Tag: psychology

psychology

The Developmental Psychology of Organizations

Organizations start change somewhere

Every living thing has a journey that starts somewhere and ends eventually. Our ability to see this, understand it, and apply what we know about how humans grow and develop (as individuals and organizations) is what helps us determine how this journey unfolds and where it ends up.

The psychology of individuals is a complicated affair that involves understanding a variety of matters from personal and family history, genetics, cultural context, education, and social situating. While all of these contribute to who we are as people, the degree of influence and mix is different from person to person. It means that we are all a product of a collection of forces that combine together in various ways that make understanding how we change a challenge because of this holistic complexity.

For example, some of us might have behaviours and preferences associated with a certain personality type (extroverted and introverted) and find that quality to be relatively stable across the lifespan. While there are times we might exhibit qualities of another type, those are more situational than stable. For those who are more of an ambivert, identification with a particular preference might be more challenging. Whatever investment you place in this kind of personality assessment, what is important is that the stability and consistency of certain characteristics are what largely shapes our identity to others (and ourselves). It’s what makes us ‘us’.

From Individuals to Organizations

It has been argued that organizations exhibit much of the same kind of characteristic habits on their own while providing an aggregation of the characteristics of those within them and leading them to various degrees. Personality theory has been applied to organizational behaviour as a means of understanding how it is that certain actions, activities, habits, and patterns form from within organizations and their implications. This involves taking ideas developed for individuals and applying them to groups and the implications of this are considerable.

If we are to consider organizations similar to humans seriously, it can have significant implications for the way in which we engage in organizational change efforts. Much of the research on organizational change is tied to the development and implementation of a strategy. Strategy, in most conventional applications, is an expression of intent manifest through specific choices of focus and action. This approach rests largely on a cognitive rational model of change (pdf) where information (e.g., data, ‘facts’, perceptions, beliefs, and opinion) guides an assessment of the situation that forms the basis for a plan of action. The idea is that we see and learn things and plan and act according to that knowledge.

Most individual behaviour change models are founded on this approach that has thinking preceding action in a relatively rational, logical manner based on an objective assessment of the facts and evidence (with some emotional contributions here and there to make life interesting). So if we tie organizational change to the similar kind of mechanisms and models that we use to understand individuals, should we not apply similar modes of change facilitation? We do — but its how we do it that might be the problem.

Change Theory to Change Reality

One of the most vexing (and little discussed) issues for behavioural scientists is that the application of the cognitive rational model to personal, organizational, and social change has a rather unimpressive track record. A look at how people change finds that relatively little change comes from rationally reviewing a threat or opportunity and planning out a strategy (nevermind executing the planned strategy as envisioned). Even when the effects are modest, factors such as the match between the person, technique or intervention approach, and the problem being addressed continues to mediate the outcomes.

What happens when our theories and our practices don’t really work? Or at least don’t work as well as we think they do?

The answer — using the very argument that we are looking to disprove — is that we will address the matter as many individuals might: disagreement, resistance, and denial.

The field of organizational decision-making and innovation is littered with case studies that show how, in the face of overwhelming evidence to the contrary, organizations (like many individuals) resist change. Whether it was the speed at which those on the Titanic accepted the fact that their ship would sink after hitting the iceberg (nevermind the perception that the ship was invulnerable, to begin with) or companies who persist with a strategy that doesn’t match with changing times (e.g., Kodak and it’s photographic film business, Sears and its retail model), the inability to see, unwillingness to perceive or accept changing situations has led to major problems.

These problems are a matter of failing to change or adapt. To quote from The Leopard:

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

Change is something we need to do even if that is simply to maintain the status quo.

Person-Centred Organizational Change

Erik Eriksen, the Austrian-American psychoanalyst whose work focused on identity formation and development, was among the few to challenge the belief that people’s essential character was immutable and resistant to change. (The dominant view was that thinking and behaviour could change, but not ‘how one was’ as a person). He did, however, acknowledge that our ability to change who we are was not easy and takes a lifetime. This flies in the face of the dominant thinking in Western societies that we can make dramatic changes in an instant.

While talk-shows and popular self-books are filled with stories of dramatic transformation and inspiration about how you can change everything in an instant, the truth is that these cases are outliers (and often exaggerations) or misrepresentations. Much like the artist who ‘breaks out’ and becomes an ‘overnight sensation’ the journey to stardom is usually a long one that follows a Pareto distribution (that is a long, slow climb over time followed by very quick punctuation at the end). What is misread into these success stories is that the rapid change is a factor of a long, protracted build-up.

