Snowshoeing five years ago, on the Palouse Divide

A nod to Jake Leachman, good friend and debating partner for the title.  Check out his blog:  hydrogen.wsu.edu!

One of the key things to understanding the answer to the evolution of servant leadership — and yes, the concept has to evolve — is to understand the likely mindset of Jim Collins, the inventor of the term, when he made it.  There’s lots of data, with his definition of servant leadership, that Collins is firmly ensconced in the Performance v-Meme (what does it take to have enduring financial performance is a huge theme of his writing), and then that tracks to the Inner Hedgehog (the one thing one’s company does well, subject to constraints.)  Collins makes the point that one can’t become a servant leader without his or her employees connecting profoundly with him or her — which at some level, implies an independent, trust-based, data driven relationship — that has to be reciprocated, as much as is possible.  Pretty Communitarian v-Meme, if you ask me.

And for those that remember past posts, that all fits.  Someone in the Performance v-Meme is going to allude in a meaningful way to the v-Meme above them as being core to leadership — in this case, building a community where individuals are valued.

But after, or really above that, it’s also no surprise that things start to run dry.  It’s been a while since I read the book, but I can’t remember any nod at all to Self Awareness (Global Systemic — Tier 2 V-meme).  And on up, it doesn’t get any better.  Collins, with his prescriptive Hedgehog, doesn’t even consider the Global Holistic obligations any truly evolved leader has in today’s global marketplace.  In fact, he might very well consider it a conflict — out of the range — or compacted down into the elusive nature of servant leadership which he says is poorly understood.  How do you build the core integrity of a low probability, magical animal?  Like every other business writer, Collins is v-Meme limited.  It’s gonna get down to things like ‘spirituality’ sooner or later — that ‘nod to God’.

And it’s also no surprise that there are Coral/Bodhisattva allusions.  One thing I’ve seen is that open-minded people can recognize enlightenment when they see it, even if they’re going to have a hard time getting there themselves.  One of my favorite little anecdotes is traveling around the world and finding people like the movie ‘Groundhog Day’.  People get the enlightenment path — even if it’s staged in Punxsutawney, PA.

Collins pulled his definition out of an exhaustive, algorithmic search, with a little heuristic messing-about where he used his own personal judgment.  He did it from data collected in the ’90s — in so many ways, a very different world.  And then he pulled the 11 companies out from his own judgment after he applied his rubric.

I want to reiterate — there is nothing wrong with that.  And the concept of servant leadership, I’d argue, is fundamentally a Spiral/Empathetic Ladder.  Good on him.  But how can we build on his insight, as our societies continue to evolve?  What might an Evolved Hedgehog look like?

Enter Servant Leadership 2.0.  The biggest leap  to be made from Servant Leadership 1.0 (Collins’ model) is the idea that the Servant Leader is aware of their own motivations in their actions.  Why is that important?  Because then the Servant Leader has the potential for self-compensatory feedback.  They don’t need someone else at their level to tell them about themselves (though outside influences and coaches never hurt!)  They are aware of their own Confirmation Bias, and instead of searching out case studies and data that support their worldview, are aware of knowledge coming their way that doesn’t support their worldview.  And, as an extension, are accepting of that.  Confirmation Bias is a huge vector for down converting Heuristic Thinking to Algorithmic Thinking.  Self-awareness can prevent that.

What that does, more than anything else, is prevent the shift in one’s thinking, out of Roger Martin’s Heuristic down to Algorithmic thinking.  Confirmation Bias is a huge vector for down converting Heuristic Thinking to Algorithmic Thinking.  Self-awareness can prevent that.  It keeps one data-driven, instead of, over time, creating a set of beliefs that become more rigid.  It keeps meta-cognition alive, and keeps the individual Servant Leader on an evolutionary path. Which then makes that person more resilient in the face of change, and more open to input channels from especially younger employees, as the tools and paradigms available for business change.

But most importantly, what it likely does is this:

It makes it more possible for the Servant Leader to collaborate across other industries/divisions with equivalent personalities. Or even non-equivalent, less-evolved individuals.

Why does this matter so much?

