Business Design: A Misnomer


I just came from IDEO’s Tim Brown’s blog, Design Thinking, post on “A Curriculum for Business Design” and I can see his want to emphasize the need for design, but he misses the point.

I think the word “design” is becoming too much of a “to a hammer, every problem is a nail” conundrum. Every problem is not a design problem.  Business is very diverse.  What I would like to see is the following curriculum:

Business Science Inductive (Problems and Visions)
Business Science Deductive (Entrepreneurship and Leadership)
Business Design (Climates and Trends)
Business Engineering (Location and Movement)
Business Skill (Innovation and Professionalism)
Business Training (Imitation and Apprenticeship)
Business Education (Memorization and Theory)
Business Networking (Fraternity and Sorority)
Business Products (Culturing and Manufacturing)
Business Services (Sharing and Caring)
Business Marketing (Branding and Pricing)
Business Transactions (Closing and Accounting)

Design plays a part in solving every problem, but not every part of a problem is a design problem.

Let’s instill the diversity of business with design as part of the solution, not the only solution.

Oh, and if you call a problem an “issue”, that is another misnomer.  Problems are scientific and can be solved.  Issues are political and can never be solved.

Databases: Structured Associative Model


For years now I have been struggling with Relational DBMS technology and Associative DBMS technology attempting to get them to do what I want.  In my first efforts, Relational models were structurally restrictive, Dimensional models were unable to grow organically, EAV models are incompatible with relational architecture.  I came upon Simon Williams Associative Model of Data and although enthralled with its potential I found it too had limitations.  It was semi-structured and allowed for too much flexibility.  25 years in Information Technology had taught me that there was a single standard classification system for setting up databases not a plethora of ontologies.  I was determined to find the theoretical structure and was not concerned with hardware limitations, database architecture, abilties of current query languages or any other constraints.

The Associative Model of Data had made the difference in liberating me from Relational and Dimensional thinking.  A traditional ERD of the Associative Model of Data I at first thought would look like the following:


Basically what you have is a Schema composed of Nodes with Node Associations through Verbs and Associations with Nodes Attributions through Verbs. The range of Node Entities, Verb Entities, Association Entities and Attribution Entities are endless.  As well the population of the Schema has an unlimited dataset of natural key values.  I have been challenged by Relational database specialists and SQL experts regarding the viability of this model within current limitations, however their arguments are irrelevant.  What is important is the logical validity of the model, not the physical validity.

After receiving the criticism I decided to revisit the model in order to simplify it.  I went over Simon William’s explanations of his model and its application and found I could reduce it to the following:


This was profoundly simpler and better reflected the Associative Model of Data’s Architecture.  But even with this simpler architecture I was not satisfied.  I felt that the Associatve Model although giving the benefit of explicitly defining the associations was a tabula rasa.  Research has shown that tabula rasa’s are contrary to the behavior of the finite physical universe.  There is an intermediate level of nature and nuture.  And this is what I sought to model.


When I first encountered the Zachman Framework, something about it struck me in a very profound way.  I could see there was something fundamental in its description of systems, however I felt that the metaphors that John Zachman used were wrong because they themselves lacked a fundamental simplicity.  The consequences of this were that those who studied under Zachman ultimately could not agree on what he was talking about.  Also the “disciplines” that Zachman’s Framework generated were continually reinventing the wheel.  Zachman had created a world of vertical and horizontal stovepipes.  To further the confusion Zachman refused to conceive of a methodology based upon his framework.  Consequently, there was no way to determine what the priorities were in creating a system.  I call this the Zachman Clusterfuck.

Zachman’s work spawned years of work for me.  I could see that systems had a fundamental structure, but I could not agree with Zachman.  Focuses and Perspectives were useless terms.  The construction metaphor was useless.  I read anything I could get my hands on dealing with systems, methodologies, modeling, networks and a broad range of other literature across the disciplines.  Out of this came a set of conclusions:

  1. There were a fundamental set of Noun Entities
  2. There were a fundamental set of Verb Entities
  3. There were a fundamental set of Association Entities
  4. There was a clear order in which the Nouns were addressed
  5. There was a clear order in which the Verbs were executed
  6. The structure was fractal
  7. The content was a scale-free network

I made some attempts at creating the vocabulary and experimented with this new Structured Thinking Language.  However, the real break came when I worked with John Boyd’s OODA Loop:


The OODA Loop revealed a governing structure for the methodology and guided my way into the following hybrid relational/dimensional/associational model I call the Structured Associative Model of Data:


One of the key things this model demonstrates is the sequence followed by the OODA Loop.  Starting from the top, each dimension set spawns the next.  Choices are created from the dimensions.  There is no centrism to this model which is an inherent flaw in Service Oriented Architecture (SOA), Event based architecture, Data centric architecture, Goal-Directed Design, Rule based systems among others.  The stove pipes of Focuses and Pespectives disappear by reasserting a clear order of priorities and dependencies for achieving success.  The model also supports bottom up inductive as well as top down deductive sequencing.  This will make the system able to reconfigure to handle exceptions.

Some of the things I have learned in designing this model include the realization that unit defines datatype and that all measures are variable character string text.  This is because any displayed value is only a symbolic representation of the actual quantity.  If operations are to be performed on measures they are converted to the correct type as part of the operation.  I also recognized that Unit was necessary to define the scale and scalability of the system.  Further, it became apparent that analog calculations should not be practiced.  Every value should be treated as discrete and aggregated.

Another aspect of this system is the inclusion of currency and amount.  I have been critical of Zachman and academics for their hypocrisy regarding the economics of systems.  All systems have a cost and a benefit and they are measurable in currency.  Contrary to the reasoning of the majority, every decision is ultimately economic.

Tim Brown of IDEO has coined the term “Design Thinking” and has been toying with the concept for some time.  Many designers dwell on the two dimensional concept of divergence and convergence as modes of thought.  If we look at my model, divergence is the creation of choice while convergence is selection of choice.  There is no alteration or deletion of choice in my model as history is preserved.

Now what you have is a unencumbered framework with a clear methodological sequence.


Welcome to the Cognitary Universe.

Universe: History Rhymes


In a Forum interview by Michael Krasny of NPR with Futurist Paul Saffo brought to my attention in a blog by Tim Brown of IDEO, Paul quotes Mark Twain who said, “History does not repeat itself, but sometimes it rhymes.”

My work on the Czerepak Framework is an effort to look back as far as possible to find the rhymes of the history of systems and out of it has come the following:

Trivergent Thinking

Freedom and Fiat

Divergent Thinking

Future and Flow

Univergent Thinking

Function and Form

Convergent Thinking

Fruition and Fulfillment

I have adopted the above process for my company, Cognitary, Inc.,  and call it “Cognitary Stratus”.  It is both a methodology and, when extended to additional dimensions, a framework for designing a system.


My usage of the root “verto” with the prefixes “tri-“, “di-“, “uni-” and “con-” are intended to create new terms to deal with a four dimensional perspective (not three) of systems.  The eight sub-forms of thinking correspond to the eight interrogatives:

  1. Why: Freedom
  2. Who: Fiat
  3. When: Future
  4. Where: Flow
  5. How: Function
  6. What: Form
  7. How Much: Fruition
  8. How Many: Fulfillment

These rhymes and sub-rhymes are the stratus of all systems and all systems design.  Together they are the basis of Cognitary Stratus.


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.