Abstract
Organizations utilize Key Performance Indicators (KPIs) to monitor whether they attain their goals. For this, software vendors offer predefined KPIs in their enterprise software. However, the predefined KPIs will not be relevant for all organizations due to the varying needs of them. Therefore, software vendors spend significant efforts on offering relevant KPIs. That relevance determination process is time-consuming and costly. We show that the relevance of KPIs may be tied to the specific properties of organizations, e.g., domain and size. In this context, we present our novel approach for the automated prediction of which KPIs are relevant for organizations. We implemented our approach and evaluated its prediction quality in an industrial setting.
| Original language | English |
|---|---|
| Title of host publication | Business Information Systems - 22nd International Conference, BIS 2019, Proceedings |
| Editors | Rafael Corchuelo, Witold Abramowicz |
| Publisher | Springer Verlag |
| Pages | 283-299 |
| Number of pages | 17 |
| ISBN (Print) | 9783030204846 |
| DOIs | |
| Publication status | Published - 1 Jan 2019 |
| Event | 22nd International Conference on Business Information Systems, BIS 2019 - Seville, Spain Duration: 26 Jun 2019 → 28 Jun 2019 |
Publication series
| Name | Lecture Notes in Business Information Processing |
|---|---|
| Volume | 353 |
| ISSN (Print) | 1865-1348 |
Conference
| Conference | 22nd International Conference on Business Information Systems, BIS 2019 |
|---|---|
| Country | Spain |
| City | Seville |
| Period | 26/06/19 → 28/06/19 |
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Keywords
- Key Performance Indicators
- Prediction
- Relevance
Cite this
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Automated Prediction of Relevant Key Performance Indicators for Organizations. / Aksu, Ünal; Schunselaar, Dennis M.M.; Reijers, Hajo A.
Business Information Systems - 22nd International Conference, BIS 2019, Proceedings. ed. / Rafael Corchuelo; Witold Abramowicz. Springer Verlag, 2019. p. 283-299 (Lecture Notes in Business Information Processing; Vol. 353).Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Automated Prediction of Relevant Key Performance Indicators for Organizations
AU - Aksu, Ünal
AU - Schunselaar, Dennis M.M.
AU - Reijers, Hajo A.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Organizations utilize Key Performance Indicators (KPIs) to monitor whether they attain their goals. For this, software vendors offer predefined KPIs in their enterprise software. However, the predefined KPIs will not be relevant for all organizations due to the varying needs of them. Therefore, software vendors spend significant efforts on offering relevant KPIs. That relevance determination process is time-consuming and costly. We show that the relevance of KPIs may be tied to the specific properties of organizations, e.g., domain and size. In this context, we present our novel approach for the automated prediction of which KPIs are relevant for organizations. We implemented our approach and evaluated its prediction quality in an industrial setting.
AB - Organizations utilize Key Performance Indicators (KPIs) to monitor whether they attain their goals. For this, software vendors offer predefined KPIs in their enterprise software. However, the predefined KPIs will not be relevant for all organizations due to the varying needs of them. Therefore, software vendors spend significant efforts on offering relevant KPIs. That relevance determination process is time-consuming and costly. We show that the relevance of KPIs may be tied to the specific properties of organizations, e.g., domain and size. In this context, we present our novel approach for the automated prediction of which KPIs are relevant for organizations. We implemented our approach and evaluated its prediction quality in an industrial setting.
KW - Key Performance Indicators
KW - Prediction
KW - Relevance
UR - http://www.scopus.com/inward/record.url?scp=85068180534&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068180534&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-20485-3_22
DO - 10.1007/978-3-030-20485-3_22
M3 - Conference contribution
SN - 9783030204846
T3 - Lecture Notes in Business Information Processing
SP - 283
EP - 299
BT - Business Information Systems - 22nd International Conference, BIS 2019, Proceedings
A2 - Corchuelo, Rafael
A2 - Abramowicz, Witold
PB - Springer Verlag
ER -