Social Media and Health: Leaders(hip) and Followers(hip)

Posted: May 18, 2012 | Author: | Filed under: behaviour change, eHealth, health promotion, innovation, public health, Social media, systems thinking | Tags: , , , , , , , , , , , , , , , , , | Leave a comment »

Social media is finally catching on with healthcare, public health, and  health promotion. With a few recent articles published in the academic literature to rest on, academic health sciences has finally (and I might argue, begrudgingly) conceded that 900+ million users and $100B valuations (Facebook), and thousands of messages exchanged every milisecond (microblogs like Twitter and Sina Wiebo) might have some value for the public beyond entertainment.

If you note how long it took the health sector to start using the telephone as a serious means of engaging their patients or the public, this is lightning-quick adoption. Still, the barriers to adoption are high and the approach to using the technology is scattered. Indeed, just like the start of Internet-delivered telehealth (or cybermedicine (PDF), which has now evolved into eHealth), there is a mad rush to get liked, followed or some other metrics that most health professionals barely understand.

And that is part of the problem.

Meaningful Social Media Metrics

What is a meaningful metric for social media and health? A recently published article in Health Promotion Practice suggested four metrics that are taken from social marketing and applied to social media. These Key Performance Indicators (KPI’s) are:

  • Insights (consumer feedback)
  • Exposure (media impressions, visits, views, etc..)
  • Reach (# people who connect to the social media application)
  • Engagement (level of interaction with the content)

These are reasonable, but to to the uninitiated I would suggest a few words of caution and commentary to this list.

Firstly, the insights suggested by Neiger and colleagues “can be derived from practices such as sentiment analysis or data mining that uses algorithms to extract consumer attitudes and other perspectives on a particular topic” (p.162). While not incorrect, this makes the job sound relatively simple and it is not. Qualitative analysis + quantitative metrics such as those derived from data mining are key. Context counts immeasurably in social media use. It’s only in situations where social media is used as a broadcasting tool that gross measures of likes and sentiment analysis work with little qualification.

Even that is problematic. Counts of ‘likes’, ‘visits’, ‘follows’ and such are highly problematic and can be easily gamed. I am ‘followed’ on Twitter by people who have tens of thousands of followers, yet virtually no presence online. Most often they are from marketing fields where the standard practice is to always follow back those who follow you. Do this enough and pretty quickly you, too can have 23,000 followers and follow 20,000 more. This is meaningless from the perspective of developing relationships.

Engagement is the most meaningful of these metrics and the hardest to fully apply. This category gets us to consider the difference between “OMG! AWESOME!” and “That last post made me think of this situation [described here] and I suggest you read [reference] here for more” as comments. Without understanding the context in which these are made within the post, between posts (temporally and sequentially), and in relation to a larger social and informational context, simple text analysis won’t do.

Social Media Evidence: Problems and More Problems

One of the objections to the use of social media by some is that it is not evidence-based. To that extent I would largely agree that this is the case, but then we’ve been jumping out of airplanes with parachutes despite any randomized controlled trial to prove their worth.

Another article in Health Promotion Practice in 2011 highlights potential applications for social media and behaviour change without drawing on specific examples from the literature, but rather on theoretical and rhetorical arguments. An article published in the latest issue of Perspectives on Psychological Science highlights the current state of research on Facebook, which is timely given that its IPO is set for today. That review by Wilson and colleagues illustrates the largely descriptive nature of the field and offers some insight on to the motivation of Facebook users and their online activities, but rather little in what Facebook does to promote active change in individuals and communities when they leave the platform.

The answer to whether social media like platforms such as Facebook ‘work’ as methods of promoting change is simply: we don’t know.

Does social media provide support to people? Yes. Does it inform them? Yes to that too. Does that information produce something other than passive activity on the topic? We don’t know.

