How Serious Are We About Learning?
Posted: July 26, 2012 Filed under: behaviour change, education & learning, health promotion, innovation, public health | Tags: behaviour change, Dan Pink, discovery, education, innovation, Jonah Lehrer, knowledge integration, learning, mindfulness, organizational change, psychology, public health, Robert Scott Root-Bernstein, social innovation, social systems, Steven Johnson, systems thinking, Toronto, University of Toronto 6 Comments »
How Serious Are We About Learning?
When journalist and book author Daniel Pink tweeted the above image the other day it provoked thinking about what real learning means and what it takes to achieve it. We produce enormous amounts of knowledge, yet struggle to put it into use, but we also teach much and learn little because the systems we’ve designed for education and experience don’t match our expressed interest and rhetoric around learning.
In my graduate course on behaviour change I would ask students on the first day why they were taking the class in the first place. Aside from the few students for whom the course was required everyone else was doing it by choice because there were many others to choose from. So why would they choose this one?
The answers would vary, but inevitably I’d hear over and again that students love learning and wanted to understand more about behaviour change, because they were interested in change and some would even say they were good at it and wanted to help others do it.
These are all well-meaning and said in a spirit that I think was honest and true. Except the reality is that it is likely a big, huge lie and one that we all share in its telling.
I would counter with two things:
- Loving the idea of learning something new is different than actually seeking out learning opportunities and that most of us love the former, but are not so enthused about the latter;
- The only people who regularly welcome change are babies with soiled diapers.
To illustrate the first point I simply ask people to consider the last conference they went to where there were options on what sessions to attend. How many of the sessions did they attend that featured content that confirmed or gently extended what they already knew versus content that was new? If you’re a health promoter doing community engagement work, sessions on Bayesian modelling for epidemics might offer far more learning than a session on working with diversity in communities (particularly if that is what you already do). Even more, how often do people go to sessions from people they know or have already seen speak? Chances are, many.
One could argue that there are subtleties that a conference presentation might offer on a familiar topic that are worth attending and while I would say that has merit, most learning that has impact is uncomfortable at some level. It extends our thinking, challenges our beliefs, or re-arranges our worldview — in ways small and large.
Wanting knowledge and living learning
Many people will say “I love change”, but that is usually in the context that everyone else is changing, not them. When I was the boss and said “things must change” it was very different than when my staff or my boss would say “things must change“. As a behaviour change educator and intervener, I need to be mindful of my own ironies and resistance to change. So should we all.
The same thing goes for knowledge. Academics are famous for ending studies with “more research is needed”. We never seem to have enough knowledge. There are two problems with this idea.
The first is that, in dynamic and evolving environments, we will never have perfect knowledge that fits like a glove, because the contexts are always novel. This isn’t to say that evidence isn’t useful, but ‘good enough’ knowledge might be a more reasonable demand than ‘best evidence’ in many of the situations where complexity is high and so is change. That’s why data gathering techniques like developmental evaluation aren’t attractive to those who need certainty.
But there is another problem with the knowledge quest and that is one of integration. In our efforts to seek more knowledge, are we integrating what we are learning from what we already have? Are we savouring the data we collect, the articles we read, the Tweets and blogs that get forwarded are way?
We quest for more, but should we quest for better?
A newly published paper synthesized research on event horizons on memory and found that shifts in activities around an event — boundaries — can prompt forgetting and recall. We remember transitions between activities, but they also prompt forgetting depending on the mindfulness associated with the act. When we are deluging ourselves with more data, more media, more everything, we are increasing the potential remember rate, but due to the volume of content, I would surmise that we are increasing the forget rate much more. Simply reflect on your high school or undergraduate education and ask yourself if you remember more than you forgot about what you learned.
We are so busy with our search for new knowledge that we interrupt opportunities to learn from what we have.
Serious learning means non-doing
Returning to the tweet from Dan Pink, it’s worthwhile considering what it means to learn and the systems we have in place to facilitate learning. The tweet links to a discussion of how German companies give their employees five days of off-site continuing education each year. This concept of Bildungsurlaub is a leave designed to allow employees to stretch their thinking and integrate something new. Not only is off-site learning important, but the time associated with integrating material is critical.
