QUOTIENT SUMMARY

This page provides a summary of the quotients that have been established so far in these pages.

PROVENANCE QUOTIENT – This value quantifies the origins of our designs.  The more original the provenance, the higher the PQ.  If Pinterest was used to find an interesting image which was then copied, the PQ is low.  If, on the other hand, a form was generated via choisey one point from one of Ellsworth Kelly’s plant drawings, then the PQ will be high.  If you leafed thru your favorite architect’s monograph, found something that interests you, and then copied the building, the PQ will be low, very low.

ANALOGUE QUOTIENT – Quantifies the degree our designs were not touched or influenced by the machine.  Did you utilize the Google Image search algorithims?  If so, the AQ is greatly reduced.  If, on the other hand, the design solution was developed via a few cycles of paper models and sketches, the AQ will be high: you did it all with your hands.  Or if the design was generated your arrangement of flower petals from which a drawing was then produced, the AQ will be high.

OPTIMISM QUOTIENT – Our design solutions should be optimistic.  An iPhone is optimistic.  A building solution that is integrated with the site, brings in natural light, and employs passive energy usage is optimistic.  A Greek Revival mishmash is pessimistic.  A solution that provides unique and satisfying user experiences is optimistic.  We are architects.  What we do is based on optimism;  we can create something unique.

DESIGN RISK COEFFICIENT – This could just as easily be called design risk quotient.  This provides a value to the risk and uncertainty that the design imposes upon a client and community.  Any design has a degree of risk;  there are unknowns.  As we have established, clients have an innate tendency to avoid risk.  Therefore, the higher the DRQ, the more that the design pushes the artistic boundaries of the client.

These are the quotients and values that have been established so far.  All of these values are an attempt to begin to quantify design.  The quantification of design will move it towards the scientific method.

Here’s an example.  Let’s imagine that the drawing above is what the interior lobby of an office building would look like.  The design was generated by projecting the basic outline of my arrangement of fuchsia flower petals on a white plate.   If each of the quotients has a scale from 1-10, the design above would have this quotient summary:

PQ:  10.  Flower petal form generation.  Unique!  Great provenance!

AQ:  10.  I collected and arranged the flower petals.  I made an (analogue) drawing from this arrangement.  With my hands.

OQ:  8.   Any historical reference is basically non-existent.

DRQ:  9.  The construction of this would be a risk for anyone.

With these quotient values, this is a good Analogue Design.

As we have seen, the scientific method has many parallels with design.  There is a creative urge in the development of scientific solutions;  see SCIENTIFIC CREATIVE URGE.  We have acknowledged that the act of solving a scientific problem is primarily visual;  see SCIENTIFIC VISUALIZATION.

If science is quantifiable, then why not design?  Let’s admit it, the ability to quantify design would give, among other factors, the numerical basis with which to get paid.  Good numbers means good compensation, plain and simple.  A high PQ and OQ might mean that you get paid more for your ideas.

So it would make sense to develop quantifiable standards by which to measure design.  Doing so would open up a means of discussing design that does not now exist.  Design quantification would enable the use of values in our discussions with clients.  Quantification would provide values to help determine if the design solution is working toward the correct solution.

These values, which quantify the means of the design, will improve the understanding of the quality of the design for the client.