In order to answer these questions, health sciences professionals, evaluators, and tech developers need to consider not just followership, but leadership. In this respect, it means creating changes to the way we gather evidence, the tools and methods we use to analyse data, and the organizational structures necessary to support the kind of real-time, rapid cycle evaluation and developmental design work necessary to make programs and evidence relevant to a changing context.

As Facebook launches into its new role as a public company it is almost assured to be introducing new innovations at a rapid pace to ensure that investor expectations (which are enormous) are met. This means that today’s Facebook will not be next month’s. Having funding mechanisms, review and approval mechanisms, a staff trained and oriented to rapid response research, and an overall organizational support system for innovation is the key.

Right now, we are a long way from that. Hospitals are very large, risk averse organizations; public health units are not much different. They both operate in a command-and-control environment suited for complicated, not complex informational and social environments. Social media is largely within the latter.

Systems thinking, design thinking, developmental evaluation, creativity, networks and innovation: these are the keywords for health in the coming years. They are as author Eric Topol calls the dawning of the creative destruction of medicine.

The public is already using social media for health and now the time has come for health (care, promotion and protection) systems to get on board and make the changes necessary to join them.

Common Sense, Complexity and Leadership

Posted: January 23, 2012 | Author: | Filed under: complexity, social systems | Tags: , , , , , , , , , | Leave a comment »

Bye, Bye Common Sense

Great leaders are often ascribed traits that include ample common sense. But what passes for common sense is often a grab bag of miscellaneous, inconsistent ideas that are context dependent and less useful in the complex environments where leadership is called for most. 

common sense |ˌkɑmən ˈsɛns|

noun

good sense and sound judgment in practical matters: use your common sense | [ as modifier ] : a common-sense approach.

Today Research in Motion announced that its founder Mike Lazaridis and his co-CEO Jim Balsillie would be relinquishing their roles with the company. In their place, a ‘pragmatic, operational-type guy ‘was installed. Presumably, Thorsten Heins has the common sense to lead RIM after the founders lost theirs. Yet, the pragmatic, common sense that RIM is looking for might not be what they need given the complexity of the environment they are leading in.

Common sense is a false lure in complex systems. In his recent book, Everything is Obvious *Once You Know the Answer, social network researcher  and Yahoo! Research scientist Duncan Watts eloquently critiques the concept of common sense, illustrating dozens of times over how “common sense” doesn’t fare so well in decisions that go beyond the routine and into the complex. Indeed. the very definition of the term implies that the problems that common sense works towards addressing are relatively simple and pragmatic.

Certainly, navigating daily social conventions might lend itself well to what we might call common sense. Watts refers to sociologist Harry Collins’ term ‘collective tacit knowledge‘ that is encoded in social norms, customs and practices of a particular world to describe common sense. However, what becomes common is a byproduct of many small decisions, dynamic and flexible changes to perspective, an accumulation of knowledge gained from small experiments over time, and the application of all of this knowledge to particular, context-dependent, situations. This constellation of factors and its interdependent, contextual overlap is why artificial intelligence systems have such a difficult time mimicking human thought and action. It is this attention to context that is most worth noting for it is this context that keeps common sense from being anything but common:

Common sense…is not so much a worldview as a grab bag of logically inconsistent, often contradictory beliefs, each of which seems right at the time but carries no guarantee of being right any other time.

Watts goes on to argue:

Commonsense reasoning, therefore, does not suffer from a single overriding limitation but rather from a combination of limitations, all of which reinforce and even disguise one another. The net result is that common sense is wonderful at making sense of the world, but not necessarily at understanding it.

Thus, we often concoct a narrative about the way something happens that sounds plausible, rational and be completely wrong. Throughout the book, Watts shows how often mistakes are made based on this common sense approach to solving problems.

