Category: innovation

innovation

Acting on Failure or Failure to Act?

3100602594_ce7a92e966_o

Who would have thought that failure would be held up as something to be desired just a few years ago? Yet, it is one thing to extol the virtues of failure in words, it is quite another to create systems that support failure in action and if the latter doesn’t follow the former, failure will truly live up to its name among the innovation trends of the 21st century. 

Ten years ago if someone would have said that failure would be a hot term in 2014 I would have thought that person wasn’t in their right mind, but here we are seeing failure held up as an almost noble act with conferences, books and praise being heaped on those who fail. Failure is now the innovator’s not-so-secret tool for success. As I’ve written before, failure is being treated in a fetishistic manner as this new way to unlock creativity and innovation when what it might be is simply a means reducing people’s anxieties.

Saying it’s OK to fail and actually creating an environment where failure is accepted as a reasonable — maybe even expected — outcome is something altogether different. Take strategic planning. Ever see a strategic plan that includes failure in it? Have you ever seen an organization claim that it will do less of things, fail more often, and learn more through “not-achieving” rather than succeeding?? Probably not.

How often has a performance review for an individual or organization included learning (which is often related to failure) as a meaningful outcome? By this I refer to the kind of learning that comes from experience, from reflective practice, from the journey back and forth through confusion and clarity and from the experimentation of trying and both failing and succeeding. It’s been very rare that I’ve seen that in either corporate or non-profit spaces, at least in any codified form.

But as Peter Drucker once argued: what gets measured, get’s managed.

If we don’t measure failure, we don’t manage for it and nor do our teams include failure as part of their core sets of expectations, activities and outcomes and our plans or aspirations.

Failure, mindfulness and judgement

In 2010 post in Harvard Business Review, Larry Prusak commented on the phenomenon of measurement and noted that judgement — something that comes from experience that includes failure — is commonly missing from our assessments of performance of individuals and organizations alike. Judgement is made based on good information and knowledge, but also experience in using it in practice, reminding me of a quote a wise elder told me:

Good judgment comes from experience, but experience comes from bad judgment.

One of the persistent Gladwellian myths* out there is that of the 10,000 hours rule that suggests if we put that amount of time into something we’re likely to achieve a high level of expertise. This is true only if most of those 10,000 hours were mindful, deliberate ones devoted to the task at hand and involve learning from the successes, failures, processes and outcomes associated with those tasks. That last part about mindful, reflective attention or deliberate practice as the original research calls it (as so many Gladwellian myths suffer from) is left off of most discussions on the subject.

To learn from experience one has to pay attention to what one is doing, what one is thinking while doing it, and assessing the impact (evaluation) of that action once whatever is done is done. For organizations, this requires alignment between what people do and what they intend to do, requiring that mindful evaluation and monitoring be linked to strategy.

If we follow this lead where it takes us is placing failure near the centre of our strategy. How comfortable are you with doing that in your organization?

A failure of failure

Failure is among the most emotionally loaded words in the English language. While I often joke that the term evaluation is the longest four-letter word in the dictionary, failure is not far off. The problem with failure, as noted in an earlier post, is that we’ve been taught that failure is to be avoided and the opposite of success, which is viewed in positive terms.

Yet, there is another reason to question the utility of failure and that is also related to the term success. In the innovation space, what does success mean? This is not a trivial question because if one asks bold questions to seek novel solutions it is very likely that we don’t know what success actually looks like except in its most general sense.

A reading of case studies from Amazon to Apple and Acumen to Ashoka finds that their success looks different than the originators intended. Sometimes this success is far better and more powerful and sometimes its just different, but in all cases the path was littered with lessons and few failures. They succeeded because they learned, not because they failed.

Why? Because those involved in creating these ‘failures’ were paying attention, used the experience as feedback and integrated that into the next stage of development. With each stage comes more lessons and new challenges and thus, failure is only so if there is no learning and reflection. This is not something that can be wished for; it must be built into the organization.

So what to do?

  • Build in the learning capacity for your organization by making learning a priority and creating the time, space and organizational support for getting feedback to support learning. Devoting a small chunk of time to every major meeting to reflecting back what you’re learning is a great way to start.
  • Get the right feedback. Developmental evaluation is an approach that can aid organizations working in the innovation space to be mindful.
  • Ask lots of questions of yourself, your stakeholders, what you do and the systems you’re in.
  • Learn how to design for your particular program context based on feedback coming from the question asking and answering. Design is about experimenting without the expectation of immediate success.
  • Develop safe-fail experiments that allow you to try novel approaches in a context that is of relatively low risk to the entire organization.

There are many ways to do this and systems that can support you in truly building the learning capacity of your organization to be better at innovating while changing the relationship you have with ‘failure’.

For more information about how to do this, CENSE Research + Design offers consultation and training to get organizations up to speed on designing for social innovation.

