Analytics
Davenport (2006) used the term analytics for the first time
in an article titled ‘Competing on Analytics’ in Harvard
Business Review. This article was followed by a book with
the same title by Davenport and Harris (2007). This book is
widely credited with creating awareness around analytics. A
simple definition of analytics given by Davenport (2006:3) is
‘the science of analysis’ – a term most decision makers and
managers can relate to.
Davenport and Harris (2007) list three key attributes that
characterise analytics competitors. For organisations the
use of basic descriptive statistics is fairly straightforward,
but companies competing on analytics look well beyond
basic statistical analysis. The widespread use of quantitative
techniques, predictive modelling and optimisation is the
most relevant of these three key attributes, according to
Davenport and Harris (2007), which contributes towards
more profitable operations, greater profit potential and
better decision making. Many of these companies optimise
their supply chains, and through that they become more
resilient. Many different alternatives are simulated as well
through ‘what-if’ analysis. The authors go further and
provide a more elaborate definition of analytics as follows:
‘By analytics we mean the extensive use of data, statistical
and quantitative analysis, explanatory and predictive
models, and fact-based management to drive decisions and
actions’. Analytics, which they consider a subset of business
intelligence encompassing statistical analysis, forecasting/
extrapolation, predictive modelling and optimisation,
therefore provides inputs to decision making or even fully
automated decisions.
The key questions addressed by analytics, as presented in
Davenport et al. (2010), are reflected in Table 1.
An alternative definition of analytics is that of the Institute
for Operations Research and Management Science (2014):