A read of the literature on innovation and research shows consistently how time off, quiet time, slow time and down time all contribute to discovery. Robert Scott Root-Bernstein’s brilliant Discovering, Jonah Lehrer’s Imagine, or Steven Johnson’s Where Good Ideas Come From are all books that dive deep into creative production and show that great discoveries and innovations come from having time (with limits) to integrate material to learn. Freedom to create, explore and sit and mindfully reflect are all united concepts in the pursuit of good learning. Not everything requires this, but big concepts and bold ideas do from mathematics to science to social science and philosophy.
Yet, at an organizational and systems level, where is the support for this? Even university faculty (the tenured ones at least) who have generous vacations and sabbaticals are finding themselves crunched for time between the fight for one of the ever-fewer grants, increasing numbers of students and teaching demands, and the added push to ensure knowledge is translated. The image of faculty sitting and reading and thinking is truly an imagination. Most of my colleagues in academia do little of this, because they are out of time.
In the corporate and non-profit world this is worse. Every hour and day is to be accounted for. The idea of sending people off to learn and to think seems anathema to productivity, yet research shows incredible powers associated with taking a break and doing less and not more.
Getting serious about learning
To illustrate the scope of the problem, the University of Toronto holds one of the finest academic library systems in the world and has over 11.5 million books and 5.7 million microform materials. It is one university (of many) in one city. Add in the local Toronto public library system, the network of universities and other libraries it is connected to, local and global bookstores and all the content freely available online that is not part of this system and I challenge anyone working in social innovation or public health to say with conviction that there is a lack of knowledge out there on any important topic. Yes, we don’t know it all, but we don’t do nearly enough with what we do know because there is so much.
We will not read it all nor can we hope to synthesize it all, but we can do much with what we have. Just looking at my own personal library of physical books (not including all I have in the digital realm between books and papers) it’s easy to see that I have more than enough knowledge to tackle most of what I am facing in my work. Most of us do. But do we have the wisdom to use it? Do we have the systems — organizations and personal — that allow us to take the time and soak this in, share our ideas with others, and be mindful of the world around us enough to learn, not just consume?
When we spend as much time creating those spaces, places and systems, then we can answer “yes” to the question of whether we’re serious about learning.
Enough knowledge here?
Social Media and Health: Leaders(hip) and Followers(hip)
Posted: May 18, 2012 Filed under: behaviour change, eHealth, health promotion, innovation, public health, social media, systems thinking | Tags: complexity, creativity, design thinking, developmental design, developmental evaluation, eHealth, evaluation, Facebook, health, health promotion, healthcare, innovation, medicine, organizational change, organizational design, public health, social media, systems thinking 2 Comments »
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.
Systems Thinking and the Design of Empathy
Posted: September 22, 2011 Filed under: complexity, design thinking, systems thinking | Tags: Charles Leadbeater, design, developmental design, developmental evaluation, empathy, organizational change, systems thinking Comments Off
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.
Innovation and Academic Science
Posted: July 1, 2011 Filed under: knowledge translation, public health, research, systems thinking | Tags: academia, innovation, organizational change, public health, research, science, universities Comments Off
Innovation grants are a misnomer, signifying one of the greatest problems with academic science and the quest to create novel solutions to important problems.
Yesterday the Canadian Cancer Society Research Institute (the research arm of the largest charitable agency that supports cancer programming in Canada) announced its new, revamped lineup of grant funded programs to be launched within the coming months. Among the first of these new programs is one called Innovation Grants (PDF)while another is called Impact Grants (PDF). In fact, both of these new program announcements include the definition of each of the key terms in their program call:
Innovation: The action of innovating; the introduction of novelties; the alteration of what is established by the introduction of new elements or forms. -Oxford English Dictionary
and
Impact: the action of one object coming forcibly into contact with another; a marked effect or influence -Oxford English Dictionary
This is impressive in how they can clearly and distinctly linked the definition of the word to the program call. Why? Because too often grant program calls and their expression in reality are too often separate. I once served on a grant panel that was looking at grants aimed at ensuring quality knowledge translation only to find that most reviewers were comfortable with things like “prepare academic manuscript based on research” and “present findings at major conference” to be acceptable knowledge translation goals by themselves. I was appalled.
