Figure 1: Correlations can potentially mask deeper relationships.
2. Knowledge is power
In their book, “Big Data: A Revolution That Will Transform How We
Live, Think, And Work,” Viktor MayerSchonberger and Kenneth Cukier contend that it doesn’t matter “why” there’s
correlation, just that there “is” correlation. They provide an example of
greater Pop-Tart sales during storms, a
learning that WalMart has used to better merchandize. (Read more.) According to the authors, simply knowing that
Pop-Tart sales are likely to increase is
sufficient and doesn’t necessitate deeper investigation into underlying causes.
While there’s no doubt this finding
has valuable business implications,
relying on correlations alone can limit
broader applications and can even entail risk. Case in point: the 2008 financial
a na l y t i c s
crisis. Analysis of AAA rated Collateralized Debt Obligations suggested they
were sound investments (i.e., AAA =
safe), but deeper analysis would have
revealed danger. (Read more.)
Takeaway: As the role of data in decision-making increases, never before
has understanding underlying relationships been more important.
3. Correlation measures
relationship strength
A strong case can be made for questioning the extent to which correlation
reflects a relationship between even
seemingly interdependent variables.
Consider U.S. healthcare expenditures
and deaths from heart disease. Between
1960 and 2010, spending on healthcare
in the United States increased more
s e p t e m b e r / o c t o b e r 2 014
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