When it comes to RIM, some have pointed to the late Steve Jobs’ assertion that they would have difficulty catching up to firms like Apple given that the consumer market is not their strength, the enterprise market is. Yet, Steve Jobs didn’t let the fact that Apple was a computer company stop him from making music players (the iPod), mobile phones (the iPhone) or becoming book, music and movie vendors (iTunes). A read of Steve Jobs’ biography by Walter Isaacson reveals a man who was able to lead and be successful through what appeared to be common sense, yet was decidedly uncommon among media and technology leaders. That is why Apple is where it is and why so many other technology companies lag behind them or simply disappeared.

The reason is that common sense in leadership looks as simple in hindsight only, not in foresight or even in the present moment. This is one of the big points that Watts makes. He uses the example of Sony’s MiniDisc system that, when introduced, had all of the hallmark features of the innovations that Apple introduced (novel, high quality, portable, smaller, visible advantages over the alternatives), yet it was a spectacular failure. Canadian management consultant Michael Raynor has called this the strategy paradox. When qualities such as vision, bold leadership, and focused execution — all the commonsensical aspects of great leaders — are applied to organizations it can lead to great success (Steve Jobs and Apple) or resounding failures (RIM?).

Strategic flexibility, making small adjustments consistently, and imaging scenarios for the future in an ongoing manner are some of the potential ways to limit the damage from common sense (or use its advantages more fully). This requires feedback mechanisms and close monitoring of program activities, developmental evaluation, and a willingness to tweak programs and design on the go (what I call: developmental design) . It’s not a surprise that this incremental approach to development is consistent with the way change is best produced in a complex adaptive system.

By recognizing that common sense is less than common and is certainly not consistent, program designers, developers, evaluators and other professionals will be better positioned to provide true leadership that addresses challenges and complexity rather than adds to the complexity and creates more problems.

Photo: Goodbye to Common Sense Space by Amulet Dream from Deviant Art

The Complexity of Planning and Design in Social Innovation

Posted: January 7, 2012 | Author: | Filed under: complexity, design thinking, evaluation, Systems science, systems thinking | Tags: , , , , , , , , | 2 Comments »

The Architecture of Complex Plans

Planning works well for linear systems, but often runs into difficulty when we encounter complexity. How do we make use of plans without putting too much faith in their anticipated outcome and still design for change and can developmental design and developmental evaluation be a solution? 

It’s that time of year when most people are starting to feel the first pushback to their New Year’s Resolutions. That strict budget, the workout plan, the make-time-for-old-friends commitments are most likely encountering their first test. Part of the reasons is that most of us plan for linear activities, yet in reality most of these activities are complex and non-linear.

A couple interesting quotes about planning for complex environments:

No battle plan survives contact with the enemy – Colin Powell

In preparing for battle I have always found that plans are useless, but planning is indispensable – Dwight D. Eisenhower

Combat might be the quintessential complex system and both Gens Powell and Eisenhower knew about how to plan for it and what kind of limits planning had, yet it didn’t dissuade them from planning, acting and reacting. In war, the end result is what matters not whether the plan for battle went as outlined (although the costs and actions taken are not without scrutiny or concern). In human services, there is a disproportionate amount of concern about ‘getting it right’ and holding ourselves to account for how we got to our destination relative what happens at the destination itself.

Planning presents myriad challenges for those dealing with complex environments. Most of us, when we plan, expect things to go according to what we’ve set up. We develop programs to fit with this plan, set up evaluation models to assess the impact of this plan, and envisage entire strategies to support the delivery and full realization of this plan into action. For those working in social innovation, what is often realized falls short of what was outlined, which inevitably causes problems with funders and sponsors who expect a certain outcome.

Part of the problem is the mindset that shapes the planning process in the first place. Planning is designed largely around the cognitive rational approach to decision making (PDF), which is based on reductionist science and philosophy. Like the image above, a plan is often seen as a blueprint for laying out how a program or service is to unfold over time. Such models of outlining a strategy is quite suitable for building a physical structure like an office where everything from the materials to the machines used to put them together can be counted, measured and bound. This is much less relevant for services that involve interactions between autonomous agents who’s actions have influence on the outcome of that service and that result might vary from context to context as a consequence.