Yet, I can’t help but think, despite the good intentions here, that these new programs are going to follow in similar footsteps. The problem is not the funder, but rather the way that funding is granted and the reliance on the system to change itself.
The innovation grants are designed to :
support unconventional concepts, approaches or methodologies to address problems in cancer research. Innovation projects will include elements of creativity, curiosity, investigation, exploration and opportunity. Successful projects may involve higher risk ideas, but will have the potential for “high reward”, i.e. to significantly impact our understanding of cancer and generate new possibilities to combat the disease by introducing novel ideas into use or practice
The mechanism by which these grants are to be decided are, as much as I can tell, by peer review. It is for that reason alone that we can feel some level of confidence that these grants will fail outright. Peer review is designed to judge the quality of content by what is and has been, not by what could be. “Innovation” is about doing things differently, often markedly so. Scientific panels are about supporting incrementalism, particularly in the social and behavioural sciences.
Innovation is also about risk and the potential for failure. These are two words that are highly problematic in present day academic science. Firstly, if you’re a junior scientist, you may be working desperately to fund yourself and your research (and research team). The price of failure is high. If you’re not able to publish meaningfully off your research, you will have a hard time getting your next grant and keeping yourself afloat. In public health sciences for example, CLTA (contract limited-term appointments) are dominant.
I should know as that’s the position I hold.
But the tenured faculty don’t have it much better. While they are more secure, their research teams, graduate student trainees who rely on projects to develop their skills, and the ability to develop coherent programs of research are at risk every time there is an unsuccessful grant. There are real opportunity costs to pursuing risky ventures so many don’t do it
As one who has tried to be innovative with his work and having the privilige (or curse, depending on the perspective) of having interests that have fallen into the innovation category (or “trendy” category to the cynic), I’ve seen how innovation is treated and it’s not good. Innovation programs tend to split committees. I’ve had too many comments returned to me that have some variant on “this is amazing, potentially leading edge research!” alongside “the use of non-conventional methods makes this suspect” or “I don’t understand what this is supposed to do“. As one who had to endure years of questions like “I don’t see how this Internet thing has anything to do with health” in the early days of the eHealth this kind of line of questioning is familiar to me.
I point this out not to gripe, but to illustrate how innovation can get treated in academia. When you get feedback like I described it is very hard to critically assess the true merits of the proposal for improvement. Did people not understand an idea because it could have been written more clearly or did they just not “get” the innovation? Were those who were excited just caught up in the “newness” or were they really in sync with my vision? As a scientist, I don’t know the answer and can’t improve because the feedback is so contradictory.
And because innovators often create, develop or define fields of inquiry or practice that does not exist or is in development there are few if any adequate and available reviewers with the appropriate background on the topic.
In academia, we rely on tradition, on evidence (which is part of tradition, what has been done before), not on strategic foresight and innovation to guide us. That is a problem in itself. Universities haven’t survived hundreds of years by being risky, they have because they were safe (in spite of the occasional radical shift here and there). With complex social problems and the challenges posed by things like cancer, something risky is needed because the traditional ways of doing things have either been exhausted or are no longer producing the necessary health gains. Academics just aren’t positioned to embrace this risk unless the system changes — with them helping drive that change — to support innovation and not just talk about it.
Until that happens, the opportunities to live up to the definition of innovation posed about to create the impact described above will be limited indeed.
The Complexity Challenge
Posted: June 30, 2011 Filed under: complexity, systems thinking | Tags: complexity, contemplative inquiry, education, learning, mindfulness, organizational change, simplicity, systems thinking 2 Comments »
Is Learning Falling Down When it Comes to Complexity?
