Tag: social innovation

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Developmental Evaluation’s Traps

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Developmental evaluation holds promise for product and service designers looking to understand the process, outcomes, and strategies of innovation and link them to effects. It’s the great promise of DE that is also the reason to be most wary of it and beware the traps that are set for those unaware.  

Developmental evaluation (DE), when used to support innovation, is about weaving design with data and strategy. It’s about taking a systematic, structured approach to paying attention to what you’re doing, what is being produced (and how), and anchoring it to why you’re doing it by using monitoring and evaluation data. DE helps to identify potentially promising practices or products and guide the strategic decision-making process that comes with innovation. When embedded within a design process, DE provides evidence to support the innovation process from ideation through to business model execution and product delivery.

This evidence might include the kind of information that helps an organization know when to scale up effort, change direction (“pivot”), or abandon a strategy altogether.

Powerful stuff.

Except, it can also be a trap.

It’s a Trap!

Star Wars fans will recognize the phrase “It’s a Trap!” as one of special — and much parodied — significance. Much like the Rebel fleet’s jeopardized quest to destroy the Death Star in Return of the Jedi, embarking on a DE is no easy or simple task.

DE was developed by Michael Quinn Patton and others working in the social innovation sector in response to the needs of programs operating in areas of high volatility, uncertainty, complexity, and ambiguity in helping them function better within this environment through evaluation. This meant providing the kind of useful data that recognized the context, allowed for strategic decision making with rigorous evaluation and not using tools that are ill-suited for complexity to simply do the ‘wrong thing righter‘.

The following are some of ‘traps’ that I’ve seen organizations fall into when approaching DE. A parallel set of posts exploring the practicalities of these traps are going up on the Cense site along with tips and tools to use to avoid and navigate them.

A trap is something that is usually camouflaged and employs some type of lure to draw people into it. It is, by its nature, deceptive and intended to ensnare those that come into it. By knowing what the traps are and what to look for, you might just avoid falling into them.

A different approach, same resourcing

A major trap is going into a DE is thinking that it is just another type of evaluation and thus requires the same resources as one might put toward a standard evaluation. Wrong.

DE most often requires more resources to design and manage than a standard program evaluation for many reasons. One the most important is that DE is about evaluation + strategy + design (the emphasis is on the ‘+’s). In a DE budget, one needs to account for the fact that three activities that were normally treated separately are now coming together. It may not mean that the costs are necessarily more (they often are), but that the work required will span multiple budget lines.

This also means that operationally one cannot simply have an evaluator, a strategist, and a program designer work separately. There must be some collaboration and time spent interacting for DE to be useful. That requires coordination costs.

Another big issue is that DE data can be ‘fuzzy’ or ambiguous — even if collected with a strong design and method — because the innovation activity usually has to be contextualized. Further complicating things is that the DE datastream is bidirectional. DE data comes from the program products and process as well as the strategic decision-making and design choices. This mutually influencing process generates more data, but also requires sensemaking to sort through and understand what the data means in the context of its use.

The biggest resource that gets missed? Time. This means not giving enough time to have the conversations about the data to make sense of its meaning. Setting aside regular time at intervals appropriate to the problem context is a must and too often organizations don’t budget this in.

The second? Focus. While a DE approach can capture an enormous wealth of data about the process, outcomes, strategic choices, and design innovations there is a need to temper the amount collected. More is not always better. More can be a sign of a lack of focus and lead organizations to collect data for data’s sake, not for a strategic purpose. If you don’t have a strategic intent, more data isn’t going to help.

The pivot problem

The term pivot comes from the Lean Startup approach and is found in Agile and other product development systems that rely on short-burst, iterative cycles with accompanying feedback. A pivot is a change of direction based on feedback. Collect the data, see the results, and if the results don’t yield what you want, make a change and adapt. Sounds good, right?

It is, except when the results aren’t well-grounded in data. DE has given cover to organizations for making arbitrary decisions based on the idea of pivoting when they really haven’t executed well or given things enough time to determine if a change of direction is warranted. I once heard the explanation given by an educator about how his team was so good at pivoting their strategy for how they were training their clients and students. They were taking a developmental approach to the course (because it was on complexity and social innovation). Yet, I knew that the team — a group of highly skilled educators — hadn’t spent nearly enough time coordinating and planning the course.

There are times when a presenter is putting things last minute into a presentation to capitalize on something that emerged from the situation to add to the quality of the presentation and then there is someone who has not put the time and thought into what they are doing and rushing at the last minute. One is about a pivot to contribute to excellence, the other is not executing properly. The trap is confusing the two.

Fearing success

“If you can’t get over your fear of the stuff that’s working, then I think you need to give up and do something else” – Seth Godin

A truly successful innovation changes things — mindsets, workflows, systems, and outcomes. Innovation affects the things it touches in ways that might not be foreseen. It also means recognizing that things will have to change in order to accommodate the success of whatever innovation you develop. But change can be hard to adjust to even when it is what you wanted.

