Design: Business Design Induction/Deduction


This is my latest incarnation of the Business Design Process.  Induction (Brainstorming–generation of ideas) is Counter-Clockwise.  Deduction (Refinement–elimination of ideas) is Clockwise.

Below is the Intelligence Architecture:


Here is the Media Architecture:


This is the Data Architecture for this model.  Note that all values are accepted even if they are wrong:


Below is the Network Architecture of this model.  Note that the values are unique (nodes) and they are sequential (edges):


Here is the Text Architecture:


Here is the Numeric Architecture:


Here is the Octonion Architecture:


Good Design: System International Units


I have been working to accept nature as it is. I found myself looking at the System International Measure Units:

1. Prediction – Radiation – Mission – Art – Visual – Eye – Video – Candela
2. Harmonization – Vibration – Strategy – Science – Tempal – Ear – Audio – Celcius
3. Synchronation – Duration – Tactics – Design – Signal – Nose – Events – Second
4. Information – Distance – Operation – Engineering – Gradual – Throat – Graphics – Metre
5. Validation – Mass – Product – Skill – Technical – Jaw – Text – Kilogram
6. Transaction – Current – Service – Training – Clerical – Body – Equations – Ampere
7. Satisfaction – Molarity – Price – Education – Medial – Thumb – Numbers – Mole

I am of the opinion, if we stick to the basics we will develop better systems.


Web 3.0: A Herd of Leaders

many cats

Google signaled the end of Web 1.0 Infrastructure and the beginning of Web 2.0 Information.

Is WolframAlpha signaling the end of Web 2.0 Information and the beginning of Web 3.0 Knowledge?

I have been thinking about the recent comments of Seth Godin about Social Networks on  Personally, I believe Seth is behind the curve and that Social Networking is becoming a bubble as platforms are becoming commoditized and Social Network companies are springing up everywhere without properly thought out business models.  Eventually, venture capitalists will get wise, pull their money out and the bubble will burst.  Web 2.0 is dead.  Long live Web 3.o. is probably the Web 3.0 shot that is being heard around the world.  A new generation of search engine for a new generation of knowledge-based internet technologies.

Social Networks will continue to exist.  All of the small Social Networks will be gobbled up by the biggies.  However, the center is shifting from the profiling of Web 2.0 focusing on the needs of the business to gather customer information back to the needs of the customer to gather product knowledge.

Relational databases focused on the values, information.  Associational databases will focus on the connections, knowledge.

Look forward to a new economy and a new plethora of business models.

Web 3.0 is here.  Knowledge is Power.  Power is Leadership.  Knowledge is Leadership.


Linear, Tabular and Netular Thought


Gutenberg’s creation of the western version of the printing press is regarded as a revolution and in a sense it was.  Printing led to the transition of western thought from a theocratic 1300 year deductive flat world dark age to a 500 year inductive round world renaissance.  However, printing only lead to the presentation of greater amounts of information.  The real revolutions were the discoveries of Copernicus, Galileo, Newton and Einstein culminating in the General Theory of Relativity.  With the advent of Marxism the world slipped into the polarization of the Communist/Capitalist blocks and threw the world into another deductive flat world dark age that lasted into the 1990s.  The advent of the Internet and Tim Berner Lee’s World Wide Web has led to another renaissance back into inductive thought.  Worldviews are collapsing, however we are still to see a new worldview created by the new presentation of increasing amounts of information.  In fact, the Internet age is still trapped in the models of the age of the printing press, the most prevalent being linear (scribal literacy) data and tabular (press literacy) data.  Tabulation dominates information technology architecture and until it is abandoned we are still slaves to print.  The Turing Machine was a migration of existing printing press information technology architecture not an innovation in information technology architecture.  We have yet to implement fundamental change at the foundation of our technologies.  Until we are able to rethink, reengineer, mechanize, represent, store, process and present information as netular (internet literacy) data successfully, which has yet to happen, there will be no revolutions in human thought.

Six Unities Analysis: SuiteTwo

I have recently been exposed to a new Intel intranet appliance product called SuiteTwo. SuiteTwo is an integration of MoveableType, SocialText, NewsGator, SimpleFeed, VisiblePath and SpikeSource for the enterprise to take advantage of Blogs, Wikis, Social Networking, RSS feeds, RSS aggregation and Open Source internally. Apparently, eager clients are offering plenty of ideas to even further enhance SuiteTwo and its integrated products, but let’s take a moment to analyze what an ideal tool would ultimately do from the ground up from the perspective of the Six Unities.

