CENSE Research + Design

Social Innovation by Design

Engagement for ideas

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Engage everyone in idea creation

Among the biggest success factors in any organizational change initiative is engaging staff and stakeholders in participating in the change process; this is true for idea generation through the design cycle to implementation and evaluation. How do we overcome the challenge of disengagement to produce productive creative, innovative ideas in our organizations?

Beyond brainstorming

Ideas are usually the starting point for any change initiative. Ideas produce the raw content of problem identification and the seeds for solution generation. Brainstorming is often the means people first think of as a way to generate ideas and explore concepts. However, there are some substantial problems with this approach and some ways around it.

Brainstorming has been widely criticized for good reasons. Among them: it favours those voices who think (and speak) quickly, speak early, often and loudly. Those early suggestions drive the conversation for what comes next, creating a path dependency that’s hard to escape once initiated. If you’re a quieter, perhaps more contemplative person, you’ll find that you are either late to the conversation or not included. From Jungian Personality Theory, this indicates a bias towards extroversion over introversion, which excludes about 40 per cent of the population according to some estimates.

This approach also favours what Min Basadur would classify as an ‘generator’: someone who’s work style preferences favour idea generation. Those from the other quadrants in the Basadur Profile, particularly ‘conceptualizers’ and ‘optimizers’ (ones who’s work style preference leans toward processing and organizing information) are less likely to respond quickly.

Ideas in private and public

Another problem with many ideation strategies is that many really useful ideas are a bit heretical or outlandish. While design thinking writers often refer to the need to generate ‘wild ideas’ without criticism or judgement, the truth is that’s a lot harder to do in practice, particularly when there are power dynamics in the room, reputations, and the real fear that comes with change and challenges to established practices. The public nature of the ideation process favours transparency, but induces self-censorship and produces disengagement for many and hyper-engagement for a few.

A solution is to have those involved in the process generate ideas independently and anonymously contribute them via a suggestion box (digital or analog). Keep the suggestion box open for a defined period — we recommend no more than one week or as short as three days. This allows time for those who are more reflective to mull through their ideas and contribute them, while those who are more quick to generate ideas will not be affected.

These are then collated independently by someone neutral to the problem and solution set and organized thematically. This has the advantage of potentially embedding some of the wildest ideas within a small set of other ideas that might seem far less threatening. If you create a category of ‘wild ideas’ the risk is that the entire category will be dismissed. A more public, but elaborate, means of doing this can be found in the CoNEKTR Model described elsewhere.

This process can be repeated over the design cycle at different stages – anywhere diverse perspectives and feedback is needed.

Overcoming biases to better ideas

The bias toward ‘rapid ideation’ in design thinking systematically excludes people in favour of a well-meaning intention of trying to avoid participants ‘over-thinking’ a problem. While that might happen, it still prevents many from engaging in the process fully because of personality, work preferences, cognitive style and social pressures.

The strategy listed above is a simple, but highly effective means of getting lots of ideas and engaging your entire team in the process. Try it out. You might be surprised what ideas come from it all.

Mindfulness in Developmental Evaluation

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A place to sit, reflect, observe and evaluate

One of the tools within the toolkit of a developmental evaluator is mindfulness. Mindfulness is a disciplined, regular, and persistent means of paying attention to what is going on. It is a terrific means of collecting data on regular activities, particularly in complex environments where it may be unclear what is worth paying attention to.

In an earlier article on Censemaking (our sister site), Cameron Norman outlines how mindfulness and developmental evaluation work together, highlighting some of the emerging scholarship in the area of organizational mindfulness as an example. As discussed in that piece:

Mindfulness is the disciplined practice of paying attention. Bishop and colleagues (2004 – PDF), working in the clinical context, developed a two-component definition of mindfulness that focuses on 1) self-regulation of attention that is maintained on the immediate experience to enable pattern recognition (enhanced metacognition) and 2) an orientation to experience that is committed to and maintains an attitude of curiosity and openness to the present moment.

