appears that the challenge
of measuring what – at
first – appear to be “intangible” is common for many
analysts and managers in
organizations of all types.
A third edition has just
been released, with an accompanying workbook to
facilitate classroom teaching and self-study. The
third edition also allowed
the author to include cases from new clients and to
respond to the most common challenges sent in by readers in the seven years
since the first edition. As in the two earlier
editions, readers learn how to frame the
measurement problem and how to avoid
measuring the wrong things, and they see
the value of relying on their quantitative
models over pure intuition.
However, even for the most fervent
advocates of quantitative methods among
our clients and readers, we find that they
can easily be bogged down by some of
the same obstacles as the skeptics of
quantitative methods. Even though we
make what seems to us to be a strong
argument for the correct way to approach
these issues and even though clients say
they “conceptually” agree with the argument, they sometimes still seem to repeat,
unknowingly, some of the same errors.
A NA L Y T I C S
What follows are seven
areas where we build on
the message of the previous edition by adding
new cases, new research
and new responses to the
challenges we continue
to observe among our
readers and clients.
1. It’s still true, anything
can be measured.
We haven’t found a
real “immeasurable” yet,
although many things initially appear to
be. In the past several years, HDR has
developed measures of the risk of a mine
flooding, drought resilience in the Horn of
Africa, the market for new laboratory devices, the risks of cyberattacks and the
value of industry standards, to name a
few. The other author of this article (Samuelson) measured the asset value of information technology [Samuelson, 2000]
and the value of deterrence in security
situations [unpublished]. In each of these
cases something was perceived to be virtually impossible to measure and, yet, the
authors were able to show that we can
use informative observations and simple,
established mathematical approaches to
reduce uncertainty enough to make decisions. As in earlier editions, the book explains the three reasons anything is ever
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