#91 from R&D Innovator Volume 3, Number 4          April 1994

Four Commonsense Rules for Creative Analysis
by John R. Brinkerhoff

Mr. Brinkerhoff is a writer living in Burke, Virginia, who specializes in promoting commonsense solutions to everyday problems.  He is the auther of 101 Commonsense Rules for the Office, 1991, and 101 Commonsense Rules for Making Things Happen, 1993, both published by Stackpole Books, Harrisburg, PA.

Creating something new isn't easy, and for that reason the ability to create new things is highly prized.  The nature of creativity is itself something of a mystery. 

I'll discuss "creative analysis."  Analysis isn't inherently creative, since it's the opposite of design.  Design is inherently a creative process that requires decisions to be made at each step.  Analysis is intended to tell you what is going on rather than what can be done or even ought to be done, and the analytical process per se doesn't necessitate decisions or choices.

Let me illustrate the difference between design and analysis using an example from civil engineering.  Analysis of a highway bridge occupied an entire semester of my civil engineering education.  The class was assigned to rate the capacity of an existing bridge, and went through each truss, beam, and pin to determine which critical member established the capacity of the bridge.  The analytical process was tough but straightforward, and did not require making choices about construction. 

Later, while I learned to design (create) a bridge, the entire process was about choices.  As designers, we had to choose the location of the abutments, the kind of bridge, the size and shape of the members, the placement of the lateral bracing, and so forth.  Each choice was bounded by the usually competing demands of aesthetics, cost, and safety.  And each choice, once made, foreclosed some options.  Ultimately, our creation was the aggregate of all of those design decisions.

So, design is creative, while analysis is not.  But analysis can be a useful part of the creative process if it provides insights that lead to better choices.  By way of contributing to creativity, I offer four commonsense rules for using analysis to assist the creative process.

Rule One:  Question the Question

Let's start by questioning the question, to see if the question you're seeking to answer is the correct one.  Sometimes the problem to be analyzed is obvious, but often the problem is selected by an executive who unwittingly poses it in a way that prejudices the answer.  One of the first things a creative analyst should do is examine the data to see what the real problem is.

A classic example of this kind of creative analysis was work on bomber basing done by the RAND Corporation for the Air Force in the early 1950's.  The Air Force wanted RAND to determine how to build and maintain air bases overseas at minimum cost.  But the RAND analysts decided after much thought that this relatively simple logistics problem wasn't the real question.  The real problem was "not one of the logistics of foreign air bases, but the much broader one of where and how to base the nation's strategic air forces and how to operate them in conjunction with the base system chosen."  The resulting broader study led to a decision to base more of the bombers at U.S. bases.  Questioning the question allowed the analysts to restate the problem and achieve a solution that refuted the conventional wisdom—but was adopted by the Air Force with good results and considerable savings.

My advice is to look at your problem at the outset and assure that you've stated the problem correctly for your needs.

Rule Two:  Rummage Through the Data

Creative analysis often occurs by rummaging through a mass of data more or less haphazardly just to see what comes to light. 

Data has always been a problem for analysts, and getting data occupies most of the time and effort for any analytical effort--much more than working on the data after it's assembled.  This means that most projects are data-limited, and the data are biased to provide specific results--whether or not this is a conscious act by the analysts.  In the past, most data have been ad hoc in the sense that they were compiled for a specific project.

Now, however, large amounts of data are compiled in computers, or are by-products of other processes, residuals from analytical projects, or sometimes even created for their own sake.

The process of rummaging through data consists of looking at it with no viewpoint, no problem to be solved, and no preconceived solution.  The goal is to detect patterns, trends, and numerical relationships that reflect natural phenomena.  This kind of analysis will sometimes reveal truths that are contrary to the conventional wisdom, truths that are often not self-evident.

