First, here’s a pretty cool insight from an article LiveScience:

Toddlers (do) listen, they just store the information for later use, a new study finds.

“I went into this study expecting a completely different set of findings,” said psychology professor Yuko Munakata at the University of Colorado at Boulder. “There is a lot of work in the field of cognitive development that focuses on how kids are basically little versions of adults trying to do the same things adults do, but they’re just not as good at it yet. What we show here is they are doing something completely different.”

“For example, let’s say it’s cold outside and you tell your 3-year-old to go get his jacket out of his bedroom and get ready to go outside,” Chatham explained. “You might expect the child to plan for the future, think ‘OK it’s cold outside so the jacket will keep me warm.’ But what we suggest is that this isn’t what goes on in a 3-year-old’s brain. Rather, they run outside, discover that it is cold, and then retrieve the memory of where their jacket is, and then they go get it.”

But let’s look at that, in the context of other cognitive findings.  I’d highlight ten points:

1) Abstracting the experience: A three year old’s brain is learning to abstract elements of the experience.

2) Associative modeling:   The child compares a new experience to stored models (i.e., generalizations, abstractions) – an associative “this is like / not-like” comparison.

3) Time:  The kid’s temporal sense is still developing:  differentiating now-versus-future.  Think back further to babies enjoying presence-absence -  a.k.a. peek-a-boo play.

[BTW, what  if the English language did not have a future verb tense: consider that the Japanese language doesn't. Try making some future-event statements without using the future-tense verb. Likely it will be a " ...when this, then this..."  -  think of the different sensibility that creates. ]

4) Linear sense of time – To plan, is to arrange objects along a single-line time sequence.   Planning is not an innate skill, and should be learned before the teen years.   Planning and patience both require the deliberative discipline  of “not-now-but-later”.

5) Models - The child’s brain sorts experiences to build models for analyzing and making decisions.    Faced with an unfamiliar situation,  she hesitates. Is it her deliberative mind racing to sort the data into a best-fit with one of her many logic models? Or is it frozen fear?   Try to discern her  natural inclination, as she balances the impulse, the emotion, the hesitation, the caution.

6) Decisions: The kid’s ability to make logical (causal) predictions (and decisions) depends on its yet developing sophistication to decide if the stored model fits the situation.

7) Creativity: The child’s mind wants to explore and learn – i.e., test its models, change the models, create new models, or go out into the cold without that prescribed coat.

8) Our role: We should encourage play and provide an emotionally safe environment for the experimentation – i.e., the child’s intellect to develop.  Feeling emotionally safe, would have to start with  feeling it’s ok to fail.

9) Under the hood: The”chief executive” prefrontal cortex makes decisions referring to a library of logical models: If this, then this.  Assuming the brain’s “early-response team” allows that longer process, that is.

It’s a longer route  for sensory signals to get to and back from the prefrontal cortex. That momentary hesitation could be costly, and this is why all animals do develop and keep profiles of friends or foes –  the “survival instincts” of the reptilian part of our brain.

Jet fighter pilots and emergency responders therefore need practical experiences, (1) to develop a library of ready response models, and (2) with the familiarization, to be able to moderate the reptilian reaction.

Furthermore, to make true shifts – i.e.,  decisions, –  the brain actually needs the cooperation of the amygdala to provide the emotional drivers: how will it impact me?  And think of how  traumatic situations evoke strong feelings that drive a more visceral or instantaneous reaction.

10) “Intuition” is the sophisticated ability to make a decision by quickly retrieving the best-fit model for that situation.

So there you are.  Note, though, that the theories are a more complex and still evolving science , what with our reptilian reactions, our emotions, etc.   Take the right-brain-left-brain chatter:  While the perceptual right-brain lives in the present and looks for patterns as they are,  the left brain, because of its function for language and logic, can be driven to create its own fiction and false memories  - check out  Gazzanga “…the interpretive mechanism of the left hemisphere is always hard at work, seeking the meaning of events. It is constantly looking for order and reason, even when there is none—which leads it continually to make mistakes. It tends to overgeneralize, frequently constructing a potential past as opposed to a true one…

Having followed Jonah Lehrer’s  Seed postings, I looked to the release of his new book.  How We Decide  is a fun and comprehensive survey of Decision Making’s neurologic and cognitive aspects.  http://www.powells.com/blog/?p=4507#more-4507

Book Covers the Landscape: Lehrer’s  How We Decide can seem to be a jumble of entertaining and bewildering fragments, perhaps because the book’s encyclopedic scope overwhelms.  The decision making process might not seem so chaotic, nor undefined, if we understand the sequential process of the sensory message traveling through the brain .

