an example of how Intel has begun initiatives in forecasting revenue and
predicting impairments in its capital
investments. Our findings suggest
the finance function may be moving
beyond static reports toward using
advanced analytics more broadly.
5, 11
In marketing management. With
respect to planning-related marketing work, our respondents indicated
current use to be the highest for static
reports/interactive dashboards ( 44.8%)
followed by big data analytics ( 22.4%)
(see Table 3). In the future, a significantly greater share of planning-related marketing work will likely involve
descriptive ( 14.7%), predictive ( 20.2%),
and prescriptive analytics ( 14.7%), with
a concomitant decrease in the use of
static reports/interactive dashboards
(by 20. 5 points).
With respect to implementing-related marketing work, static reports/
interactive dashboards are currently
the most frequently used analytics application ( 42.4%). The dominance of
this type of application will decrease
by 15 points in the future. On the other
hand, predictive and big data analytics
will see the greatest increases in the
future, with overall usage at 20.4% and
23.4%, respectively.
Controlling-related marketing work
follows similar current usage trends as
the other two dimensions—planning
and implementing. The use of static
reports/interactive dashboards will
again significantly decrease in the future (by 18. 5 points), and this will, it
seems, be replaced by a significant increase in the use of predictive (by 16. 4
points) analytics. The use of prescriptive (by 4. 6 points) and big data (by 6. 5
points) analytics are also projected to
increase significantly.
Our findings suggest marketing
work is leading the use of big data
analytics applications and is expected
to continue in the future. Comparing
current to future use, there is a general
shift toward more advanced analytics
applications—predictive, prescriptive,
and big data—for various tasks in the
marketing function, with predictive
analytics experiencing the greatest per-
centage points increase. This suggests
data-literacy programs will need to pro-
vide marketing managers with ways
to incorporate predictive analytics in
their work. The marketing function
involves the greatest projected drop in
the use of static reports/interactive
dashboards among all the functions.
This is consistent with prior research
that suggests recommendations, geo-
fencing, search marketing, and retar-
geting, or types of advanced analytics,
are increasingly being embedded into
the marketing function.
19
In HR management. With respect
to planning-related HR work, static
reports/interactive dashboards are
currently the most used ( 35.0%), with
predictive analytics generally being the
second most used ( 21.5%) (see Table 4).
In the future, descriptive analytics will
experience a significant increase (by 7. 7
points), matching a similar decrease in
static reports/interactive dashboards
(by 10 points). We also found the use
of big data analytics is expected to increase significantly (by 4. 4 points).
Implementing-related HR work
has a similar current usage pattern as
planning-related HR work in terms
of leading current and future analytics applications. In this dimension
of HR work, the use of static reports/
interactive dashboards will decrease
significantly (by 13. 2 points), along
with a significant increase in the use
of descriptive analytics (by 9. 5 points).
Additionally, the projected use of predictive analytics will significantly increase in the future (by 8. 8 points) to
21.5%. While prescriptive analytics
will generally continue to be the least
frequently used analytics application
in the future, its use will nonetheless
significantly increase in the future (by
4. 6 points).
Similar to implementing-related HR
work, for controlling-related HR work,
the data indicated similar significant
increases in descriptive, predictive,
and prescriptive analytics (by approximately 6 points) for controlling-related
HR work and a concomitant decrease
in projected use of static reports/interactive dashboards (by 11. 9 points).
Overall, descriptive analytics will
play a greater role in HR work, as it
is expected to experience the great-
est point increase for planning and
implementing and be tied for the sec-
ond greatest increase for controlling.
This makes it an important analytics
application for future data-literacy
programs in HR. Given that, in 2014,
12% of U.S.-based companies, includ-
dashboards ( 41.7%) and descriptive an-
alytics ( 15.5%) will be popular applica-
tions. Comparing current to future use
of analytics applications for planning-
related finance work, the respondents
in general indicated a significant in-
crease in the use of advanced analytics
applications in the future—descrip-
tive (by 7. 4 points), prescriptive (by 7.0
points), and big data analytics (by 4. 9
points). On the other hand, static re-
ports/interactive dashboards are pro-
jected to see the greatest drop in use
(by 14. 4 points).
With respect to implementing-related finance work, static reports/
interactive dashboards alone account
for almost two-thirds of the current
analytics applications used ( 63.0%).
Comparing current and future use of
analytics applications, prescriptive
analytics has the most significant increase in use (by 5. 3 points), while
static reports/dashboards are expected to have the most significant decrease in use (by 14.0 points).
For controlling-related finance work,
static reports/interactive dashboards
were the dominant application being
used ( 64.4%) and will continue to be
dominant in the future ( 54.1%). In the
future, our respondents indicated an
overall increase in the use of different
types of advanced analytics applications, though the increase is only significant for prescriptive and big
data analytics, by 5.0 and 3. 7 points,
respectively. Much like planning-and implementing-related finance
work, static reports/interactive dashboards are projected to see the greatest drop in use (by 10. 3 points).
By percentage points, prescriptive
analytics will experience the greatest
increase in implementing- and
controlling-related finance work, by
5. 3 and 5.0 points, respectively, and is
a close second for the greatest increase
in planning-related finance work (by
7.0 points) behind descriptive analytics.
Our findings suggest educating finance
managers in prescriptive and descriptive analytics applications will be imperative for success in their job performance. While the finance function is
quantitative by nature, prior findings
recognized it trailed other functions
(such as marketing, operations, and HR)
in its use of analytics.
5 More recently
though, Davenport and Tay5 provided
