Of Screwdrivers and Lug Wrenches


Some of you will recall that I recently attended the AUSA Global Force Symposium in Huntsville, Alabama. Having had a great many meetings with Army and defense industry folks of all stripes gave me some new insight into the Army’s goals and challenges—and what I came away with caused me to ponder how we define and develop products.

It’s really interesting to me that we all, to some extent, race down our own rabbit holes of thought when considering a solution to a given problem. Convinced that we have the answer, we generate PowerPoints, white papers, proposals and media that support our view. We visit customers and state our value proposition with confidence. Sometimes we get lucky, hitting on just the right thing, but most times we don’t. (Ever had that experience when the customer, after enthusiastically responding to your pitch, gives you that one reason why your thing just will never work?) Nancy Nardin at Smart Selling Tools describes 10 reasons that can happen. This is great insight, but there's an even more fundamental divide between the things we get right and the things we get wrong.

The “things we get right” are almost always certain solutions to certain problems; that is to say, it’s possible to deduce a certain solution when the problem can be stated with certainty. For example: “I have a loose wheel lug" (certain problem). The solution can then be deduced as, “Here is a lug wrench” (certain solution).  Deductive reasoning works here because we have a set of conditions (the problem and the solution) that are unequivocally certain. Businesses love to pursue these kinds of solutions, precisely because they are certain; they can be costed, and their monetary value determined. 

It’s not all deductive

The “things we get wrong” are not always the result of a poor buying decision or promotion; they are often the result of our tendency to treat all problem solving as a deductive process, when in fact most problems are not certain and/or cannot be stated with certainty. Undeterred, we still apply the formula: A Problem + My Process + My Technology =  Solution. This is where we fail, because the real formula is: Uncertain Problem + My Certain Process + My Certain Technology ≠ Certain Solution.

In our world of embedded computing for the Army, rarely are problems stated in certain terms.

I hear things like “Smaller, faster, more expeditionary” and “the Art of the Possible.” Nothing certain there! The Army has needs that contain uncertain problems and to be successful in solving those problems (and answering those needs) industry mustn’t define the problem, but rather, industry must define the problem space. (A problem space is a place where the problem and its solution are in harmony. An example is; the problem space of two boards, a screw and a screwdriver. Fastening these boards together is the problem—the solution is the screw plus the screwdriver. Neither the screw nor the screwdriver alone can be the solution, but together they are.) Defining a problem space that seeks to meet the need of “smaller, faster and more expeditionary” requires a level of inductive reasoning because we have only some of the elements needed in the problem space. (Aristotle defined inductive reasoning as connecting effects to causes—basically, using experience and observation to provide answers). Here’s the catch. Inductive reasoning cannot provide certain success. It can only approach it. If we desire certain success, then how can it be achieved?

The problem space

We must try things, we must conceive products (which we can call “tools”) that work to define the problem space and have the goal of delivering a solution. We need a deep dialog with the customer; trying and adapting as we learn (and teach)—describing a problem space and then learning where it resonates and where it falls short, inducing options and deducing answers, iteratively defining the problem space and creating the solution. 

This is what we've been doing at GE's Intelligent Platforms business. What we have learned is that, with small changes in our products, we can define a solid problem space; we can define a set of tools within it and provide solutions. To do this we must be open and constantly vigilant against defining “the art of the possible” as “the art of what we have now”. 

We build embedded computers and we believe they are the best at providing the facility of “smaller, faster and more expeditionary”—but not because they are simply great “screwdrivers”; rather because they fit the other tools in the problem space (the screws) to provide the Army’s desired facility. 

Larry Schaffer

Larry Schaffer has been with us in a business development role since 2001, and works to create and maintain long-term, strategic relationships with key companies engaged in embedded computing for ground systems applications with a strong emphasis on image processing and distribution. He was born in Pennsylvania and educated as an Electrical Engineer in New Jersey and California (where he now lives). Just don’t ask him to tell you about being a war baby…

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