It’s one thing to talk mindfulness, but what does this mean for evaluators and organizations in practice? How can we use mindfulness practice and theory to inform developmental evaluation in a practical manner?

We present some strategies we’ve employed in our client work and offer some suggests for those seeking to bring a mindfulness approach to their developmental evaluations.

1. Introduce meditative practice through demonstrations. Let’s get the most obvious link out of the way: meditation. Meditation is usually the first thing that most people think of when hearing the word mindfulness. Meditation is a practice and while it is often linked with spiritual traditions from different cultures it does not need to have a spiritual dimension included if that’s not appropriate or useful. One of the simplest exercises to do is to walk members of the evaluation team through a short mindfulness exercise involving just sitting, closing or dimming the eyes, and paying attention to the breath and the thought patterns going through their head in a non-judgemental manner. A simple one-minute exercise can alert people to the massive amount of stimuli — both inner and outer — that is going on that they either aren’t fully attuned to or wasn’t as clear to them. Developmental evaluation is very much like this: it opens up our awareness of what’s happening in a living system on the go.

2. Build a mindful culture. While meditation is useful, it’s benefits are only accrued when applied collectively as part of the evaluation. Not everyone will take to the idea of meditating (and it needs to be introduced safely), but the idea of paying attention at regular intervals, consistently is effectively at the heart of a developmental evaluation, particularly in a highly complex context. To do this, create regular check-in’s where people answer the simple question: What’s going on? It’s like the equivalent of the “how was your day?” question we might ask our spouse or child. It allows people a momentary space to reflect on what happened within a time period and pick out what was meaningful to them? A follow-up question is: “what did you notice?”

3. Practice non-judgement, at first, and often. Evaluation is about judgement as much as anything else, but in a developmental evaluation context we may not know what benefits, drawbacks, implications or opportunities are present in a situation in the present moment. Encourage participants to simply take note of what is going on, when, and on what was observed without attributing cause and effect, judgement (“good” or “bad”) right away. Attribution is something that can be made later on through a more structured process of sensemaking.

4. Make it social. Mindfulness is generally thought of as a solitary, intra-personal activity. In a developmental evaluation you’re collecting information from across an organization or program and it involves many people and many perspectives: it has to be social to work. This is where sensemaking comes in – a critical component of developmental evaluation. The meaning of any activity won’t be readily apparent without an ability to translate individual observations and reflections into a more collective understanding. Further, because developmental evaluation is used in contexts that are usually complex, the meaning of something will be best determined by having multiple perspectives on the issue — diverse perspectives on the system — brought to bear. Ensure that teams are scheduling regular sensemaking meetings alongside regular reflections.

5. Make it visual. Mindfulness yields a lot of data. In terms of social research methods, mindfulness practice is as close to yielding ‘big data‘ as you’ll get. Lots of small observations over time will produce a lot of data. Sensemaking is a means of identifying potential patterns and meanings in the data, but even then there can be times when it’s hard to make sense of things. Using visual methods such as sketching, map making, and creative visualizations can help, tool. Visualizations allow people to abstract from one concept to the next and literally allow people’s attention to get on the same page. Tools like a gigamap can map and model a problem and potential solutions. Attractor maps can also include different elements that represent certain properties, feelings, experiences, observations and other data and put them together.

The timing of all of these activities is highly dependent upon the complexity and dynamism within the program domain. For example, a 12-week program aimed at educating individuals might have a lot of dynamism in it from week-to-week, enough that weekly check-ins and tri-weekly or monthly sensemaking sessions might be required. However, if the work being done is a collective impact model looking at advocacy for a major policy change, the activities and actions might be more long term. In that case, bi-weekly checkins and maybe quarterly sensemaking sessions are needed.

Mindfulness is a very powerful tool when employed in a developmental evaluation. Creating spaces and practices that allow people to mindfully reflect on their work, capture it and organize it can be a way of collecting data on and detecting subtle, evolving patterns of activity that are the hallmark of complex systems and programs.

Good luck. Be mindful.