It’s a strange truth that many non-profits are designed to put themselves out of business. If there were no more political injustices or human rights violations around the world there would be no Amnesty International. The World Wildlife Fund or Greenpeace wouldn’t exist if the natural world were deemed safe and protected. Conversely, there are no prominent NGO’s developed to eradicate polio anymore because pretty much have….or did we?

Self-sabotage exists for many reasons including a discomfort with change (staying the same is easier than changing), preservation of status, and a variety of inter-personal, relational reasons as psychologist Ellen Hendrikson explains.

Seth Godin suggests you need to find something else if you’re afraid of success and that might work. I’d prefer that organizations do the kind of innovation therapy with themselves, engage in organizational mindfulness, and do the emotional, strategic, and reflective work to ensure they are prepared for success — as well as failure, which is a big part of the innovation journey.

DE is a strong tool for capturing success (in whatever form that takes) within the complexity of a situation and the trap is when the focus is on too many parts or ones that aren’t providing useful information. It’s not always possible to know this at the start, but there are things that can be done to hone things over time. As the saying goes: when everything is in focus, nothing is in focus.

Keeping the parking brake on

And you may win this war that’s coming
But would you tolerate the peace? – “This War” by Sting

You can’t drive far or well with your parking brake on. However, if innovation is meant to change the systems. You can’t keep the same thinking and structures in place and still expect to move forward. Developmental evaluation is not just for understanding your product or service, it’s also meant to inform the ways in which that entire process influences your organization. They are symbiotic: one affects the other.

Just as we might fear success, we may also not prepare (or tolerate) it when it comes. Success with one goal means having to set new goals. It changes the goal posts. It also means that one needs to reframe what success means going ahead. Sports teams face this problem in reframing their mission after winning a championship. The same thing is true for organizations.

This is why building a culture of innovation is so important with DE embedded within that culture. Innovation can’t be considered a ‘one-off’, rather it needs to be part of the fabric of the organization. If you set yourself up for change, real change, as a developmental organization, you’re more likely to be ready for the peace after the war is over as the lyric above asks.

Sealing the trap door

Learning — which is at the heart of DE — fails in bad systems. Preventing the traps discussed above requires building a developmental mindset within an organization along with doing a DE. Without the mindset, its unlikely anyone will avoid falling through the traps described above. Change your mind, and you can change the world.

It’s a reminder of the needs to put in the work to make change real and that DE is not just plug-and-play. To quote Martin Luther King Jr:

“Change does not roll in on the wheels of inevitability, but comes through continuous struggle. And so we must straighten our backs and work for our freedom. A man can’t ride you unless your back is bent.”

 

For more on how Developmental Evaluation can help you to innovate, contact Cense Ltd and let them show you what’s possible.  

Image credit: Author

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Decoupling creators from their creations

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The world is transformed by creators — the artists, the innovators, the leaders — and their creations are what propel change and stand in the way of it. Change can be hard and its made all the more so when we fail to decouple the creator from the created, inviting resistance rather than enticing better creations. 

If you want to find the hotspot for action or inaction in a human system, look at what is made in that system. Human beings defend, promote and attend to what they made more than anything. Just watch.

Children will rush to show you what they made: a sandcastle, a picture, a sculpture, a…whatever it is they are handing you. Adults don’t grow out of that: we are just big kids. Adults are just more subtle in how we promote and share what we do, but we still place an enormous amount of psychological energy on our creations. Sometimes its our kids, our spouses (which is a relationship we created), our ideas, our way of life, our programs, policies or businesses. Even something like a consumer purchase is, in some ways, a reflection of us in that we are making an identity or statement with it.

Social media can feel like one big echo-chamber sometimes, but it’s that way because we often are so busy sharing our opinions that we’re not listening — focusing on what we made, not what others made. Social media can be so harsh because when we attack ideas — our 140 character creations sometimes — we feel as if we are being attacked. This is one of the reasons we are having such traumatized, distorted discourse in the public domain.

Creations vs creators

The problem with any type of change is that we often end up challenging both the creator and the creation at the same time. It’s saying that the creation needs to change and that can hurt the creator, even if done unintentionally.

The interest in failure in recent years is something I’ve been critical of, but a positive feature of it is that people are now talking more openly about what it means to not succeed and that is healthy. There are lots of flaws in the failure talk out there, mostly notably because it fails (no pun — even a bad one, intended… but let’s go with it) to decouple the creator from the creation.  In many respects, creators and their creations are intimately tied together as one is the raw material and vehicle for the other.

But when we need to apologize for, make amends because, or defend our creations constantly we are using a lot of energy. In organizational environments there is an inordinate amount of time strategizing, evaluating and re-visiting innovation initiatives, but the simple truth is that — as we will see below — it doesn’t make a lick of difference because we are confusing the creators with the creations and the systems in which they are creating.

Sometimes we need to view the creator and creation separately and that is all a matter of trust – and reality.

 

A matter of trust, a matter of reality

If you are part of a team that has been tasked with addressing an issue and given a mandate to find and possibly create a solution, why should it matter what you produce? That seems like an odd question or statement.

At first it seems obvious: for accountability, right?

But consider this a little further.