For evaluators, this is problematic because it reduces the control (and increases variance and ‘noise’) into models that are designed to reveal specific outcomes using particular tools. For program implementers, it is troublesome because rigid planning can drive actions away from where people are and for them into activities that might not be contextually appropriate due to some change in the system.

For this reason the twin concepts of developmental evaluation and developmental design require some attention. Developmental evaluation is a complexity-oriented approach to feedback generation and strategic learning that is intended for programs where there is a high degree of novelty and innovation. Programs where the evidence is low or non-existent, the context is shifting, and there are numerable strong and diverse influences are those where developmental evaluations are not only appropriate, but perhaps one of the only viable models of data collection and monitoring available.

Developmental design is a concept I’ve been working on as a reference to the need to incorporate ongoing design and re-design into programs even after they have been initially launched. Thus, a program evolves over time drawing in information from feedback gained through processes like evaluation to tweak its components to meet changing circumstances and needs. Rather than have a static program, a developmental design is one that systematically incorporates design thinking into the evolutionary fabric of the activities and decision making involved.

Both developmental design and evaluation work together to provide data required to allow program planners to constantly adapt their offerings to meet changing conditions, thus avoiding the problem of having outcomes becoming decoupled from program activities and working with complexity rather than against it. For example, developmental evaluation can determine what are the key attractors shaping program activities while developmental design can work with those attractors to amplify them or dampen them depending on the level of beneficial coherence they offer a program. In two joined processes we can acknowledge complexity while creating more realistic and responsive plans.

Such approaches to design and evaluation are not without contention to traditional practitioners, leaving questions about the integrity of the finished product (for design) and the robustness of the evaluation methods, but without alternative models that take complexity into account, we are simply left with bad planning instead of making it like Eisenhower wanted it to be: indispensable .

Systems Thinking and the Design of Empathy

Posted: September 22, 2011 | Author: | Filed under: complexity, design thinking, systems thinking | Tags: , , , , , , | Leave a comment »

Leadbeater's Systems Thinking - Empathy Grid

Scalability is an issue that faces practitioners in systems and design. How do we design systems at scale and if so, what might they look like.

Charles Leadbeater has been on a mission to find ways to make large organizations — particularly those in the social sector – more innovative. Leadbeater, like many social innovators, is hard to pin down to a single title or role. He is at once a researcher, a designer, a systems thinker, and a urbanist. Like most innovators, all and none of these descriptors truly fit.

Leadbeater was in Toronto earlier this week to speak on the issue of innovation in cross-sector collaboration for public good at the MaRS Discovery District. If you’ve seen Leadbeater speak (consider the talks on TED here or elsewehere), you’ll know that you’re in for some English-style self-depricating humour alongside of much about the manner in which people engage in change actions within a system. You’ll also get a lesson in social design, the kind that Victor Papanek advocated for.

To my delight, Leadbeater did not disappoint. Unlike other talks, the value came less from a focused “take home message” and more in a way of conceiving social systems through the combined lens of systems and design thinking (my terms, not his). At the heart of his talk was the challenge we face with building systems and empathy at scale. When things interact, eventually they become understood within a set of boundary conditions and interact, thus making a system. The system in turn begins to establish rules (or rather, the rules determine the system). These emergent properties thus shape the way the system operates or, in social situations, governs or guides the actions of those within it.

The problem is that at certain scales the very factors that create positive social relations, that is those that yield tangible emotional, resource, or informational benefits for one or more parties, get warped under the changes in that scaling. Thus, we have the countless stories of a beloved small business grown in a confined community that becomes a multinational corporation and, in doing so, loses the intimacy and connection to its customers in the process. Companies do this, government organizations show this, and so do cities.

