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176 Part One Organizations, Management, and the Networked Enterprise

SYSTEM QUALITY: DATA QUALITY AND SYSTEM
ERRORS

The debate over liability and accountability for unintentional consequences
of system use raises a related but independent moral dimension: What is an
acceptable, technologically feasible level of system quality? At what point
should system managers say, “Stop testing, we’ve done all we can to perfect
this software. Ship it!” Individuals and organizations may be held respon-
sible for avoidable and foreseeable consequences, which they have a duty
to perceive and correct. And the gray area is that some system errors are
foreseeable and correctable only at very great expense, an expense so great
that pursuing this level of perfection is not feasible economically—no one
could afford the product.
For example, although software companies try to debug their products
before releasing them to the marketplace, they knowingly ship buggy prod-
ucts because the time and cost of fixing all minor errors would prevent these
products from ever being released. What if the product was not offered on the
marketplace, would social welfare as a whole not advance and perhaps even
decline? Carrying this further, just what is the responsibility of a producer of
computer services—should it withdraw the product that can never be perfect,
warn the user, or forget about the risk (let the buyer beware)?
Three principal sources of poor system performance are (1) software bugs
and errors, (2) hardware or facility failures caused by natural or other causes,
and (3) poor input data quality. A Chapter 8 Learning Track discusses why zero
defects in software code of any complexity cannot be achieved and why the
seriousness of remaining bugs cannot be estimated. Hence, there is a techno-
logical barrier to perfect software, and users must be aware of the potential
for catastrophic failure. The software industry has not yet arrived at testing
standards for producing software of acceptable but im perfect performance.
Although software bugs and facility catastrophes are likely to be widely
reported in the press, by far the most common source of business system failure
is data quality. Few companies routinely measure the quality of their data, but
individual organizations report data error rates ranging from 0.5 to 30 percent.

QUALITY OF LIFE: EQUITY, ACCESS, AND BOUNDARIES

The negative social costs of introducing information technologies and systems
are beginning to mount along with the power of the technology. Many of these
negative social consequences are not violations of individual rights or property
crimes. Nevertheless, these negative consequences can be extremely harm-
ful to individuals, societies, and political institutions. Computers and informa-
tion technologies potentially can destroy valuable elements of our culture and
society even while they bring us benefits. If there is a balance of good and bad
consequences of using information systems, who do we hold responsible for the
bad consequences? Next, we briefly examine some of the negative social con-
sequences of systems, considering individual, social, and political responses.
Balancing Power: Center Versus Periphery
An early fear of the computer age was that huge, centralized mainframe
computers would centralize power in the nation’s capital, resulting in a Big
Brother society, as was suggested in George Orwell’s novel 1984. The shift
toward highly decentralized computing, coupled with an ideology of empower-
ment of thousands of workers, and the decentralization of decision making to

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