less.
To compound this, the learning/iteration cycle that we do manage to eke out is too long. A single cycle of research, analysis, playback, idea generation and prototyping can take several months to over a year. That’s too way long. The cycles should be shorter and there should be more of them. But so far, it’s been hard to make that happen. The problem doesn’t lie with the method itself, but with the need to conduct it at a pace that is both effective and that is manageable by organizations. We haven’t found how to do that yet.

3. Communication.

Leadership and managers are accustomed to knowing what is going on in their agencies, what sort of decisions are being made, and the rationale behind them. Rapid-fire iteration means completely new directions or 180’s can occur in a relatively short period of time (hours or days). That is hard to take in high-risk, high-accountability systems. Leadership/managers feel constantly behind and may feel slighted or upset that they haven’t been part of important decisions or iterations. Or wondering why some people were somehow involved, or knew, but not others. They worry that perhaps they haven’t given their best, or been sufficiently available. If only they could keep up. They want to contribute and open doors, but they can’t flip the pages fast enough.

Change is hard to take, especially when it is happening in one’s backyard and one doesn’t feel in control of it. “When did that happen?” “Who decided that?” “I thought we agreed/were told we were going to do ‘x’—why are we talking about ‘y’?” This is only exacerbated when research, playbacks, decisions or iterations produce a “problem” for the organization that make more work for leadership/managers and which may require them to go into damage control mode.

Such problems are bound to occur when local and quick decisions are part of the process, versus consensus or authorization, and when the method itself is about surfacing gaps in one’s agencies, questioning conventional values, roles or practices, and when it is not a system-managed process. This sort of thing triggers an impulse to better manage R&D processes so that these problems don’t occur, so that there are clearer processes in place that will prevent their recurrence. Which, of course, is a hazardous approach. Once R&D processes become the legitimate subject of systemization, it is hard to know when to stop; there is so much clarifying, structuring, and cleaning up that could be done. But then, not being on the same page with everyone else, not knowing what changes are happening, not knowing who knows what or has been part of what decision, is hard.

It is hard enough to explain what we are about to our internal and external stakeholders—how much more so when everything keeps changing? Things like our learning, hunches, roles, models, prototypes, narratives, etc.

4. Culture clash.

The cultures of social service organizations are about predictability, consistency, quality and control. The culture of social R&D is about interrogation, emergence, creativity and experiment. Social services are complicated and interconnected systems that require skilled managers, navigators and adjustors. Social R&D requires fearless questioners and makers. Social services try to avoid problems, eschewing mistakes that add more work/trouble to an already stressful environment; social R&D encourages and requires lots and lots of failure. Social services is about nurturing and supporting one another and celebrating what is done well; social R&D is about naming gaps and pain points and mobilizing against the status quo.

The very concept of “innovation” has a structural prejudice against what exists—that it is somehow insufficient, inadequate, and needs to be improved upon and/or surpassed. There is an inherent tension between what is on offer and what is being envisioned—how this unfortunate tension is handled is critical because, done poorly, it can alienate employees and teams who are doing excellent work.

At some point, leadership will face a threshold around their personal and professional comfort levels. How much interrogation can they tolerate? How much unpredictability? How much emergence? How much change and upset? What is required to run an organization is quite different than what is required to disrupt it.

All to say, it ain’t easy. Even though everyone knows it’s important.

This is the last, I think, in a series that critiques our preoccupation with scale, especially within the social sector. It’s not that scaling is a bad thing, it’s just not nearly as simple as its being portrayed. In this piece, we argue that because the social sector is deeply relational, the conditions under which solutions emerge are as much part of the intervention as the solution itself, and that this is what gives it legitimacy.

Further, in those rare instances where charities and non-profits do engage in rigorous social R&D[1] the result may not itself be scalable because the specific contexts of the work are unique. More importantly, there are qualitatively distinct characteristics of human-centered design and co-creation that resist scaling, especially when compared to traditional top-down pilot programs that are wholly baked within the system and don’t involve users until it comes time for program enrolment.

Some of these characteristics are as follows:

1. Relational legitimacy.

Contextual research, especially deep immersive methods such as ethnography or cultural anthropology, are deeply curious epistemic dispositions that build rapport and credibility between local representatives of “the system” and user groups. The representatives are not problem-solving, counselling, or imposing a professional narrative; they are paying attention. When people spend time with users groups in their everydayness, across programs, contexts and time, the stiff conventional roles are discarded and authentic connection and relationships emerge. These relationships, rooted in vulnerability, goodwill and trust, are the cornerstone to whatever solution emerges.