The more one designs for the humans within the system in ways that create meaningful engagement, the greater the empathy. Yet deep empathy is often founded upon intimacy, which is something that is difficult to scale. Leadbeater illustrates the various ways in which firms and cities have addressed this on the graph above. In each case, there are examples that fit. In business for example, there is Ryanair, which embodies a highly structured system with low empathy (top left corner).  Opposed to that is the local farmer’s market where one gets to know their grower, experience high mutual empathy, but in a manner that is unique, idiosyncratic and non-systematic in most ways. The challenge is how to design organizations at  scale from the cosy-ness of the Farmer’s Market without becoming a Ryanair.

It struck me that the food service industry might be one of the areas where the scalability can be achieved. For example, Starbucks is a gigantic corporation with shops worldwide, yet it still manages to create a very homey, local feel at each one. In the mornings I go to the gym I stop by a location to get a smoothie and my server always remembers my order. At the location near where I take classes, they gave me a free drink because they couldn’t get the computer to take off my 10 cent reusable cup discount. In each location, the benefits were not just in customer service, but in the chit-chat and relationships that I develop with the staff. It’s not like I am speaking to owner-operators at some of the great independent coffee shops around my city, but it is close.

The Starbucks experience was thought through, intentional and thus, by design. We can do this with other systems. The key is whether or not the systems themselves are aware enough to know when they have, indeed, become systems. Starbucks today could not be empathic in exactly the same way as it was when it was a one-shop place at Pikes Market in Seattle. But it can create something similar, which is parallel to Simon’s notion that design is about the science of the artificial.

I’ve been developing and advocating for an approach to creating scale — in time and scope — that I call developmental design. A developmental design approach means shifting and changing over time and designing things in a manner that adjust to the complexities associated with dynamic systems. It brings together complexity, systems, design and the detailed feedback mechanism that comes through developmental evaluation. Leadbeater’s grid helps add to this concept by giving a focus to the development, from one level of empathy to another and one systemic scale to another.

Through thinking in systems and acting through design, perhaps then we can create the kinds of services and organizations that respond to the challenges we face.

And designing for empathy will help us know when we’ve achieved it.

Design Thinking and the Metaphors of Science

Posted: August 28, 2011 | Author: | Filed under: complexity, design thinking | Tags: , , , , , , | 3 Comments »

The Chemistry of Creation

There is a certain way in which things come together to create a successful design (or relationship) that is often chalked up to “chemistry”. But design chemistry could mean something both literal and evolving just like biological organisms if we take the concept to its fullest. 

Metaphors are commonly used in tackling complex problems. The uniqueness of the situation, the level of detail of the manner by which the influencing factors coalesce, and the multidisciplinary ways of seeing the problem in the first place all present a problem of language, thus using oblique comparators can often fill the gap.

Science and mathematics have the advantage of being closer to ‘universal’ languages than many of the other forms of communication we share as a species (Leibniz’s ideas notwithstanding). They are less (not completely) influenced by cultural variations and local differences and can be shared globally. It is for this reason that the the prospect for a means of communicating concepts like design through science has appeal. As Andrea Yip has pointed out, design itself can be transformed into chemistry using the periodic table as a guide to serve as a more universal metaphor for understanding the way design thinking is experienced and practiced.

Chemistry is the study and creation of the bonds of the universe. More specifically, it is:

the science of matter, especially its properties, structure, composition, behavior, reactions, interactions and the changes it undergoes.

As a metaphor for design thinking it works beautifully. Through the Periodic Table of Design Thinking we see an attempt to lay out the properties of design thinking, map out the structure and explain their composition. Through practice and reflection we will see how these compounds play out in the design process.

Another scientific metaphor that takes up the charge from where chemistry leaves off is from developmental biology:

 the study of the process by which organisms grow and develop

In the case of this metaphor, design thinking is the organism. Just as an organism, made of chemical compounds interacting over time, evolves, so too does the design process and the thinking that comes with it. In this case, metaphors like those proposed by Ms Yip and the concept of developmental design fit harmoniously.