If a team has been given a charge, it presumably is the best group that is available given the time and resources available. Maybe there are others more suited or talented to the job, perhaps there is a world expert out there who could help, but because of time, money, logistics or some combination of reasons in a given situation that isn’t possible. We are now dealing with what is, not what we wish to be. This is sometimes called the real world. 

If that team does not have the skills or talent to do it, why is it tasked with the problem? If those talents and skills are unknown and there is no time, energy or commitment  — or means — to assess that in practice then you are in a truly innovative space: let’s see what happens.

In this case, accountability is simply a means of exploring how something is made, what is learned along the way, and assessing what kind of products are produced from that, knowing that there is no real way to determine it’s comparative merit, significance or worth — the hallmark tenets of evaluation. It’s experimental and there is no way to fail, except to fail to attend and learn from it.

This is a matter of trust. It’s about trusting that you’re going to do something useful with what you have and that’s all. The right / wrong debate makes no sense because, if you’re dealing with reality as we discussed above there are no other options aside from not doing something. So why does failure have to come into it?

This is about trusting creators to create. It has nothing to do with what they create because, if you’ve selected a group to do something that only they are able to do, for reasons mentioned above, it has nothing to do with their creation.

Failing at innovation

The real failure we speak of might be failing to grasp reality, failing to support creative engagement in the workplace, and failing to truly innovate. These are products of what happens when we task individuals, groups, units or some other entity within our organizations, match them with systems that have no known means forward and provide them with no preparation, tools, or intelligence about the problem to support doing what they are tasked with. The not knowing part of the problem is not uncommon, particularly in innovative spaces. It’s nothing to sneer at, rather something that is a true learning opportunity. But we need to call it as it is, not what we want it or pretend it to be.

My colleague Hallie Preskill from FSG is big on learning and is not averse to rolling her eyes when people speak of it, because it’s often used so flippantly and without thought. True learning means paying attention, giving time and focus to what material — experience, data, reflections, goals and contexts — is available, and in . Learning has a cost and it has many myths attached to it. It’s difficulty is why many simply don’t do it. In truth, many are not as serious about really learning, but talking about learning. This is what Hallie sees a lot.

The material for learning is what these innovators, these creators, are producing so if we are valuing creation and innovation we need to pay attention to this and entice creators to continue to generate more quality ‘content’ for us to learn from and worry less about what these creators produce when we task them with innovation missions that have no chance to ‘succeed’ just as they have no chance to ‘fail’

A poor question leads us to poor answers.

Consider what we ask of our innovators and innovation and you’ll see that, if we want more and better creators and if we want more and better creations we need to see them in a new light and create the culture that sees them both for what they are, not what we want them to be.

Image credit: Author

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Jaded: Whether You Are a Plant or a Stone Makes All the Difference

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An attempt to innovate – do something new to produce value — is always fraught with risk and a high likelihood that things won’t go as planned, which can leave people jaded toward future efforts. Whether that metaphor of jade is one of a rock (static) or a plant (growth) makes all the difference. 

Innovation is hot. Innovation is necessary. Innovation is your competitive advantage. Innovate or die.

You’ve probably heard one or all of these phrases or one of the myriad variants of them out there. Innovation is a hot word. To innovate is to transform new thinking into new value, but it is used euphemistically to represent all kinds of ‘hot’ things without appropriate framing. It’s not just doing something different, it’s about producing something new that improves on the situation at hand, even if the solution might actually be an old idea re-introduced.

A recent article for the online version of Harvard Business Review suggests that many companies are just giving up, ceding the ‘innovation’ space to large firms with a reputation for innovation. Why? One of the reasons cited is that the developing social and technological change has created a situation where “many firms seem to be unable to keep up with the pace at which this development is unfolding.”

The painful experience of failure

Another reason might be the problem of failure. Failure has become another cool word in the language of business and social innovation (even, government) to the point of being fetishized as something noble. The issue with failure is not just accepting that it can happen, but learning from it and acting on that learning. It also means understanding what failure is and whether an outcome is even best described in terms like “success” and “failure” . Too often in innovation, particularly social innovation, we actually don’t know what success looks like so how is it that we can use the term failure so readily?

Failure is a word with enormous negative cultural baggage. Despite all the positive rhetoric of failure, corporations, social enterprises and governments are judged on their ability to deliver what is expected of them. Expectations are really the key here. If you’re a corporation that promises to deliver a certain rate of return on investment over a specific time period, you’re going to be held to task for that. We can speak of failure positively all we’d like, but try explaining the ‘learning’ outcomes to a group of angry shareholders?

Politicians don’t get judged on their ability to manage complexity, they are judged by making and keeping promises — even if those promises are based on (overly) simplistic ways of viewing complex problems. As we entangle ourselves with more complex problems, the promise of a simple solution will be harder to come by. Yet, it’s that hope for the solution that is what ultimately gets us. As I once read in a newsletter advertising an online dating service in a very cheeky manner:

It’s not the rejection that kills you, it’s the hope.

It’s actually quite true. If you don’t expect to succeed, “failure” isn’t really that bad.

