Tag Archives: Systems

Cruising is ultimately about individuals accepting accountability for their own choices. You’ll see that comment in our disclaimer. In a recent comment dialog on Attainable Adventure Cruising, the subject of inflatable life-jackets has received a lot of useful exploration. In the course of participating, I started rethinking the issue of “choices.” With equipment in mind, there are:

• Caveat Emptor–you are on your own with respect to what the market provides.
• Lightly guided/constrained choice–government or private groups assist through testing (UL, etc), and specification (USCG, SAE, IEEE, etc).
• Tightly guided/constrained choice–the government defines the range of choice, but no choice remains an option (EPIRBs).
• Quod est Lex — it is the law — government defines the range of choice and enforces it with penalties (no choice option only available to scoff-laws).

When making choices, humans tend to fall between two extremes with a peak in the middle.  Near zero on the axis is how little can I do to meet the most probable need (called sufficing). On the far end is minimizing one’s maximum regret (sort of a belt + suspenders/braces + helium balloon approach.)  Both of these ends tend to be risk tolerance constrained choices.

The middle causes the doubt. The middle tends to be a muddle of the entrepreneurial “new thing” and the enduring “good enough for my Da/Ma, good enough for me.”

Three things to remember when navigating this muddle.

• Statistically speaking, cruising involves a small, heterogeneous sample set with high anecdotal content (relative to automobiles & airlines for example). Because anecdotes tend to be more interesting than data, we tend to listen to the best stories rather than look at the data all the way back to its accumulation rules.
• Coincidence and Causation frequently sleep in separate bunks. Look for the confounding variable. One can often drill a very shallow well to get a gusher of “not so fast.” Because there are more influences on the outcome than are being reported or collected, our minds tend to fill in the blanks according to our pre-existing biases. The most frequent error is the apples and oranges fallacy.
• A product or a service sits on the tip of a pyramid. Its corners are business reality of the provider/market, provider product/service focus, endurability of the support infrastructure, and government involvement. Because we are bombarded with new, New, NEW, we tend to be herded in the direction of non-durable products/suppliers. & Because the current business environment favors consolidation, many of the market’s suppliers are diluting their focus.

Consistent with the disclaimer, I wouldn’t even attempt to suggest an approach, but I will say:

1. If a highly hyped product has no statistics, or they won’t share them, we walk away–if we are going to be someone’s market development experiment, we have to include early/frequent product/service failure as an acceptable outcome.
2. If the statistics jump to a connection between widely separated or potentially confounded data, we ask to see more. If more isn’t available, we often loop back to #1 above.
3. For any product that may require service or spares, we tend to look for suppliers who have a high probability of survival. We would rather have fewer features and benefits in favor of endurance between retrofit, than smokin’ hot performance that can’t be fixed or supplied or serviced should the need arise.
4. Finally, we believe it best to buy from suppliers who have more than a business commitment to their product. Usually, that can only be determined by a visit to the company. (Boat Shows are Shows, not necessarily Tells.)