Designing for and with complexity requires attention to a dynamism that can be lost if one takes the approach that product development happens at only stage of its life cycle. For many products this might be appropriate, but it falls short when we describe social design issues such as creating policies or social programs such as those found in health and education. I’ve referred to this concept as developmental design. Developmental design, like developmental evaluation, implies an evolved, dynamic approach to generating knowledge or outcomes and while I only loosely conceived of it in a way that matched developmental biology, it may be time to revisit that more intently. Designing developmentally means working through the design process on an ongoing basis, like perpetual beta in the software industry. It means evolving strategies for adaptation rather than solving problems because true solutions to wicked problems are often more dream than reality.

Taking the chemistry metaphor, it means that the ingredients, dosage and combinatorial mixes change over time in the production of a new compound or design. They may require catalysts — such as the inclusion of new perspectives or a particular discipline — to provoke certain reactions and move ideas into new space. It may also involve the same type of intervention from the designer to bring these chemicals to life. The chemist is not removed from her creation.

All of these are metaphors, yet they provide us with a means of taking the messiness of the language, something discussed in previous posts, to a new place until we can find the language that is most appropriate. Until that time, science might offer one of the better means of conveying design, complexity and the creativity that comes when we apply them both to generating products and services.

Photo Chemistry! by matfred used under Creative Commons Licence from Flickr.

Developmental Thinking and Evaluation

Posted: June 20, 2011 | Author: | Filed under: evaluation, innovation, research | Tags: , , , , | 1 Comment »

Think developmentally before evaluating developmentally

Developmental evaluation is difficult to initiate, largely because the thinking behind it is so foreign to normal program planning and reporting. It appears that developmental thinking needs to be in place before one can hope to implement a DE project successfully.

Over the next few days I will be meeting with colleagues working with the Social Innovation Generation Group, Michael Quinn Patton  and others who share an interest and wrestle with developmental evaluation (DE) in practice.

Over the course of the last year we have been meeting monthly to discuss our experiences, challenges and learning on the issue of developmental evaluation. Although our group members come from diverse fields — government, academia, non-profit and others — and are focused on projects that range in scope, we all share one common experience: frustration with implementing DE.

Reading through a case study the other night I couldn’t help be see something I’d seen before: the principal barrier to the implementation of DE is that the program, its partners, or the stakeholders associated with the program didn’t individually or collectively function in a manner that supported DE. Whether they actually bought into DE in the first place is also not known, but it seems to me that the two are related.

Developmental thinking about social issues has shown itself in my work to be a linchpin for any progress on developmental evaluation. Commiserating with colleagues in this area, it seems evident to me that assessing for DE is a critical step in the pre-work that needs to come before any evaluation takes place. Without developmental thinking, developmental actions and evaluation is hard to reasonably achieve.

If you do not see your program as one that evolves, but rather just gets bigger, better, stronger, weaker etc.., having real-time evaluation tools will be less useful or perhaps even harmful in the absence of a thinking framework to make sense of the data. Real-time, consultative evaluation, and its utilization-focused actions makes DE stand apart from other approaches to evaluation, even if the methods and tools are similar.

The implications for this assertion in practice are enormous. It means that a DE practitioner cannot be just an evaluator or at least must find others that can work with a program to educate, inspire and contemplate collaboratively about developmental thinking and what it means for a program. It also brings the evaluation function far closer to program planning than evaluators (and program planners) might be used to. It also means holding a willingness to think different, not just implement different thinking. To that end, knowledge of motivation and some sense of how one provokes or creates space for change is also important.

Taken together, we have ourselves a real challenge. The “core competencies” for DE already include qualities like people skills, knowledge of complexity, and communication skills (in addition to fundamental skills in evaluation methods and process implementation), but now we are adding additional ones. Systems thinking, behaviour change, program planning and design are all reasonable skills that would assist an evaluator in doing this work. Nice in theory, but how about in practice? Can we reasonably expect that there are enough people out there with these skills to do it well? Or is this a call for more of a team-science (or rather, team evaluation) approach to evaluation?

