Our
present approach to producing products tends to limit the amount of
information needed by those potentially affected by the products to
adequately avoid waste and other adverse impacts. This can be traced
to how businesses treat problems.
Some
problems are known (identifiable and understood) and can be fixed
based on experience and a basic learning curve; while others, or
parts of others, are unknown along with how they can be fixed. A
problem is typically identified by the differences between
observations and expectations, which is the function of testing.
Understanding the problem is more challenging because it involves
finding the causes of those differences (troubleshooting). Testing
and troubleshooting together are considered a task that is often
performed by a person or team, just as fixing the problem can be
considered a task performed by a person or team.
Both
"finding" and "fixing" tasks are often performed
simultaneously, resulting in some fraction of the overall problem
being fixed over a given time. Fixing the problem stops when its
total cost exceeds either the available resources or the cost of
living with what's left to fix. This economic approach to fixing
problems has the important downside that the finding task is also
stopped, which limits knowledge about how much is really left to fix
and makes its assessment more of a guess.
Some
simple
modeling using basic learning curves shows that, as a rule of
thumb, the effort required to find and fix a practically unknown
problem is three times the effort required to fix an entirely known
problem, assuming that each task uses the same number of people and
everyone performing those tasks has at least average preparation and
proficiency. If guessing is unavoidable, then prudent planning would
include this margin. If knowledge about the minimum effort is
unavailable, then we can assume (also as a rule of thumb) that it
will be ten times the effort that an ideal team under ideal
conditions would need to expend.
In
my experience, most of the "find" task is typically done
during research and development, before large-scale production of a
product is even attempted. Most potential problems are identified and
fixed during redesign of the product. Also, it is common to complete
only up to 80% of the find task prior to production, which my
modeling suggests is the result of a plan to use the minimum effort
for both finding and fixing (instead of just fixing).
The
20% difference in quality may or may not be found by customers, whose
feedback could be incorporated into future "products" along
with new features that justify them paying more. This is a way of
masking and evading twice the acknowledged economic cost (whose
largest component is essentially effort). The physical cost still
exists, however; and can become much larger when the product is used
in a dependent relationship with other products and conditions that
are combined in a system. If a system's performance degradation
becomes large enough due to multiple problems that haven't been
totally fixed, then an additional cost may be added to fix it, some
of which is indirectly due to deficiencies in an individual product
and is thus passed along to the customer of the product.
One
way that a producer can ensure keeping their own cost down is to
define product performance to only include what they choose to
totally fix. The success of this strategy depends on knowing what
that is before they set expectations for the product with their
customers, and having a way to deflect responsibility for the
consequences of what they missed. This may be one reason that
businesses try to eliminate government oversight in the form of
inspections and regulations beyond what they explicitly promise to
their customers, because accountability for consequences of what they
missed could force the cost back on them.
Application
of the precautionary
principle would also force the cost on the producers, by making
them assess the impact of their products on people and environments
where the products might be used, and not deploying products where
any of those impacts are negative. A major argument against this is
the stifling of innovation which might result in advantages over
existing products, an argument that is implicitly built into
biological evolution, a process of creating "products"
(species) that die out if they don't provide an advantage to
procreation.
Since
the main test of products is their continuing sale to customers, and
sales can't be made if customers die before they buy, it might make
better sense to ensure that full investigations of problems and
potential problems are conducted, either by businesses or agencies of
the public, and the the results released to everyone for
evaluation. The investigations and release of results would continue
as the conditions, environments, and underlying understandings change
beyond those originally considered.
Key
to enabling evaluation would be development of truly universal and
quality education that includes unbiased access to basic knowledge,
understanding, and skills, along with experience in the investigation
of products over a wide range of types. If the complexity of products
exceeds the ability to adequately investigate and evaluate them, then
people would become less likely to accept them and they would
ultimately be discontinued.
