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.



Systematic Innovation

The thing that set’s Peter F. Drucker’s legacy apart from all the pop management books is one thing: Empiricism. Peter concentrated on observable, reproducible, systematic methodology. And he took the same attitude in Innovation and Entrepreneurship.

The secret to successful innovation and entrepreneurship for a private enterprise, a public enterprise or a fledgling enterprise involved pre-planning before any attempt to realize the idea took place. The success stories in Peter’s book took an idea that was not even necessarily their own and took the time to foresee the requirements for possibility, compatibility, reliability, affordability, distributability and ubiquity before they entered the life cycle of the product or service. They built a management team to achieve each of these milestones before they entered the life cycle as well. Only then did they execute, because there was no turning back.

It is just like a volley in tennis. The ball (opportunity) approaches and the tennis player observes that ball, positions herself, assesses her capabilities, decides where the return will land and only then makes her power curve lead into the ball, singularity contact, and power curve follow through, all the time never letting her eye off the ball until that volley’s life cycle ends.

Like I said to Seth Godin’s book, The Dip, you don’t make your decisions mid-stroke. It is not empirical and it is bad physics. Peter would say the same thing. He would say it is bad management as well.

The Innovator’s (and SQL’s) Dilemma

Let’s look at Christensen’s four marketing issues again:

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

How can this be correlated with SQL? First, data availability is determined by the SELECT statement. You query the database to determine if data that meets search criteria exists. Second, data compatibility is determined by the INSERT statement. Data is accepted if it is within the database structure’s definition. Third, data reliability is determined by the UPDATE statement. Data has to change as the database’s state changes to continue to meet the database’s objectives. Finally, data economy is determined by the DELETE statement. Data that is no longer of use can be removed from the database to free up available resources to achieve cost effectiveness.

  1. Select
  2. Insert
  3. Update
  4. Delete

Christensen’s Innovator’s Dilemma tetrad has provided us with another viewpoint on the SQL tetrad.