The Survey Engagement Dividend

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amsterdamsign
Engaging with your products, people and places

Wouldn’t you love to know how you customers, clients, constituents or colleagues think about an issue of importance so that you can use their position to help inform design of your services or validate the choices already made?

For those looking for this kind of data they are probably thinking of using a survey of some sort. You know the survey, it’s something that you’ve probably been invited to complete at least once in the last week (maybe the last hour); and that is part of the problem.

Use an app for more than a few times and you’ll likely get a question about whether you like it and whether you will rate it on the iTunes Store or Google Play. Rent a car, stay at a hotel, take a plane/train/bus trip, buy something online, visit an attraction, or even visit a health centre and there is a very good chance that, if someone connected to that transaction has your contact information, you will be asked for your opinion and to rate the experience. Polling, or the use of surveys to determine voter preferences or public opinion on a variety of issues, is used to illustrate the ‘mood of the public’ and guide political decision making.

In a commentary in the New York Times, professor of public policy Jeff Zukan describes the situation as dire for those seeking to make political decisions based on current polling data.

Evaluation research (pdf) continues to point to an overall decline in response rates over time although recent research from Japan suggests that valid response data can still be obtained from small response rates, but that it remains sub-optimal.

In short: it’s getting harder to get responses to a survey and that is casting doubt on the validity of the data that is being generated.

Going from passive surveys to active engagement

Part of the problem is the sheer volume of surveys being deployed in the world. There was a time when a survey was a unique thing to encounter, something done through the census or perhaps through the decision to participate in a research study at a university or hospital. Research was also done by trained professionals for professional purposes that were made obvious to the respondent (e.g., contributing to scientific knowledge). Now that has shifted to include a panoply of reasons from guiding product marketing to quality improvement to scientific research and often to no obvious destination by people who know little about the scientific basis for survey methods.

Easy to deploy survey creation tools such as Google Forms or through Facebook or even Twitter allow anyone to develop and distribute a survey to a nearly unlimited number of people.

But just because you can survey doesn’t mean you should or that it is worthwhile. Here are some tips to increase the utility of your surveys, get better data and better response rates while doing more for your organization at the same time:

  1. Engage your community/clients/potential respondents early. We worked with the folks at Eat Right Ontario to see how to improve the feedback process on new health promotion materials using surveys and we found that the organization’s Facebook group was a place where people had already self-selected as being interested in the subject matter. In a study published earlier this year, we demonstrated that we could get data of similar quality, quantity and utility drawing on this engaged population than we could if using a personalized, face-to-face approach (which is often the gold-standard for recruitment).
  2. Make it simple and to the point. Ask questions that are clear, direct and to the point. Make the survey clearly relevant to the participants. If you are asking questions about some underlying hypothesis that doesn’t seem obvious to the participants, they will see less relevance in it and will be less likely to complete the survey. You have a limited amount of attention time; use it wisely
  3. Ask only what you can use. Related to the previous point, there is a tendency to think that because you’re doing a survey that you need to ask certain questions like demographics for example. However, if you have no perceived need for the data, don’t ask. Sure, you might find a reason down the road, but if you can’t think of one now it’s less likely you’ll need this information. For example, we designed a survey for a client looking to get feedback on their network and advised against any demographic data because there was no obvious need for it on their part because no matter what the responses were they were not in a position to use it for anything. Thus, asking things like age, gender or location didn’t matter and would only put people off as it makes data that was meant to be impersonal and anonymous more personal and more risky.
  4. Tell them the story of the data when you’re finished. Share what you learn so that your participants can learn with you. Giving back the data invites engagement, creates transparency, and fosters accountability. Many reasons people disengage from surveys is that they believe the data isn’t going to be used. By not only showing the data, but also what you learned from it and did with it, you create a trust for future participants to engage with you on future projects.

These four tips can help you get people interested in your survey and increase the likelihood that they will respond to the questions you ask. After all, that is the reason you want to do a survey in the first place.

If you need support developing data collection strategies for your organization, contact us and we’d be happy to discuss survey development or many other methods that can help you get the right information at the right time.