While there are some things that do follow this pattern much change is also linear and progressive. We see this in the work of another Ericsson: Anders Ericsson. His work is widely cited (and mis-cited) as being behind the ‘10,000 Hour Rule’ that suggests that expertise — a change from an unskilled novice to a skilled expert — is developed over that much time of practice. While the time itself is important, what is often missed in the citation of this work is that the key is on deliberative practice (pdf), which makes all the difference.

If we extrapolate from the work of both Eriksen/Ericsson’s we might develop a model of behaviour change that looks quite different than we have at present. Instead of trying 5-year plans, strategic goals, and inspirational visions of the future, we might be better off delving into an organization’s past, it’s formation, it’s core beliefs and personality, and spend more time looking at what it is already doing than what it seeks to do.

Developmental Organizations

We might then find what it seeks to deliberate on day-in-and-out and emphasize the ways in which to amplify the feedback that helps people learn deliberately and consistently. We might take these lessons — much like those small, tiny adjustments that expert violinists, athletes, and surgeons make to hone their craft — and make them visible and build on them. We would look upon organizations as developing organizations using approaches that fit with them developmentally (e.g., developmental evaluation). We would treat organizations like we would people.

Which is kind of funny because organizations are made of people. That’s some change.

Photo by Stanislav Kondratiev on Unsplash

behaviour changebusinessdesign thinking

How do we sit with time?

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Organizational transformation efforts from culture change to developmental evaluation all depend on one ingredient that is rarely discussed: time. How do we sit with this and avoid the trap of aspiring for greatness while failing to give it the time necessary to make change a reality? 

Toolkits are a big hit with those looking to create change. In my years of work with organizations large and small supporting behaviour change, innovation, and community development there are few terms that light up people’s faces than hearing “toolkit”. Usually, that term is mentioned by someone other than me, but it doesn’t stop the palpable excitement at the prospect of having a set of tools that will solve a complex problem.

Toolkits work with simple problems. A hammer works well with nails. Drills are good at making holes. With enough tools and some expertise, you can build a house. Organizational development or social change is a complex challenge where tools don’t have the same the same linear effect. A tool — a facilitation technique, an assessment instrument, a visualization method — can support change-making, but the application and potential outcome of these tools will always be contextual.

Tools and time

My experience has been that people will go to great extents to acquire tools yet put little comparative effort to use them.  A body of psychological research has shown there are differences between goals, the implementation intentions behind them, and actual achievement of those goals. In other words: desiring change, planning and intending to make a change, and actually doing something are different.

Tools are proxies for this issue in many ways: having tools doesn’t mean they either get used or that they actually produce change. Anyone in the fitness industry knows that the numbers between those who try a workout, those who buy a membership to a club, and those who regularly show up to workout are quite different.

Or consider the Japanese term Tsundoku, which loosely translates into the act of acquiring reading materials and letting them pile up in one’s home without reading them.

But tools are stand-ins for something far more important and powerful: time.

The pursuit of tools and their use is often hampered because organizations do not invest in the time to learn, appropriately apply, refine, and sense-make the products that come through these tools.

A (false) artifact of progress

Bookshelf

Consider the book buying or borrowing example above: we calculate the cost of the book when really we ought to price out the time required to read it. Or, in the case of practical non-fiction, the cost to read it and apply the lessons from it.

Yet, consider a shelf filled with books before you providing the appearance of having the knowledge contained within despite any evidence that its contents have been read. This is the same issue with tools: once acquired it’s easier to assume the work is largely done. I’ve seen this firsthand with people doing what the Buddhist phrase decries:

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

It’s the same confusion we see between having data or models and the reality they represent.

These things all represent artifacts of progress and a false equation. More books or data or better models do not equal more knowledge. But showing that you have more of something tangible is a seductive proxy. Time has no proxy; that’s the biggest problem.

Time just disappears, is spent, is used, or whatever metaphor you choose to use to express time. Time is about Kairos or Chronos, the sequence of moments or the moments themselves, but in either case, they bear no clear markers.

Creating time markers

There are some simple tricks to create the same accumulation effect in time-focused work — tools often used to support developmental evaluation and design. Innovation is as much about the process as it is the outcome when it comes to marking effort. The temptation is to focus on the products — the innovations themselves — and lose what was generated to get there. Here are some ways to change that.

