Thursday, July 9, 2015

The Theory of Form, Fit, and Function

What motivates a system to operate according to a certain set of principles? A well-known version of this question relates to people: 


What motivates a person to act or think the way he or she does? 


Form, Fit and Function. 

Wikipedia eloquently states that 

Design science research involves the design of novel or innovative artifacts and the analysis of the use and/or performance of such artifacts to improve and understand the behavior of aspects of Information Systems (IS). In design science research, as opposed to explanatory science research, academic research objectives are of a more pragmatic nature. Research in these disciplines can be seen as a quest for understanding and improving human performance. [1]

The aim of the explanatory sciences, like natural sciences and sociology, is to develop knowledge to describe, explain and predict. When directed toward an objective, these guidelines serve as three pivotal points from which truthful propositions can arise, which can be utilized as a lens for deeper investigation into contingencies and complexities. The most accurate method of analysis to examine form, fit, and function is a method composed of form, fit, and function.

Take Evolutionary Psychology, which is essentially the combination of two sciences ~ evolutionary biology and cognitive psychology. These two sciences fit together in a way that supports a form, fit, function construct, enabling scientific accounts of human nature plausible.

Cognitive Psychology

Cognitive psychology is a theory of mind. It transformed psychology from a vague set of unclear ideas into a science. The two main ideas are:

  1. Actions are caused by mental processes
  2. The mind is a computer
Mental Processes

Psychology is the science of human behavior. It attempts to explain why humans do what they do? Everyone is an amateur psychologist, constantly offering explanations for our actions and for the actions of others. For example when I see someone texting and then crashing into someone else, I might explain this action in the following way:

  • This person thinks they will not crash as a result of their texting

This kind of explanation is called a mentalistic explanation because it refers to mental processes like beliefs and desires. When we explain actions by referring to beliefs and desires, we are claiming that these mental processes are the causes of our actions. Philosophers call this "commonsense psychology" or "folk psychology", which has been around since there were folk talking about other folk.




Scientific accounts of human nature are made plausible by examining the biological construct of the human mechanism (form/beliefs), the consequences of that construct (fit/function), and the core operating system (motivations/function).

Psychologists utilize the form, fit, function system to explain and predict human behavior. Generally the first two propositions: Form and Fit, are sufficient enough to explain and predict *90% of human behavior. The other 10% account for unknown propositions associated with the core operating system or key motivation (function). This is an unknown unless the subject under evaluation does the following:

  1. Analyzes through a series of quantifiable tests their core operating system, i.e., their Prime Motivator
  2. Correctly identifies that Prime Motivator
  3. Correctly correlates the Prime Motivator to actions
So long as these measures are executed precisely, our ability to explain and predict human behavior would increase to 99%, leaving a 1% chance for variable behavior based on systems outside the human mechanism, such as those catastrophic events only precisely designed instruments can detect. 

Big Data 

Big Data is a broad term representing large or complex data sets that traditional processing applications are inadequate. Understanding Big Data is understanding that 1% variable form, fit, and function cannot answer.

Data sets grow in size because new variables are constantly and exponentially being added to the mix. With each addition the memory capacity explodes, sensors go off, and even the size of the pixels in each scenario multiply.

The plot of this CPU transistor counts against dates of introduction is a visual example of data mapped on logarithmic vertical scale, with the line corresponding to exponential growth, in this case, the transistor count is doubling every two years.

Strategians studying Big Data with the aim of explaining and, more importantly, predicting the results of human behavior have their work cut out for them. Skilled Strategians can explain and predict 90% of Big Data metrics by merely considering Form and Function.

However, to reach the 99% accuracy tipping point in analyzing Big Data one must abandon Behaviourism and folk psychology and enter the domain of precise mental processes where computations take us to the realm of the 10% motivator function.

This variable, when executed precisely, can lead one in the direction of their Prime Motivator (function). If the Prime Motivator is to provide the world with insight, a brilliant psychologist is born. If the Prime Motivator is to make money, the next billionaire is born. Of course there is the "1%-Lucky" group; you know, those people who win the lottery, though admittedly Joan Ginther might be a different case entirely.

Is Luck the Successful Execution of a Skill Set?

Whatever subject upon which one chooses to test the Theory of Form, Fit, and Function; this theoretical system + it's 1% variable seems to account for the majority of experiences associated with human behavior and its constructs.

We can test out the Theory of Form, Fit, and Function by mapping out any given subject according to the method described herein.

If, however, you're a person who likes to complicate things by painstakingly spelling them out, then Hevner gives the world 7 Guidelines for conducting this type of research:

  1. Design as an Artifact - Design-science research must produce a viable artifact in the form of a winning lottery ticket ~ just kidding! ... in the form of a construct, a model, a method, or an instantiation. 
  2. Problem Relevance - The objective of design-science research is to develop technology-based solutions to important and relevant business problems. 
  3. Design Evaluation - The utility, quality, and efficacy of a design artifact must be rigorously demonstrated via well-executed evaluation methods. 
  4. Research Contributions - Effective design-science research must provide clear and verifiable contributions in the areas of the design artifact, design foundations, and/or design methodologies. 
  5. Research rigor - Design-science research relies upon the application of rigorous methods in both the construction and evaluation of the design artifact. 
  6. Design as a Search Process - The search for an effective artifact requires utilizing available means to reach desired ends while satisfying laws in the problem environment. 
  7. Communication of Research - Design-science research must be presented effectively both to technology-oriented as well as management-oriented audiences. 

If, on the other hand, you're a person who likes to keep things simple, then the maxim "think hard & keep things simple" can also yield similar results.

*Random percentage utilized in lieu of determiner pronoun: most.

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