 

 

 

 

Thinking Developmentally About Social Issues

Posted: June 4, 2011 | Author: | Filed under: Education & Learning, innovation, systems thinking | Tags: , , , , , , , , | 1 Comment »

Thinking About Development or Being Consumed By Linear Progress?

An often unstated assumption in efforts to provoke change in complex, developmental environments is that people are primed to think in those terms. That might be  a false assumption and the reason why concepts like developmental evaluation are so hard to take root. 

Difference is hard to grasp. So too, is development. Add the two together and you have a real problem. This is an opinion I’ve formed through my work in complexity science, education and health promotion.

We humans are great at categorizing things. Our eyes are in the front of our head and our bodies are designed for forward movement so we are biologically positioned to look forward. Over the last few centuries, forward has often been linked with progress. Forward imposes a directionality to it and progress imposes an evaluative standard. But what if what we were dealing with in social issues had neither of these assumptions proven right?

Romantic relationships provide an example. Classic literature to pop culture typically present relationship narratives as linear (e.g, characters meet, date, fall in love, get married, buy a home, have kids, grow old together…), which has the effect of imposing an enormous burden of expectation on society that seems out of sync with the manner in which we live as human beings. Why can’t relationships come into being, intensify, draw back, morph, fade and grow simultaneously?

There are many healthy relationships out there and the one described above might only be one example rather than the standard. The problem is that we seek to create standards — best practice – and impose these standards when they might be ill-fitting to the circumstances or context. They don’t take into account development or contextual differences, nor do they appreciate complexity.

We do this with education too, assuming that people all learn the same way. Consider the absurdity of lumping all kids together in grades based on age. Is it reasonable to assume that because you and I were born the same year that we will learn content and evolve our knowledge base about the world in the same way? We put kids (and adults — even graduate students) in rows and talk at them for hours hoping that they will all absorb knowledge and do the same thing with it. That might explain why many students struggle and teachers get frustrated.

Thinking developmentally means attenuating oneself to nuance, punctuated learning, ongoing feedback, and inconsistent behaviour. I don’t blame people for wanting to impose a simple cause-and-effect narrative on the world, but doing so doesn’t mean its useful. As I’ve argued elsewhere, unless we consider changing our thinking we may continue to spend time devising ways to do what systems thinker and management leader Russell Ackoff called “the wrong things, righter”.

It is one thing to complain about this, but another to do it. And it is here that the lens needs to be turned back on us systems thinkers and developmental evaluators or designers. Perhaps it is time to stop assuming that people think this way and shift it towards assuming the converse, yet adding that people have the capability to think this way. Of course many will surprise us by already thinking in terms consistent with development and find it very comforting, but that exception will delight us rather than inspire frustration at the thought of “why doesn’t everyone else think like this?”

With so many social narratives that point towards linear thinking about the world we should not be surprised when we find something akin to psychologist Abraham Maslow‘s often paraphrased sentiment:

When the only tool you own is a hammer, pretty soon every problem resembles a nail

A developmental perspective on things, supported through concepts like design thinking, systems thinking, and creative education and learning is something that isn’t standard in our work, but perhaps should be. Building these muscles, much like a good personal trainer does with his or her client, requires attuning oneself to where a person is at and what kind of space they are in to work.

As this 30-day blogging challenge exploring social innovation, design and creativity continues so too will this discussion. It will be, developmental.

 

 

 

** Photo titled dimensional change by alasis used under Creative Commons license from Flickr

Developmental Design and Human Services

Posted: March 2, 2011 | Author: | Filed under: behaviour change, complexity, design thinking, evaluation, innovation, public health, research, Social media | Tags: , , , , , , , , , | 5 Comments »

The ever-changing landscape

One of the principal challenges for program evaluators and researchers is overcoming design limitations imposed by programs that fail to account for time and development. What might it look like if we took this path and what does it mean to engage in developmental design?

