Universe: Interrogative Spaces


In my previous post I gave thought to Tim Brown of IDEO’s “design thinking”, Clayton Christensen’s “Innovator’s Dilemma”, Malcolm Gladwell’s “Tipping Point”, and Buckminster Fuller’s “Synergetics” concepts.  What emerged was the above Czerepak Framework.  My claim is this framework is fundamental to designing a system.

The thing that the above table shows is interaction within what I am now going to call the “Interrogative Spaces”: HowSpace, WhatSpace, WhySpace, WhoSpace, WhenSpace, WhereSpace, HowMuchSpace, HowManySpace.  Each ellipse I call a “vortice”.  The Interrogative Spaces are composed of one or more vortices.  The Framework above shows how Spaces are composed within the Interrogatives,  but what about interactions between the Interrogative Spaces?   A good example is speed or velocity.  Speed is the intersection of WhenSpace and WhereSpace:

v = r / t

Where v is velocity, r is radius and t is time.

If you are increasing Speed, which is acceleration, you have one dimension of WhereSpace and two dimensions of WhenSpace:

a = r / t’ * t”

Where a is acceleration, r is radius, t’ is the first clock and t” is the second clock.  You cannot measure acceleration with one clock. This uniqueness of every vortice applies to all the Interrogative Spaces and all inter-relationships between all of the Spaces.  .

Another way to look at the Interrogative Spaces is as sets and subsets.  The first row are the complete Space vortice sets.  The second row are the first Space vortice subsets.  The third row is the intersect between the row two and row three Space vortice subsets. And the fourth row are the intersects between the row two and row three and row four Space vortice subsets.

I do not believe that anything is constant.  Not the speed of light, not gravity, not cosmology.  Every intersection of dimensions creates a vortex in Universe and every one is unique.  We are simply unable to measure and manage the uniqueness of everything, therefore we make generalizations which create models that can always be falsified.


Universe: The Czerepak Framework

I just visited the archive of Tim Brown’s Design Thinking Blog and came across the following post:

Definitions of design thinking

Tim Brown » 07 September 2008 » In design thinking »

In my HBR article I gave a ‘definition’ of design thinking. It was:

Design thinking can be described as a discipline that uses the designer’s sensibility and methods to match people’s needs with what is technologically feasible and what a viable business strategy can convert into customer value and market opportunity.

On reflection this is a narrow description that focuses on design thinking’s role within business. The next sentence that I wrote.“….design thinking converts need into demand” , which I borrowed from Peter Drucker, broadens things out a bit but still assumes an economic motivation.

I am grappling with two questions as I think about this.

1. Is there a general definition of design thinking?

2. Is it useful to have one?

I think Tim has something very good here and suggest that the following would be a further breakdown of his classification:

  • Viable: Business
    • How Much: Quality
    • How Many: Quanitity
  • Feasible: Technology
    • What: Material
    • How: Process
  • Desirable: Human
    • Why: Goal
    • Who: People

Obviously, if you have been following my blog, you can see the same pattern appearing and reappearing as we explore other’s concepts.  The six interrogatives continue to reassert themselves.  However, I think I finally nailed one more aspect on the head.  I hate to say it, but it came to me in a dream about working on a programming project:

  • Reliable:
    • Where: Location
    • When: Timing

Quantity and Quality are two aspects of design/system thinking that are continually overlooked by academics and specialists, but not business people.

Interestingly enough this perspective is not new.  Clayton M. Christensen in his book The Innovator’s Dilemma discusses a four part model that fits nicely with this:

  1. Availability
  2. Compatibility
  3. Reliability
  4. Cost

I consider, Clayton’s the most empirical ordering.  Consequently, I would like to mesh Tim’s, Clayton’s and my perspective into the following:

  1. Feasibility: Technology
    1. How
    2. What
  2. Compatibility: Personality
    1. Why
    2. Who
  3. Availability: Market
    1. Where
    2. When
  4. Viability:  Business
    1. How Much
    2. How Many

Now, looking at this I am reminded of Malcolm Gladwell’s book, Tipping Point, and it adds the following character to the model:

  1. Feasability: Mavin
    1. How: Processes
    2. What: Materials
  2. Compatibility: Connector
    1. Why: Goals
    2. Who: People
  3. Availability: Salesman
    1. Where: Locations
    2. When: Schedules
  4. Viability: Customer
    1. How Much: Costs
    2. How Many: Units

Universe: A Multi-Dimensional Medium

Let’s do a thought experiment.  I want to take design thinking and abstract it to a system.


