Most of us have debt.
We may owe money to the bank or favors to our friends. We may owe allegiance
to our country, company, or commitments. We may owe a debt to ourselves for things we
have or have not done. We live in a sea
of debt, most of it simply the cost of living.
Those of us without debt are either lucky
or just not living.
Another form of debt, technical debt, has emerged only in
last 25 years. Originally, it was
created as an aspect of computer code.
When a large code is created, many decisions must be made. Often budget or time issues take a commanding
position. Sometimes, the quality of the
software engineers is not up to the tasks of the complex demands. Similarly, the knowledge base can be
insufficient to proceed correctly. The
orders may be, “Get the code online and quickly, and reduce the costs wherever
possible.” The debt is with the
readjustments, fixes, and rewriting of the code as it fails or becomes
outdated. Similar notions apply to most
solutions involving complex systems. In
the systems world, technical debt is a consequence of actions and decisions,
and it appears to grow with time, ala financial instruments. As a rule of thumb and a bit oversimplified, the
magnitude of downstream technical debt is proportional to resources originally committed.
Now consider what we call the
technical debt of our lives through our actions, solutions, and changes. For the many activities and situations of
daily life, we all make decisions. These
decisions often have ranges of options depending on priorities we set or face. Here
are a few.
Quality: low
vs. high – Do we take the time to consider whether the decision is well-considered,
or do we just take a “shotgun” approach and go with it, or anything? I want to buy a car. Do I go with the pitch of the salesman so I
can have the right now, or do I shop around? After all, we may not actually like the car
after a few months.
Time: slow
vs. fast – How much time is available to make a decision. Must we make an instant, often intuition-based
decision, or are we allowed the time to deliberate? Sometimes, when buying a house or something
of major importance, one is tempted to close the deal quickly and have it
done. When our child is having problems,
do we think carefully about the prescribed treatment for this real person,
whose life is in our hands. Such debts may not be repayable.
Prediction:
approximate vs. accurate – When projecting prospects of a decision, is the
approximate sufficient or do we need or strive for assurances of greater accuracy? Making a marriage proposal is certainly one
where the debt involved can be substantial.
As the old saying goes: “Marry at haste, repent at leisure.”
Resources:
few vs. many – How many resources can we apply to the problem. These include
time and money. How many resources do
you have in time, money, friends, colleagues, reading, and thought to regard a
pending decision?
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Ward Cunningham first defined
the term in 1992. You can Google “technical debt” and find, remarkably, it has become
a mainstream topic in systems software engineering. Many companies now compute technical
debt as a component of new project design and costs. What we have done here is apply the concept to
human systems, highly complex and fuzzy to boot.
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