 

* Refers to ideas popularized by journalist and essayist Malcolm Gladwell that are based on the scientific research of professionals and distilled into accessible forms for mass market reading that become popular and well-known through further social discussion in forms that over-simplify and even distort the original scientific findings. It’s a social version of the “telephone game“. The 10,000 hour ‘rule’ was taken from original research by K. Anders Ericsson and colleagues on deliberate practice and is often discussed in the context of professional (often medical) training, where the original research was focused. This distortion is not something Gladwell intends, rather becomes an artifact of having ideas told over and again between people who may have never seen the original work or even Gladwell’s, but take ideas that become rooted in popular culture. A look at citations on failure and innovation finds that the term deliberate practice is rarely, if ever, used in the discussion of the “10,000 rule”.

 

Photo Credit: Project365Fail by Mark Ordonez used under Creative Commons license via Flickr. Thanks for sharing, Mark!

 

 

behaviour changeeducation & learninginnovation

Isolation: The New Innovator’s Dilemma

It's can be a long, lonely climb

It’s can be a long, lonely climb

 Innovators transform the world around them in big and small ways and while a successful effort can be lauded by pundits, politicians and the public there is a long road to making change happen. That road is also a lonely one and doing things different means more than just innovating and experiencing what it means to be resilient firsthand. 

Clayton Christensen’s seminal book The Innovator’s Dilemma has been one of the leading sources of thinking-inspriation in business and social innovation. The book reflects the challenges with those seeking to introduce new ideas, products or services into established markets (or ecosystems) in the aim of addressing both people’s present and future needs.

These innovators — change-makers — risk disrupting the very markets they seek to influence bringing uncertainty for everyone. What innovators bet on is that the changes they introduce will have wide-ranging, positive benefits even if they don’t fully know what those are before setting out. Not surprisingly, these efforts are not always welcome at first and the road toward understanding and acceptance is a long one.

Innovation means doing something new and while we like to talk about new, many don’t actually like doing ‘new’ because that means questioning and changing things. Indeed, change — profound change — in thinking is often vigorously opposed as Albert Einstein pointed out in a quote that is paraphrased as:

Great spirits have always encountered violent opposition from mediocre minds

This opposition is a challenge for anyone, but the long slog towards innovation is not only hard on the spirit, it is often a lonely path.

The lonely lives of leaders

To innovate means to lead through ideas and products. We live in a society that admires and elevates the innovators. No better or perhaps inspiring example is the 1997 advertisement from Apple as part of the Think Different campaign in the 1990’s.

What is missing from the platitudes, plaudits and celebrations is the quiet, often lonely, life away from the attention that successful innovations bring (nevermind those that are not deemed successful). To innovate is to lead and to lead is often to be lonely by definition because there are few leading and more following. This leadership by thought or action is often what makes leaders appear creative, innovative and — as Seth Godin affectionately calls being weird. A study discussed in the Harvard Business Review and dissected in Forbes pointed to high rates of loneliness among those at the CEO level, which is among those who “made it”. Consider those who haven’t yet “made it”, who haven’t had their idea “succeed” or take off and it might feel even more lonely.

At a recent workshop I conducted a participant expressed publicly a sense of gratitude for simply having the opportunity to connect with others who were simply open to seeing the world in the same way that they were. In hosting a learning workshop for social innovators a positive byproduct was that attendees who might have been isolated in their activities and thinking in one context could come together in another.

Innovation, because it is new, means that innovators have few peers available to directly commiserate with and may need to find ways to connect on idea, method, philosophy or role, but rarely something direct. That requires extra work in the search and more effort to connect in the finding, which takes time and energy — two things innovators are often short of.

But that doesn’t diminish the value and importance of time and energy and directing it towards efforts to reduce isolation.

Creating deep community

Paul Born, Director of the Tamarack Institute for Community Engagement, recently published a book on creating deep community connections as a necessary means of fostering transformative change. Born offers four pillars to a deepening community are:  1) sharing stories, 2) taking the time to enjoy one another, 3) taking care of one another, and 4) working together towards a bigger social goal.

While there is little to argue with here, these pillars rest on the ability to locate, co-locate and create the space to share, enjoy, care and collaborate in the first place. For many innovators this is the hardest part. Where do we find the others like ourselves and how do begin to frame this journey?

There is a reason that innovators have flocked to tools like the Business Model Canvas and the Lean Startup method to help people define, refine and develop their products and mission. It’s easy to point to firms like Apple as examples of clear-focused innovators now, but 20 or 30 years ago it wasn’t so clear. Apple’s overall mission and vision are easy to see lived out in hindsight, not at the beginning. A read of Steve Jobs’ biography illustrates how often his way of approaching the world clashed with nearly everyone and everything and how difficult life was for him.

But Steve Jobs happened to be challenging the world in a place that would come to be known as Silicon Valley. For the last thirty years the San Francisco bay area has been a spark for creative thinking and innovation, one of many hotbeds of business and cultural transformation that Richard Florida documented as home of the Creative Class(es). But not all innovation takes place in these centres and even within such centres it might be hard to connect when an idea is ill-formed or new. We lose out when innovation is only done in certain places by certain people.

(Social) innovators are part of a diffuse and sometimes lost tribe.