One of the things that has been bothering me quite a bit in my thinking are Beck’s statistics on percentages of individuals occupying various v-Memes.  Most of the information I’ve received comes from web pages, and these, for some reason, vanish and reappear.  Not very encouraging.  But there are a couple of numbers that stick in my head:

Performance v-Memes in the US population:  30%

Communitarian v-Memes in the US population ~ 10-20%

Global Systemic v-Memes ~ 1%

Global Holistic v-Memes ~.1%

So, let’s think of the implications.  What this means is that the odds that someone with a global perspective, with an evolved sense of global empathy and the decision-making ability to create meaningful management and change, is basically 0%.

Yet what we see is that there are global corporations.  Their behavior ranges on a spectrum from a moral good -> bad scale (I’m not going to list the bad actors, but it’s not hard to guess) and they’re proceeding apace.  How can that be?  Is Spiral Dynamics wrong?

I think what we are seeing is the emergence of combined higher thinking in management teams across global enterprises.  Global enterprises require global thinking — there’s simply no way to get away from the fundamental exigencies of the situation.  And so, true to form, global thinking becomes emergent.  Networks of individuals embody the communication needs across continents and countries, and start the process of evolving the people inside.

That does not mean that a more profound empathy is always created — one that satisfies our moral codes for justice, egalitarian treatment, and human and environmental rights.  Those types of values must be developed more deeply in the scaffolding of organizations, and cannot come without interaction with governments, NGOs, and basic populations.  As has been discussed before, diversity is key.  But it is hard to argue that Amazon or Shell isn’t globally interactive.  They may be, in certain ways, pathological because of poor scaffolding — a recent siting of an Amazon computing cloud in Dayton, driven by the desire for cheap, coal-powered electricity might be an example.  More progressive players like Apple and Google, in announcing their data centers, for example, said they would be powered 100% by renewables.  But this is likely a result of poor scaffolding — not the lack of global thinking and the demanding interconnectivity it requires.

What is likely required for the modern corporation, then, is the more achievable goal of Servant Leadership 2.0 — an evolved mindfulness of the individual leader.  And that may lead to fixing the larger deficits we see in corporate governance across the planet.

Takeaways:  Servant leadership, defined as elusive, and potentially non-achievable by most, is unsatisfying to say the least.  Implying there is no causal chain to get there  is also not so hot.  We can do better than just describe it.  We can think of it in evolutionary terms.  And that gives us paths, and actions that we can take to have a more evolved leadership team — Servant Leadership 2.0.

Old Highway 195, outside of Thornton, WA, south of Spokane

After pondering the characteristics of environments that, unfortunately, we’re all familiar with — Authoritarian and Legalistic v-Meme sets that dominate a large part of our world — you’re probably looking for a little hope that higher level leadership is even possible.

The good news is that it is.  Work environments that, at some level, prioritize performance can evolve.  The common denominator that starts the process may not be as appealing to the idealists in the crowd.

What is that common denominator?  Believe it or not, it’s money.  Money is a great generator of information coherence inside an organization.  It’s an external measure of performance.  People are only going to buy your product if they want to.  And money comes from customers.  And interaction with customers, through their diverse personalities, is going to drive empathy development — especially rational place-taking — throughout a given company.

Continuing along this track, we can also see that industries that rely on customer preference also have the greatest potential for empathetic development of their employees.  It’s no wonder that oil, gas and mining companies are chronically running afoul of varieties of public opinion.  No one really has a gasoline preference nowadays, other than regular/premium.  Whereas companies with semi-infinite supply chains (like aerospace) or ones driven by consumer preference (like selling tennis shoes) are more likely to have accelerated empathetic development.  And once again, companies with larger empathetic backgrounds are much more likely to have avenues where servant leadership can develop.

Let’s put up Collins’ Servant Leadership pyramid and do a little examination for the Performance v-Meme in his levels.

Collins explicitly prioritizes making money as part of his tripartite prioritization of the Hedgehog Principle.  So it should come as no surprise that one of the primary characteristics of a servant leader is to service that one thing the company does well as a vehicle for creating economic value.  And every level of his management development schema emphasizes performance.  Let’s review, one by one.

Level 1 — the person themselves must be capable of performance and being productive.

Level 2 — the person must have all of Level 1, plus connect to others to share information (both emotional and rational empathetic.)

Level 3 — Efficient resource manager implies a perspective toward optimal resource allocation, as well as the first nod toward multi-solution thinking.  Optimal is inherently going to be time dependent, and means evolving the operation to current market conditions.  And that means multi-solution thinking, which comes out of an environment where rational place-taking, with its nonlinear connections, is encouraged.

