vi
views, which are convincingly presented in such books as How to Measure
Anything…
2
offering five-step procedures for defining new measurands and new
measurement methods for business applications. In light of those guidelines, what
was considered a joke 50 years ago may become today a serious business approach
to measurement. One of such jokes, most frequently repeated at that time by the
students of measurement science, went as follows:
Examiner: “How to measure the height of the university building using a
barometer?”
Student: “By offering this barometer to the administrator in exchange for the access
to the technical documentation of the building.”
Measurements, considered to be the most reliable sources of information, are
omnipresent in the life of information society which, by definition, is intensively
and extensively involved in the usage, creation, distribution, manipulation, and integration of information. The reliable measurement data are indispensable for
decision- making processes, especially if the latter are supported by IT tools. The
demand for such data appears not only in a research laboratory but also on a production line and in a hospital. The growing demand for such data may be observed in
various institutions of public administration, education, and transportation. Unlike
in the nineteenth century, the institutions of business and bureaucratic management
are the main driving forces behind the avalanche generation of new measurands,
especially so-called performance indicators, and the corresponding methodologies
for their evaluation. Despite the socioeconomic damages implied by the reckless
application of those indicators for decision-making, despite the common awareness
of the so-called Campbell’s law
3
and Goodhart’s law,
4
their use is not getting less
frequent or more prudent. The reasons are obvious:
• They are claimed to be more objective than experts’ opinions.
• They may be easily “digested” by the algorithmic procedures supporting the
decision-making processes.
• Once agreed by the decision-making bodies, they play the role of excuse for
pragmatically or morally wrong decisions.
• They effectively replace intellectual qualifications of the decision-makers.
Another driving force of measurement massification is self-tracking biometrics,
a growing interest in acquisition of data related to different aspects of our personal
2 Hubbard, D.W. (2014). How to measure anything: Finding the value of intangibles in business.
Hoboken (NJ, USA): John Wiley & Sons, Inc. (3rd edition). Hubbard, D.W., & Seiersen, R. (2016).
How to measure anything in cybersecurity risk. Hoboken (NJ, USA): John Wiley & Sons, Inc.
3 “The more any quantitative social indicator is used for social decision-making, the more subject
it will be to corruption pressures, and the more apt it will be to distort and corrupt the social processes it is intended to monitor.” (cited after en.wikipedia.org/wiki/Campbell’s_law [as of July 20,
2020]).
4 “When a measure becomes a target, it ceases to be a good measure.” (cited after en.wikipedia.org/
wiki/Goodhart’s_law [as of July 20, 2020]).
Foreword
views, which are convincingly presented in such books as How to Measure
Anything…
2
offering five-step procedures for defining new measurands and new
measurement methods for business applications. In light of those guidelines, what
was considered a joke 50 years ago may become today a serious business approach
to measurement. One of such jokes, most frequently repeated at that time by the
students of measurement science, went as follows:
Examiner: “How to measure the height of the university building using a
barometer?”
Student: “By offering this barometer to the administrator in exchange for the access
to the technical documentation of the building.”
Measurements, considered to be the most reliable sources of information, are
omnipresent in the life of information society which, by definition, is intensively
and extensively involved in the usage, creation, distribution, manipulation, and integration of information. The reliable measurement data are indispensable for
decision- making processes, especially if the latter are supported by IT tools. The
demand for such data appears not only in a research laboratory but also on a production line and in a hospital. The growing demand for such data may be observed in
various institutions of public administration, education, and transportation. Unlike
in the nineteenth century, the institutions of business and bureaucratic management
are the main driving forces behind the avalanche generation of new measurands,
especially so-called performance indicators, and the corresponding methodologies
for their evaluation. Despite the socioeconomic damages implied by the reckless
application of those indicators for decision-making, despite the common awareness
of the so-called Campbell’s law
3
and Goodhart’s law,
4
their use is not getting less
frequent or more prudent. The reasons are obvious:
• They are claimed to be more objective than experts’ opinions.
• They may be easily “digested” by the algorithmic procedures supporting the
decision-making processes.
• Once agreed by the decision-making bodies, they play the role of excuse for
pragmatically or morally wrong decisions.
• They effectively replace intellectual qualifications of the decision-makers.
Another driving force of measurement massification is self-tracking biometrics,
a growing interest in acquisition of data related to different aspects of our personal
2 Hubbard, D.W. (2014). How to measure anything: Finding the value of intangibles in business.
Hoboken (NJ, USA): John Wiley & Sons, Inc. (3rd edition). Hubbard, D.W., & Seiersen, R. (2016).
How to measure anything in cybersecurity risk. Hoboken (NJ, USA): John Wiley & Sons, Inc.
3 “The more any quantitative social indicator is used for social decision-making, the more subject
it will be to corruption pressures, and the more apt it will be to distort and corrupt the social processes it is intended to monitor.” (cited after en.wikipedia.org/wiki/Campbell’s_law [as of July 20,
2020]).
4 “When a measure becomes a target, it ceases to be a good measure.” (cited after en.wikipedia.org/
wiki/Goodhart’s_law [as of July 20, 2020]).
Foreword