On the Piazza, Lucca, Italy

Once we understand the origination of a given paradigm, we can map how it might evolve empathetically — as well as assess how difficult it might be to move groups of people up the Spiral to higher levels of connectivity.  Servant leadership is one paradigm that can motivate a group of individuals — leaders in the business community — to start that journey.  Even though, as we’ve seen, servant leadership rests on independent, trust-based relationships, it is a status trigger for those down there in external relationship v-Meme land.  Getting to deny, then proclaim oneself striving for servant leadership is good bait for the status conscious.

But because it is based not on title, but an aggregate of empathetic relationship construction and actual performance, anyone that’s healthy in the head is along for an upward ride.  That’s the point of Servant Leadership 1.0.  It’s an implicit evolutionary ladder.  You do the various tasks — build your team, focus on performance and measurement, catalyze your team, and so on — you’re going to grow empathetically.  Because you have to.

Servant Leadership 2.0 is also an evolutionary, empathetic ladder — with Servant Leadership 1.0 nested inside of it.  But with its focus on self-awareness, and inner development of the individual, it unlocks larger potentials in terms of leadership team function.  And because mindfulness training is millennia-old, far more evolved minds have debated and discussed it.

But if you have to boil it down, it’s going to come down to two core practices.  The first is debate with others.  One has to open oneself up to exchange with other constituencies — the broader, the better.  It can’t just happen with a bunch of white men sitting in a board room.  The broader the constituencies, the larger the growth.

The second is meditation and reflection.  The two are tied intrinsically together, because you simply can’t get to the silence of meditation without reflection.  For me personally, it happens on my bike — I start riding, and after about 30 minutes of getting through my stress and anger about whoever I perceive is doing me wrong today, I get to a point of positivity, and then start thinking about the good things in my life.  And then, after about 15 more minutes, I’m through those thoughts.  And then there’s just me.

Debate is an intrinsic element of learning to build independent relationships with others.  Anyone that aspires to servant leadership has to effectively, empathetically master it — because without it, the information coherence in the channel simply can’t be sufficient for the effective leader to receive accurate information.  That means the Servant Leader must place-take constantly, because if not, the person they are talking to may shut down, and not tell them something critical they need to know.  The quality of the grounding of experience with others is directly related to the openness one approaches the dialogue.

And as well, reflection and meditation must be core practices for Servant Leadership 2.0.  Why?  Because without an inner dialogue, where one deals empathetically with oneself, how can one develop an honest dialogue with our own insides?  Because if we want to have data-driven, trust-based relationships with others, the first person we must construct one with is ourselves.

Once we accept this paradigm, many pathways open up for development of Servant Leadership 2.0.  There may be some direct algorithmic training involved — breathing exercises and so on.  But by and large, it’s going to involve interacting with others — experiential learning.  Varying the scales of such learning, both temporally and spatially — from short-term to long-term relationships, as well as friends here, and friends across the globe, in different cultures and places — is key.

When enough of a cohort of such individuals are gathered together, the possibility of interconnected, empathetic collaborative teams offer a pathway to larger, Global Holistic modes.  No one independently needs to be the spiritual master.  It’s the whole — not the one.  And skilled in open debate, as well as private reflection, decisions can be jointly made that benefit the larger whole.  That’s how you get Global Holistic out of a team of Global Systemic thinkers.  Each one is a self-aware node on their authority and realm of influence and responsibility.  And because all parties are well-formed, they know what they know — as well as what they don’t.  That then yields to the integrated landscape necessary for running the modern, empathetic global corporation.

Further Reading:  Some interesting work on the development and merging of rational thought with spiritual practice.  Though I haven’t heard much since I read about this four years ago — teaching Tibetan monks neuroscience —  I’m wondering how Arri Eisen’s work has proceeded.  Not surprisingly for followers of this blog, the development of a rational spirituality opens the door, when even previously unexposed, to the methods of science.

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.

Dubai Sunrise, from the Conrad Hotel

How did we get started with the most recent, modern chapter of design?  Pre- big ‘D’ Design Thinking, lots of engineers went to school to learn design — stuff like Thermodynamics, Statics, Circuits and Dynamics.  They still learn this today, and most of the subject matter engineers cover in their degree programs matches what was taught over 100 years ago.