  1. Timelines. Creating live (regular) recordings of what key activities are being engaged and connecting them together in a timeline is one way to show the journey from idea to innovation. It also provides a sober reminder of the effort and time required to go through the various design cycles toward generating a viable prototype.
  2. Evolutionary Staging. Document the prototypes created through photographs, video, or even showcasing versions (in the case of a service or policy where the visual element isn’t as prominent). This is akin to the March of Progress image used to show human evolution. By capturing these things and noting the time and timing of what is generated, you create an artifact that shows the time that was invested and what was produced from that investment. It’s a way to honour the effort put toward innovation.
  3. Quotas & Time Targets. I’m usually reluctant to prescribe a specific amount of time one should spend on reflection and innovation-related sensemaking, but it’s evident from the literature that goals, targets, and quotas work as effective motivators for some people. If you generate a realistic set of targets for thoughtful work, this can be something to aspire to and use to drive activity. By tracking the time invested in sensemaking, reflection, and design you better can account for what was done, but also create the marker that you can point to that makes time seem more tangible.

These are three ways to make time visible although it’s important to remember that the purpose isn’t to just accumulate time but to actually sit with it.

All the tricks and tools won’t bring the benefit of what time can offer to an organization willing to invest in it, mindfully. Except, perhaps, a clock.

Try these out with some simple tasks. Another is to treat time like any other resource: budget it. Set aside the time in a calendar by booking key reflective activities in just as you would anything else. To do this, and to keep to it, requires leadership and the organizational supports necessary to ensure that learning can take place. Consider what is keeping you from taking or making the time to learn, share those thoughts with your peers, and then consider how you might re-design what you do and how you do it to support that learning.

Take time for that, and you’re on your way to something better.

 

If you’re interested in learning more about how to do this practically, using data, and designing the conditions to support innovation, contact me. This is the kind of stuff that I do. 

 

 

 

 

 

complexityevaluationsocial innovation

Developmental Evaluation’s Traps

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

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

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

Powerful stuff.

Except, it can also be a trap.

It’s a Trap!

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

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

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

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

A different approach, same resourcing

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

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

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

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

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

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

The pivot problem

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

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

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

Fearing success

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

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

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

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

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

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

Keeping the parking brake on

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

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

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

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

Sealing the trap door

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

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

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

 

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

Image credit: Author

behaviour changebusinesspublic healthsocial mediasystems science

Genetic engineering for your brand

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DNA doesn’t predetermine our future as biological beings, but it does powerfully influence it. Some have applied the concept of ‘DNA’ to a company or organization, in the same way, it’s applied to biological organisms. Firms like PWC have been at the forefront of this approach, developing organizational DNA assessments and outlining the principles that shape the DNA of an organization. A good brand is an identity that you communicate with yourself and the world around you. A healthy brand is built on healthy DNA.

Tech entrepreneur and writer Om Malik sees DNA as being comprised of those people that form the organization:

DNA contains the genetic instructions used to build out the cells that make up an organism. I have often argued that companies are very much like living organisms, comprised of the people who work there. What companies make, how they sell and how they invent are merely an outcome of the people who work there. They define the company.

The analogy between the DNA of a company as being that of those who make it up is apt because, as he points out, organizations reflect the values, habits, mindsets, and focus of those who run them. For that reason, understanding your organizations’ DNA structure might be critical to shaping the corporate direction, brand and promoting any type of change, as we see from the case of Facebook.

DNA dilemma: The case of Facebook

Facebook is under fire these days. To anyone paying enough attention to the social media giant the issue with Facebook isn’t that it’s happening now, but why it hasn’t happened sooner? Back when the site was first opened up to allow non-university students to have accounts (signaling what would become the global brand it is today) privacy was a big concern. I still recall listening to a Facebook VP interviewed on a popular tech podcast who basically sloughed off any concerns the interviewer had about privacy saying the usual “we take this seriously” stuff but offering no example of how that was true just as the world was about to jump on the platform. I’ve heard that same kind of interview repeated dozens of times since the mid-2000’s, including just nine months before Mark Zuckerberg’s recent ‘mea culpa’ tour.

Facebook has never been one to show much (real) attention to privacy because its business model is all about ensuring that users’ are as open as possible to collect as much data as possible from them to sell as many services to them, through them, about them, and for others to manipulate. The Cambridge Analytica story simply exposed what’s been happening for years to the world.