Before acting in a manner consistent with complexity principles, people need to understand what they are, how they are different from other systems, and what it means for their work. With mainstream education, professional practice so geared to linear forms of learning this bodes poorly for building better systems thinkers.
“Let’s just throw some social media at it” is a variant of an expression I often hear in my work in health communications consulting and training. Organizations seeking to use the new tools and media employed by Facebook, Twitter, and YouTube genuinely want to “get in the game” and use them effectively. Where things get problematic is when I tell them that social media is principally about building relationships and that extends to organizations: you need to relate and therefore act according to how you build relationships.
Just as no one (at least no one I’ve met) would consider drawing up a flowchart and showing a prospective mate the planned trajectory of their dating relationship with milestone targets and deliverables, no organization should think that they can just shovel content to people and expect their audience to relate better to them.
At first one might attribute this to a lack of understanding of social media, but that is only a small part of it. Empathy is another. But the third and perhaps biggest reason is a fundamental lack of understanding of complexity and what it means.
The seductive nature of the “best practice” and the prescription for change in 5,7, 10, 12 or whatever easy steps is something that is endemic in our society. These forms of thought suggest a linear trajectory of events, suggest an ability to control for externalities and parse out their impact, and provide a prescriptive solution that removes much of the worry about unknowns. But H. L. Mencken’s often quoted phrase (which I’ve used often) suggests the folly in this.
Simplicity is another way to get around complexity. It is something sought, but rarely achieved in its application to the lived reality of the human condition, and although much discussed it hasn’t been widely achieved as a means of policy effectiveness. The reason lies with the nature of complexity itself and its resistance to reductionism. Evidence from biology through psychology (see previous links for examples) points to the considerable problem that science has with applying linear modes of thought and inquiry to complex systems.
The problems here are multifold and complicated, if not complex.
1. Our education system is designed for linear, progressive modes of learning not discovery and non-linearity. We sit kids (and adults) in rows, we talk at them, we present material front-to-back. In short, we don’t design education for learning, but for knowledge transmission. Complexity is all about learning. Every situation has a degree of novelty to it that presents new challenges and what happens today might not be the same thing that happens tomorrow even if much is similar. Teaching to discover, adapt, play and risk is something our system doesn’t do well. How can we expect complexity and systems thinking to thrive when the muscles used
2. It’s more convienient to think in dichotomies than spectrums. As I’ve written previously, spectral thinking is something critical to many of the issues we face in complex systems. Good/bad, strong/weak, X/Y lose their meaning in complex environments where there is a. Of all the dichotomies that work, only Ying/Yang comes close. But its a more difficult concept to grasp that maybe things aren’t all one way or the other, that there is use in even something that isn’t well constructed. This problem (and the ones that follow) are tied to the first one: education and learning systems are not set up for this. We are primed for either/or thinking. Think in criminal justice terms how easy it is to demand harsh punishment for criminal acts without considering that the perpetrators are human too, even if their behaviour is unacceptable.
The only dichotomy that works in complex systems?
3. Our decision-making tools are ill-equipped to handle ambiguity. Health care is a great example of how badly we do at complexity thinking. Consider the systematic review, often viewed as the gold standard for evidence for adoption into healthcare organizations. If it has a good systematic review, then the chances that we will see that evidence translated into practice is good, right? No. Surprisingly, even systematic reviews of systematic review use shows a mixed bag in adoption. Systematic reviews are designed to reduce ambiguity, but (for those on human social systems at least) they only illustrate how much there is. A systematic review only looks at the evidence created, it doesn’t include all those questions that were never asked, never funded for inquiry, or couldn’t be structured in a manner that fits the criteria for a good review. It is, by its design, reductionistic in its approach to complexity.
4. Our institutions are resistant to complexity. Complexity takes time, nuance, and relationship development; all the things that screw up plans. You can’t plan a relationship, but you can anticipate some things. You might even be able to use scenario tools and strategic foresight methods to anticipate what might happen, but you can’t plan it. John Lennon is right:
Life is what happens when you’re busy making other plans
While we plan, the complex systems move along. We can plan and fail, fail and plan, or plan to fail and work build the strategic foresight to know what to do with these “failures”.