For those that don’t know what is actually taught in those classes, don’t worry.  Here’s the basics.  Usually a class is centered around a particular branch of physics — thermodynamics, for the most part, is about the physics of boiling water — vital information if you want to design a boiler for a steam locomotive, or a reactor vessel for cooking up some chemicals.  Information about the process is calculated — there are lots of formulas.  Some are so well known that they are part of what are called ‘codes and standards’, where engineers literally over generations have worked out the predictability of such situations that the answers are really what we engineers call ‘plug and chug’ problems.  You select the right algorithm, put in the numbers, and, well, ‘plug and chug’.

This process is not trivial.  Many of these formulae are complex, and knowing which one to pick is important.  Results from one set of formulae, like thermodynamics, where one might calculate temperature and pressure of a reaction, then feed ANOTHER set of algorithms to calculate the stress in materials used in the boiler.  Those feed yet another set of formulae regarding selection of materials for actually constructing a boiler.  If all this isn’t done correctly, the boiler could explode, killing people.  In fact, this is what happened that spurred the birth of much of the engineering profession.  Steamships and locomotives were blowing up — so algorithmic methods were developed that gave predictive capacity to designers so that this wouldn’t happen.

Refinement of such processes happened over time.  And in many ways, there was no arguing with the results.  It wasn’t about empathy or connection with a customer, as it is with so much of consumer design today.  It was about making a locomotive that could pull 100 coal cars up a mountain.

This mindset, or rather, v-Meme set, continues today in a good hunk of engineering, and without question in engineering education.  Legalistic/Absolutistic in nature, governed by algorithms, with only one right answer, hierarchies of engineers have been created to solve many of these problems.  Much of the work used to take a career to master, and there are still many certifications that say what engineers get to sign off on certain types of design.

Algorithmic design is often the bedrock of families of designs.  One of my favorites is below — the Titan missile family.  

Through addition of extra rockets, refinement of existing technology, substitution of materials, all these different types of things — an algorithmic smorgasbord of rockets, for varying missions and payloads, ranging from satellites to nuclear warheads, has been created.

Designing a rocket engine, or perhaps a better example, modifying the fundamental design of a liquid fuel rocket engine, where a propellant and an oxidizer are mixed in a combustion chamber, doesn’t require input from a focus group.  It, on the surface, doesn’t really require much empathy at all — though obviously, engineers working on a large project need some level of empathy to share successfully information.  This is ‘In-group’ empathy at its finest — a group of individuals, taking extremely similar curricula,  trading information in a language that is largely impenetrable to the masses — so much that such kind of talk is called, appropriately ‘rocket science’!

And who do you need in order to make progress?  The basic design of a rocket engine hasn’t changed that much.  The effort required to get it all to work hasn’t either (lots! rocket engines are basically controlled explosions encased in metal), though refinement continues, with adoption of new materials and such.  But who you need are authorities — lots of them.  Experts with increasingly fine-grain knowledge about very specific areas.  You need legalistic authorities, and they need to be absolutistic in their thinking.  If they’re not, then your rocket will blow up.

It should come as no surprise, therefore, that such people organize themselves in authoritarian hierarchies.  It’s the knowledge set that is needed.  Until very recently, such projects were often headed up by one individual — the master designer.  No better example exists of transcultural similarity than aircraft fighter design from the first flight to the late ’60s.  Mitsubishi’s chief designer, Jiro Horikoshi, was responsible for the famous WWII fighter, the Mitsubishi A6M Zero.  Dr Waldemar Voigt and Robert Lusser led the team that designed the first operational jet fighter, the ME-262 — this after the Messerschmitt Bf-109 .  Edgar Schmued, was the chief designer of both the P-51 Mustang and the F-86 Sabre while at North American Aviation.

Because of the social structure of such teams, integration of the design effort necessarily had to be mostly at the top.  There had to be a chief designer, one with experience and capable of mastery of multiple disciplines.  And here is the main thing — the level of detail and complexity was such that one person could still innovate.  The need for complex, transdisciplinary teams in order to innovate had not yet arrived.