Anyone who’s tried to change their privacy settings knows that you need more than a Ph.D. to navigate them* and, even then, you’re unlikely to be successful. Just look at the case of Bobbi Duncan and Katie McCormick who were outed as gay to their families through Facebook even though they had locked down their own individual privacy settings. This is all part of what CEO Mark Zuckerberg and the folks at Facebook refer to as “connecting the social graph.”

The corporate biology of addiction

In a prescient post, Om Malik wrote about Facebook’s addiction to its business model based on sharing, openness, and exploitation of its users’ information mere weeks before the Cambridge Analytica story came out.

Facebook’s DNA is that of a social platform addicted to growth and engagement. At its very core, every policy, every decision, every strategy is based on growth (at any cost) and engagement (at any cost). More growth and more engagement means more data — which means the company can make more advertising dollars, which gives it a nosebleed valuation on the stock market, which in turn allows it to remain competitive and stay ahead of its rivals.

Whether he knew it or not, Malik was describing an epigenetic model of addiction. Much emerging research on addiction has pointed to a relationship between genes and addictive behaviour. This is a two-way street where genes influence behaviour and behaviour influences a person’s genes (something called epigenetics). The more Facebook seeks to connect through its model, the more it reinforces the behaviour, the more it feels a ‘need’ to do it and therefore repeats it.

In systems terms, this is called a reinforcing loop and is part of a larger field of systems science called systems dynamics. Systems dynamics have been applied to public health and show how we can get caught in traps and the means we use to get out of them.  By applying an addiction model and system dynamics to the organization, we might better understand how some organizations change and how some don’t.

Innovation therapy

The first step toward any behaviour change for an addiction is to recognize the addiction in the first place. Without acknowledgment of a problem, there can’t be much in the way of self-support. This acknowledgment has to be authentic, which is why there is still reason to question whether Facebook will change.

There are many paths to addiction treatment, but the lessons from treating some of the most pernicious behaviours like cigarette smoking and alcohol suggest that it is likely to succeed when a series of small, continuous, persistent changes are made and done so in a supportive environment. One needs to learn from each step taken (i.e., evaluate progress and outcomes from each step), to integrate that learning, and continue through the inevitable cycling through stages (non-linear change) that sometimes involves moving backward or not knowing where along the change journey you are.

Having regulations or external pressures to change can help, but too much can paralyze action and stymie creativity. And while being motivated to change is important, sometimes it helps to just take action and let the motivation follow.

If this sounds a lot like the process of innovation, you’re right.

Principled for change

Inspiring change in an organization, particularly one where there is a clear addiction to a business model (a way of doing things, seeing things, and acting) requires the kind of therapy that we might see in addiction support programs. Like those programs, there isn’t one way to do it, but there are principles that are common. These include:

  1. Recognize the emotional triggers involved. Most people suffering from addictions can rationalize the reasons to change, but the emotional reasons are a lot harder. Fear, attraction, and the risk of doing things differently can bubble up when you least expect it. You need to understand these triggers, deal with the emotional aspects of them — the baggage we all bring.
  2. Change your mindset. Successful innovation involves a change of practice and a change of mindset. The innovator’s mindset goes from a linear focus on problems, success, and failure to a non-linear focus on opportunities, learning, and developmental design.  This allows you to spot the reinforcing looping behaviour and addiction pathways as well as what other pathways are open to you.
  3. Create better systems, not just different behaviour. Complex systems have path-dependencies — those ruts that shape our actions, often unconsciously and out of habit. Consider ways you organize yourself, your organization’s jobs and roles, the income streams, the system of rewards and recognitions, the feedback and learning you engage with, and composition of your team.  This rethinking and reorganization are what changes DNA, otherwise, it will continue to express itself through your organization in the same way.
  4. Make change visible. Use evaluation as a means to document what you do and what it produces and continue to structure your work to serve the learning from this. Inertia comes from having no direction and nothing to work toward. We are beings geared towards constant motion and making things — it’s what makes us human. Make a change, by design. Make it visible through evaluation and visual thinking – including the ups, downs, sideways. A journey involves knowing where you are — even if that’s lost — and where you’re going (even if that changes).

Change is far more difficult than people often think. Change initiatives that are rooted solely in motivation are unlikely to produce anything sustainable. You need to get to the root, the DNA, of your organization and build the infrastructure around it to enable it to do the work with you, not against you. That, in Facebook terms, is something your brand and its champions will truly ‘Like’.

 

* Seriously. I have a Ph.D. and am reasonably tech literate and have sat down with others with similar educational backgrounds — Ph.D.’s, masters degrees, tech startup founders — and we collectively still couldn’t figure out the privacy settings as a group.