Troubled language

If you look at the language that we frame innovation we reveal many of the problems with not only our ideas, but what we do with them. As mentioned in previous posts, we privilege terms like creativity, but often ignore craft. We aspire to be learners, but often don’t like real learning. We tout the role of failure in design and innovation, yet our overloaded cultural baggage attached to the term prevents us from really failing (or asking such tepid questions we don’t really stretch ourselves).

Having access to social media and electronic communities offer a lot and something we didn’t have before, but its very difficult to forge strong, connective bonds mediated through a technological interface. Technology is good at initiating superficial connections or maintaining deeper connections, but not so good at creating deep connections. Those deeper connections as Paul Born points out are the things that sustain us and allow us to do our best work.

The dilemma is how to allocate time and resources in cultivating uniqueness, depth and connecting to similar innovators when that pool is small or integrating more with those in the convention system. Of course innovators need to relate to both groups at some level because an innovation doesn’t grow if we only connect to ‘true believers’, but at different stages it matters how we’re allocating our time, energy and enthusiasm particularly along that journey up Mt. Isolation.

Options

There is no ready answer for this problem. Indeed, the lonely path to being different, weird or constructively challenge the harmful or less effective parts of the status quo may be one of the most wicked ones innovators face.

For those interested in social innovation there are a few examples for those who want to find peers and connect:

  • The Tamarack Institute for Community Engagement (mentioned earlier) has different communities of practice focused on various aspects of community building and social innovation. They host events and have created a vibrant community of learners and action-oriented professionals across Canada and the United States;
  • LinkedIn has a number of topical groups that have evolved on a variety of social and innovation topics that include local, global and topical foci;
  • The Social Innovation Generation Group convenes formal and informal events connecting those working in the social innovation space in the Greater Toronto Area and across Canada;
  • Meetups are self-organized gatherings on virtually every topic under the sun in communities across the globe. Check out and see if there is something near you;
  • In Toronto and New York City, the Centre for Social Innovation is a part co-working space, social action community, and venture incubation support group that connects and enlivens the work that social innovators do. They have many events (many are free and low cost) organized by their members that seek to bring people together and offer skill development. If you’re in Ottawa, check out The Hub. In Calgary? Check out EpicYYC ;  In Vancouver, visit the great folk at the HiVE. Throughout the United States Impact Hub spaces offer innovators options to work and connect and in Cambridge, MA there is the amazing Cambridge Innovation Centre for innovation more broadly. MaRS in Toronto offers another option.
  • Lastly, CENSE Research + Design hosts a series of webinars and free and paid workshops to create capacity for social innovation. For more information visit: www.cense.ca/learning .

References:

Born, P. (2014). Deepening Community: Finding Joy Together in Chaotic Times (p. 216). San Francisco, CA: Berrett-Koehler Publishers.

Wheatley, M. (2006). Leadership and the New Science: Discovering Order in a Chaotic World (3rd. ed., p. 218). San Francisco, CA: Berrett-Koehler Publishers.

Wheatley, M. (2007). Finding Our Way: Leadership for an Uncertain Time (p. 300). San Francisco, CA: Berrett-Koehler Publishers.

Wheatley, M. (2010). Perseverance (p. 168). San Francisco, CA: Berrett-Koehler Publishers.

Photo: Mt. Isolation This Way on Flickr by Tim Sackton used under Creative Commons License. (Thanks for the great shot Tim and making it available for others to use!)

art & designdesign thinkinginnovation

Creativity and Craft, Myth and Muscle

Applying Creative Muscle

Applying Creative Muscle

Creativity is a word shrouded in myth that has been held up as this elusive, seductive object that will reveal the true secrets of innovation if ever reached. Creativity is something we all have, but not all of us are craftspeople and knowing where these two are separate and meet is the difference between myth and the muscles needed to turn creativity into innovations.  

A tour of blogs, journals, and magazines that cover innovation from Inc, Fast Company, Harvard Business Review, The Atlantic, Entrepreneur and all the way to Brain Pickings will find one topic more visible than most: creativity.

Creativity is one of those terms that everyone knows, many use, has multiple meanings and is highly dependent on person and context. It’s also something that many of us feel we lack. This is not surprising given the way we set our schools and workplaces up as Sir Ken Robinson has discussed throughout his career.

Robinson has delivered perhaps one of the best and certainly most viewed talks on this at TED a few years ago illustrating the ways creativity gets ‘schooled’ out of us early on:

Accessing creativity

A look at the evidence base — which is enormous, unstructured, and varied in quality and scope — finds that creativity is hardly the mythical thing it gets made out to be and, following Sir Ken’s points raised in his TED talk, something we all have in us that may simply be hidden. More than anyone, Dr Keith Sawyer knows this having put together perhaps the strongest collection of evidence for the application of creativity in his books Explaining Creativity and, more recently, Zig Zag. (Both books are highly recommended).

Sawyer dispels such myths of the creative genius or the “flash of insight” as a linear process, rather pointing to creativity as often the cultivation of practices and habits that people go through to generate insights and products. This ‘zig zag’ represents metaphorically taking switchbacks to climb a mountain rather than going straight uphill. As you engage in creative thinking and action you build a deeper knowledge base, hone and acquire skills, and simply become more creative. “Creative people” are those that engage in these practices, build the habits of mind of creativity, and persist through each zig and zag along the way.