Level 4 — Interestingly enough, this level implies a larger level of emotional empathy with individuals that they work with.  It is impossible to catalyze commitment from people who sense you do not care about their larger well-being.

Level 5 — Finally at Level 5, we establish enduring performance and embodiment of larger care and concern for more aspects of his/her employees lives (and even destinies) as critical.  And the only way for an individual to do this is to develop those larger temporal and spatial scales in their own head that are possible through empathetic development.

We can also start seeing that Design Thinking starts coming into play, from Level 3 on up — if the objectives that Collins is referring to are generated in part from their customers.

In short, the Performance v-Meme, along with Design Thinking at the higher levels, is ingratiated into Collins’ model.  Along the way, Collins emphasizes indirectly the need to build community along with this.  Employees are individuals, and optimal performance can only be drawn out of those people with some level of independent connection and knowledge through leadership.

Yet at the same time, Collins’ model, originally published in his book in 2001, shows some element of age.  Is there servant leadership, and corporate performance, beyond his definition and the Hedgehog Principle?  The Hedgehog Principle itself, requiring a company to do one thing well, should draw your suspicions.  Within the last 15 years, much has changed with companies that aspire to SOTA performance.  That not only they do well (with solid profits) but they also do good.  What kind of leadership gets us there?

Takeaways:  Collins’ model of servant leadership, while having nods to higher Spiral levels above Performance/Communitarian, and showing some appearance of the Coral/Bodhisattva v-Memes, is, like all our structures, a creation of knowledge structures of our time.  It’s true that servant leadership is a huge step up from the tired Authoritarianism of the past.  But there are (and always will be) higher levels to aspire to.

Braden on a roll at nine, starting on the journey between Passau, Germany, and Vienna, Austria.

When I started the Industrial Design Clinic (IDC) over 22 years ago, it can be fairly safe to say I had no idea what I was doing.  I was a nonlinear physicist, essentially, by training — though my degree was in mechanical engineering.  Helped by my as-yet-unmade friend, Les Okonek, from ARCO/BP/now retired, and fellow refinery engineer Brett Emmons, I implemented a pretty standard design process.  This was further enhanced by the adoption of the book, Product Design and Development, by Karl Ulrich and Steven Eppinger. The First Edition came out in 1995, and it was the first textbook I folded into my efforts.  It may seem just a little dated now, but it’s a solid book, and describes what most people recognize as a canonical design process — in fact, it documents THE canonical design process that most people use.  There are variations on modification of design ‘gates’ and decision points, dependent on the agency and organization (is it any surprise, for example, that MILSPEC has ‘gates’?).  But it still holds up — and my students have literally built hundreds of designs using some modification of this process.

What’s the short version?

1.  Scoping.
2. Specification, using some form of Needs/Metrics/House of Quality toolset.
3. Conceptual and Preliminary Design, with a focus on generation of multiple designs, followed by review and down-select.
4. Final Design.
5. Manufacturing.
6. Benchmarking of the design against the specification.
7. Redesign (if benchmarks aren’t met) or Delivery to the Customer.

This all seems reasonable, of course.  And it is.  Yet like all knowledge products, its dominant characteristics are inseparable from our social/empathetic structure.  Both Ulrich and Eppinger are professors at MIT, and it’s not surprising that this design process sits squarely on the transition between the Legalistic v-Meme and the Performance v-Meme.  Design necessarily must have a large focus on performance and hitting goals, and these are rigorously enshrined in the process.

I’ve said that we can see that the knowledge product of the design process itself is a function of the v-Memes of the people documenting and generating it.  How?

1.  The process is meta-linear.  Varying diagrams may show this process as a straight line, or perhaps as a circle, but the bottom line is ‘we get one thing done, we move to the next one.’
2. Ulrich and Eppinger are big on a variety of algorithmic tools — more meta-linear, step-by-step processes that scaffold each of the heuristic steps, that lead in a predictable fashion to the next level.
3. Customers are included at the start of the project, as focus groups primarily.  Their input is then distilled into numbers (Measure to Manage!) and these are represented in the House of Quality/Metrics type tools.  Customers typically don’t loop around back into the process until the Benchmark/Delivery steps.
4. Empathetic development of the team does not allow for evolution of empathy and relationships with the customer.  The idea of evolving an experience along with the customer, while not particularly disallowed,  is not so much in the cards.
5. Larger synergies are not intrinsic between designers of the product and the outside world.  Synergies in that form are largely an afterthought — not surprising, considering the relative level of empathetic connection in the process.