Note: the Six Unities are resource groups and resources are both internal and external to the enterprise.

Location – Contact Resources

Locations for each of the entities for each of the unities would be available. I would be able to track the location of staff and inventory according to internal and external coordinates be it geographic, facility, postal, telecom, internet or any other. These are all the enterprise’s touch points. Where are we receiving and transmitting to/from the enterprise? REPOSE. Where the resource contacts.

Trigger – Event Resources

Activations for each of the entities for each of the unities would be available. Ultimately, all events are reactive–dependent on internal or external entities. REFLEX. When the resource contacts.

Data – Product Resources

Inventories of all entities for each of the unities. I would know the quality and quantity of any fixed, virtual and liquid assets of the company according to internal and/or external metrics internally and externally. Data is a repository of all enterprise resources allowing check in and check out. RECORD. What the resource contacts.

Information – Service Resources

Functions performed by all the entities for each of the unities. Whether digital, mechanical or manual all the processes would be documented in human readable form. The work and play done and being done within the enterprise and externally. REPORT. How the resource contacts.

Knowledge – Human Resources

Social Network for all entities for all unities. In every case someone is responsible for every entity internally and externally. Who are we, who do we report to, who do we share with internally and externally? RELATE. Who the resource contacts.

Wisdom – Policy Resources

Meaning and mantra for every entity for every unity. It is important to know the motive of everyone and everything both internally and externally that involves the system in order to know whether they will abide by the greater goal of the enterprise. Why are we united according to internal and external rules? REVISE. Why the resource contacts.

Take a look at the products SuiteTwo integrates and ask yourself if they answer the needs of the six unities. In my opinion SocialText’s Wiki is bearing the brunt of the requirements, but does it stand up? I don’t think it does, because it does not correctly incorporate location, event and inventory.






Systema: The Six Hats, Six Coats Hypercube

Later in this post we will discuss this man:


The following table represents my interepretation of the Zachman Framework:


I have taken this framework and applied the following de Bono metaphor:


I also incorporated my own metaphor to differentiate the axes:


These two modifications produced the following table:


This is where I had an “aha” moment. I asked myself what the entities would be:


I also recognized that in each column these entities were related hierarchically allowing the creation of a six dimensional hypercube. In creating the hypercube it was possible to look at a variety of “slices”. For example:


The table above combines Motive with Person. We can see that Motive is verbal while Person is a noun.

Next we will combine Function and Data to create another slice:


Again, Function is a verb and Data is a noun.

Let’s look at one final slice:


Here we see that nodes and time have many possible states.

But, why am I doing this exhaustive analysis of the possible combinations in the Six Hats, Six Coats hypercube?

Let’s go back in time for a moment and look at this table:


When Dmitri Mendeleev created this table to describe periodic behaviour of the elements, many of the elements had not been discovered. However, the table projected what the properties of those elements would be making the search much easier.

The Six Hats, Six Coats hypercube is also a form of periodic table. Its entire collection of possible cells are called the framework space. Many of the cells in the hypercube do not yet exist, however their properties can be predicted. This makes their search and discovery of system components systematic instead of random or organic.

Related Posts:

Systema: Seven Hats, Seven Links

Systema: CI-DIKW Hierarchy Definitions

I have been wanting to clearly define each of the terms Data, Information, Knowledge and Wisdom for some time. I have thought about Artificial Intelligence, Knowledge Bases, Knowledge Management, Data Management and other disciplines and have decided on the following simple definitions:

  1. Wisdom is the ability to model entities in a system. This is extrapolative.
  2. Knowledge is the ability to model relationships in a system. This is interpolative.
  3. Information is the ability to model attributes in a system. This is intrapolative.
  4. Data is the ability to model constraints in a system. This is extrapolitive.
  5. Intuition is the ability to model definitions in a system. This is interpolitive.
  6. Communication is the ability to model manipulations to and from a system. This is intrapolitive.

I have been forced to come up with the root “polite” to describe a single input value as opposed to “polar” which is a collection of input values. But what I want to point out is there is no automated tool capable of creating new models of communication, intuition, data, information, knowledge or wisdom, as simply defined as this is, that can be regarded as “intelligent.”
The above six perspectives affect the following focuses or modeling languages:

  1. Motivation Modeling
  2. Network Modeling
  3. Data Modeling
  4. Process Modeling
  5. Person Modeling
  6. Time Modeling

The perspectives CIDIKW and focuses MNDPPT make a thirty-six cell framework I call the Six Hats, Six Coats Framework. What I am pointing out here is that no system is simply one dimensional. Human systems are six dimensional at least. There is also a meta-layer, the model, and a data-layer, the database, for each dimension. The modeling systems and databases for all the dimensions are still very primitive and incompatible. Slowly, we are getting there, but there is more than enough work out there for anyone who wants to come up with a consistent modeling language. And if you do, you will have the foundation for a true AI.