If you are like me, climate change scares you. I live in Canada, so in some ways (particularly these cold winter days), the thought of having the season be a little warmer has some appeal. But complex systems don’t work quite that way as there are intense costs projected with the privilege of having more days of the year wearing a light jacket or shorts than an overcoat or parka. What makes climate change an interesting example from the perspective of service programming, design and evaluation is that it provides a look at a real-world way to conceive of development over concepts like improvement and takes change in a whole new direction.

Humans are rather paradoxical creatures in that we are both attuned to moving forward (consider the design of the body: everything is oriented to one direction) and a perfect example of a developmental system.

A developmental system is one that evolves and adapts to changing inputs and transforms itself over time as more information is added to it (i.e., it is a complex adaptive system). From a programming standpoint, it means things don’t “get better” or “improve” per se — those are value judgements places by us — but rather, they build adaptive capacity.

Concepts like developmental evaluation, introduced and discussed in this space before, are ways to respond to this from an evaluation standpoint. DE provides a method of feedback generation that can enable programs to adapt and evolve by using the principles of complexity science with program evaluation methods to create a platform to detect and monitor emergent conditions and support innovation. And while there are some questions to ask of a program to see if it is suited to a developmental evaluation, we often forget to ask whether the program was designed to develop in the first place. What if we placed that at the centre of our discussion and started with development in mind?

My previous post looked at designing for time and space, but designing for development takes this one step further. Social media and technology-delivered program spaces provide an example of an environment where development is most obvious. Facebook was designed to expand and evolve, although one might challenge how well they’ve really developed. If you consider how effective, long-lasting software and services survive, they develop over time. In some cases, this development was designed into the process. Many open source software platforms are designed with this in mind — the Firefox browser and even Google’s Chrome are examples of tools that were built to be developed on. The originators designed  the basic foundation with the idea that they would evolve into something else.

This doesn’t happen very often with human services. There are few programs that are designed with development in mind. When it is acknowledged that things will change, it is done so reluctantly. Program in this context refers to any organized effort to change behaviour and produce products for human need. In public health, the further irony is that programs aimed at changing behaviour — whether it is supporting healthy eating, smoking cessation, mental health promotion or others — are often designed with rigid controls built in. We develop manuals, create ‘best practice guidelines’, amass evidence and create toolkits that can be applied to any circumstance, without attention to context or adaptation.

Indeed, when you relax these controls, many get concerned.

Having conducted a few social media trainings and presentations over the years, the most consistent question I am asked by those in public health is: how do I control the message. The answer is: you don’t. This can lead to questions about evaluation, which gets into problems of research design and trusting the findings, because research typically applies rigid controls for quality assurance.

With social media, what can be done is to use a process of developmental design by engaging with the audience/client/public in an authentic manner with the explicit thought that the program that launches today will not be the one that people engage with in a year, or a month or sooner. Support this evolution through developmental evaluation (which I would include as a part of the developmental design process) and you’ll have a feedback mechanism that encourages shifts over time.

Developmental design takes into account the complexity of the environment in which a product or service takes place and enlists a continued process of engagement with stakeholders over time — a true relationship (which is why social media can serve as a good example). Rather than take a static design brief, a living design brief would be used and constantly revisited and tweaked over time. Paying attention to changes in the brief over time would also enable program developers to detect weak signals that could precede large shifts in behaviour and potentially support strategic foresight and planning. Developmental design, as I’ve conceived of here, is attuned to complexity and innovation in human systems and designs for it and adapts with it, rather than assuming the opposite.

Applying developmental design may get us past the inevitable square-peg-round-hole problem that many evaluators, program planners and policy makers find themselves in as they seek to get greater value from their programs and demand more return on their investments. Evaluation and research is sought as the means to do it and with programs designed for evolution from the start, perhaps we won’t be surprised when the metaphorical ice sheets start to fall apart (as seen above) and see it as a developmental step to a new reality.

** Photo Nature Antarctica 17 by Christian Revival Network used under Creative Commons Licence.

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