As I’ve said earlier, we’ve used this process (and still use it!) for literally hundreds of successfully shipped products.  And for most products developed by the students in the IDC, it’s great.  Those products are necessarily Rev. 1, due to time limitations — the students only spend 4 months in the class.  Rev. 2 designs are sometimes commissioned by customers/sponsors, but are usually refinement projects (that algorithmic devolution thing again) — this system developed an unexpected crack during testing/use, etc., and the customer wants to take the extant design and improve it.

What is this design process great at?  Not surprisingly, it works very well for assembling engineered components (what I call ‘Lego Engineering’) into a new product, designing components with a large basis in the laws of physics (contrasting, evaluating and selecting, for example, different boiler designs), and some limited systems work, where interfaces are well-known.  Students often will be asked to visit a factory where a problem has been specified within a given system boundary, and students, in coming up with different preliminary designs, will often draw different system sizes and zones of inclusions.

Because multiple solutions are mandated in the preliminary design phase, there is the necessary headroom for different members of a group to be heard.  I often task everyone in the group with coming up with at least one potential design, and in order to dump a little empathetic development in the mix, often insist of pairing among students to generate ideas.  Students naturally tend toward solitary innovation — that comes straight out of their dominant authoritarian social structure (we’ve penalized them for working together their whole career — we call it cheating!) and so it is often necessary to order collaboration and sharing at the beginning of the project.  Students (and often multidisciplinary teams) will often take any project and fractionate it according to specific titles and established skill sets. Synergies, if any, will come at the end.

So much of what happens with this given design process will depend on the manager(s) of the effort.  If they implement things like pairing, the odds of synergies will increase.  If they insist more time spent with the customer, then it will happen.  Much rests on their Authority.  There is only a minimal level of emergent empathetic connection in the process itself.

And that shouldn’t be surprising.  That would be the natural construction of the professors who created it.

What’s especially fascinating is that in a follow-on paper, in the Harvard Business Review, Are Your Engineers Talking to One Another When They Should?, by Manuel Sosa, Steven Eppinger, and Craig Rowles — the same Eppinger of the book above — they recognize some of these problems.  They note the lack of metacognition — not with the language of this blog, but by stating in large projects (such as the Airbus A380) the existence of unattended interfaces.  They then state that the effort is really a failure of planning, and not surprisingly, introduce a set of algorithmic tools called Design Interface, Team Interaction, and Alignment Matrices — a Legalistic v-Meme intervention and tracking tool.  None of this is, of course, surprising.  The Principle of Reinforcement, where social/relational systems and their respective empathetic levels, reinforce and develop the behavior of its participants, and vice-versa, is at play even at MIT.

For things like large aircraft, where configurations are relatively fixed (look at the Boeing 737 family of designs) such tools are in themselves not such a bad thing.  Mapping out the interfaces, and who’s talking to whom is important.  There’s all sorts of implicit assumptions built into this, of course — that not only are they talking to each other, but the protocol that exists is actually getting the message across.  It’s an Authoritarian v-Meme idea that communication is 100% effective, even when it’s not.

But at the same time, the point of all this is that one must be aware of where our tools come from, and what kind of behavior they generate.  Ulrich and Eppinger’s process is great (not surprisingly) for the uses listed above.  Those map well within the social structure created to accomplish those given designs.  But we’ve got to think out-of-the-box, or perhaps better said, with a truly expanded sense of metacognition, if we’re going to attack larger problems, or larger synergistic systems — or cater more effectively to varying human preferences.  If we want more breakthroughs, we have to have more opportunities for larger rational empathetic interactions, and more nonlinear behavior.  We have to make a larger commitment to empathetically evolving the people inside the problem so they can naturally recognize and solve these types of challenges.  That’s not going to happen so much with the design process sketched out above.

And with the above design process, synergistic behavior is not intrinsic or emergent.  If leadership doesn’t order some of it up, with the social physics discussed in this blog, we likely won’t see it.  In fact, we may see failure because of a lack of it.  The system is not self-correcting.  Like Clint Eastwood as the character Dirty Harry so famously said — “A man’s got to know his limitations.”