One good example of this process is the work of Johannes Kepler, an early seventeenth-century German mathematician.  Using observations of planetary motion made by others, Kepler spent years calculating the orbit of Mars.  While the data indicated that the orbit was an oval, Kepler noticed a pattern that generalized into his first law:  The radius vector (the line from a focus to a point on the orbit) sweeps equal areas in equal intervals of time.  This motion is true only for an ellipse, and so Kepler was the first to notice that the planets traveled in elliptical orbits about the sun.  This discovery provided the basis for Newton's later work on mechanics and opened the door to modern astronomy and physics.  By rummaging through data, Kepler used analysis to create a new world.

(Incidentally, while Kepler was founding the science of astronomy, he earned a living by casting horoscopes.) 

My advice is to use the available data--carefully, systematically, slowly--and see what results.  You might be surprised.

Rule Three:  Note the Exceptions

Analysis is mostly boring, particularly now that computers allow us to crunch so many numbers.  Before computers, a few analysts spent an eternity doing manual calculations.  Many analysts in that pre-computer period resorted to intuitive generalizations because they had no choice. 

The ability to perform many repetitions has virtue because it allows alert observers to note the exceptions.  One good example of this was an occasion when the computer told us something we refused to believe. 

I was part of an analysis shop for the Army running a combat simulation called ATLAS.  This theater-level model simulated war between NATO and the Warsaw Pact in Central Europe; it was organized into 10 corps-sized sectors running from Denmark to the Swiss border.  Force ratios were calculated in each of these sectors, and they determined the rate of advance and the casualties for each side.  One of NATO's advantages was reinforcements from the U.S., and the computer allocated these forces by a rule that placed them where they were needed most--in areas where the force ratios were the worst for NATO.  We kept running the model, and usually the reinforcements were sent to the "wrong place."  There were complaints that the model was wrong, but it was just following orders and providing us a useful insight--if we had the wit to see it.

Finally, we understood that the model was telling us that our plans to reinforce in the south were wrong, and that we needed instead to reinforce the north.  Once this vital insight was accepted, the plan was changed to have some of the newly arriving forces form a third U.S. corps on the north German plain, and in the computer, at least, NATO started winning the battles.

My advice is to look for the inexplicable, the dumb answers, the discontinuities, the blatantly wrong solutions--and take them seriously.

Rule Four:  Clarify the Presentation

A lot of creativity lies in finding things that aren't readily apparent but that are obvious once discovered.  Much of this has to do with presentation--it isn't enough to compile or analyze data to discover new insights; we must also communicate the results.

In my opinion, the best aid to communication is clarifying the presentation.  Done properly, this will allow even the most complicated concepts to be understood by outsiders to a discipline.  There is a genuine danger that the truth may be distorted in clarification, but presenting so much data that it's incomprehensible doesn't serve truth either.   The trick is to design your presentations to provide the essence of the truth while doing no damage to the details.

I was able to clarify the true meaning of some time-series data by deftly manipulating the range of dates to make my point.  The subject was strategic warning for World War II, and my hypothesis was that although the United States was tactically surprised by the Japanese attack on Pearl Harbor, it wasn't strategically surprised and in fact was well prepared for war.  To demonstrate the extent of mobilization, I prepared charts with data from 1933 to 1946 showing the numbers of military personnel, combat aircraft, navy ships, and percent of gross national product spent for defense.  The results were disappointing because the gigantic efforts made during the war itself--from 1942 to 1945 --simply overwhelmed the data for the pre-war period.  On these charts the pre-war data showed no growth at all.

In a fit of desperation, I made charts including only 1933 through 1941.  These charts clearly showed that the preparation for World War II started as early as 1933 for some areas, and more generally, in 1939.  While the pre-war preparations were small relative to the war-time mobilization, they were substantial compared to the pre-1933 period.  This creative mode of presentation was important to show what really happened.

Try to understand what exactly you are trying to demonstrate and--without distorting the facts--use creative means to do so.

Analysis may not be creative per se, but it helps to apply creativity to the analytical process.  Properly used, analysis can lead to motivation.

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