Lowered expectations, risk avoidance & path dependencies

When you’re jaded, you tend to lower your expectations. The analogy of online dating above is also an apt descriptor for ways in which lowered expectations changes the very game of innovation in real ways in people’s lives. As divorce rates approach 50%, it is becoming common that many people are starting over sometime in their 30’s and 40’s and trying, once again, to find love. What’s interesting in terms of dating is that, particularly if you’ve been dating a little, you face two big issues: 1) you’re a bit cautious about what you do or say because you know that things might not last and you want to conserve your energy and 2) you’ve become accustomed to the way you do things on your own.

The result might be less adventurousness, more conservative thinking about the choice of partner, a greater willingness to settle for what is, rather than what could be (risk avoidance). An established pattern of living might also predispose you to looking for partners who are a lot like you, which maintains a level of consistency (path dependence). An argument can be made that this is more about knowing yourself and your preferences than being set in your ways, but there is a fine line between that and resistance to change.

This is exactly what we see in organizations around innovation.

They have tried innovation before, it’s failed to deliver what they expected (because they probably set their expectations poorly, not realizing that the outcomes of innovation could be something other than they had designed for), and now don’t want to try. Or rather, they don’t want to try enough. This is why we see so many organizations trumpet themselves as innovative, when what they are really doing is the most basic, simplistic forms of innovation. Rather than a moonshot, they are looking to simply move the yardsticks just a little.

Plant vs stone

Jade is both a plant and a stone. A jade plant is a solid, semi-broad leafed plant that is well suited to dry climates and a variety of light situations, making it a great houseplant. It’s adaptive, easily transplantable and hearty. Jade, as a stone, is relatively soft and while it is also adaptable, once carved into a shape, it’s no longer going to change.

The jade / jaded metaphor is designed to consider the ways in which we approach developing our innovation potential. A jade plant is still firm, but flexible. It grows and changes over time, but isn’t as free flowing as others. The jade plant offers a useful metaphor for ensuring that lessons learned from past actions inform future strategy, but not to the point where the fear of risk calcifies the organization into a static state, unable to change.

A plant exists largely because it has a steady stream of nutrients, water, sunlight and a reasonable stability of growing conditions, yet conditions that can change and will change over time. This consistency as well as requisite variety (in systems terms) is what keeps a plant alive and thriving. The same is true for an organization. Ongoing, steady innovation, consistency over time and the occasional change in conditions to keep things on their toes (and used to adaptation) are all a part of what makes an organization or individual innovative. Build in a regular practice, become a mindful organization (or practitioner) and consider changes in the way you speak about innovation to yourself and others.

Bruce Lee would advocate that his students become like water. Innovators? They should become more like plants for that water.

Image Credit: Jade Plant by Andrew Rivett used under Creative Commons License. Thanks for sharing Andrew!

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Lost together

Lost and found

A post certainty world

Doing new things to create social value means going into the great unknown, yet our fear of being lost need not prevent us from innovating, wisely and sustainably. Instead of being lost alone, we can be lost together. 

I’ve heard it all so many times before

It’s all a dream to me now
A dream to me now
And if we’re lost
Then we are lost together

– Blue Rodeo (Lost Together)

Humans have real problems with uncertainty. Risk mitigation is an enormous field of work within business, government and politics and permeates decision making in our organizations. It’s partly this reason that our politicians too often speak so cryptically to the point of basically uttering nonsense – because they want to avoid the risk of saying something that will hurt them. The alternative perhaps is to spout so much untruth that it no longer matters what you say, because others will create messages about you.

Thankfully, we are still — and hopefully into the future — in a world where most of what organizations do is considered and evaluated with some care to the truth. ‘Truth’ or facts are much easier to deal with in those systems where we can generate the kind of evidence that enable us to make clear decisions based on replicable, verifiable and defensible research. Ordered systems where there is a cause-and-effect relationship that is (usually) clear, consistent and observable are those where we can design interventions to mitigate risk with confidence.

Risky options

There are four approaches to risk mitigation.

  1. Risk Acceptance involves awareness of what risks are present within the system and establishing strategy and an organizational culture where the nature, type and potential consequences of risks are (largely) known, accepted and lived with.
  2. Risk Avoidance takes the opposite approach and seeks to steer operations away from activities where risk is limited.
  3. Risk Limitation seeks to curtail and mitigate the effects of risk where possible and often involves contingency planning and balancing activities with higher levels of uncertainty with areas of greater confidence and certainty.
  4. Risk Transference involves finding ways to offload risk to a third party. An example can be found in many partnerships between organizations of different sizes or types where one is able to absorb certain risks while others cannot for various reasons and the activities allow for one partner to take lead on an activity that isn’t feasible for another to do so.

Within social innovation — those activities involving public engagement, new thinking and social benefit — there are few opportunities for #2, plenty for #1 and #3 and a growing number for #4.

Risk is a core part of innovation. To innovate requires risking time, energy, focus and other resources toward the attempt at something new to produce a valued alternative to the status quo. For many human service organizations and funders, these resources are so thinly spread and small in abundance that the idea of considering risk seems like a risk itself. Yet, the real problem comes in assuming that one can choose whether or not to engage risk. Unless you’re operating in a closed system that has relatively few changing elements to it, you’re exposed to risk by virtue of being in the system. To draw on one of my favourite quotes from the author Guiseppe di Lampedusa:

If we want things to stay as they are, things will have to change.