Unpleasant Design

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Fall_Bench_Snapseed

Much of what we speak of when we talk about design, products and space is making things more livable, attractive or delightful. But what happens when we want the exact opposite to happen? That is the concept behind Unpleasant Design. The term comes from work being done by Gordan Savičić and Selena Savić who have been curating examples of the way governments and business alike have sought to discourage behaviour rather than encourage it through design choices.

The team at 99% Invisible recently profiled this work drawing on examples of how design has been used to discourage things like homeless people sleeping on benches, kids loitering around a shop, or ‘unintended uses’ of public washrooms.

The hallmark object to define this way of designing for non- or limited use is the Camden Bench, named after the London-based council that commissioned the original. You might have seen these in places you’ve travelled. They are these weirdly angular, almost always uncomfortable, and barely functional slabs that serve as benches. But unlike the one pictured above, they are pretty much impossible to use as a bed if you don’t have one, which is exactly its point.

Unpleasant design represents an illustration of design’s power for multiple purposes and not always good. While these designs address certain problems that are posed by behaviours that some find undesirable, they speak to a larger role that design can play in social life. Another example of unpleasant design is not about what’s designed into something (such as spikes), but also what’s designed out of something. One example is the presence of ‘leaning benches’ to replace places to sit. Another is the absence of water fountains in public spaces. The latter is less about providing hydration to people, but more about getting them to buy water rather than take it for free.

Design is as much about what is invisible as it is visible, which is why the brilliant podcast 99% Invisible is such an appropriate name for a show dedicated to looking the often un-noticed ways we shape the world and how it shapes us.

Photo credit: Fall by Clive Powell under Creative Commons License and adapted for use.

The Experimentation Myth

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Innovation Growth Lab: Making innovation and growth policy work from Nesta UK on Vimeo.

The world of social innovation is filled with wonderful things and, like any creative space, has its share of myths. One of these is the role of experimentation. One view is that social innovation operates in such a space of complexity that the use of methods such as randomized controlled trials are not only inappropriate, but harmful.

The alternative perspective is one held by folks like Geoff Mulgan, the Chief Executive of Nesta UK. According to Mulgan (discussed in the video embedded above):

the only way you figure out what works is by doing experiments using control groups and seeing who benefits from an intervention.

This latter position is also a myth. Like any myth, it makes complexity much easier to handle and accept because it takes away the need to invest energy in determining ‘what is going on’.

Alas, that ‘what’s going on’ is at the crux of understanding impact in the realm of social enterprises, because we humans have a tendency to resist standardization in how we behave. This is not to suggest that there is no place for experiments, because as Nesta UK and others have shown, it can be done. But to suggest that the only way to find out whether something works is experimentation is taking things too far.

To be fair, Mulgan was speaking on matters of public policy, which have enormous consequences and his comments after the quote above about understanding potential impact before scaling are spot-on, but there are different paths to understanding how impact is achieved and what it is that go beyond experiments.

Disrupting experiments

A true controlled experiment, as the name suggests, requires control. The one way to get around some of the constraints imposed by controls are to have large numbers of participants. The problem facing the controlled experiments is that we often do not have both — either control or large numbers of participants. Further, the amount of control needed is dependent on the amount of social complexity inherent in the problem. For example, imagine comparing two options: renewing a required document like your drivers licence online or in person. This is a process that might involve a lot of effort (depending on where the nearest location of your motor vehicle registration office is), but it’s not complex. This is something that is amenable to experimentation.

However, a policy or program designed to help individuals manage chronic disease conditions involves enormous complexity given that each participants’ condition will have a combination of shared qualities with unique manifestations and that those will all be mediated by different social, biological, economic, geographic and situational variables that, depending on the chronic condition, might play a significant role in how a program is received and its impact.

This is a far more challenging task, but one that is worth doing lest we, in the words of systems scholar Russell Ackoff, do “the wrong things, righter” by imposing an experimental design on something that warrants something different. Or, put another way, perhaps we need to redesign the experiment itself to suit the conditions.