2. Method as Intervention

human-centered design and co-creation are exceptional examples of promoting self-determination because they invite user groups to articulate the problems and to shape the solutions. This invitation, this empowering of an often oppressed and disempowered population group, is itself a powerful intervention. It is part of the final product and yet cannot be scaled when the solution is exported to other jurisdictions.

3. Ownership

These methods create a sense of local ownership because stakeholders have participated in the solution from the very beginning. It is a community solution, one wherein professionals may have played a role but they are not the sole owners. The moment the system undertakes to scale a solution that has been birthed under such conditions, it presumes the conceit of ownership and users in new jurisdictions are again relegated to the role of helpees who can enroll if they qualify. Unless there is some sort of adaptation methodology that allows for a transfer of ownership, the solution will belong to the system, not a community of stakeholders.

When a solution is grown in a local context and then scaled to a different one, there is a presumption that the solution is discretely bound such that it can be extracted and replicated without any loss of fidelity. This is rarely the case in social services.

For starters, the new context is probably anything but receptive; it could even be toxic to the solution. Organizations, their employees and user groups will likely experience any new program or service, even ones that are not particularly innovative, as an imposition from without—as yet another example of those with institutional power blundering into regional complexities. The prevalence of wariness and mistrust between most governments and service organizations, and between organizations and user groups, can salt the soil against any program replication–especially if it signals a future trend preferred by decision-makers, or if it is associated with having to give something up/closing other programs.

More importantly, the originating conditions involved methods, competencies and relationships that are essential to solutions taking root. Unless the new jurisdiction has these characteristics, it is unreasonable to think that any scaled solutions can be adopted, adapted and continuously iterated. Instead, as suggested in a previous post, the solution will be “frozen” in some form that resists adaptation to local conditions or ongoing development, and which, when imposed, will exacerbate misgivings regarding both the government agenda as well as the new program’s applicability.

From scaling to co-creating

The social sector is heavily relational. Irrespective of the expert knowledge, competencies and credentials that are brought to bear, such things are virtually always mediated by relationships. Too often, these relationships are saddled by dynamics that are not particularly constructive—where power accrues to the professional, deficit lenses prevail, and the relational binaries are restricted to helpers:helpees (there is no reciprocal exchange of something of value).

Co-creation—that is, involving user groups in both the problem and outcomes definitions, as well as solution development and implementation—disrupts a static and non-generative relationship and makes space for meaningful dialogue, learning, creativity and development. But it requires lots of work to build trust and credibility, adjust to the implications and limits of power-sharing, and to define and build new relationships. In those rare instances where co-creation does occur, we cannot assume that what emerges can be disentangled from its origin, from the relationships and processes that gave it birth, and embedded in new sociopolitical and relational contexts.

[1] posAbilities, BACI, Kinsight, West Neighbourhood House, InWithForward

Social innovation discourse has a persistent intoxication with big, scalable ideas. But in our mind, social innovation has patterned itself after idealized private sector models without critical discernment about what might be applicable and what might not. One cannot simply supplant “financial return on investment” with “social return for investment” and then run a social proposition through the same private sector mechanisms. The ecosystem is different. The ends are different. The market is different. While the private sector provides reference points with which to think about social innovation strategies, they ought not to be applied wholesale.

For starters, the validation of goods and services in the free market lies in the demand for them. The more a service is purchased, and the more purchases are sustained over time, the more that service is validated. In the social economy, because the government is the customer and not the end user, there are different market implications and effects:

1. The needs of service recipients do not completely align with those of governments and service providers, and yet those receiving services are excluded from the transaction. This bizarre omission in the demand and supply chain presents a material aberration from what occurs in the free market economy. The intended customer—those accessing services—are disempowered rather than empowered, and the experience is often one of humiliation as there is no reciprocal exchange of something of value.

2. It becomes trivial to say that services are validated because there is a paying customer (government). A social return on investment is different than a financial one and consists of different validation criteria. What are the outcomes? What is the impact? And yet, program evaluation is notoriously inadequate. The things that usually get counted are things that don’t really get at effectiveness or impact at all—things like satisfaction surveys, number of hours of service, number of consumer touch points with a service, etc. Outputs and efficiencies tend to be the measurements of social service systems, while a better life is the hope of users. It is no wonder that existing solutions don’t respond to user needs and yet still persist.