So even keeping things away from risk involves risk because if the world around you is changing the system changes with it and so, too does your position in it. If this makes you feel lost, you’re not alone. Many organizations (individuals, too) are struggling with figuring out where they fit in the world. If you want evidence of this consider the growing calls for skilled knowledge workers at the same time we are seeing a crisis among those with a PhD — those with the most knowledge (of certain sorts) — in the job market.

Community of flashlights

There is a parable of the drunkard who loses his keys on his way home at night and searches for them under the streetlight not because that’s where he lost them, but because it’s easier to see that spurred something called the Streetlight Effect. It’s about the tendency to draw on what we know and what we have at our disposal to frame problems and seek to solve them, even if they are the wrong tools — a form of observation bias in psychology. Streetlights are anchored, stable means of illuminating a street within a certain range – a risk zone, perhaps — but remain incomplete solutions.

Flashlights on the other hands have the same limitations (a beam of light), are less powerful, but are adaptive. You can port a flashlight or torch and aim it to where you want the light to shine. They are not as powerful as a streetlight in terms of luminosity, but are far more nimble. However, if you bring more than one flashlight together, all of a sudden the power of the light is extended. This is the principle behind many of the commercial LED systems that are in use. Small numbers of lights brought together, each using low energy, but collectively providing a powerful, adaptive lighting system

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This same principle can apply to organizations seeking to make change. Like an LED flashlight, they need a housing to hold and focus the lights. This can be in the form of a backbone organization such as those advocated in collective impact strategies. It can also be a set of principles or simple rules that provide a set of guides for organizations operating independently to follow, which will stimulate a consistent pattern of activity when applied, allowing similar, focused action on the same target at a distance.

This latter approach differs from collective impact, which is a top-down and bottom-up approach simultaneously and is a good means of focusing on larger, macro issues such as poverty reduction, climate change and city-building. It is an approach that holds potential for working within these larger issues on smaller, more dynamic ones such as neighbourhood building, conservation actions within a specific region, and workplace health promotion. In both cases the light analogy can hold and they need not be done exclusive of one another.

Let there be light

A flashlight initiative requires a lot of things coming together. It can be led by individuals making connections between others, brokering relationships and building community. It requires a vision that others can buy into and an understanding of the system (it’s level of complexity, structure and history). This understanding is what serves as the foundation for the determination of the ‘rules’ of the system, those touch points, attractors, leverage points and areas of push and pull that engage energy within a system (stay tuned to a future post for more detailed examples).

Much of the open-source movement is based on this model. This is about creating that housing for ideas to build and form freely, but with constraints. It’s a model that can work when collective impact is at a scale too large for an organization (or individual) to adequately envision contribution, but an alternative to going alone or relying only on the streetlight to find your way.

You might be lost, but with a flashlight you’ll be lost together and may just find your way.

Image credits: Author (Cameron Norman)

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Flipping the Social Impact Finger

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Look around and one will notice a lot of talk about social enterprise and social impact. Look closer and you’ll find a lot more of the former and far less of the latter. 

There’s a Buddhist-inspired phrase that I find myself reflecting on often when traveling in the social innovation/entrepreneurship/enterprise/impact sphere:

Do not confuse the finger pointing to the moon for the moon itself

As terms like social enterprise and entrepreneurship, social innovation, social laboratories and social impact (which I’ll lump together as [social] for expediency of writing) become better known and written about its easy to caught up in the excitement and proclaiming its success in changing the world. Indeed, we are seeing a real shift in not only what is being done, but a mental shift in what can be perceived to be done among communities that never saw opportunities to advance before.

However exciting this is, there is what I see as a growing tendency to lose the forest amid the trees by focusing on the growth of [social] and less on the impact part of that collection of terms. In other words, there’s a sense that lots of talk and activity in [social] is translating to social impact. Maybe, but how do we know?

Investment and ROI in change

As I’ve written before using the same guiding phrase cited above, there is a great tendency to confuse conversation about something with the very thing that is being talked about in social impact. For all of the attention paid to the amount of ventures and the amount of venture capital raised to support new initiatives across the social innovation spectrum in recent years, precious little change has been witnessed in the evaluations made available of these projects.

As one government official working in this sector recently told me:

We tend to run out of steam after (innovations) get launched and lose focus, forgetting to evaluate what kind of impact and both intended and unintended consequences come with that investment

As we celebrate the investment in new ventures, track the launch of new start-ups, and document the number of people working in the [social] sector we can mistake that for impact. To be sure, having people working in a sector is a sign of jobs, but the question of whether they are temporary, suitably paying, satisfactory, or sustainable are the kind of questions that evaluators might ask and remain largely unanswered.

The principal ROI of [social] is social benefit. That benefit comes in the form of improved products and services, better economic conditions for more people, and a healthier planet and wellbeing for the population of humans on it in different measures. These aren’t theoretical benefits, they need to be real ones and the only way we will know if we achieve anything approximating this is through evaluation.