References: For those interested in system dynamics or causal loop modeling, check out this great primer from Nate Osgood at the University of Saskatchewan. His work is top-notch. Daniel Kim has also written some excellent, useful, and practical stuff on applying system dynamics to a variety of issues.

Image credit: Shutterstock used under license.

design thinkingpsychologyresearch

Elevating Design & Design Thinking

 

ElevateDesignLoft2.jpgDesign thinking has brought the language of design into popular discourse across different fields, but it’s failings threaten to undermine the benefits it brings if they aren’t addressed. In this third post in a series, we look at how Design (and Design Thinking) can elevate themselves above their failings and match the hype with real impact. 

In two previous posts, I called out ‘design thinkers’ to get the practice out of it’s ‘bullshit’ phase, characterized by high levels of enthusiastic banter, hype, and promotion and low evidence, evaluation or systematic practice.

Despite the criticism, it’s time for Design Thinking (and the field of Design more specifically) to be elevated beyond its current station. I’ve been critical of Design Thinking for years: its popularity has been helpful in some ways, problematic in others.  Others have, too. Bill Storage, writing in 2012 (now unavailable), said:

Design Thinking is hopelessly contaminated. There’s too much sleaze in the field. Let’s bury it and get back to basics like good design.

Bruce Nussbaum, who helped popularize Design Thinking in the early 2000’s called it a ‘failed experiment’, seeking to promote the concept of Creative Intelligence instead. While many have called for Design Thinking to die, it’s not going to happen anytime soon. Since first publishing a piece on Design Thinking’s problems five years ago the practice has only grown. Design Thinking is going to continue to grow, despite its failings and that’s why it matters that we pay attention to it — and seek to make it better.

Lack of quality control, standardization or documentation of methods, and evidence of impact are among the biggest problems facing Design Thinking if it is to achieve anything substantive beyond generating money for those promoting it.

Giving design away, better

It’s hard to imagine that the concepts of personality, psychosis, motivation, and performance measurement from psychology were once unknown to most people. Yet, before the 1980’s, much of the public’s understanding of psychology was confined to largely distorted beliefs about Freudian psychoanalysis, mental illness, and rat mazes. Psychology is now firmly ensconced in business, education, marketing, public policy, and many other professions and fields. Daniel Kahneman, a psychologist, won the Nobel Prize in Economics in 2002 for his work applying psychological and cognitive science to economic decision making.

The reason for this has much to do with George Miller who, as President of the American Psychological Association, used his position to advocate that professional psychology ‘give away’ its knowledge to ensure its benefits were more widespread. This included creating better means of communicating psychological concepts to non-psychologists and generating the kind of evidence that could show its benefits.

Design Thinking is at a stage where we are seeing similar broad adoption beyond professional design to these same fields of business, education, the military and beyond. While there has been much debate about whether design thinking as practiced by non-designers (like MBA’s) is good for the field as a whole, there is little debate that its become popular just as psychology has.

What psychology did poorly is that it gave so much away that it failed to engage other disciplines enough to support quality adoption and promotion and, simultaneously, managed to weaken itself as newfound enthusiasts pursued training in these other disciplines. Now, some of the best psychological practice is done by social workers and the most relevant research comes from areas like organizational science and new ‘sub-disciplines’ like behavioural economics, for example.

Design Thinking is already being taught, promoted, and practiced by non-designers. What these non-designers often lack is the ‘crit’ and craft of design to elevate their designs. And what Design lacks is the evaluation, evidence, and transparency to elevate its work beyond itself.

So what next?

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Elevating Design

As Design moves beyond its traditional realms of products and structures to services and systems (enabled partly by Design Thinking’s popularity) the implications are enormous — as are the dangers. Poorly thought-through designs have the potential to exacerbate problems rather than solve them.

Charles Eames knew this. He argued that innovation (which is what design is all about) should be a last resort and that it is the quality of the connections (ideas, people, disciplines and more) we create that determine what we produce and their impact on the world. Eames and his wife Ray deserve credit for contributing to the elevation of the practice of design through their myriad creations and their steadfast documentation of their work. The Eames’ did not allow themselves to be confined by labels such as product designer, interior designer, or artist. They stretched their profession by applying craft, learning with others, and practicing what they preached in terms of interdisciplinarity.

