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Propositional logic can build better estimators

Tuesday, May 1, 2018 - 07:00
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Words evoke thoughts and emotions. They are the reason we feel happy, agreeable, uncomfortable, confused or upset. But, why is that? This is because words create statements. Statements contain evidence that helps form a premise and make a conclusion. The premise and conclusion together form an argument and we analyze the argument to see if it makes sense. The idea of making sense is a function of the argument’s logical structure. Well-formed arguments fill in all the blanks and lead right to the conclusion while not so well constructed arguments leave you feeling seemingly unconvinced or confused. 

Estimators are tasked every day with using sound logic and forming valid arguments to advise customers and negotiate repair costs. There is an opportunity for employers to enhance their training regimens and benefit their employees by looking outside the industry for solutions. One of the toughest positions in a shop to train for, from scratch, is estimating. Estimating does require knowledge of cars and there is training available from I-CAR, paint companies, tool companies, 3M, and more. 

The curriculum supplied in these courses is excellent and beneficial to the estimator. However, there is a component that is missing, that in its absence will spell almost certain failure for a new estimator. The missing component is logic. Logic is required for writing an estimate, negotiating a supplement, researching OEM repair procedures, and many more job related activities. You have used a form of logic if you have written any formulas in Microsoft Excel. Propositional logic, however, is the study of words — more specifically, the logical connectives of words and the statements they create. Propositional logic teaches how to take words and turn them into equations. It teaches good reasoning skills and allows the student to make valid assumptions and inferences based upon a specific set of rules. Propositional logic will aid estimators not only in estimating, but also in problem solving. It is with these math equations that an argument’s validity can be judged and the truth or falsity of a statement can be determined.

The tools learned in the study of propositional logic will aid estimators in writing thorough estimates using conditional statements. It will enable them to draw inferences and conclusions from the database reference manuals and construct valid arguments for use while negotiating for not included items. It will enable them to overcome poorly formed objections during negotiations and will make researching, interpreting, and applying OEM research easier.

Propositional logic has five main symbols called logical connectives. The table below shows the connectives and describes their connection to words and their function. Propositional logic uses sentential letters when creating equations to represent statements. The sentential letters used in the equations have been bolded in the statements and the connective elements have been underlined to highlight them in this article.

The statement: it is Winter but it is not Snowing can be depicted as follows and would read W and not S.

Statements create premises and conclusions, which form arguments. Arguments have two parts, the antecedent and the consequent. The antecedent is the premise of the argument and the consequent is the conclusion. In the next example if you were to read an OEM’s position statement on reconditioned wheels it would read something like this: OEM Approves of repairs to wheels that only involve the Removal of the painted surface and does not require any Straightening, Welding, or Machining when reconditioning their wheels.  The formula would look like this:

The equation would read: if the wheel requires removal of the painted surface and does not require straightening, welding, or machining, then it is an approved repair by the OEM. If the truth value of S, W, or M is known, the equation can be solved for A. From the other side of the equation if A is known, then inferences can be made about the truth values of R, S, W, and M. These have been two very basic examples and the real application of propositional logic begins when estimators learn about proofs and how to solve them. Proofs in propositional logic consist of a series of formulas such that each formula is derived either from a previous formula’s premise or created from an inference rule that is taught in propositional logic.

Training on propositional logic is readily available. Courses can be found at local colleges, through apps such as Coursera, and even on YouTube. The best part about the online options is that they are driving down the cost of education and delivered at a pace convenient to the student. Coursera has an introduction to logic class that is available from Stanford University for free. I would encourage you to investigate propositional logic and how it can benefit your businesses training regimen and improve your results. After all, it’s only logical.

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