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