Takeaways:  The canonical design process above is a huge step up from the arbitrary design processes of the past.  It successfully promotes multi-solution thinking, benchmarking with metrics, and working from a specification.  But there are limitations in generating new synergies, as well as tackling more complex, time-dependent projects.  

Passau, Germany — on the Beautiful, Blue Danube

At some level, it’s instructive to go back and review the longer definition of a Heuristic, and then consider what the implications are behind NOT going with a particular algorithmic approach.  Academics typically get conniption fits with heuristic thinking — usually along the lines of NOT RIGOROUS ENOUGH.  Too touchy-feely — which is really a term for a poor understanding of more evolved empathy!

Some of this might be a manifestation of v-Meme conflict that we’ve covered earlier.  The non-empathetic don’t particularly like, nor understand more empathetic approaches.  And if the stretch is long enough, we’ve already covered the fact that one can run into major hostility.  But do they have a point?  And if they do, what can we do to remediate their concerns of rigor?

The definition from Wikipedia is as follows —  A heuristic technique (/hjʉˈrɪstɨk/; Ancient Greek: εὑρίσκω, “find” or “discover”), often called simply a heuristic, is any approach to problem solving, learning, or discovery that employs a practical methodology not guaranteed to be optimal or perfect, but sufficient for the immediate goals. Where finding an optimal solution is impossible or impractical, heuristic methods can be used to speed up the process of finding a satisfactory solution. Heuristics can be mental shortcuts that ease the cognitive load of making a decision. Examples of this method include using a rule of thumb, an educated guess, an intuitive judgment, stereotyping, profiling, or common sense.

Often, heuristic methods involve ‘messing around’ with some problem (experiential learning) and embodying the ‘fail early, fail cheaply, fail often’ mentality we introduced in the last post.  That’s not going to make the Power and Control, or the Rule-Following crowd very happy.  With such processes, it looks like there is some indeterminate end, or even worse, an end determined in some fashion by the participants in the process.

And if you scroll back and remember how timescales are calibrated by empathetic development, now you’re bringing on the Major Crazy to the Authoritarians (time scales are decided by the authority above them) or the Legalists (time scales follow rules set from the outside — remember the creation of time zones/railroads story.)  The people involved in the process aren’t supposed to have the agency to set the limits on time for a project.  That’s above their pay grade.

What is needed by the Performance v-Meme crowd (get to the goal) that will mollify those lower down on the v-Meme Spiral is some kind of heuristic design process that resembles an algorithm, or at least a plan.  And then dependent on the technical requirements of the process, this plan appropriately scaffolds analysis effort into the design, in the quest for validity, with enough reliability to move forward with confidence.  These naturally fall out of the different Spiral v-Meme levels for a given project.

What might those be?  Just like a Matryoshka doll, higher/larger levels must be filled with the lower levels.

Matryoshka dolls, from Wikimedia

1. Legalistic/Absolutistic — enough analysis steps and algorithms (think computer-based finite element analysis, cursory flow analysis, statics, thermodynamics, etc.) that the potential designs do not violate the laws of physics.
2.  Authoritarian — enough facts, figures, and understanding prior art that a design is appropriately referenced to what has come before.
3. Tribal/Magical — referencing prior knowledge and stories that exist in the organization on past projects that have created the iconography behind specific choices.  This last one, in many ways, is the toughest, because of past failures with particular technologies.  A deeper dive will be necessary to understand the story well enough that changed conditions and technology development arcs will create an argument that will allow larger change.  A great example might be the adoption of lithium-ion batteries in the Boeing 787, and the resultant battery fire.  Clearly, lighter batteries are going to be used in aerospace applications.  The challenge is to assure reliability to commercial aviation standards.  Yet the experience was so traumatic (potentially nothing is worse than a fire inside an aircraft) that the story has been encoded into Boeing’s collective memory as the threshold statement for a major crisis!
4. Survival — the circumstances inside the company RIGHT NOW are amenable to a given design process.  This likely means sufficient budgeting, no other ongoing crises demanding the attention of group members, and so on.