It’s now time for another elevation moment. Designers can no longer be satisfied with client approval as the key criteria for success. Sustainability, social impact, and learning and adaptation through behaviour change are now criteria that many designers will need to embrace if they are to operate beyond the fields’ traditional domains (as we are now seeing more often). This requires that designers know how to evaluate and study their work. They need to communicate with their clients better on these issues and they must make what they do more transparent. In short: designers need to give away design (and not just through a weekend design thinking seminar).

Not every designer must get a Ph.D. in behavioural science, but they will need to know something about that domain if they are to work on matters of social and service design, for example. Designers don’t have to become professional evaluators, but they will need to know how to document and measure what they do and what impact it has on those touched by their designs. Understanding research — that includes a basic understanding of statistics, quantitative and qualitative methods — is another area that requires shoring up.

Designers don’t need to become researchers, but they must have research or evaluation literacy. Just as it is becoming increasingly unacceptable that program designers from fields like public policy and administration, public health, social services, and medicine lack understanding of design principles, so is it no longer feasible for designers to be ignorant of proper research methods.

It’s not impossible. Clinical psychologists went from being mostly practitioners to scientist-practitioners. Professional social workers are now well-versed in research even if they typically focus on policy and practice. Elevating the field of Design means accepting that being an effective professional requires certain skills and research and evaluation are now part of that skill set.

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Designing for elevated design

This doesn’t have to fall on designers to take up research — it can come from the very people who are attracted to Design Thinking. Psychologists, physicians, and organizational scientists (among others) all can provide the means to support designers in building their literacy in this area.

Adding research courses that go beyond ethnography and observation to give design students exposure to survey methods, secondary data analysis, ‘big data’, Grounded Theory approaches, and blended models for data collection are all options. Bring the behavioural and data scientists into the curriculum (and get designers into the curriculum training those professionals).

Create opportunities for designers to do research, publish, and present their research using the same ‘crit’ that they bring to their designs. Just as behavioural scientists expose themselves to peer review of their research, designers can do the same with their research. This is a golden opportunity for an exchange of ideas and skills between the design community and those in the program evaluation and research domains.

This last point is what the Design Loft initiative has sought to do. Now in its second year, the Design Loft is a training program aimed at exposing professional evaluators to design methods and tools. It’s not to train them as designers, but to increase their literacy and confidence in engaging with Design. The Design Loft can do the same thing with designers, training them in the methods and tools of evaluation. It’s but one example.

In an age where interdisciplinarity is spoken of frequently this provides the means to practically do it and in a way that offers a chance to elevate design much like the Eames’ did, Milton Glaser did, and how George Miller did for psychology. The time is now.

If you are interested in learning more about the Design Loft initiative, connect with Cense. If you’re a professional evaluator attending the 2017 American Evaluation Association conference in Washington, the Design Loft will be held on Friday, November 10th

Image Credit: Author

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A mindset for developmental evaluation

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Developmental evaluation requires different ways of thinking about programs, people, contexts and the data that comes from all three. Without a change in how we think about these things, no method, tool, or approach will make an evaluation developmental or its results helpful to organizations seeking to innovate, adapt, grow, and sustain themselves. 

There is nothing particularly challenging about developmental evaluation (DE) from a technical standpoint: for the most part, a DE can be performed using the same methods for data collection as other evaluations. What stands DE apart from those other evaluations is less the methods and tools, but the thinking that goes into how those methods and tools are used. This includes the need to ensure that sensemaking is a part of the data analysis plan because it is almost certain that some if not the majority of the data collected will not have an obvious meaning or interpretation.

Without developmental thinking and sensemaking, a DE is just an evaluation with a different name

This is not a moot point, yet the failure of organizations to adopt a developmental mindset toward its programs and operations is (likely) the single-most reason for why DE often fails to live up to its promise in practice.

No child’s play

If you were to ask a five-year old what they want to be when they grow up you might hear answers like a firefighter, princess, train engineer, chef, zookeeper, or astronaut. Some kids will grow up and become such things (or marry accordingly for those few seeking to become princesses or they’ll work for Disney), but most will not. They will become things like sales account managers, marketing directors, restaurant servers, software programmers, accountants, groundskeepers and more. While this is partly about having the opportunity to pursue a career in a certain field, it’s also about changing interests.

A five-year old that wants to be a train engineer might seem pretty normal, but one that wants to be an accountant specializing in risk management in the environmental sector would be considered odd. Yet, it’s perfectly reasonable to speak to a 35-year-old and find them excited about being in such a role.

Did the 35-year-old that wanted to be a firefighter when they were five but became an accountant, fail? Are they a failed firefighter? Is the degree to which they fight fires in their present day occupation a reasonable indicator of career success?

