tion, with 22.4%, 15.8%, and 18.7% for
planning-, implementing-, and controlling-related marketing work. This
is perhaps due to the need to better
manage customer relationships with
(big) data generated outside organizations on social media platforms and
the long history of using analytics for
marketing decisions.
19 Predictive analytics applications are most frequently
used for planning-, implementing-,
and controlling-related HR work, with
21.5%, 12.7%, and 13.0%, respectively.
Comparing current and future use
(see Figure 1b), it seems that, in general, static reports/interactive dashboards will still be the predominant
analytics application in the near future. The exceptions include the projected use of descriptive analytics for
planning- and implementing-related
HR work ( 26.7% and 26.6%, respectively) and the use of big data analytics
for controlling-related marketing work
( 25.2%). However, compared to current
use, our respondents indicated the
dominance of static reports/interactive
dashboards will diminish in the future,
in the range of 10.0 percentage points
to 20. 5 percentage points (henceforth
referred to as “points”). This implies
there is indeed an increasing trend
toward using more advanced types of
analytics applications—descriptive,
predictive, prescriptive, and big data.
In the following paragraphs, for
each business function we compare
current and future use of different
types of analytics applications with
respect to a specific type of managerial work—planning, implementing,
and controlling. For each such type of
work, we highlight the greatest negative and positive difference in yellow
and green (background), respectively,
in Table 2, Table 3, Table 4, and Table
5. We excluded “None” from this consideration. Based on Likelihood Ratio
Chi-square tests, we note statistically
significant differences in each table.
This test assumes a null hypothesis
that the distribution of responses for
using a particular analytics applica-
tion is the same between the current
and the future. An asterisk in the dif-
ference indicates there is a significant
change in the number of respondents
who reported their intention to use a
specific analytics application in the
future (five years out) vs. their current
boards ( 56.1%) and predictive analytics
( 12.1%) were the top two analytics ap-
plications currently used (see Table 2).
In the future, static reports/interactive
use of the same analytics application.
In finance management. With re-
spect to planning-related finance
work, static reports/interactive dash-
Table 4. Current vs. future use of analytics applications in HR management.
Type of Analytics Applications Current Future Difference
Pl
a
nni
ng
None 11.7% 4.7% - 7.0**
Static reports/interactive dashboards 35.0% 25.0% - 10.0*
Descriptive analytics 19.0% 26.7% 7. 7**
Predictive analytics 21.5% 22.7% 1. 2
Prescriptive analytics 7.4% 11.0% 3. 6
Big data analytics 5.5% 9.9% 4. 4*
Imp
lem
enti
ng
None 17.7% 7.9% - 9. 8**
Static reports / interactive dashboards 38.6% 25.4% - 13. 2*
Descriptive analytics 17.1% 26.6% 9. 5**
Predictive analytics 12.7% 21.5% 8. 8**
Prescriptiveanalytics 4.4% 9.0% 4. 6**
Big data analytics 9.5% 9.6% 0.1
C
on
tr
o
ll
in
g
None 11.5% 6.3% - 5. 2**
Static reports/interactive dashboards 40.4% 28.5% - 11. 9**
Descriptive analytics 19.3% 25.3% 6.0**
Predictive analytics 13.0% 19.4% 6. 4**
Prescriptive analytics 4.1% 10.1% 6.0**
Big data analytics 11.9% 10.4% - 1. 5
Note
* indicates significant Chi-square difference at the p ≤ . 10 alpha level
** indicates significant Chi-square difference at the p ≤ .05 alpha level
Table 5. Current vs. future use of analytics applications in operations management.
Type of Analytics Applications Current Future Difference
P
l
an
ni
ng
None 23.2% 9.0% - 14. 2**
Static reports/interactive dashboards 36.4% 25.0% - 11. 4**
Descriptive analytics 13.2% 15.2% 2.0
Predictive analytics 9.2% 21.5% 12. 3**
Prescriptive analytics 7.9% 12.9% 5.0**
Big data analytics 10.1% 16.4% 6. 3**
Im
pl
eme
nti
ng
None 9.3% 4.4% - 4. 9**
Static reports/interactive dashboards 41.5% 27.6% - 13. 9**
Descriptive analytics 18.3% 19.1% 0.8
Predictive analytics 12.5% 21.9% 9. 4**
Prescriptive analytics 8.3% 11.3% 3.0*
Big data analytics 10.0% 15.7% 5. 7**
Co
nt
r
ol
li
ng
None 13.9% 5.2% - 8. 7**
Static reports/interactive dashboards 42.2% 29.9% - 12. 3*
Descriptive analytics 18.5% 17.5% - 1.0
Predictive analytics 9.2% 21.6% 12. 4**
Prescriptive analytics 6.4% 10.8% 4. 4*
Big data analytics 9.8% 14.9% 5. 1*
Note
* indicates significant Chi-square difference at the p ≤ . 10 alpha level
** indicates significant Chi-square difference at the p ≤ .05 alpha level