Ken Ganshirt @ Yahoo
ken_ganshirt at yahoo.ca
Sat Oct 10 10:54:08 PDT 2009
--- On Sat, 10/10/09, Jebadiah Moore <jebdm at jebdm.net> wrote:
> Assuming we're talking business success, there's definitely
> a sliding
> scale. Companies A, B, and C all sell widgets in the
> same market. Fixed
> cost of a million dollars to build a widget factory for all
> A sells a million units at $10 profit each
> B sells half a million at $8 each
> C sells only 50k at $10 each before going out of business
> C is obviously a failure (no profit), but you could
> reasonably call both A
> and B "successes". But A seems clearly more
> "successful" than B with three
> times the profits.
I have no difficulty with a "scale" of success if it's defined. Your example is no help. What are we measuring the success of? The operation of the million dollar factory? The decision to spend the million dollars to build a factory rather than investing it in something else? The pricing decisions? The sales efforts?
What criteria are you using for determining success? Sales numbers? Gross Profit? Net Profit? Return on the million dollars of capital invested?
I could think of other factors but induction is useless in a discussion like this. For your example to be useful you need to define what you are measuring the success of and how you are measuring it (specifics of the metrics).
You didn't define either, so I can neither agree nor disagree with your assertions of the relative success of A, B and C, either as a binary condition or on a scale, because I have no idea what you are measuring nor how.
My point is that there are no definitions of the metrics used in the chart that was offered in the original post so while the chart may be "correct" and may even be "accurate" it's not useful for anything. There's nothing we can learn from it because the information we need is missing.
Induction is not only useless in such a situation, it's dangerous. If we intend to learn something from the information presented AND put it into practice, if we guess wrong about what's inside the metrics we're in trouble before we begin.
Example using the chart in the original post: if we decide to improve the marketing-to-engineering ratio by reducing the engineering component of our projects (appealing in today's One-Minute Manager/Silver Bullet environment) but the metrics found that the success was based on increasing marketing efforts, we've just screwed ourselves.
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