So now what? Being aware of these things is a start, but making systems change is really the key. Making change is about questioning the way we have been taught to learn, and what our assumptions are about the universe are. Learning the difference between a simple, complicated, complex and chaotic system and the means to identify when those systems present themselves (and how they often change) is another. This means finding like minds, sharing stories, and building networks. It means creating space for relationships — even in our linear planning models if we must keep them (or better yet, get rid of most of them) — and considering what kind of returns we get from paying attention, being mindful of our systems, and what kind of things contemplative inquiry might offer that simple, detached data analysis does.
These are starting points, but not all of them. Addressing the challenge of complexity is, ironically or perhaps appropriately, complex. But the challenge of dealing with the negative outcomes resulting from overly simple approaches to dealing with complexity will ultimately be far more so.
Creating the Future Through Systems-Design Thinking
Posted: August 20, 2010 Filed under: complexity, design thinking, eHealth, innovation, science & technology, systems science, systems thinking | Tags: complexity science, design thinking, eHealth, ICT, innovation, organizational change, social innovation, systems thinking Comments Off
Back to the Future
Arturo Muente-Kunigami wrote in the World Bank’s Information and Communication Technology blog about the challenge of innovation and putting new information technology into practice in governments worldwide. Muente-Kunigami writes:
Most governments that introduce ICTs in their service delivery structure have basically applied technology to the exact same workflow they had before, replacing papers with emails and signatures with digital certificates. But ICTs in general – and broadband in particular – do not just improve the efficiency of governments. They have the potential to transform how governments work, redefining their relationship with citizens and expanding the array of services and transactions that could be provided and implemented.
This, however, is a very risky proposition for governments. And if most private companies rely on analytical thinking due to their overall aversion to risk, governments in most developing countries have a much less functional innovation system (in many cases, equivalent to a “copy-paste” function to be applied to “best practices” in other countries).
This is basically a ‘back-to-the-future’ problem: how to use the past to shape the future? How do we create best practices in areas where there are constant shifts, changes and altered contexts? Marty Neumaier would argue that we can’t. This is a design problem, not a knowledge transfer one. Muente-Kunigami also recognizes the potential for design thinking here and argues that governments need to follow their private sector peers in applying it to ICT and innovation:
So what is design thinking for governments anyway? It is not that much different than its private sector equivalent. It is about going back to the basics. And I mean the basics, trying to understand what citizens need from their governments (yes, that far back) and then answering the question: how could governments (hopefully, leveraging the new set of technologies and devices that exist today – and their spread among the general population) be able to satisfy these needs? Then, it is all about building prototypes, testing, trial and error, and of course a good set of evaluation and feedback mechanisms2.
This scary territory for a lot of organizations, particularly governments where decisions are not only shaped by history, but capital P politics. It’s also a language problem: Design gets equated with style instead of substance. Innovation is something done in business, not social and public services. Technology is something for wealthy nerds, not everyday citizens.
Marty Neumaier, Bruce Mau, Roger Martin and other design thinkers have been trying to shape this attitude, but it is an uphill battle. Language is one barrier, thinking differently is another. Both are challenges that I’ll address in future blogs, but the one I want to focus on here is the concept of best practices and the pull of the past on the present. Indeed, this is as good of an example of the power of an idea that you can find. Ideas may be the most powerful concept in human thinking as they shape the cognitive space that we inhabit by illustrating what is, what was, and what could be.
It is when what was becomes what could be that problems occur, particularly in the space of complex systems, which is where a great deal of government’s work is. Best practices is one of those ideas that is seductive because it reduces variation and provides a blueprint for how to handle problems. Indeed, best practices are pretty good when your problems are simple, or maybe even complicated at a very low level of abstraction, but lousy when you get into the realm of complexity.
Another point that Muente-Kunigami hints at is the systems problem; that is, the need to design systems to accommodate change. Implementing ICT-based strategies into a system straight-away is a recipe for failure. Technical systems do not enhance functionality without corresponding changes in social systems. An organizational shift in the way ICT is deployed is necessary if there is much chance of these tools and technologies living up to their potential. This, too, requires design thinking – in creating usable technologies and receptive social systems (including those that are literate enough to take advantage of them).