If there is a takeaway, that is it — complexity of systems had not yet increased to the point where it was essentially impossible for one person to know everything for success to occur.  But there are others.  Manifestation of reliability were many and varied.  While one might argue that each of those designers, at the top of their pyramid, could reliably be predicted to create breakthrough visions in aircraft production, the breakthrough aircraft, in the traditional sense, were not reliable. The Me-262, for example, had only an eight hour engine life, before both engines had to be swapped out.  The hierarchies that would develop the sophisticated jet engines that power our own commercial jet fleets had not yet had a chance to evolve.  The exotic materials, the advanced turbine blade designs, and the integrated and aggregated information that was required had not yet arisen — because the social structures required to produce that knowledge that would then produce those designs did not yet exist.

Takeaways:  Algorithmic design is the basis of many of the systems that create modern life.  It is non-empathetic in nature, and backed up by social hierarchies that are legalistic in nature, and practice complex rule following.  Creativity has its place, but the laws of physics must be followed — because those are the rules that govern the game.  And that leads to the legalistic hierarchies that are required to produce the knowledge — in a never-ending feedback loop.

Pantanal Cacique Bird (a Weaver Bird variety)

Well, it’s taken a while, but we’re finally getting around to one of the big themes of this whole blog — Design Thinking, and a larger, systemic understanding of both design and the design process.

What is Design Thinking?  That’s a very good question.  The most broadly accepted definition is a mode of thinking that lends itself to innovating new solutions, instead of just solving old problems.  This spins out into all sorts of angles from all sorts of experts — from solving ‘wicked problems’ — problems resistant to resolution for a variety of reasons, both technical and social, to epiphanies.  We’ve covered some of these phenomena earlier and shown how they are intrinsically part of social structure — but there’s more to unpack.

There’s some leads toward how to do Design Thinking in these definitions — tools, methods, processes and such are the typical way of approaching the topic.  What we’d like to do is understand Design Thinking on a deeper level, so that as managers or constructors of design teams, we can understand whom, and what processes we have to assemble, and what sidebars and culture needs to be generated so that we can do Design Thinking consistently, at the right level, for consistent innovation.

As I’ve explained in earlier posts, we arrived at this point of wanting to understand Design Thinking with the diversity of various group thought processes (and their outputs) by way of Conway’s Law — the idea that a manifested design will resemble in structure the communication network (and therefore the social/relational structure — that design team thing!) that created it.

We then introduced the Big Idea of the Intermediate Corollary, illustrated below:

and that led us to the idea of how people socially organize (and their empathetic levels) will dictate what they CAN know or design, or are CAPABLE of routinely processing.  This is then summed up in the following slide:

which, then again extends off the right side of the slide to the design itself.  Synergistic designs, for example, require empathetic teams who can readily exchange information with high levels of coherence — meaning, basically, they can pretty much understand what the other side is talking about, and know when to trust them.  Synergy is often a good thing.  But for anyone trying to debug a synergistic system, they know it can be a bad thing as well.  Trying to find a root cause of failure for a synergistic system is far more difficult than for one that has been well-compartmentalized — because everything is hooked together, and changing one thing ends up having unpredictable consequences with the other parts.

In the past couple of posts, we’ve also explored the idea of metacognition — knowing what you don’t know — and then showed how various social structures either promote or impede its existence.   Different levels of innovation are going to require different levels of exploration, as well as people who are comfortable with those different levels.  There is no ‘one size fits all’ — just an awareness of ‘what size fits you’!

If we’ve accepted the idea that Conway’s Law is true (and there’s been a fair amount of study that indicates that it is), then we also have to recognize that there is going to be, if we want to be sticklers about all of it, a different level of Design Thinking for every social structure — each one processing a different level of existent (or non-existent) synergy.

But instead of listing out every one, associated with every major v-Meme, let’s go at this from a different tack.  Let’s look at the fundamental dichotomy of human relationships — belief-based, externally defined relationships vs. independently generated, trust-based relationships — and go from there.

Externally-defined relationships tend to maximize reliability.  Reliability, in the case of relationships, goes along with predictability.  If you talk to a doctor, the odds are that person knows something about medicine and healing.  If you talk to a mechanic, that person likely knows something about fixing your car. And so on.  If it’s a broadly recognized title, that person likely has a document or diploma behind their name.  (Mathematicians will recognize such a diploma as an integral representation of information inside that person’s head — it’s functionally a single point, scalar representation of years of training!)