Design and design thinking is often associated with creativity because it is, in part, about creatively finding, framing and addressing problems through a structured process of inquiry, prototyping and revision. David and Tom Kelley in their recent book Creative Confidence point to design thinking as a layered foundation that is what much creativity is built upon. The disciplined, guided process that design thinking (well applied) offers is a vehicle for building creative confidence in those who might not feel very creative in what they do.

The process of design thinking — illustrated in the CENSE model of innovation development below — fits with Sawyer’s assertion of how creativity unfolds.

The design and innovation cycle

The CENSE design and innovation corkscrew model

The role of craft

What Robinson, Sawyer, the Kelley brothers and others have done is dispelled the myths that creativity is some otherworldly trait and shown that its something for all of us. What can get lost in the blind adoption of this way of thinking is attention to craft.

Craft is the technical skill of applying creativity to a problem or task and that is something that is quite varied. The debate over whether or not the term designer belongs to everyone who applies creativity to solving problems or those with formal design training largely is one of craft.

Craft is the thing that brings wisdom from experience and technical skill in transforming creative ideas into quality products, not just interesting ones.

In our efforts to free people from the shackles of their education and a social world that told them they weren’t creative we’ve put aside discussion of craft in the hopes that we simply get people moving and creating. That is so very important to unlocking creative confidence and ensuring that our efforts to develop social innovations are truly social and engage the widest possible numbers of participants. However, it will be craft that ensures these solutions don’t turn into what George Carlin referred to as (great) ideas that suck. 

Building design practice in the everyday

The habits of creativity are just that, habits. And if design is the way of applying creativity to problems then building a design practice is key. This means bringing elements of design into the way you operate your enterprise. Spend a lot of time finding the right problems is a start (as discussed in a previous post). Discover, inquire and be curious. Visualize, prototype, create small ‘safe-fail’ experiments, and ensure that there is a learning mechanism through the evaluation to allow your enterprise to adapt.

This is all easier said than done. It can be easy to be satisfied with being creative, but to be excellent involves craft and that requires something beyond creativity alone. It may involve training (formal or otherwise), it most certainly involves mindful attention to the work (which is what underlies the ‘10,000 hour rule’ of practice that make someone an expert), but it also requires skill. Many will find their creative talents in art, management, leadership, or service, but not all will be remarkable in exercising that skill.

To put it another way; it’s like a muscle. Everyone can work their muscles and develop them with training, nutrition, rest, and attention, but some will respond to this differently for a variety of reasons due to how all of those activities come together. This is what helps contribute to reasons why someone might be better adept at long-distance running, while others are good at bulking up and still others are far more flexible on the yoga mat.

We are all creative. We are all designers, too. But not all of us are stellar designers for all things and its important to build our collective design literacy, which includes knowing when and how to cultivate, hire and retail craftspeople and not just assume we can design think our way through everything. This last point is what will ensure that design thinking doesn’t fade away as a fad after it “didn’t produce results” because people have confused creativity with craft, myth with muscle.

References: 

Kelley, T., & Kelley, D. (2013). Creative confidence: unleashing the creative potential within us all. New York, N.Y.: Crown Publishers.

Sawyer, R. K. (2012). Explaining creativity: The science of human innovation (2nd Edition.). Oxford, U.K.: Oxford University Press.

Sawyer, R. K. (2013). Zig Zag: The Surprising Path to Greater Creativity. San Francisco, CA: Jossey-Bass.

complexityemergenceevaluationinnovation

Do you value (social) innovation?

Do You Value the Box or What's In It?

Do You Value the Box or What’s In It?

The term evaluation has at its root the term value and to evaluate innovation means to assess the value that it brings in its product or process of development. It’s remarkable how much discourse there is on the topic of innovation that is devoid of discussion of evaluation, which begs the question: Do we value innovation in the first place?

The question posed above is not a cheeky one. The question about whether or not we value innovation gets at the heart of our insatiable quest for all things innovative.

Historical trends

A look at Google N-gram data for book citations provides a historical picture of how common a particular word shows up in books published since 1880. Running the terms innovation, social innovation and evaluation through the N-gram software finds some curious trends. A look at graphs below finds that the term innovation spiked after the Second World War. A closer look reveals a second major spike in the mid-1990s onward, which is likely due to the rise of the Internet.

In both cases, technology played a big role in shaping the interest in innovation and its discussion. The rise of the cold war in the 1950’s and the Internet both presented new problems to find and the need for such problems to be addressed.

Screenshot 2014-03-05 13.29.28 Screenshot 2014-03-05 13.29.54 Screenshot 2014-03-05 13.30.13

Below that is social innovation, a newer concept (although not as new as many think), which showed a peak in citations in the 1960’s and 70s, which corresponds with the U.S. civil rights movements, expansion of social service fields like social work and community mental health, anti-nuclear organizing, and the environmental movement.  This rise for two decades is followed by a sharp decline until the early 2000’s when things began to increase again.