3. The urgency of the problem is confused with a demand for existing services. It is a confusion that occurs frequently in the minds of service providers and funders. The desperate need for solutions, even when paired with capital flow, is not a validation of the solutions already in place.

4. Demand is artificial because end users are driven to only a handful of solutions (versus nothing at all). The volume of people in services produces a false sense of service validation—something that is only exacerbated and exaggerated when there are waitlists.

5.  An extensive and uninterrupted flow of capital into the social sector diminishes the imperative to innovate—especially when an ecosystem is developed and consolidated around this capital flow (policy, procurement, delivery, accountability, messaging, etc.).What is the urgency to innovate when the taps are always on? During periods of budgetary contractions, agencies tend to apply political pressure to get funds to preserve the status quo, rather than re-imagining solutions. Concerns over system sustainability begin with the assumption that the system is working; it just lacks sufficient funding. Rarely, if ever, is the generative question asked: “ought the current system be sustained?”

The absence of a social R&D function means that the imperative to innovate is unlikely to come from within. Irrespective of where that imperative comes from, there is little or no in-house competency to deliver it. These are key reasons why there are so many static programs and services within the social sector.

These conditions in the social economy can make the scaling of solutions particularly hazardous. This is because they are more likely to be adapted to the needs of existing institutions and their interconnected systems, which will all have a role in shaping them, rather than to end-users. They are more likely to be appropriated and adapted to the very system(s) they are supposedly disrupting.

Further, when a solution is scaled-out, it needs to be codified for the purposes of replication—purposes, policies, procedures, employee roles and training, and so on. This codification only hastens it along the conservation continuum and, without any capacity or competency within the host organization to meaningfully iterate, evaluate or embed innovative solutions, it will quickly come to resemble the sorts of familiar offerings we see in our social institutions—offerings that are rigid, unresponsive and requiring reform. Scaled solutions in the social services are at risk of ossifying quickly, which means they will more quickly become part of the problem rather than being part of the solution.

The secondary operating system

Unless an organization is prepared to firewall the new solution, and develop a secondary operating culture and system (organizational policies, processes and roles) —one that is designed to specifically support and iterate the new solution—then it is likely to be ground down within the machine of the system until it resembles every other sort of program or service. Creating that secondary operating system is a Herculean task because not only do organizations have an imperative to achieve consistency and continuity, but they exist within a giant ecosystem where funders, regulators, licensors, labour agreements and accreditors are invested in achieving some form of collective stasis or equilibrium, to become collectively coordinated and coherent. Attempts to shake up the status quo bump up against countless systems and sub-systems such that, after decades of consolidation, there is very little room left to support genuine creativity or novelty. It is in this context that we are contemplating scale. It should be no surprise that those who try to be creative within complicated systems typically must do so “under the radar,” because it requires non-compliance with one or more sets of rules.

In sum, the conditions that legitimate scale in the free market economy may not be in force in the social economy, and the conditions in which scale is achieved in the social economy may actually neutralize the effectiveness of the solution.

The social innovation community is entranced by scale. Foundations, incubators, accelerators, governments, social investors and thought leaders are consistently driving expectations that new solutions should be designed and supported to achieve scale. But, what scale are we talking about?

Currently, there are three types of scaling movements that tend to dominate the literature: scaling-up, scaling-out, and scaling-deep. Proposed solutions that promise one or more types, are more likely to be preferred by funders than those that don’t.

 

 

Source: Darcy Riddell and Michele-Lee Moore (2015)

1) Scaling-up consists of shifting the laws and policies of systems in order to either remove oppressive precepts, or to introduce game-changing rules that will bring social benefit to large numbers of people.

2) Scaling-out is about growing or replicating a solution to other geographic areas, including lateral scaling to new target populations.

3) Scaling-deep involves activations intended to promote transformation at the sociocultural level of individuals, organizations or communities.

Scaling-up and out are often confused and the terms used interchangeably, probably because they are fundamentally about spreading or growing solutions in order to bring social benefit to as many people as possible; they are about numbers.

Whereas these forms of scale dominate the social innovation literature, little is comparatively said about scaling-deep. Scaling-deep recognizes that there is power in transforming culture. It acknowledges that interventions at the level of meaning and culture can prove powerful axes for levering change. Sadly, there are relatively few solutions that are attempted in this space and even fewer of which are understood by funders or investors.

We argue that:

These three conceptual models of scale are not exhaustive and that there are additional ways to think about scale: scree-scaling and the scaling of conditions (versus solutions).

The normative privileging of solutions that can scale out or up is short-sighted and can actually impede impact.