It then follows that if people in networks or hierarchies dominated by externally defined relationships do design, they’re also very likely to be familiar with, and able to refine prior art.  (For math junkies — since the interaction is simplex, and information is only aggregated in an additive fashion at a level above the nodes where it’s generated, odds are the process is also meta-linear in nature.)

Therefore, in a hierarchy, design mostly consists of refinement.  Old stuff made better, but likely no new stuff.  This is still design, of course, but is typically not what is generally understood to be Design Thinking by the majority of design practitioners.

Things are considerably different for organizations that allow more independently generated, data driven, trust-based relationships.  There, the social structure is more flexible, and determined not just by managers, but to some extent by the individuals inside the organization.  Also very important are relationships they have with customers outside the organization.  Because of the nature of those relationships — more unpredictable information exchange, more interface with the customer by more people inside the organization — these kinds of networks are more likely to have Design Thinking that maximizes validity —  will the design make the customer happy?  With the customer actively in the mix, with multiple employees, this dramatically increases.

That’s a start.  There’s much more to say.  And I will — in the next couple of blog posts.

Takeaways:  If you believe Conway, then you have to believe that design thinking will vary based on the social structure that is doing the designing.  The easiest way to split it apart, however, is from the external relationship definition/independent relationship definition dichotomy.  These two types will maximize either reliability or validity. 

This is not what most of the Design Community calls Design (Big D) Thinking, however.  Design Thinking is usually associated with jumps in innovation, or new ways of thinking about problems, as opposed to refinement.

Further reading:  I didn’t want to go into it in the main body of the post, but design thinking has been around for a while — since the ’40s, if you believe Wikipedia.  I certainly didn’t invent it.  

Definitions are all over the map, not surprisingly, because those definitions are made by various experts who occupy various v-Meme levels.  As I said above, breaking things up along the ‘solve the problem vs. innovate the solution’ isn’t too bad a way to approach it.  The ‘proactive vs. reactive’ paradigm (watch this 3 minute video by colleague Roger Martin, Dean at the Rotman School, University of Toronto, and David M. Kelley and Tim Brown of IDEO) maps well to the social/relational structure stuff in this blog — basically, if you’ve got metacognition, and you’re functioning at a Performance v-Meme level, then you’re going to try to innovate to reach a goal, instead of just willy-nilly refining a product.  

My personal opinion is the main discriminator, as it’s understood on the outside, is that Design Thinking drives multiple-solution thinking followed by down-selection, as opposed to single-solution thinking.  We’ll unpack this a little more as we go along.

Wild land fire, Selway-Bitterroot Wilderness, Clearwater NF, Idaho

Sometimes, when I read my own prose, I find myself victim to the same Dunning-Kruger effects I discuss.  Seems like I did this in the last post, so let me expand.

One of the interesting concepts that come out of Roger Martin’s book, The Design of Business, where he presents the system model for business evolution going from mystery -> heuristic -> algorithm.  In this previous post, I document how this also relates to a regression in social/relational structure, and in a related fashion, empathetic development.  Martin does a good job of contrasting this to what he calls the reliability/validity trade-off.  As a company ages, if it is not careful, it will follow a decay path where Legalistic/Algorithmic v-Meme hierarchies will slowly subsume the organization, and creativity will die.  The only person who gets to be creative is the person with Creative in their title.

This should not come as a surprise to readers of this blog.  If one understands rational empathy, and the creative energy it releases through unpredictable, nonlinear interactions between independent actors as a primary driver, then when you give everyone a job with a title, and tell them with whom they get to talk to, it’s  no surprise that you get in to a ‘New Idea Rut’.  Everyone’s saying the same old, same old, to the same old.  Barring a personal crisis in someone’s life, there’s just nothing new under the sun.