Systema: Exteroception and Interoception


I was reading an article in Scientific American MIND this evening which discussed the research of Hugo Critchley on emotional intelligence and interoception. Interoception which is narrowly defined as the perception of stimuli inside the body. Interoception activates the brain’s right insular cortex and has lead Critchley to a broader definition of interoception. The reason being that not only perception of internal stimuli, but of emotion results in intense activity in the insular cortex. It has also been found that another center in the brain associated with ideas, motives and values often shows activity in conjunction with insular cortical activity. The right insular cortex appears to be the location where mind and body meet. Neurologically, you perceive hunger in the same way you perceive anger. You have a physical location for intuition, that “gut feeling”.

So, why do I bring this up? The main reason is I am thinking about Maslow’s hierarchy and the DIKW hierarchy. I have been struggling to substantiate a hexad as opposed to a tetrad for the number of layers of input and output and I think this provides another cornerstone for my argument. Interoception, the perception of stimuli inside the body, and exteroception, the perception of stimuli outside the body, fill the gap beneath data and divide Maslow’s physiological needs. I am proposing the following hexad:

  1. Green Hat: Wisdom. Self-Actualization. Conceptualization.
  2. Yellow Hat: Knowledge. Esteem. Contextualization.
  3. White Hat: Information. Belonging. Logicalization.
  4. Black Hat: Data. Safety. Physicalization.
  5. Red Hat: Intuition. Physiological. Humanization. Interoception.
  6. Blue Hat: Communication. Existential. Detection and Effection. Exteroception.

In my future discussions I am not going to talk about the movement of data or information or knowledge or stimuli. I am simply going to refer to input and output. Input ascends the hierarchy and output descends the hierarchy. From which level it originates is also irrelevant if it is ascending it is always input, if it is descending it is always output. The transformations are discrete. They are not increases or decreases in detail, but changes in perspective.

If you are following this lengthy thread you may notice my terms changing a bit each time. It is an iterative refinement of my understanding that is leading to these changes. Hopefully, I get closer to a final version with each change.

Six Hats, Six Coats and Knowledge Management

I was passed this link to a free Knowledge Management Course by a friend today.

I gave the entire course a read (it is not that long) and concluded that there was only one thing that the course covered that is not covered by the Six Hats, Six Coats as it has been explained so far. The issue is valuation, how do we know the cost/benefit of any fact. Otherwise, the authors wave the term “knowledge” around with little restraint to the point of its being meaningless. If they had it their way, everything would be knowledge. (I’ve been known to rant that everything is objects.)


To perform valuation of the Six Hats, Six Coats Framework, facts are each of the Six Coats columns: Motive, Locale, Object, Method, Person and Moment. Each of these can be reduced to their atomic granularity at the Blue Hat perspective row. One additional row can be added to the bottom, which is the benefit per manipulation. Each of the Six Hats is a row and can be accumulated in a seventh column, which is the cost per perspective. Each cell of the Six Hats, Six Coats Framework has a cost when it is created, but the benefit accumulates with each manipulation of its column at the Blue Hat level and is rolled up to the appropriate cell.

The rest of the Knowledge Management concepts are covered by the Six Hats, Six Coats Framework.

The Six Hats, Six Coats Framework provides not only knowledge. The Six Hats provide:

  1. Green Hat: Wisdom. Conceptualization. Creativity.
  2. Yellow Hat: Knowledge. Contextualization. Relativity.
  3. White Hat: Information. Logicalization. Optimicity.
  4. Black Hat: Data. Physicalization. Pessimicity.
  5. Red Hat: Regulation. Humanization. Anthropicity.
  6. Blue Hat: Conduction. Detectors and Effectors. Synchronicity.

The Six Hats, Six Coats Framework gives a clear definition of knowledge. Meta-Knowledge is the modeled relationships between the each of the entities within a system. This is the entity relationship diagrams for the facts. Knowledge is the actual references between each of the instances within a system. This is the actual database containing the facts. A rule relationship model, a node relationship model, a data relationship model, a function relationship model, a person relationship model and an event relationship model are meta-knowledge. Rule instance references, node instance references, data instance references, function instance references, person instance references and event instance references are knowledge.