We propose that if we are to use the language of scale—and we think it is a legitimate way to think about social impact—we add two other critical form of scale, Scree-scaling, and Scaling initial conditions.

4) Scree-scaling

This conception of scale is less about growing and spreading single solutions and more about legitimizing and cultivating many “small” ones. It represents the view that system change is less likely to occur as a result of a few big ideas than by the accumulation of many little ones.

The proliferation of local solutions not only results in more relevant services that are more likely to achieve results, but they supply the larger system with a pluralistic menu of creative approaches and they put pressure on that system to be able to sustain and support them. They also begin to shift cultural norms and expectations because there are a lot more agents driving new visions, rather a handful of visions being introduced and/or imposed by a few.

The expectation that a worthwhile solution ought to be spreadable or replicable beyond the proximal area that gave birth to it is simply wrong.

Yes, we should glean what we can from small solutions in order to share and disseminate creative approaches to complex challenges and, when we can, accomplish scale with some of them. But the signature of a worthy idea is not necessarily that it is scalable. Not every private business is scalable nor is it desirable to scale every business. The backbone of national economies is small businesses, not giant corporations, and the seduction of the growth model is as problematic in the social sector as it is within the private sector.

A preoccupation with populating the innovation landscape with scalable ideas is actually inimical to achieving the deeper system change because (1) it limits creativity to ideas that work across multiple geographies, conditions and populations—a far more restrictive criterion than one that invites ideas to proliferate in diverse local contexts; (2) given the complexity and diversity of human beings and the social landscapes they inhabit, we see the need for pluralistic solutions, not homogenous ones that need to be retrofitted to different contexts; (3) emphasizing and supporting only scalable solutions deprives social change of the power of small solutions to have a cumulative effect; (4) the more system change or improved outcomes rests in the hands of a few, the less likely it is to occur; the more everyone can play a role, irrespective of the size or scope of their solution, the more we will see the change we are after.

A sociocultural landslide is not about the few boulders loosened down a gorge, it is about the millions of stones that sweep down like a tide and transfigure the landscape. In the end, as compelling and inspirational as single, scaled solutions can be, it’s not just about the few—it’s about the many.

5) Scaling initial conditions.

Within the private sector there are a range of public and private mechanisms to support and scale innovation—access to capital, data, talent and connectivity (knowledge dissemination and networking).

None of this infrastructure exists within the social sector, or at least, not in any sort of coherent way. If we want to see a verdant proliferation of solutions, and if we want to see them succeed, we need to attend to the ground that gives birth to them and that nourishes them.

Program grants for innovation are limited are unsuitable for many reasons, not the least of which is that they invest in projects and not infrastructure. Applications ask for solutions that are ready to be delivered, but innovation emerges out of a social R&D engine that begins with questions (What is the problem? What assumptions, values, conditions and practices are sustaining it? What ideas might work? What interactions can we test?). Applications typically require respondents to identify multi-year activities, objectives and outcomes; social R&D is about making frequent pivots based on ongoing insights.

Worse, there is an assumption that organizations have the capacity to deliver innovation, as though running a new program or pilot is the equivalent of engaging in innovation.Nothing could be further from the truth. With few exceptions, we would argue that the public sector, non-profits and charities lack the culture, competencies, capacities and resources to engage in meaningful social R&D. As such, the ambition for innovation is severely hampered.

Social service organizations are not designed to develop novel solutions, nor to embed these solutions into their organizations and to continuously iterate them. Were a novel solution to emerge, it would be operationalized within a bureaucratic ethos that cannot help but neutralize what makes it unique. A truly novel idea will cut against the grain of most every function within an organization—human resources, risk management, communications, finance, philosophy and values, etc. It will chafe fiercely, and complicated systems have an internal imperative to achieve internal coherency and consistency. The cultures and competencies required for delivery are simply not the same as those required for development.

What passes for innovation in the social services sector tend to be “small-i,” incremental innovations that occur within a well-established paradigm.

It is unreasonable to expect innovation to occur when there is no discernable social R&D infrastructure and when those proposing solutions are managers steeped in the service paradigm. Where consultancies do enter the picture, they tend to produce small, project-based solutions, but do not influence or contribute to organizational capacity for ongoing social R&D.

If we want to see more innovative solutions, we need to scale the conditions that produce and nourish them. It’s not about a few good ideas that somehow make it; it’s about tending the ground that could produce a bounty. By building a social R&D infrastructure within the public/social sector, we nourish the conditions from which many innovations can grow and find purchase.