risk

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In 1625 the king of Sweden, GustavII Adolph, ordered the construction of a new warship, to be christened in 1628 as the Vasa. Not content with average, or even excellent, he insists that his shipwright build the most powerful warship of the age, adding a second deck of cannon above the first.  The Vasa was designed to carry 64 guns, 300 sailors and 150 marines, positioned on a quarterdeck built extra high to allow them the shoot downward in close engagements.  A splendid design, a glorious ship, with extra attention paid to adding attractive carvings of royal images.

It is unclear if the shipwright made any attempt to push back on the good king as to the unreasonableness of the design. Of course design validation testing was not a common term at the time, and no one had coined DFMEA as an acronym in that century, but still there was a great body of knowledge available on ship design, stability and the principles of naval engineering.  Perhaps the shipwright did speak up , or perhaps he feared for his head and was silent.  This was after all the 17th century.

On August 10, 1628 the Vasa set sail in Stockholm’s harbor for the first time.  The king’s loyal subjects lined the quays and waterfront to watch the great ship, in an atmosphere of great festivity.  Within minutes of setting just four of the ten sails, the great ship heeled to port, then heeled harder, taking water in through the open gunports, and capsized, in full view of the onlookers.  The ship sank immediately, with at least 30 lives lost.

Fast forward to the 21st century. Substitute CEO for kingengineer for shipwright, job security for fear of beheading, product launch party for festive atmosphere along the quay, and industrial design for royal carvings, and the analogy is complete.  As engineers we should not blindly design and build a product to a set of flawed requirements. It is our duty to raise the flag when we believe, based on proper analysis and backed up by rigorous data, that a design is flawed.  When we see requirements for that extra gundeck that compromise our design margins, threaten the reliability of a product, or create product liability risk, we need to speak up.  Which is not to say that engineering concerns should always trump marketing or business requirements–far from it. (product safety is another matter, especially when risk to life or limb is present, in which case do not take no for an answer). But management needs to weigh engineering data into their decisions carefully, and make risk decisions–after all, business almost always means taking risks–based on hard data.

As to the Vasa, it was raised from the depths in 1961 and reconstructed painstakingly by the Swedish descendants of those that built her, a marvel of modern engineering and preservation science. The warship is on display at  the Vasa Museum in Stockholm (http://www.vasamuseet.se/), a must-see if you are in the area.

Skål!

Chuck

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It’s shockingly easy for guys like me to get up on our virtual soapboxes and basically say, “You gotta do the right thing.”  Let’s face it—we all want to take the high road; we all thinkthat we do take that road more times than not.  So wanna be blog-meisters like me can easily say “thou shalt test more” or “thou shalt conduct design reviews” or whatever and it sounds good, albeit a bit pompous.  But let’s face it: business is, for better or for worse, about making money.  So when we make decisions on productization—or most other topics—we gotta do the right thing  and make money.

So to the question at hand—how do we make the right decisions on investing (incurring expenses) on productization?  The answer can be summarized in two words: Risk and IRR.

Risk is easy to understand but tough to quantify.  In general productization efforts lower risk.  Examples of risks that proper productization efforts can mitigate include:

  •  Risk of delays
  • Risk of field failures
  • Risk to brand / image
  • Risk of damage to property or person
  • Liability risks
  • Inventory risks

Examples of productization efforts that fundamentally reduce risk include:

  • Design Validation Testing (see our earlier Productization blog on this topic http://www.zebulonsolutions.com/productizationblog/?p=50/ ), which can mitigate the risk of field failures, property damages, risk to life and limb, and liability risks.
  • Production test development basically mitigates the risk of test escapes that can lead to field failures, returns, and damage to brand, as well as potential risk to property, life and limb
  • DFx reviews address schedule risks, can mitigate inventory risks if proper attention is paid to Design for Supply Chain, etc

The other topic is IRR—Internal Rate of Return—is not so easy to comprehend but easy to calculate.  IRR is a form of return on investment calculation that better handles non steady state conditions than traditional ROI or ROIC calculations.  IRR calculates the return from a series of disparate cash flows—often a negative cash flow representing monthly investments in say a cost reduction redesign and then positive cash flows in the term of lowered cost in production.  Sounds complicated but fortunately spreadsheets can do this calculation easily (almost easily—it’s actually an iterative solver at least in Excel so sometimes needs help to converge, and there is the tricky issue of salvage value.  I can expand on either of these offline if anyone is interested in the details…).  IRR is thus a way to quantify the benefits received from investments in productization.  IRR can deal with time easily by using appropriate time units—months, quarter, weeks, years.

Then the really cool part (I show my age—does anyone use “cool” anymore?)  is one can combine both risk and IRR by using an expected value methodology for calculating IRR.  For example, if one can reduce the risk of field returns by say 10% by doing extensive Design Validation Testing, then one should calculate an IRR using 10% of the current cost of field returns as the payback. In fact even for mundane tasks such as cost reductions the return is never 100.0% certain (Murphy’s Law if nothing else) so one should really use expected value, in such cases as a derating factor,  in any IRR calculation.

The tricky part of course is assigning the right costs, the right risks, the right expected values and the right time frames.  But even if the calculation is not perfect, it’s far better than nothing or the omnipotent finger in the air.

Chuck

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