Crashing, but not wrecking the party

Evaluation needs to crash the party, but it need not kill the mood. A latent fear among many in [social] is likely that, should we invest so much energy, enthusiasm, money and talent on [social] and find that it doesn’t yield the benefits we expect or need a fickle populace of investors, governments and the public will abandon the sector. While there will always be trend-hunters who will pursue the latest ‘flavour of the month’, [social] is not that. It is here to stay.

The focus on evaluation however will determine the speed, scope and shape of its development. Without showing real impact and learning from those initiatives that produce positive benefit (or do not) we will substantially limit [social] and the celebratory parties that we now have at the launch of a new initiative, a featured post on a mainstream site, or a new book will become fewer and farther between.

Photo credit: Moonrise by James Niland used under Creative Commons licence via Flickr. Thanks for sharing your art, James.

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Confusing change-making with actual change

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Change-making is the process of transformation and not to be confused with the transformed outcome that results from such a process. We confuse the two at our peril.

“We are changing the world” is a rallying cry from many individuals and organizations working in social innovation and entrepreneurship which is both a truth and untruth at the same time. Saying you’re changing the world is far easier than actually doing it. One is dramatic — the kind that make for great reality TV as we’ll discuss — and the other is rather dull, plodding and incremental. But it may be the latter that really wins the day.

Organizations like Ashoka (and others) promote themselves as a change-maker organization authoring blogs titled “everything you need to know about change-making”. That kind of language, while attractive and potentially inspiring to diverse audiences, points to a mindset that views social change in relatively simple, linear terms. This line of thinking suggests change is about having the right knowledge and the right plan and the ability to pull it together and execute.

This is a mindset that highlights great people and great acts supported by great plans and processes. I’m not here to dismiss the work that groups like Ashoka do, but to ask questions about whether the recipe approach is all that’s needed. Is it really that simple?

Lies like: “It’s calories in, calories out”

Too often social change is viewed with the same flawed perspective that weight loss is. Just stop eating so much food (and the right stuff) and exercise and you’ll be fine — calories in and out as the quote suggests — and you’re fine. The reality is, it isn’t that simple.

A heartbreaking and enlightening piece in the New York Times profiled the lives and struggles of past winners of the reality show The Biggest Loser (in parallel with a new study released on this group of people (PDF)) that showed that all but one of the contestants regained weight after the show as illustrated below:

BiggestLoser 2016-05-03 09.17.10

The original study, published in the journal Obesity, considers the role of metabolic adaptation that takes place with the authors suggesting that a person’s metabolism makes a proportional response to compensate for the wide fluctuations in weight to return contestants to their original pre-show weight.

Consider that during the show these contestants were constantly monitored, given world-class nutritional and exercise supports, had tens of thousands of people cheering them on and also had a cash prize to vie for. This was as good as it was going to get for anyone wanting to lose weight shy of surgical options (which have their own problems).

Besides being disheartening to everyone who is struggling with obesity, the paper illuminates the inner workings of our body and reveals it to be a complex adaptive system rather than the simple one that we commonly envision when embarking on a new diet or fitness regime. Might social change be the same?

We can do more and we often do

I’m fond of saying that we often do less than we think and more than we know.

That means we tend to expect that our intentions and efforts to make change produce the results that we seek directly and because of our involvement. In short, we treat social change as a straightforward process. While that is sometimes true, rare is it that programs aiming at social change coming close to achieving their stated systems goals (“changing the world”) or anything close to it.

This is likely the case for a number of reasons:

  • Funders often require clear goals and targets for programs in advance and fund based on promises to achieve these results;
  • These kind of results are also the ones that are attractive to outside audiences such as donors, partners, academics, and the public at large (X problem solved! Y number of people served! Z thousand actions taken!), but may not fully articulate the depth and context to which such actions produce real change;
  • Promising results to stakeholders and funders suggests that a program is operating in a simple or complicated system, rather than a complex one (which is rarely, if ever the case with social change);
  • Because program teams know these promised outcomes don’t fit with their system they cherry-pick the simplest measures that might be achievable, but may also be the least meaningful in terms of social change.
  • Programs will often further choose to emphasize those areas within the complex system that have embedded ordered (or simple) systems in them to show effect, rather than look at the bigger aims.

The process of change that comes from healthy change-making can be transformative for the change-maker themselves, yet not yield much in the way of tangible outcomes related to the initial charge. The reasons likely have to do with the compensatory behaviours of the system — akin to social metabolic adaptation — subduing the efforts we make and the initial gains we might experience.

Yet, we do more at the same time. Danny Cahill, one of the contestants profiled in the story for the New York Times, spoke about how the lesson learned from his post-show weight gain was that the original weight gain wasn’t his fault in the first place

“That shame that was on my shoulders went off”

What he’s doing is adapting his plan, his goals and working differently to rethink what he can do, what’s possible and what is yet to be discovered. This is the approach that we take when we use developmental evaluation; we adapt, evolve and re-design based on the evidence while continually exploring ways to get to where we want to go.