I would also argue that this approach requires an evaluation approach that supports incremental evaluation and rapid-response feedback like we see in developmental evaluation (PDF), which I discuss elsewhere.
Taken together, the future of government may well be in design, but to create this future we need both the systems and design thinking to make it one day be the past.
Indispensibility and Organizational Change
Posted: February 26, 2010 Filed under: Uncategorized | Tags: behaviour change, innovation, organizational change, organizational learning, Seth Godin, social innovation, systems change, systems thinking Comments Off
Seth Godin‘s recent book throws out the challenge to its readers to be indispensable in the jobs that they do. This is a tall order for most, but Godin points to ways of thinking, approaching problems and examples of how even the most mundane, mechanical jobs can be more when we bring the best of ourselves to what we do each day — no matter what the job is. He wants us all to reclaim our genius. The message is an unusual one in that it applies very well to individuals — you and me — but is a lot harder to apply at the organizational level. This is an important issue for those wanting to create better, healthier systems and it is here that the role of individual and system can get confounded.
Mike Myatt, from Blogging Innovation, wrote a critique of the indispensibility position in terms of its implications for organizations. His post, a fair and appreciative one regarding Seth’s position in many areas, is nonetheless critical of the idea of fostering indispensibility in firms:
A well managed company does not allow itself to become dependent upon the performance of any single individual. Those individuals who attempt to hoard knowledge, relationships, or resources to attain job security should not to be valued or viewed as indispensable, but should be admonished as ineffective and deemed a liability. Corporate talent that cannot be shared, duplicated, distributed, or leveraged is not nearly as valuable as talent that can.
It is here that I first disagree. Godin is not advocating for valuing the hoarder, rather he is suggesting the opposite: unparalleled sharing and generosity. Someone who hoards will not advance system change: period. Systems rely on exchange of information and intense conservation of knowledge or information reduces the response capacity of a system (which could be an organization). An organization that relies on a hoarder for survival hasn’t been paying attention or created processes of openness that allow information to move through the system. If you have a hoarder, one needs to ask: how did we create an organization that enabled that person to become so important? How can we transform it so that person’s unique talents can come out and that knowledge that is sharable and distributed gets to whomever it needs to when its needed?
I would like to address two of Myatt’s issues:
Myatt goes on:
In fact, I would go so far as to say that anyone who sets out to make themselves indispensable would be the one committing career suicide for two reasons:
- Anyone who is “perceived” as indispensable in their current role completely eliminates any possibility of promotion
- Any good leadership team who finds themselves dependant upon a linchpin will immediately move to mitigate the risk of finding themselves in such an untenable position
Regarding point 1: What would one promote themselves to? This pokes a hole at the dominant model of organizational development that suggests that promotions work vertically (including the entire thinking about why we need directions to move, embedded in the term “promotion”). When you’re the best salesperson on a team doing something you love and are good at and you get a “promotion” does it mean pulling you off the sales team into a management position, which may rely on a completely different skill and mindset? Does this really make sense?
Regarding point 2: If you have a real linchpin, your task is creating a dynamic, exciting environment to let them do their thing well. After all, they are linchpins precisely because they are good at what they do. You’re always in an “untenable position” of not being able to replace them because they are, by definition, unreplaceable. Do you have a work culture that brings in unique talent and nurtures it to allow it to succeed or do you try to create positions that are defined by a set of duties that can be done by anyone?
Myatt’s argument is counter to what Linchpin is all about in its approach. If you create standards and clearly defined roles and evaluate solely based on those standards, which is the position that is being argued from, you will suffer under a linchpin promotion strategy.
Maybe. At least, your business model will suffer.
But that misses the bigger point: Why build an organization around such a model to begin with? Maybe the system needs to change as much as the individuals within it. Maybe then, a linchpin promotion strategy doesn’t look so strange or problematic.