Evaluation however, saw the most sustained increase over the 20th century of the three terms, yet has been in decline ever since 1982. Most notable is the even sharper decline when both innovation and social innovation spiked.

Keeping in mind that this is not causal or even linked data, it is still worth asking: What’s going on? 

The value of evaluation

Let’s look at what the heart of evaluation is all about: value. The Oxford English Dictionary defines value as:

value |ˈvalyo͞o|

noun

1 the regard that something is held to deserve; the importance, worth, or usefulness of something: your support is of great value.

• the material or monetary worth of something: prints seldom rise in value | equipment is included up to a total value of $500.

• the worth of something compared to the price paid or asked for it: at $12.50 the book is a good value.

2 (values) a person’s principles or standards of behavior; one’s judgment of what is important in life: they internalize their parents’ rules and values.

verb (values, valuing, valued) [ with obj. ]

1 estimate the monetary worth of (something): his estate was valued at $45,000.

2 consider (someone or something) to be important or beneficial; have a high opinion of: she had come to value her privacy and independence.

Innovation is a buzzword. It is hard to find many organizations who do not see themselves as innovative or use the term to describe themselves in some part of their mission, vision or strategic planning documents. A search on bookseller Amazon.com finds more than 63,000 titles organized under “innovation”.

So it seems we like to talk about innovation a great deal, we just don’t like to talk about what it actually does for us (at least in the same measure). Perhaps, if we did this we might have to confront what designer Charles Eames said:

Innovate as a last resort. More horrors are done in the name of innovation than any other.

At the same time I would like to draw inspiration from another of Eames’ quotes:

Most people aren’t trained to want to face the process of re-understanding a subject they already know. One must obtain not just literacy, but deep involvement and re-understanding.

Valuing innovation

Innovation is easier to say than to do and, as Eames suggested, is a last resort when the conventional doesn’t work. For those working in social innovation the “conventional” might not even exist as it deals with the new, the unexpected, the emergent and the complex. It is perhaps not surprising that the book Getting to Maybe: How the World is Changed is co-authored by an evaluator: Michael Quinn Patton.

While Patton has been prolific in advancing the concept of developmental evaluation, the term hasn’t caught on in widespread practice. A look through the social innovation literature finds little mention of developmental evaluation or even evaluation at all, lending support for the extrapolation made above. In my recent post on Zaid Hassan’s book on social laboratories one of my critique points was that there was much discussion about how these social labs “work” with relatively little mention of the evidence to support and clarify the statement.

One hypothesis is that evaluation can be seen a ‘buzzkill’ to the buzzword. It’s much easier, and certainly more fun, to claim you’re changing the world than to do the interrogation of one’s activities to find that the change isn’t as big or profound as one expected. Documentation of change isn’t perceived as fun as making change, although I would argue that one is fuel for the other.

Another hypothesis is that there is much mis-understanding about what evaluation is with (anecdotally) many social innovators thinking that its all about numbers and math and that it misses the essence of the human connections that support what social innovation is all about.

A third hypothesis is that there isn’t the evaluative thinking embedded in our discourse on change, innovation, and social movements that is aligned with the nature of systems and thus, people are stuck with models of evaluation that simply don’t fit the context of what they’re doing and therefore add little of the value that evaluation is meant to reveal.

If we value something, we need to articulate what that means if we want others to follow and value the same thing. That means going beyond lofty, motherhood statements that feel good — community building, relationships, social impact, “making a difference” — and articulating what they really mean. In doing so, we are better position to do more of what works well, change what doesn’t, and create the culture of inquiry and curiosity that links our aspirations to our outcomes.

It means valuing what we say we value.

(As a small plug: want to learn more about this? The Evaluation for Social Innovation workshop takes this idea further and gives you ways to value, evaluate and communicate value. March 20, 2014 in Toronto).

 

 

behaviour changeinnovationsystems sciencesystems thinking

Social Innovation Laboratories

Social Innovation bottled up

What’s inside the lab?

Zaid Hassan’s new book The Social Labs Revolution provides a look at the messy world of social change making. While far from being a how-to guide, the book provides a rare glimpse at the thinking behind the lab concept and some stories that illustrate how challenging, complex, and contradictory social change can be in its making. 

Zaid Hassan‘s newly released book looks at a concept that has become increasingly popular in the world of social innovation and design: the social laboratory. These labs are sometimes referred to as a design lab, solutions lab, or social innovation lab, but the general point is that they represent a combination of think tank, research unit, social action planning group, convener, community mobilizer and system change architect rolled into one entity.

These labs are focused on social issues at the systems level (at different scales) and tackle large and small issues that are generally complex in nature. Some have real, physical homes and others are located wherever their audience is or some combination.

At the crux of this concept of a social laboratory is a desire to integrate the spirit of discovery one expects to find in a traditional scientific laboratory complete with an emphasis on experimentation with a social mission, social engagement and a focus on complex problems.