“Mentifacts” and “Sociofacts” are obtuse terms. Person associations are extragroup, intergroup, intragroup, extrapersonal, interpersonal and intrapersonal. They are different perspectives a human takes to interaction and the adoption of facts from another system. Motive, locale, object, method, person and moment are all artifacts, better termed entities.

The definitions the course offers: “Know-what”, “Know-why”, “Know-how”, “Know-who” is incomplete and ill defined.

  1. Yellow Hat, Green Coat is Know-why. Contextual Motive.
  2. Yellow Hat, Yellow Coat is Know-where. Contextual Locale.
  3. Yellow Hat, White Coat is Know-what. Contextual Object.
  4. Yellow Hat, Black Coat is Know-how. Contextual Method.
  5. Yellow Hat, Red Coat is Know-who. Contextual Person.
  6. Yellow Hat, Blue Coat is Know-when. Contextual Moment.

Knowledge management is not simply Informal and Formal. Knowledge Management can be Implicit, Explicit, Tacit and Sonit. Implicit knowledge management handles knowledge that is documented and unchanging in the organization. Explicit knowledge management handles knowledge that is documented and changing. Tacit knowledge management handles knowledge that is undocumented and unchanging. Sonit knowledge management handles knowledge that is undocumented and changing.

The Six Hats, Six Coats Framework does not use the metaphor of a factory for knowledge processing. Instead the framework uses a system lifecycle of induction and deduction. The system repeats, refines, records, reports, relates and revises input; and revises, relates, reports, records, refines and repeats output. Only during the relate phase is input or output knowledge.

The concept of knowledge claims, I found intriguing, but confused between what is meta-knowledge and what is knowledge. I could only conclude that a knowledge claim is really a meta-knowledge claim. Validation of references, knowledge, is protected by referential integrity. A meta-knowledge claim would be validated by a corroboration of exceptions.

The quality of meta-knowledge is a question of how well the relationships for the dimensions handle input and output. If the probability of no exceptions is high the quality of the meta-knowledge is high. A change in context is a change in interacting systems and will affect the quality of an entire system’s performance not just one of its dimensions or of only its knowledge.

Validation of a system is not only knowledge validation. Validation of Conduction, Regulation, Data, Information, Knowledge and Wisdom are all necessary excercises. Because no system is completely Implicit, Explicit, Tacit or Sonit there will always be room for normal and exceptional input and output that has not been accounted for.

Knowledge has intrapolative predictive capabilities. Wisdom has extrapolative predictive capabilities. From this course Knowledge Management appears to know little about systems at all.

The course also attempts to use the three layer ANSI model of World, Knowledge, Meta-Knowledge to describe itself. I have no problem with that. However, because of the poor definition of knowledge in the first place the author begins fantasizing about endless additional layers. I have only found there needs to be three layers in every case I’ve tested. There is the world, the referential and the relational layers.

The sixth lesson of the course talks about innovation as the goal of Knowledge Management. I beg to differ. Innovation is a completely different perspective in the Six Hats, Six Coats Framework. Innovation is the Green Hat, conceptualization perspective. Knowledge assists conceptualization, however conceptualization is concerned with the entities of each of the fact dimensions, not the relationships. Relationships are interpolative, they can only exist between entities that exist. Entities are extrapolative, they can come into existence out of nothing and do not depend upon relationships to exist.

As far as the seventh section, Metrics, goes there is ultimately a cost/benefit ratio. All other metrics are irrelevant if the cost/benefit is done correctly. Cost is the expenditure required to build each cell, each model, of the system framework down to the atomic level. Benefit is the profit gained from each manipulation of the system at the atomic level.

“Knowledge Transfer” is the ability of your system to induct another system and then deduct with a profitable outcome.

You don’t need a Knowledge Management Team. You need a System Modeling Team and the Six Hats, Six Coats Framework. “Everything is a system” holds up to scrutiny better than any knowledge management claim.

Listening is Inductive; Speaking is Deductive

After going over the system models in an earlier post I had to revise my thinking and conclude that the Structured Thinking Lifecycle takes on the following character:


What this reveals is the lifecycle of a system is about communication. It also reveals that the Six Hats, Six Coats metaphor is actually a continuum from Repeating Moments to Revising Motives for induction and from Revising Motives to Repeating Moments for deduction.


This is Edward de Bono’s wisdom: “Analyze the Past, Design the Future”. That is all there is to communication. Listening is inductive; speaking is deductive.

Think about this from the perspective of the DIKW hierarchy:


listening is inductive; speaking is deductive listening is inductive; speaking is deductive listening is inductive; speaking is deductive