But hierarchies (and to some extent, power structures) are good at some level of incremental, algorithmic improvement.  If we’re trying to grow our company with ‘solid growth’ — 4%/year — it might be prudent to just keep on with incremental product improvements.  But as anyone with a high school math background might remember, even 4% a year turns into exponential growth — something we count on for compound interest, our kids’ college savings account, and our retirement.  And companies, sooner or later, will reach size thresholds, or business/innovation events will happen that will demand restructuring and re-thinking.

So why do people cling to past ways, especially in Authoritarian/Legalistic v-Meme environments? This gets back to the core principles that we’ve discussed regarding Reliability and Validity, and the way we form relationships.  It’s a good guess that if we want an authority on engineering, we’d go talk to a Licensed Professional Engineer, or an engineering professor.  But if we wanted someone to tell us how to hang-glide — a profoundly aerodynamic venture, but something a little more off the beaten path– we’re as likely to have a Valid discussion with an amateur hobbyist as an engineering prof in my department whose specialty is micro-fluidics.

Going back to the business world — an Authoritarian company is likely to seek the usual outlets for product refinement, which might seem like it makes sense.  But over time, their metacognitive reach is going to naturally shrink and shrink.  The knowledge that they may have  becomes more reliable, in that it is tried-and-true.  But as circumstances change, that lack of metacognition prevents proactive solutions.  The product or the game can only change after a failure.  There’s no better example than Kodak’s demise.  The largest film photo company in the world utterly failed to understand the power of the digital revolution.  And now they’re pretty much gone.

What’s so interesting about this insight is now we can understand the roots of how someone thinks when they say things like ‘you learn more from your failures than your successes.’  If there ever was an Authoritarian v-Meme statement, it’s that one.  Because of the lack of metacognitive sweep — actively confronting unknowns without fear — there’s just no learning.  Except when things fall apart.  And then it’s a surprise.

Contrast that to a Performance v-Meme.  If we want to improve, we design Process for Practice, and adapt strategy to find out what we don’t know, before it fails.  When confronted with the question, “do you learn more from your successes than failures?” folks might say that they learned more from failure, but that’s just the lower v-Memes talking.  In the class I teach, the Industrial Design Clinic, I teach successful practice, with an emphasis on Design Thinking and an exploration of multiple options.  Because there is no engineering company in this world that will accept a graduate who constantly, chronically fails after shipping product.  Even if they’re learning.

Takeaways:  Understanding how demands from the different v-Memes reinforce Reliability and Validity is key in not falling into the trap of only incremental product performance.  I’m sure the folks at Kodak thought film was going to last forever.

Further reading:  Complacency, Reliability?  Poe-tay-toe, Poe-tah-to.  Read here for a quickie piece on Kodak’s downfall.  Published in Forbes, no less.

Big Sand Lake,Selway-Bitterroot Wilderness, Clearwater National Forest, Idaho

Why are Authoritarians so sure of themselves, while the self-aware are constantly questioning their very existence?  And how do these very large questions fit into the larger schema of social/relational structure?

One of the things that I work with students on is development of metacognition, which is the technical term for “knowing/being aware of what you don’t know.”  At its root, metacognition involves an individual self-assessing knowledge that they have, being aware of knowledge that they do not have, and in its largest form, being aware of the fact that there may be more subjects/areas that they haven’t encountered yet.  In a certain sense, this is a meta-awareness.  Though I was never a big fan of Donald Rumsfeld, one of the most profound things he ever said was his famous ‘known unknowns’ and ‘unknown unknowns’ comments.  The quote is reproduced below:

There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know.

Donald Rumsfeld

Rumsfeld didn’t invent the idea of metacognition — that probably goes back to the great Buddhist and Hindu philosophers.  But by packaging it in contemporary lingo, and then being subject to the scorn of the press corps, speaks loudly about the level of media discourse today.  And not in the press corps’ favor.  In an evolved society, knowing what you don’t know is a key toward curing your ignorance — not an insult toward your status.

How can we understand metacognition in terms of empathetic development?  Profound metacognition requires that we have a data-driven, inner dialogue with ourselves — assessing what we know relative to the data available — and at some level, still valuing ourselves at the end of the process — in short, we have to develop empathy for ourselves.