It’s perfectly reasonable to plan to be a princess when you’re five, but not if you’re 35 or 45 or 55 years old unless you’re currently dating a prince or in reasonable proximity to one. What is developmentally appropriate for a five-year-old is not for someone seven times that age.

Further, is a 35-year-old a seven-times better five-year-old? When you’re ten are you twice the person you were when you were five? Why is it OK to praise a toddler for sharing, not biting or slapping their peers, and eating all their vegetables and weird to do it with someone in good mental health in their forties or fifties? It has to do with developmental thinking.

It has to do with a developmental mindset.

Charting evolutionary pathways

We know that as people develop through stages, ages and situations the knowledge, interests, and capacities that a person has will change. We might be the same person and also a different person than the one we were ten years ago. The reason is that we evolve and develop as a person based on a set of experiences, genetics, interests, and opportunities that we encounter. While there are forces that constrain these adaptations (e.g., economics, education, social mobility, availability of and access to local resources), we still evolve over time.

DE is about creating the data structures and processes to understand this evolution as it pertains to programs and services and help to guide meaningful designs for evolution. DE is a tool for charting evolutionary pathways and for documenting the changes over time. Just as putting marks on the wall to chart a child’s growth, taking pictures at school, or writing in a journal, a DE does much of the same thing (even with similar tools).

As anyone with kids will tell you, there are a handful of decisions that a parent can make that will have sure-fire, predictable outcomes when implemented. Many of them are created through trial-and-error and some that work when a child is four won’t work when the child is four and five months. Some decisions will yield outcomes that approximate an expected outcome and some will generate entirely unexpected outcomes (positive and negative). A good parent is one who pays attention to the rhythms, flows, and contexts that surround their child and themselves with the effort to be mindful, caring and compassionate along the way.

This results in no clear, specific prototype for a good parent that can reliably be matched to any kid, nor any highly specific, predictable means of determining who is going to be a successful, healthy person. Still, many of us manage to have kids we can proud of, careers we like, friendships we cherish and intimate relationships that bring joy despite no means of predicting how any of those will go with consistency. We do this all the time because we approach our lives and those of our kids with a developmental mindset.

Programs as living systems

DE is at its best a tool for designing for living systems. It is about discerning what is evolving (and at what rate/s) and what is static within a system and recognizing that the two conditions can co-exist. It’s the reason why many conventional evaluation methods still work within a DE context. It’s also the reason why conventional thinking about those methods often fails to support DE.

Living systems, particularly human systems, are often complex in their nature. They have multiple, overlapping streams of information that interact at different levels, time scales and to different effects inconsistently or at least to a pattern that is only partly ever knowable. This complexity may include simple relationships and more complicated ones, too. Just as a conservation biologist might see a landscape that changes, they can understand what changes are happening quickly, what isn’t, what certain relationships are made and what ones are less discernible.

As evaluators and innovators, we need to consider how our programs and services are living systems. Even something as straightforward as the restaurant industry where food is sought and ordered, prepared, delivered and consumed, then finished has elements of complexity to it. The dynamics of real-time ordering and tracking, delivery, shifting consumer demand, the presence of mobile competitors (e.g., food trucks), changing regulatory environment, novelty concepts (e.g., pop-ups!), and seasonality of food demand and supply has changed how the food preparation business is run.

A restaurant might not just be a bricks-and-mortar operation now, but a multi-faceted, dynamic food creation environment. The reason could be that even if they are good at what they did if everything around them is changing they could still deliver consistently great food and service and fail. They may need to change to stay the same.

This only can happen if we view our programs as living systems and create evaluation mechanisms and strategies that view them in that manner. That means adopting a developmental mindset within an organization because DE can’t exist without it.

If a developmental evaluation is what you need or you want to learn more about how it can serve your needs, contact Cense and inquire about how they can help you. 

Image Credit: Thinkstock used under license.

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Reframing change

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Change is one of the few universal constants as things — people, planet, galaxy — are always in some state of movement, even if it’s imperceptible. Change is also widely discussed and desired, but often never realized in part because we’ve treated something nuanced as over-simplified; it’s time to change. 

For something so omnipresent in our universe, change is remarkably mysterious.