A marathon, not a sprint, in a laboratory

The Biggest Loser is a sprint: all of the change work compressed into a short period of time. It’s a lab experiment, but as we know what happens in a laboratory doesn’t always translate directly into the world outside its walls because the constraints have changed. As the show’s attending physician, Dr. Robert Huizenga, told the New York Times:

“Unfortunately, many contestants are unable to find or afford adequate ongoing support with exercise doctors, psychologists, sleep specialists, and trainers — and that’s something we all need to work hard to change”

This quote illustrates the fallacy of real-world change initiatives and exposes some of the problems we see with many of the organizations who claim to have the knowledge about how to change the world. Have these organizations or funders gone back to see what they’ve done or what’s left after all the initial funding and resources were pulled? This is not just a public, private or non-profit problem: it’s everywhere.

I have a colleague who spent much time working with someone who “was hired to clean up the messes that [large, internationally recognized social change & design firm] left behind” because the original, press-grabbing solution actually failed in the long run. And the failure wasn’t in the lack of success, but the lack of learning because that firm and the funders were off to another project. Without building local capacity for change and a sustained, long-term marathon mindset (vs. the sprint) we are setting ourselves up for failure. Without that mindset, lack of success may truly be a failure because there is no capacity to learn and act based on that learning. Otherwise, the learning is just a part of an experimental approach consistent with an innovation laboratory. The latter is a positive, the former, not so much.

Part of the laboratory approach to change is that labs — real research labs — focus on radical, expansive, long-term and persistent incrementalism. Now that might sound dull and unsexy (which is why few seem to follow it in the social innovation lab space), but it’s how change — big change — happens. The key is not in thinking small, but thinking long-term by linking small changes together persistently. To illustrate, consider the weight gain conundrum as posed by obesity researcher Dr. Michael Rosenbaum in speaking to the Times:

“We eat about 900,000 to a million calories a year, and burn them all except those annoying 3,000 to 5,000 calories that result in an average annual weight gain of about one to two pounds,” he said. “These very small differences between intake and output average out to only about 10 to 20 calories per day — less than one Starburst candy — but the cumulative consequences over time can be devastating.”

Building a marathon laboratory

Marathoners are guided by a strange combination of urgency, persistence and patience. When you run 26 miles (42 km) there’s no sprinting if you want to finish the same day you started. The urgency is what pushes runners to give just a little more at specific times to improve their standing and win. Persistence is the repetition of a small number of key things (simple rules in a complex system) that keep the gains coming and the adaptations consistent. Patience is knowing that there are few radical changes that will positively impact the race, just a lot of modifications and hard work over time.

Real laboratories seek to learn a lot, simply and consistently and apply the lessons from one experiment to the next to extend knowledge, confirm findings, and explore new territory.

Marathons aren’t as fun to watch as the 100m sprint in competitive athletics and lab work is far less sexy than the mythical ‘eureka’ moments of ‘discovery’ that get promoted, but that’s what changes the world. The key is to build organizations that support this. It means recognizing learning and that it comes from poor outcomes as well as positive ones. It encourages asking questions, being persistent and not resting on laurels. It also means avoiding getting drawn into being ‘sexy’ and ‘newsworthy’ and instead focusing on the small, but important things that make the news possible in the first place.

Doing that might not be as sweet as a Starburst candy, but it might avoid us having to eat it.

 

 

 

behaviour changecomplexitypsychologysocial innovationsocial systems

Decoding the change genome

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Would we invest in something if we had little hard data to suggest what we could expect to gain from that investment? This is often the case with social programs, yet its a domain that has resisted the kind of data-driven approaches to investment that we’ve seen in other sectors and one theory is that we can approach change in the same way we code the genome, but: is that a good idea?

Jason Saul is a maverick in social impact work and dresses the part: he’s wearing a suit. That’s not typically the uniform of those working in the social sector railing against the system, but that’s one of the many things that gets people talking about what he and his colleagues at Mission Measurement are trying to do. That mission is clear: bring the same detailed analysis of the factors involved in contributing to real impact from the known evidence that we would do to nearly any other area of investment.

The way to achieving this mission is to take the thinking behind the Music Genome Project, the algorithms that power the music service Pandora, and apply it to social impact. This is a big task and done by coding the known literature on social impact from across the vast spectrum of research from different disciplines, methods, theories and modeling techniques. A short video from Mission Measurement on this approach nicely outlines the thinking behind this way of looking at evaluation, measurement, and social impact.

Saul presented his vision for measurement and evaluation to a rapt audience in Toronto at the MaRS Discovery District on April 11th as part of their Global Leaders series en route to the Skoll World Forum ; this is a synopsis of what came from that presentation and it’s implications for social impact measurement.

(Re) Producing change

Saul began his presentation by pointing to an uncomfortable truth in social impact: We spread money around with good intention and little insight into actual change. He claims (no reference provided) that 2000 studies are published per day on behaviour change, yet there remains an absence of common metrics and measures within evaluation to detect change. One of the reasons is that social scientists, program leaders, and community advocates resist standardization making the claim that context matters too much to allow aggregation.