Modern Computer-Aided Design and Analysis tools have made addressing #2 even easier than before.  Reliability of such tools has increased that a minimum of training is necessary for cursory results, and the acceptance that this is actually the case has spread even in the hierarchy of engineering schools.  It used to be that, for example, stress analysis using computers was taught as a graduate class, and there was much consternation about error control, meshing, and such.  Now, freshmen engineering students in our drafting class are taught the basics of how to find out the stress on a part given a loading condition, and the analysis tool itself is used to develop heuristics inside students’ heads for material behavior!

So what might a more structured heuristic design process look like?  That will be the subject of the next post.  But before we get carried away, I think it is very important to note: we’ll only discuss one potential heuristic.  Like all products of thought, it evolves out of the social structure that created it — this is absolutely inescapable, until we obtain some level of self-awareness on why we think the way we do.  In future blog posts, I’ll discuss other design heuristics and methodologies that are reflective of exactly those same types of mental dynamics, but at a higher v-Meme level.  And then, finally, we’ll wrap up with some speculation on how understanding higher-order connectivity can help us design the multiply connected, synergistic systems of the future.

Takeaway:  You can’t just wing it when it comes to the design of complex, technological systems.  You have to provide appropriate scaffolding that recognizes past Tribal Knowledge, known facts, the Laws of Physics, and whether there are enough donuts on the counter.  Because the Second Law of Thermodynamics is the law.  And if people are hungry, they won’t pay attention!

Credit where credit is due:  Lou Agosta, of the Chicago Empathy Project, pointed out to me that using the matryoshka analogy for empathy didn’t start with me.  Franz De Waal, in his seminal text, The Age of Empathy, he has equivalent mapping in the bottom three levels of his empathy model, and rightly deserves credit for being first to talk about the nested level of the bottom three levels of my Empathy Pyramid.

On the train between Liverpool and Manchester, England

We now move on to talking about Heuristic Design — the core behind New School Design Thinking, with a capital ‘D’.  But first, let’s talk about what’s meant with the term ‘design heuristic’.  A design heuristic is a pattern of problem solving where the person or group doing the solving assembles a series of steps that guide the group toward designing a solution for a problem.  Design Thinking relies heavily on various methods for multiple concept ideation, input from the outside, and interface with a customer.  As was said a couple of posts back, there is no hard definition — but it is geared toward innovation, as opposed to refinement.

Products evolved through Design Thinking are often the first of their kind — take the iPhone, for example.  By rethinking the interface from hard keys to a touchscreen display, as well as creating essentially, a portable computer, the iPhone developed a different paradigm for how phones might be used — and quite literally conquered the world in the process.

At the same time, once a breakthrough product is made, typically continuing refinement and evolution with the development of hierarchies has to continue.  Below is a graph of iPhone evolution, taken from here: (a Korean language website — not much in the text.)

Continual refinement in cameras, battery capacity , screen resolution — if not done at Apple, was done by suppliers, all providing expertise in refinement of the individual components, and cleverly combined for an aggregate improved package.  The takeaway?  We often start with New School, and end up back at the Old School.   This also tracks well to Martin’s Mystery -> Heuristic -> Algorithmic transition discussed earlier.

The history of Design Thinking is profiled here in Wikipedia, and I think it’s safe to say it really got rolling around the mid ’60s.  My favorite example has to be the famous Lockheed Skunkworks, headed up by Clarence ‘Kelly’ Johnson, and known for the breakthrough SR-71 spy plane.

Lockheed SR-71 spy plane, NASA 831 out of Dryden Research Center

The Skunkworks were likely a transition site from old-school design thinking to New School Design Thinking, in that  Johnson was a crack designer in his own right, creating the Lockheed AQM-60 Kingfisher, an unmanned aerial drone used to test missile systems.  Johnson was also one of the first systems engineers — specialists in tech integration that filled the evolved need that arose from both sides of the aero-space program.  There’s plenty of evidence, though, in Warren Bennis’ book, Organizing Genius — the Secrets of Creative Collaboration, that appropriately scaffolded, independent relational generation dominated the Skunkworks, and people were not constrained by following the usual communication channels in hierarchies, and talked to whom they needed to talk to get the job done.  Johnson served as the buffer between a much more traditional organizational structure at Lockheed, that eventually led to his dismissal — one can easily suspect the standard v-Meme conflicts discussed earlier on this blog.

Independent relational formation, and the evolved empathy that is required is the backbone of the social/relational structures that can effectively use Design Thinking.  One of the main reasons for this is the need throughout the process of a combination of important elements.  These are:

1.  Multiple potential solutions.
2. Goal-based thinking.
3. Enhanced metacognition — knowing what we don’t know, and what we must find out.
4. Involvement of the customer in the design process.

