We are scientists

We always remember the first time. For me, it was in high school. I was taking a drafting course focused on the manual application of graphite to paper. However, my family had recently acquired a Macintosh SE — a little beige box with monochrome screen and a huge 20-MB hard drive. Along with MacPaint, MacWrite, and something called HyperCard was a little program called MacDraw. This was to be my initiation into the vector-based CAD world. With my drafting instructor’s permission, I began experimenting with this new tool and, using my newly acquired skills, was able to turn out decent facsimiles of my hand-drafted assignments.

This was notable for two reasons. The first was that as long ago as these events were (during a year which shall not be named), computer technology was already rapidly evolving; any specific procedures that I learned would soon be obsolete. The other was my teacher’s willingness to allow a bit of experimentation to see what the little Mac could do. This unique learning environment taught me not just the technical aspects of drafting but also an awareness of how fluid any particular skill set must be. Even more so now: Just as we master our software or new cell phone, the next version comes along, requiring us to alter our actions to fit the new environment. But as frustrating as this may seem, there is a silver lining. Science depends on human ability to make and test predictions, and so does everyday business.

Business, however, does not have the luxury of knowledge for its own sake. Any investigation must conclude with a recommendation and a decision on a course of action. The science, as it were, must yield to the real world. Perhaps in recognition of this, we don’t often use terms such as hypothesis or theory in the scientific sense, but are rather quite comfortable with assumptions, gut feelings, and ideas — concepts that are worth pursuing, but which still require further development and supporting data.

Like engineering itself, the business environment demands conformance to its rules. Unfortunately, while our designs are governed by unchanging physical principles, the regulatory, technological, and financial constraints that shape our livelihoods counteract our efforts to build a rigid framework for our decisions. Returning to the opening story, I had an idea that it might be feasible and faster to produce my drafting assignments on the computer. But without any data to back it up, it was necessary to evaluate the speed and quality of the work during my “experiment.” Furthermore, as the rules and constraints changed, I needed to reevaluate my procedures, using existing methods and results as the new baseline.

Likewise, you may have the feeling that a particular method may benefit your business. What do you do about it? You might look to the “scientific literature” that is your industry’s journals and textbooks, or you might undertake some experimentation of your own to prove out your hypothesis. This is where it becomes necessary to balance your need for data with the tendency to get caught in analysis paralysis. You want just enough information to build a reasonable model of the real world and make a suitable prediction, without pursuing information at the expense of your other projects.

But two pitfalls await you. Beware of the “no brainers” as well as the “best practices.” It is tempting to pursue a seemingly obvious course quickly when all the evidence points to its success, or to adopt practices blindly that seem to work for your competitors or the industry at large. The former are often crying out for additional analysis to better quantify the benefit while the latter may not truly be the “best” for your particular business situation. Both are prone to unintended consequences.

The answer? Engineering education is built on a foundation of scientific discovery and application. Every technical course is dependent on following the scientific method to some degree. In sum, we learn as much about the critical thinking necessary to apply it properly as we do about the mathematical results at the end. Take advantage of this background to further develop this skill in your staff. From utilizing your engineers to perform basic market research to determining the break-even point for project costs, opportunities abound for rigorous data analysis and educated conclusions. Make the most of our science-based heritage and remember that the knowledge you develop is often priceless.

Jason Burke, P.E., is a project manager in Billings, Montana. Find additional information at http://pmug.wordpress.com.

E-mail comments in care of bdrake@stagnitomedia.com.


Posted in Uncategorized | January 29th, 2014 by

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