The social labs revolution

The Social Labs Revolution
The Social Labs Revolution

The book is an interesting read and is well-written, but contrary to what some readers might desire, it is not going to provide a how-to guide in enough detail to start one up. However, it will inspire some foundational thinking in what labs are about, the theories and models that guide the work that Hassan and his partners at Generon and later Reos Partners founded the labs on and that is a significant contribution alone.

Labs are trendy and thus are vulnerable to hype and lazy thinking and one thing readers will soon learn is that Zaid Hassan is far from lazy. If anything, he’s exhausted from all the work he’s done.

The greatest strength of the book is in its very real account of the challenges that the work of labs involves. Hassan is forthcoming about the contradictions, tensions, hypocrisies, and strengths that get embedded in social labs as they try to realize fuzzy goals in ever-changing environments. It’s tiring work. That Hassan has been so forthright in his honesty about the experience of running social labs is truly commendable at a time when there is an enormous amount of hype around labs. It is a story of frustration, hope, possibility and uncertainty rolled into one.

Solutions and their laboratories

Another of the great strengths of the book is the discussion of the complexities that social labs face in their genesis and execution and Hassan does an excellent job of highlighting the evolution in thinking that has taken place between the original labs and what he calls the Next Generation Social Labs.

Alas, there is little in the book that will aid the reader in setting up a next generation lab or even recognizing one if they came across it. Chapter 8 outlines 7 How-to’s that feel like something an editor insisted on adding to the book and sadly does a disservice to the nuanced recollection of experience of labs that comes before it.

The 7 How-to’s are:

  1. Clarify intention
  2. Broadcast an invitation
  3. Work your networks
  4. Recruit willing people
  5. Set direction
  6. Design in stacks
  7. Find cadence

These points are rather vague and, with some exception, could be applied to almost any social venture. There is also little clarity on what they mean in practice. For example, the ‘design in stacks’ recommendation is supported with a single page of text, hardly enough to build a lab on or consider the design qualities such a lab needs to be successful. Not that the book necessarily claims to be a textbook for setting up a social lab, but its easy to see that the marketing team behind the book is OK with encouraging some hyperbole that suggests one might be able to use the book as the vehicle to change the system (see the back page for quotes and endorsements that illustrate this point).

What is missing from the book is the kind of qualities one might expect to find in a venture called a laboratory. There is little attention to data, to curiosity, to methods of inquiry and to knowledge translation. There are some numbers offered that account for some of the work that was done in the lab examples, but there is little in the way of causal or attributional linkages made that would satisfy an evaluator. To be fair to the author, this is missing from most other accounts of social labs I’ve seen. Much discussion of their impact and how they continue to “work” is made without attention to the very science-inspired concepts that are at the bedrock of a laboratory and that is a shame. It’s not to say that good work wasn’t done, it’s just hard to know exactly what it was and how that was determined to be connected to the program.

Now one might argue that the lab is metaphorical and thus it’s not worth getting too nit-picky about the details and how social labs resemble scientific labs. But this is not just a language issue, because if we are not careful we may make the same mistakes of association with causation that bedevil accounts of many other strategies for social change. In complex systems, causation is not linear and is rarely (if ever) predictable or controllable. Yet, there are ways to rigorously account for what was done, where things went, and what kind of patterns of activity are connected to others. It’s not all numbers, but its also more than stories.

A scientific approach to the social lab?

Social labs may not be able to prove cause-and-effect in a clean, neat manner, but they can document what they did from the lens of a system. They can show how their roles led to joined-up activities that manifest throughout a system in many ways. But most importantly, social labs can play a role in stimulating learning for the systems they engage. Learning is very often non-linear, associative, punctuated, and dynamic just as the complex systems in which social labs work and it would have been wonderful to have seen how the 7 recommendations were generated, supported and realized in the examples provided. We can be more scientific about our labs even if that means using the science of systems and complexity.

It also would have been useful to have seen how the lessons could be realized within the context of the design of the lab, which should flow through each of the seven steps. Perhaps that is for the next book.

The Social Labs Revolution is an important contribution to the literature and our collective understanding of what social labs look like from within, not just without. I recommend it for anyone who thinks this is something worth considering for it will caution you against any belief that labs are simple tools for solving simple problems, simply. Quite the opposite.

Cover Image: iStockphoto, used under licence.

businesscomplexityinnovation

What’s the big idea and how are you going to make it real?

What is your strategy?

What is your strategy?

Concepts like design thinking and developmental evaluation are best used when they help ask big questions before seeking answers. How we frame the problem is much more important than the solution we generate, but that way of thinking means going into an area that is much talked about and rarely delivered on: strategy.

Many companies and human service organizations are getting desperate for solutions to the vexing problems they face. However, it may be that the organizations are as stuck finding solutions because they are tackling the wrong problem.

Problem framing is among the most critical, yet often overlooked, steps in design and innovation and often leads to more solutions that fail than those that succeed. Asking better questions is a start and developing a strategy from that is where to go next.

The big idea is your problem, making it real is the strategy to solving it.

What is the big idea?

Herbert Simon wrote about problem forming, framing and solving as the central tenets of design. Albert Einstein, another Nobel laureate, was famously (mis?)quoted as saying this about the discovery process:

If I had only one hour to save the world, I would spend fifty-five minutes defining the problem, and only five minutes finding the solution.