Let’s start with #1 — multiple potential solutions.  Multiple potential solutions are much less likely to happen in a hierarchy or power structure.  Both of these social structures exist primarily to maximize the relative status of the individuals involved.  As such, having multiple ideas on the table is more likely to be construed as a threat to authority.  Further, the people who move up in such systems are likely to be famous for being ‘righter than right.’  Such thinking dominates reputations in places like universities.  Is it any wonder we have problems with critical thinking at universities?

Multiple solutions thrive when groups of individuals are focused on the goal, and support of everyone in the community.  Further, they grow out of interactions between peers, or at least in environments where peer-level treatment is the norm, regardless of rank.  One of the more interesting examples of this is in the Marine Corps — the only branch of the US Armed Services where officers and enlisted people attend the same schools.  According to my military friends, it is much easier to talk up the chain of command in the Marines than any other of the service branches.

Peer-level treatment and exchange also promotes nonlinear interactions — meaning that there is the possibility for all sorts of shifting opinions after rational empathetic interactions that are not nearly as predictable as those based on emotional empathy.  It may almost always take 5 minutes to soothe a baby (emotional empathy), but a given concept for a new product may be discussed for hours.

#2 — Goal-based thinking — is also a huge coherence generator in the world of Design Thinking.  On a team, it’s not who’s the smartest guy in the room.  It’s whether the team can achieve the goal.  And when customer happiness is included in the goal set, an interesting phenomenon occurs.  Now the team must not only process the technical requirements of a given product development process.  They must also involve themselves with the customer’s emotional state.  One can see that this linkage of both emotional and rational empathy drives development not just of the team members individually, but the sense of unity of the entire group.

#3 — enhanced metacognition becomes extremely important in innovation.  If disruptive innovation is the desire, it necessarily means that the team driving a Design Thinking process is going to have to consider things that have not been considered before.  There will be Known Unknowns (and Unknown Unknowns) without question.  And that will often involve failure.  But since heuristics must be, in part, built on experience, creating an initial prototype that is imperfect is often the only way to learn.

Finally, #4 — Customers involved in the design process contribute profoundly to enhanced metacognition, in that the knowledge that they possess must be respected, regardless if they can deliver explicit reasoning for why they want something.  If the customer wants a yellow bike, they don’t have to have reason — if you want them to be happy, you’d better give them a yellow bike.  In applying Conway’s Law with this, there is also the addition of an unknown social structure that generated the knowledge inside the customer’s head — and that can add to the richness and diversity of the final solution.

And designers must develop empathy and connection with the customer, often to tease out exactly why customers want something.  In my design class, my students once had a project where they had to design a temperature measuring device for water jackets on enormous, industrial-size wine vats.  The customer specified stainless steel for the device, which is typical for food processing.  But in this case, the temperature measuring device was never going to touch the wine.

The students complained.  And I told them the customer was always (well usually) right.  Turns out one of the main uses for the device was a display item at trade fairs for the equipment.  The real reason was that the customer didn’t want their customers getting confused on whether they used stainless steel in their wine processing equipment.  And the only way to assure this was to make sure everything in their booth was made of stainless steel.  Any solution that wouldn’t let them sell more wine vats wouldn’t be more globally valid.  Because the task for the device the students created wasn’t just to measure temperature.  It was to sell more wine vats.

As usual, there’s more to unpack — the big thing being scaffolding.  We’ll save that for the next post.

Takeaways:  New School Design Thinking uses flexible, trust-based social structures that involve the customer in both specification and some level of decision making as the design process continues.  Coherence and happiness are both more likely outcomes when the customer participates in deciding the trajectory of given designs.  Multiple potential solutions, goal-based thinking, enhanced metacognition and customer involvement are all signs to look for in any Design Thinking process.

Further Reading:  “Fail Forward” or “Fail Fast, Fail Often” are two mantras of some contingent of the Design Thinking crowd.  I don’t like the word ‘fail’ nearly as much as like the concept delivered by ‘experiment and incorporate experiences.’  I think it’s more indicative of the actual execution of the process.  You can read about how some of the Masters do it here — no question Toyota makes some of the most sophisticated cars on the planet.