I have sometimes been amused during my attendance at high-level business meetings in American industry, amused at the discrepancy between the way we are told that important decisions get made and the truth. (Donald A. Norman, Things That Make Us Smart: Defending Human Attributes in the Age of the Machine, 1993, Basic Books, New York)
The logical-rational decision making models that we are taught in college are worthwhile and necessary, but they are rarely used in the course of everyday business. Although there are times when they ought to be used but aren’t, it is appropriate that they are used seldom. One reason for this is that these processes require a great deal of time — something we rarely have. The other reason is that if you have expertise in a domain, you are able to make decisions that are usually just as good, but require little time.
Gary Klein, Chief Scientist at Klein Associates, Inc., has written an informative book about decision making that approaches the topic quite differently from most other books and articles. In the introductory chapter of Sources of Power: How People Make Decisions (MIT Press, 1999) he sets the stage for his treatment of the topic as follows:
During the past twenty-five years, the field of decision making has concentrated on showing the limitations of decision makers — that is, that they are not very rational or competent. Books have been written documenting human limitations and suggesting remedies: training methods to help us think clearly, decision support systems to monitor and guide us, and expert systems that enable computers to make the decisions and avoid altogether the fallible humans.
This book was written to balance the others and takes a different perspective. Here I document human strengths and capabilities that typically have been downplayed or even ignored.
Klein has studied decision making for years and has filled the book with research findings of his own and others, along with story after story of decision making in action.
Despite the fact that we at times and for good reason use “deductive logical thinking, analysis of probabilities, and statistical methods” to inform decisions, Klein reports that in natural settings decisions are rarely analytical, but are usually informed by intuition, mental simulation, metaphor, and storytelling.
The power of intuition enables us to size up a situation quickly. The power of mental simulation lets us imagine how a course of action might be carried out. The power of metaphor lets us draw on our experience by suggesting parallels between the current situation and something else we come across. The power of storytelling helps us consolidate our experiences to make them available in the future, either to ourselves or others.
If you are new to a field, having not yet developed expertise in the domain, decision making must be informed by a relatively slow process of information gathering and evaluation. If you are an expert, however, this research-laden and brain-taxing process is necessary much less often. According to Klein, experts usually make decisions based on what he calls the “Recognition-Primed Decision Model” (RPD). It combines two processes: “the way decision makers size up the situation to recognize which course of action makes sense, and the way they evaluate that course of action by imagining it”. Experts can often look at a situation and quickly recognize it as familiar, knowing intuitively what’s going on and how to respond. When multiple courses of action seem possible, they can take the first from their immediately prioritized list and evaluate its merits by running a quick mental simulation. If problems are discovered during the mental simulation, they proceed to the next possible course of action, until they find one that works, and then without further delay, take action. Are they always right? No, but if they’re experts in the field, they’re right most of the time.
How does this relate to data visualization? People who analyze data, if they are experts in the domain, usually know what’s important and make sense of it based on pattern recognition. They’ve seen it before, or something similar. Nothing presents meaningful patterns that reside in data better than properly chosen and well designed visual representations. More than any other tool, data visualization software can support meaningful pattern recognition for a broad range of people and can enable them to clearly present what they’ve found to others. Good visual analysis software pares information down to its essence in the form of a picture, removing the noise to enable clear focus on the signal. It translates abstract patterns of meaning in the data into images that can be easily perceived by our eyes and discerned by our brains, thereby serving as an external tool of cognition.
Good decisions must be based on clear presentations of data that allow experts to bypass time-consuming and often unnecessary mental gymnastics and software mechanics so they can spend their precious resources assessing the situation and responding while there’s still time. If you don’t have good visual analysis and presentation tools to support this process, you’re wasting valuable time and working partially blind.