Like so many of these ‘famous’ quotes, its origins are murky and the (hypothesized) original is much less poetic, but the spirit of the phrase is that problem finding and forming is enormously important for innovation. Case studies from design missions, innovation labs, and my own personal experience suggest that this ratio of 55 and 5 in resourcing is probably not far off from the truth.

Problem forming is also tied to a greater sense of mission, which is where a lot of organizations get it wrong. A clear, appropriately scoped mission provides the boundaries for creativity to flourish and innovation efforts to focus. Steve Jobs charged Apple with the mission of developing tools to enable people to create. That may have started with computers, but it soon grew to software with features that were design-forward and attractive, and then mobile devices and the ecosystems that powered them. When viewed from the mission of enabling creativity, the move to being a music and bookseller isn’t a leap from Apple’s roots as a maker of desktop computers.

Where are you going?

Strategy is about saying what you don’t do as much as it is about saying what you do. It also means saying what you do clearly and meaning it. Both of these have enormous implications for what a program focuses on and what feedback systems they develop to help them innovate and guide their strategy moving forward.

A good, simple resource on strategy is Howell J. Maltham Jr‘s recent book I Have a Strategy, No You Don’t. In the book the author illustrates the many ways in which we claim strategy when really it’s a wish. Malthan asserts that a strategy has:

  1. A purpose
  2. A plan
  3. A sequence of actions or tactics
  4. A distinct, measurable goal

However, most importantly according to Maltham is that this all needs a narrative – the story of what you do and how you do it. Too often we see the absence of narrative or a lack of connection to any of the four components above. Apple has famously developed a strong narrative for how it operates and realizes it mission.

Maltham’s four-point description of strategy works when you are dealing with simple and maybe slightly complicated systems; those with some measure of predictability and control. It doesn’t work well for complexity, which is where many human services are either immersed or shifting to. For that, we need some form of adaptive strategy that provides guidance, but also works with, rather than against complexity. Yet, it still requires a narrative.

Strategy for complex times

Like the above cartoon from Tom Fishburne, the tactics should not precede the strategy. It’s interesting to see how often the term tactic and strategy get confused and conflated. It’s easy to see why. Tactics are tangible. They — like 90% of meetings, answering email and phone messages — offer the illusion of productivity and impact. Getting hundreds or thousands of likes, followers, and re-tweets is a proxy for impact for a lot of people.

But if you’re looking to make real change, it doesn’t matter so much that you’re doing stuff, but rather whether you’re moving stuff.

It’s why adaptive strategy is difficult, because it means moving your ideas, your thinking, your relationships and your operations to constantly re-calibrate your focus. Just like looking at birds through binoculars or watching a football game from the stands, you need to constantly adjust your focus to maintain engagement. The same thing happens with strategy.

At the same time, difficult shouldn’t be the reason not to do something.

This is the new thinking that is needed to innovate and that is why many organizations seek to do the wrong thing righter by doubling down on trendiness to appear innovative without thinking deeply about what the big idea is and how it is supposed to become real. Whether static or adaptive, the narrative will tie that together. So what is your organization’s story and do you know how to tell it?

 

complexitydesign thinkingevaluationinnovationsystems thinking

Developmental Evaluation and Complexity

Stitch of Complexity

Stitch of Complexity

Developmental evaluation is an approach (much like design thinking) to program assessment and valuation in domains of high complexity, change, and innovation. These three terms are used often, but poorly understood in real terms for evaluators to make much use of. This first in a series looks at the term complexity and what it means in the context of developmental evaluation. 

Science writer and professor Neil Johnson  is quoted as saying: “even among scientists, there is no unique definition of complexity – and the scientific notion has traditionally been conveyed using particular examples…” and that his definition of a science of complexity (PDF) is:  “the study of the phenomena which emerge from a collection of interacting objects.”  The title of his book Two’s Company, Three’s Complexity hints at what complexity can mean to anyone who’s tried to make plans with more than one other person.

The Oxford English Dictionary defines complexity as:

complexity |kəmˈpleksitē|

noun (pl. complexities)

the state or quality of being intricate or complicated: an issue of great complexity.

• (usu. complexities) a factor involved in a complicated process or situation: the complexities of family life.

For social programs, complexity involves multiple overlapping sources of input and outputs that interact with systems in dynamic ways at multiple time scales and organizational levels in ways that are highly context-dependent. Thats a mouthful.

Developmental evaluation is intended to be an approach that takes complexity into account, however that also means that evaluators and the program designers that they work with need to understand some basics about complexity. To that end, here are some key concepts to start that journey.

Key complexity concepts

Complexity science is a big and complicated domain within systems thinking that brings together elements of system dynamics, organizational behaviour, network science, information theory, and computational modeling (among others).  Although complexity has many facets, there are some key concepts that are of particular relevance to program designers and evaluators, which will be introduced with discussion on what they mean for evaluation.