Imagine that there are no solids, liquids, gases or plasmas or particles.  That the Universe is a fluid medium swirling between equilibrium and non-equilibrium in multiple dimensions.  What we perceive to be solid, liquid, gas or plasma are not states, but intersections of dimensions that describe interdimensional vortices.  Energy is the intensity of a vortice.  Mass is a vortice of a set of dimensions.  Light is a vortice of a set of dimensions.  All of the particles are vortices of sets of dimensions.  Each influence the other based upon which dimensions they are composed of.

R. Buckminster Fuller clearly states in his work that we should perceive the systems as finite four dimensional spheres.

There are only four fundamental states:  vortice verge, vortice converge, vortice emerge, vortice diverge.


Everything we perceive are combinations of these vortice states.  The states are +/- vortice yaw, +/- vortice pitch, +/- vortice roll.

If any vortice is spiraling toward you it is positive, if any vortice is spiraling away from you it is negative.  By definition, no vortice can be stationary with respect to you.

There are only eight fundamental vortices: How, What, Why, Who, When, Where, How Much, How Many.

This gives us the following eight vortice, four state table:


Take the time to look at the terms defining each of the white cells in the table.  Each row is the addition of a dimensional vortice.  For example: Each additional “when” vortice is another separate clock.  Each additional “where” vortice is another separate radius.  All of them are factors in a system or a design.

And even this representation is inaccurate.  If we consider fractal geometry and chaos theory, there are no points, no straight lines, no arcs, no planes, no circles, no polygons, no polyhedrons, no spheres, only vortices that are above, within or below our range of perception.  Space cannot be filled with any geometric shape.  Everything is composed of vortices–spirals.

We have to abandon the flat world, flat space models we currently cling to.  The world and the universe are not infinite planes.  The world is a finite island of non-equilibrium in a predominantly equilibrium universe.

And that is it, the Czerepak (Chair-eh-pak) Framework.

Copyright (c) 2008 Grant Czerepak.  All rights reserved.


Romanticism vs. Empiricism

I’ve just finished reading The Long Tail by Chris Anderson as well as a fine article “Should you invest in the long tail?” in the Economist by Anita Elberse. Although I take both pieces of writing with a grain of salt one thing stands out. The scientist, Chris, conjured up a theory without any supporting data and the marketer, Anita, provided substantial supporting data and conjured up a conclusion. Chris said the long tail is fatter, while Anita found the tail is flatter. On the surface, what we have is a romantic physicist and an empirical marketer. But what lies deeper? It is a third party that Anita brings into play: William M. McPhee.

I could not find a book cover image for Formal Theories of Mass Behavior or a photo of William online, but his research is very interesting. In his Theory of Expousure, two concepts stand out: “Natural Monopoly” and “Double Jeopardy”. Natural monopoly says light users simply buy the most popular product. Double jeopardy says heavy users buy less popular products and like them less.  Another way to say it is 20 percent of us are polarized (double jeopardy) while 80 percent of us choose what the polarized like (natural monopoly).

This can be looked at in the context of a tipping point. Heavy users (Mavins, Connectors, Salesmen) will experiment with more products with a low benefit and high cost and light users (Accountants, Secretaries, Receptionists) will experiment with fewer products with a low cost and high benefit. It ain’t rocket science.

The same goes for stores, but in an interesting way. Heavy users will experiment with more stores with few products and light users will experiment with fewer stores with many products. Store count is regarded as cost and product selection is regarded as benefit.

Chris Anderson’s book appeals to a demographic that wants the benefits of heavy users and the costs of light users.

Anita Elbrese’s article appeals to a demographic that wants the costs of heavy users and the benefits of light users.

William M McPhee’s book appeals to a third demographic that says we ultimately all end up with much the same thing.

Systema: Art and Method

I have been spending considerable time in the University of Notre Dame Latin English Dictionary this past week looking to refine my terminology for Systema. One of my discoveries is that “modus” is not a term for “method”, but “standard” such as “modus operandi” — “standard operation”. The actual word for method or skill is “ars” or “art”. Thus “Art of War”–Artis Armus–is synonymous to “Method of War” or “Skill of War”. Consequently, I will be referring to the How interrogative with the response as “Artus” not “Modus”. The six interrogatives and responses are as follows:

  1. Why – Causus – Cause
  2. Who – Ductus – Command
  3. How – Artus – Method
  4. What – Datus – Given
  5. When – Eventus – Result
  6. Where – Locus – Location

Interestingly enough, this fits very well into the Empirical Process. All that is left out is the conclusion. The conclusion determines “how much” the system corroborates (benefits) the cause.

7. How Much – Conclusus – Conclusion

Structured Thinking System: Attributes R0.2

I was thinking about what values the entity attributes could be assigned based on my earlier post and I thought I would provide a portrayal of the six values in a different visual context. Each attribute value can be portrayed as a ratio and the goal in each case (and not necessarily intuitively) is to be “high and to the right”.