Despite the enormous amount of attention paid to the concept of change, innovation, creation, creativity, and such we have relatively little knowledge of change itself. A look at the academic literature on change would suggest that most of human change is premeditated, planned and rational. Much of this body of literature is focused on health behaviours and individual-level change and draws on a narrow band of ‘issues’ and an over-reliance on linear thinking. At the organization level, evidence on the initiation, success, and management of change is scattered, contradictory and generally bereft of clear, specific recommendations on how to deal with change. Social and systems change are even more elusive, with much written on concepts like complexity and system dynamics without much evidence to guide how those concepts are to be practically applied.

Arguments can be made that some of the traditional research designs don’t work for understanding complex change and the need to match the appropriate research and intervention design to the type of system in order to be effective.  These are fair, useful points. However, anyone engaged in change work at the level where the work is being done, managed and led might also argue that the fit between change interest, even intention, and delivery is far lower than many would care to admit.

The issue is that without the language to describe what it is we are doing, seeing and seeking to influence (change) it’s easy to do nothing — and that’s not an option when everything around us is changing.

Taking the plunge

“The only way to make sense out of change is to plunge into it, move with it, and join the dance.” – Alan Watts

Dogs, unlike humans, never take swim lessons. Yet, a dog can jump into a lake for the first time and start swimming by instinct. Humans don’t fare as well and it is perhaps a good reason why we tend to pause when a massive change (like hopping in a pool or a lake) presents itself and rely both on contemplation and action — praxis — to do many things for the first time. Still, spend any time up near a cottage or pool in the summer and you’ll see people swimming in droves.

The threat of water, change of fear of the unknown doesn’t prevent humans from swimming or riding a bike or playing a sport or starting a new relationship despite the real threats (emotional, physical, and otherwise) that come with all of them.

Funny that we have such a hard time drawing praxis, patience, and sensemaking into our everyday work in a manner that supports positive change, rather than just reactive change. The more we can learn about what really supports intentional change and create the conditions that support that, the more likely we’ll be swimming and not just stuck on the shore.

Whatever it takes

“If you don’t like change, you’re going to like irrelevance even less.”—General Eric
Shinseki, retired Chief of Staff, U. S. Army

“It’s just not a good time right now”

“We’re really busy”

“I’m just waiting on (one thing)”

“We need more information”

These are some of the excuses that individuals and organizations give for not taking action that supports positive change, whatever that might be. Consultants have a litany of stories about clients who hired them to support change, develop plans, even set out things like SMART goals, only to see little concrete action take place; horses are led to water, but nothing is consumed.

One of the problems with change is that it is lumped into one large category and treated as if it is all the same thing: to make or become different (verb) or the act or instance of making or becoming different (noun). It’s not. Just as so many things like waves, moods, or decision-making strategies are different, so too is change. Perhaps it is because we continue to view change as a monolithic ‘thing’ without the nuance that we afford other similarly important topics that we have such trouble with it. It’s why surfers have a language for waves and the conditions around the wave: they want to be better at riding them, living with them and knowing when to fear and embrace them.

What is similar to the various forms that change might take is the threat of not taking it seriously. As the above quote articulates, the threat of not changing is real even if won’t be realized right away. Irrelevance might be because you are no longer doing what’s needed, offering value, or you’re simply not effective. Unfortunately, by the time most realize they are becoming irrelevant they already are.

Whatever it takes requires knowing whatever it takes and that involves a better sense of what the ‘it’ (change) is.

Surfing waves of change

To most of us, waves on the beach are classified as largely ‘big’ or ‘small’ or something simple like that. To a surfer, the conversation about a wave is far more delicate, nuanced and far less simplistic. A surfer looks at things like wind speed, water temperature, the location of the ‘break’ and the length of the break, the vertical and horizontal position of the wave and the things like the length of time it takes to form. Surfers might have different names for these waves or even no words at all, just feelings, but they can discern differences and make adjustments based on these distinctions.

When change is discussed in our strategic planning or organizational change initiatives, it’s often described in terms of what it does, rather than what it is. Change is described as ‘catastrophic‘ or ‘disruptive‘ or simply hard, but rarely much more and that is a problem for something so pervasive, important, and influential on our collective lives. It is time to articulate a taxonomy of change as a place to give change agents, planners, and everyone a better vocabulary for articulating what it is they are doing, what they are experiencing and what they perceive.

By creating language better suited to the actual problem we are one step further toward being better at addressing change-related problems, adapting, and preventing them than simply avoiding them as we do now.

Time to take the plunge, get into the surf and swim around.

 

 

Image credit: June 17, 2017 by Mike Sutherland used under Creative Commons License via Flickr. Thanks for sharing Mike!