We know that the sensory signals coming in through the brain stem must first run the limbic gauntlet, the

brain’s front-line guards.  The emotions are associated with the amygdala which sits close to the brainstem.  It is not surprising that our emotions can be tied closely to our sense of smell, given their roles as front-line guards.

The incoming signal pattern is compared against a library of friend-or-foe profiles, “caricatures” of the usual suspects, designed for quick recognition for fast response -  as much as some would consider profiling impolitic.

If (a) the sensory signal patterns have not roused the front-line emotional guards, and (b) the brain decides there’s time for a more deliberate analysis, then the patterns are sent up to the rational PFC (prefrontal cortex) tecchie upstairs, which keeps a library of models of cool logic, abstracted from knowledge and experience.

Hopefully, there is a matching model – and a quick “intuitive” response is triggered

The process is sequential , and it’s not as if the brain consciously mulls, “Hmm, I wonder if I should get the PFC (prefrontal cortex) guys  work on this, if not I’ll just push it on my subconscious …”

The brain performs a triage on the incoming signal:  (Case 1) Do the incoming patterns match any known threat models?  If so, then the amygdala shuts the gates and sounds the alarms.   Case (2):  If the patterns are non-threathening, and there’s time,  then the sensory signals are sent up the to the PFC which then checks for a match against its abstracted models.

The brain’s two collections of models: To make decisions the brain has two “libraries” of models learned from its experiences and knowledge: (1) the rational (logical) and, (2) the emotional and instinctual models.     As a defensive mechanism for survival, Fear understandably predominates among the emotions.

We can train ourselves to recognize – i.e., “intuit” – without conscious analysis when a situation matches a model.  The incoming signal must first pass the instinctive and the emotional screens, before the signal is passed on to the rational PFC “techie” on the fifth floor, who might have  ready modules and won’t have to kludge a long analysis .

Two lines of defense : Some studies argue further that we cannot even make decisions without emotions.   You’d see this when the more savvy salespeople instinctually flank their prey:  When the purchase is a major shift for the buyer,  sell first to the fear: create a gap, a pain point. When  the buyer has made that shift, then sell on the product’s features, rationalizing the decision.

And impulse buyer that I am,  my survival instincts know to latch on to the practical features-  to justify later to the wife my latest and greatest gottahavit gizmo.    –

This series targets three topics (decision making, strategic execution, and project management).  You will also find links to thinkers, books, tools and other resources.

Looking at the recent years’ book releases, we see a shifting from rigidly closed decision and management models, to open-ended approaches and analytical tools. Why?  Information now floods us; it’s a faster flux of events, and reactions from a global pool of players.

Dilemma of Project Management

Recall that Microsoft Project and the PMI BOK co-evolved in over 20 years, back when organizations were localized with simpler markets and competition.  MS Project still narrowly defines “issues” as scheduling.  Ironically, the more detailed the GANTT chart, the less likely it can be maintained for day-to-day management.

Management modeling’s  roots are in manufacturing whose processes tend to be linear and determinate.  We  dismiss messy “unquantifiables”.  But complexity and the change flux may not allow methodical analysis.   Newer product life cycles are shorter and discontinuous.

Irony of Making Decisions in a Surplus of Information

Closed “rational” analyses need to be supplemented,  and perhaps not by another model, but an approach, plus shorter decision feedback loops. Think of a stance, rather than a stand:  aligning to the most strategic goals, alert to changes, updates, and collaboration.

“What’s measured is what gets done,” true enough, but often it’s what cannot be measured that may render a plan undone. We forget that straight lines and metrics are human devices. Nature neither draws straight lines, nor follows our plans.

System Reliability and Accidents

With the internet and globalization, has come an unprecedented complexity.  With complexity,  some say,  “system accidents” are a certainty.   Do we step back enough for a larger context,  searching for what we don’t know that we don’t know. Until the the 2007 financial collapse, risk was a matter of actuarial hedging.  Perpetual motion  powered by technology and optimism:  the 1987 market’ “system accident” from programmed trading was a distant lesson.  Until the “lightning victory” in Iraq,  war was a matter of technology and logistics.

This blog series, then, is a search for ways to see the grays and not merely the binary; and for clearer values to navigate to, as goals must be ever more adaptive.