Decisions you make, and Actions you take
, are the result of forming a conclusion. How you form a conclusion is almost always based on either Deductive or Inductive Reasoning. Even emotional or “from the gut” decisions are mostly Inductive reasoning at work. A brief understanding Inductive reasoning can prevent false conclusions and costly mistakes.
“Every time we release a new product we are deluged with technical support calls. How do we avoid this?”
First, a few simple examples of Logic:
“If you change they way a product works, customers are initially less productive. We are changing the way our product works, therefore our customers will initially be less productive”. If the initial premise is true, the conclusion must be true.
: We released 5 products last year. With each release we had less than 10 known “bugs”, and our customers rated us high in quality. At release, our new product will have less than 10 known bugs. Therefore it too will score high on quality. Hmmm … not certain?
Inductive reasoning is all about Probabilities
. Given a circumstance that results in a particular outcome, there is a probability that the same circumstance again will result in the same outcome, but not without the possibility that it might not. Examples:
High probable Inductive conclusion: “When we speak with our customers, they are happy we called. Therefore, when we call Joe our customer, he will be happy we called”. There is no guarantee here, but the evidence is strong that Joe will be happy we called.
Low probable inductive conclusion: “We increased our advertising by 25%, and our sales increased by 25%. Therefore, we should increase our advertising by 40%, and our sales should increase by 40%.” A few things to worry about here. First, the premise is weak, i.e. there may have been many factors, not just the advertising that went into increased sales. Second, the logic implies there is a linear relationship between advertising and sales. Maybe … maybe not.
The initial statement will drive the thinking
. Is it “Fact” or is it being stated in a way that sounds like fact, but is actually speculation or a “most, many or sometimes”. “The customers are crying out for feature X”. Is this overwhelmingly true amongst the majority of customers, is it the feedback from a respected customer, or is it input from an overzealous sales rep who will close the sale if a feature is added. If the probability of truth in the premise is high, then induction will result in a conclusion with a high probability of truth.
Back to the example HeadScratcher
. So is it every time, many times, or just the last time? What are the customers calling about? Can you reach a conclusion from the symptoms? For example, if many of the calls are “You made it harder”, and it’s because you changed the interface, then the logic might follow, that “When you change the interface, you get deluged with customer calls”. This is different then “every time we release a product”.
Beware of the bad logic
. It is possible, and common, to error in applying logic. While the premise might be clear and true, conclusions can be made based on “faulty” logic. This especially happens when applying a “Not” condition. For example: “Customers like us when we call them”. The faulty logic is “Customers don’t like us if we don’t call them”. The Takeaway
: What matters is “How strong is the premise?”. Is it a certainty, or just a high probability? Understand the strength of the premise before you draw conclusions. Then, make sure you don’t have a logic bust. Conduct a “Let me check the logic here” conversation with someone. For the emotional, gut conclusions … they are Induction at work, often with an intuitive sense that the premise is strong … still check the logic that leads to the conclusion.