Saul isn’t denying that there is truth to the importance of context, but argues that it’s often used as an unreasonable barrier to leading evaluations with evidence. To this end, he’s right. For example, the data from psychology alone shows a poor track record of reproducibility, and thus offers much less to social change initiatives than is needed. As a professional evaluator and social scientist, I’m not often keen to being told how to do what I do, (but sometimes I benefit from it). That can be a barrier, but also it points to a problem: if the data shows how poorly it is replicated, then is following it a good idea in the first place? 

Are we doing things righter than we think or wronger than we know?

To this end, Saul is advocating a meta-evaluative perspective: linking together the studies from across the field by breaking down its components into something akin to a genome. By looking at the combination of components (the thinking goes) like we do in genetics we can start to see certain expressions of particular behaviour and related outcomes. If we knew these things in advance, we could potentially invest our energy and funds into programs that were much more likely to succeed. We also could rapidly scale and replicate programs that are successful by understanding the features that contribute to their fundamental design for change.

The epigenetic nature of change

Genetics is a complex thing. Even on matters where there is reasonably strong data connecting certain genetic traits to biological expression, there are few examples of genes as ‘destiny’as they are too often portrayed. In other words, it almost always depends on a number of things. In recent years the concept of epigenetics has risen in prominence to provide explanations of how genes get expressed and it has as much to do with what environmental conditions are present as it is the gene combinations themselves . McGill scientist Moshe Szyf and his colleagues pioneered research into how genes are suppressed, expressed and transformed through engagement with the natural world and thus helped create the field of epigenetics. Where we once thought genes were prescriptions for certain outcomes, we now know that it’s not that simple.

By approaching change as a genome, there is a risk that the metaphor can lead to false conclusions about the complexity of change. This is not to dismiss the valid arguments being made around poor data standardization, sharing, and research replication, but it calls into question how far the genome model can go with respect to social programs without breaking down. For evaluators looking at social impact, the opportunity is that we can systematically look at the factors that consistently produce change if we have appropriate comparisons. (That is a big if.)

Saul outlined many of the challenges that beset evaluation of social impact research including the ‘file-drawer effect’ and related publication bias, differences in measurement tools, and lack of (documented) fidelity of programs. Speaking on the matter in response to Saul’s presentation, Cathy Taylor from the Ontario Non-Profit Network, raised the challenge that comes when much of what is known about a program is not documented, but embodied in program staff and shared through exchanges.  The matter of tacit knowledge  and practice-based evidence is one that bedevils efforts to compare programs and many social programs are rich in context — people, places, things, interactions — that remain un-captured in any systematic way and it is that kind of data capture that is needed if we wish to understand the epigenetic nature of change.

Unlike Moshe Szyf and his fellow scientists working in labs, we can’t isolate, observe and track everything our participants do in the world in the service of – or support to – their programs, because they aren’t rats in a cage.

Systems thinking about change

One of the other criticisms of the model that Saul and his colleagues have developed is that it is rather reductionist in its expression. While there is ample consideration of contextual factors in his presentation of the model, the social impact genome is fundamentally based on reductionist approaches to understanding change. A reductionist approach to explaining social change has been derided by many working in social innovation and environmental science as outdated and inappropriate for understanding how change happens in complex social systems.

What is needed is synthesis and adaptation and a meta-model process, not a singular one.

Saul’s approach is not in opposition to this, but it does get a little foggy how the recombination of parts into wholes gets realized. This is where the practical implications of using the genome model start to break down. However, this isn’t a reason to give up on it, but an invitation to ask more questions and to start testing the model out more fulsomely. It’s also a call for systems scientists to get involved, just like they did with the human genome project, which has given us great understanding of what influences our genes have and stressed the importance of the environment and how we create or design healthy systems for humans and the living world.

At present, the genomic approach to change is largely theoretical backed with ongoing development and experiments but little outcome data. There is great promise that bigger and better data, better coding, and a systemic approach to looking at social investment will lead to better outcomes, but there is little actual data on whether this approach works, for whom, and under what conditions. That is to come. In the meantime, we are left with questions and opportunities.

Among the most salient of the opportunities is to use this to inspire greater questions about the comparability and coordination of data. Evaluations as ‘one-off’ bespoke products are not efficient…unless they are the only thing that we have available. Wise, responsible evaluators know when to borrow or adapt from others and when to create something unique. Regardless of what design and tools we use however, this calls for evaluators to share what they learn and for programs to build the evaluative thinking and reflective capacity within their organizations.

The future of evaluation is going to include this kind of thinking and modeling. Evaluators, social change leaders, grant makers and the public alike ignore this at their peril, which includes losing opportunities to make evaluation and social impact development more accountable, more dynamic and impactful.

Photo credit (main): Genome by Quinn Dombrowski used under Creative Commons License via Flickr. Thanks for sharing Quinn!

About the author: Cameron Norman is the Principal of Cense Research + Design and assists organizations and networks in supporting learning and innovation in human services through design, program evaluation, behavioural science and system thinking. He is based in Toronto, Canada.