Non-linearity: The most central start point for complexity is that it is about non-linearity. That means prediction and control is often not possible, perhaps harmful, or at least not useful as ideas for understanding programs operating in complex environments. Further complicating things is that within the overall non-linear environment there exist linear components. It doesn’t mean that evaluators can’t use any traditional means of understanding programs, instead it means that they need to consider what parts of the program are amenable to linear means of intervention and understanding within the complex milieu. This means surrendering the notion of ongoing improvement and embracing development as an idea. Michael Quinn Patton has written about this distinction very well in his terrific book on developmental evaluation. Development is about adaptation to produce advantageous effects for the existing conditions, improvement is about tweaking the same model to produce the same effects across conditions that are assumed to be stable.

Feedback: Complex systems are dynamic and that dynamism is created in part from feedback. Feedback is essentially information that comes from the systems’ history and present actions that shape the immediate and longer-term future actions. An action leads to an effect which is sensed, made sense of, which leads to possible adjustments that shape future actions. For evaluators, we need to know what feedback mechanisms are in place, how they might operate, and what (if any) sensemaking rubrics, methods and processes are used with this feedback to understand what role it has in shaping decisions and actions about a program. This is important because it helps track the non-linear connections between causes and effects allowing the evaluator to understand what might emerge from particular activities.

Emergence: What comes from feedback in a complex system are new patterns of behaviour and activity. Due to the ongoing, changing intensity, quantity and quality of information generated by the system variables, the feedback may look different each time an evaluator looks at it. What comes from this differential feedback can be new patterns of behaviour that are dependent on the variability in the information and this is called emergence. Evaluation designs need to be in place that enable the evaluator to see emergent patterns form, which means setting up data systems that have the appropriate sensitivity. This means knowing the programs, the environments they are operating in, and doing advanced ‘ground-work’ preparing for the evaluation by consulting program stakeholders, the literature and doing preliminary observational research. It requires evaluators to know — or at least have some idea — of what the differences are that make a difference. That means knowing first what patterns exist, detecting what changes in those patterns, and understanding if those changes are meaningful.

Adaptation: With these new patterns and sensemaking processes in place, programs will consciously or unconsciously adapt to the changes created through the system. If a program itself is operating in an environment where complexity is part of the social, demographic, or economic environment even a stable, consistently run program will require adaptation to simply stay in the same place because the environment is moving. This means sufficiently detailed record-keeping is needed — whether through program documents, reflective practice notes, meeting minutes, observations etc.. — to monitor what current practice is, link it with the decisions made using the feedback, emergent conditions and sensemaking from the previous stages and then tracking what happens next.

Attractors: Not all of the things that emerge are useful and not all feedback is supportive of advancing a program’s goals. Attractors are patterns of activity that generate emergent behaviours and ‘attract’ resources — attention, time, funding — in a program. Developmental evaluators and their program clients seek to find attractors that are beneficial to the organization and amplify those to ensure sustained or possibly greater benefit. Negative (unhelpful) attractors do the opposite and thus knowing when those form it enables program staff to dampen their effect by adapting activities to adjust and shift these activities.

Self-organization and Co-evolution: Tied with all of this is the concepts of self-organization and co-evolution. The previous concepts all come together to create systems that self-organize around these attractors. Complex systems do not allow us to control and predict behaviour, but we can direct actions, shape the system to some degree, and anticipate possible outcomes. Co-evolution is a bit of a misnomer in that it refers to the principles that organisms (and organizations) operating in complex environments are mutually affected by each other. This mutual influence might be different for each interaction, differently effecting each organization/organism as well, but it points to the notion that we do not exist in a vacuum. For evaluators, this means paying attention to the system(s) that the organization is operating in. Whereas with normative, positivist science we aim to reduce ‘noise’ and control for variation, in complex systems we can’t do this. Network research, system mapping tools like causal loop diagrams and system dynamics models, gigamapping, or simple environmental scans can all contribute to the evaluation to enable the developmental evaluator to know what forces might be influencing the program.

Ways of thinking about complexity

One of the most notable challenges for developmental evaluators and those seeking to employ developmental evaluation is the systems thinking about complexity. It means accepting non-linearity as a key principle in viewing a program and its context. It also means that context must be accounted for in the evaluation design. Simplistic assertions about methodological approaches (“I’m a qualitative evaluator / I’m a quantitative evaluator“) will not work. Complex programs require attention to the macro level contexts and moment-by-moment activities simultaneously and at the very least demand mixed method approaches to their understanding.

Although much of the science of complexity is based on highly mathematical, quantitative science, it’s practice as a means of understanding programs is quantitative and qualitative and synthetic. It requires attention to context and the nuances that qualitative methods can reveal and the macro-level understanding that quantitative data can produce from many interactions.

It also means getting away from language about program improvements towards one of development and that might be the hardest part of the entire process. Development requires adaptation to the program, thought and rethinking about the program’s resources and processes that integrate feedback into an ongoing set of adjustments that perpetuate through the life cycle of the program. This requires a different kind of attention,  methods, and commitment from both a program and its evaluators.

In the coming posts I’ll look at how this attention gets realized in designing and redesigning the program as we move into developmental design.