If, after such an assessment, we feel worthless because there is so much we don’t know, that is extremely telling about the social/relational structure we exist in, and how it influences our thoughts.  Accurate assessment of metacognition involves us having a developed, independently generated relationship with ourselves, and at some level, also involves our developed ability to trust our own judgment.  That implies that we have some sense of our own agency (we get to evaluate whether we should trust our judgment, instead of having someone on the outside tell us whether we should trust it or not) and in a healthy, developed form, is a behavior only manifested at v-Meme levels (Performance and above) where independent relational behavior comes into play.

With this definition, we can then see that the Principle of Reinforcement will play heavily into whether we have metacognition or not.  Different social structures will dictate to their constituencies incentives (or disincentives) for metacognitive development and belonging, which then makes it interlocked with empathetic development — our primary practice tool for our own neurological processing.  We have to know that we don’t know how someone else feels in order to make the decision to collect the data to assess their emotional and cognitive state.

This is a complex thought.  But one can really see how this works when examining the different motivators relative to the different v-Memes.  Authoritarians, when confronted with their ignorance, are going to be insulted.  Their status will be diminished — hence the desire for metacognitive development is relatively low.  Those in the Legalistic v-Meme will still be tentative in their recognition of things they don’t know.  They will want the assurance of new, transformative algorithms to take them from their current, known state to newer, unknown information.

It is when we move past the primarily Belief-based social organization structures that we start to see metacognitive development accelerate.  Performance-based organizations, when confronted with unknowns that impede progress toward the goal, will recognize them, and construct mechanisms to solve those unknowns.  Communitarians will recognize unknowns as part of the hidden mystery of every individual in the community, and part of the process of increasing individuation in their community member assessment.

Higher v-Memes than these ratchet up the state, in that they force the observer to confront their position of observation.  Self-aware Global Systemic will start the cycle of asking what one’s self-interest is in knowing/not knowing.  Global Holistic will start the process of understanding the larger connection of not-knowing to potential impacts, short and long.  And just saying — I haven’t gotten this all figured out.

Nothing demonstrates this better than watching an academic audience interact with a speaker.  And I’m not talking students — I’m talking professors.  A speaker can throw out softball question after softball question in order to get the audience to participate.  But professors, by and large, unless they are a recognized authority, will largely, passively sit and not answer.  They intrinsically know that their status is directly related to always pronouncing the right answer.  Why take a chance, when there may be a trick involved?

There’s a flip side to understanding metacognition.  Aggressive lack of metacognition manifests itself both at the levels of profound sophistication and expertise, as well as in the world of profound ignorance.  The Dunning-Kruger Effect, which I have discussed before in this blog, documents this with Legalistic v-Meme reliability.  The short version is that the ignorant self-assess at a much higher level of competency than they actually possess.  And the highly skilled, if their empathetic development is lower, will self-assess at a much lower level of competency than they have — they take for granted that people don’t know stuff that they, in fact, know.

One can see how this ties back to the level of empathetic connection.  If you’re an expert giving a talk, and you’re not connected to others, you don’t see them yawning.  You just keep going on and on.  And the other side?  There are plenty of examples of aggressive ignorance out there.  They can’t see the faces turning red when they yell — or they don’t care.

Real metacognition is a great way of evaluating true expertise.  Someone with a profound sense of metacognition will readily confess to things that they know, as well as things that they don’t know.  With this thought, one can see how metacognitive development hooks back into the notions of reliability vs. validity.  If someone can recognize their level of expertise, odds are that when they give an answer, it will be valid, subject to the data presented, as well as reliable.  It will be both correct AND reproducible.  Contrast that to someone who is an expert in one thing, but doesn’t recognize their own metacognitive limitations.  For them, every problem is a nail, and they’re the hammer.

Takeaways:  Metacognition is intrinsically tied to empathetic development, which then loops it all back into social structure and the acceptability of admitting you don’t know something.  The Dark Side shows up with the well-documented Dunning-Kruger effect.

Further reading:  The famous book, How People Learn, documents the  pattern of learning that experts use to master other fields.  There’s much to take apart about this book (not surprisingly, written by academics and authoritarians,) but in case you need some level of proof of how this works, it is contained therein.

Further watching:  Perhaps the most profound demonstration of Authoritarian lack of metacognition (in a humorous vein!)  Sergeant Schultz, from Hogan’s Heros!