Abstract
The performance perspective of business processes is concerned with the definition of performance requirements usually specified as a set of Process Performance Indicators (PPIs). Like other business process perspectives such as control-flow or data, there are cases in which PPIs are subject to variability. However, although the modelling of business process variability (BPV) has evolved significantly, there are very few contributions addressing the variability in the performance perspective of business processes. Modelling PPI variants with tools and techniques non-suitable for variability may generate redundant models, thus making it difficult its maintenance and future adaptations, also increasing possibility of errors in its managing. In this paper we present different cases of PPI variability detected as result of the analysis of several processes where BPV is present. Based on an existent metamodel used for defining PPIs over BPs, we propose its formal extension that allows the definition of PPI variability according to the cases identified.
This work has received funding from the European Commission (FEDER), the Spanish and the Andalusian R&D&I programmes (grants TIN2015-70560-R (BELI), P12–TIC-1867 (COPAS) and P10-TIC-5906 (THEOS)).
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- 1.
More details available at http://www.isa.us.es/ppinot/.
References
Hallerbach, A., Bauer, T., Reichert, M.: Configuration and management of process variants. In: Handbook on Business Process Management 1. International Handbooks on Information Systems, pp. 237–255. Springer, Berlin Heidelberg (2010)
Reichert, M., Hallerbach, A., Bauer, T.: Lifecycle management of business process variants. In: Handbook on Business Process Management 1, pp. 251–278. Springer, Berlin Heidelberg (2015)
Hallerbach, A., Bauer, T., Reichert, M.: Guaranteeing soundness of configurable process variants in Provop. In: 2009 IEEE Conference on Commerce and Enterprise Computing, pp. 98–105, July 2009
da Mota Silveira Neto, P.A., do Carmo Machado, I., McGregor, J.D., de Almeida, E.S., de Lemos Meira, S.R.: A systematic mapping study of software product linestesting. Inf. Softw. Technol. 53(5), 407–423 (2011)
Milani, F., Dumas, M., Ahmed, N., Matuleviius, R.: Modelling families of business process variants: A decomposition driven method. Inf. Syst. 56, 55–72 (2016)
Aiello, M., Bulanov, P., Groefsema, H.: Requirements and tools for variability management. In: 2010 IEEE 34th Annual Computer Software and Applications Conference Workshops (COMPSACW), pp. 245–250 (July 2010)
Saidani, O., Nurcan, S.: Business process modeling: a multi-perspective approach integrating variability. In: Bider, I., Gaaloul, K., Krogstie, J., Nurcan, S., Proper, H.A., Schmidt, R., Soffer, P. (eds.) BPMDS 2014 and EMMSAD 2014. LNBIP, vol. 175, pp. 169–183. Springer, Heidelberg (2014)
Rosa, M.L., Dumas, M., ter Hofstede, A.H., Mendling, J.: Configurable multi-perspective business process models. Inf. Syst. 36(2), 313–340 (2011)
La Rosa, M., van der Aalst, W.M.P., Dumas, M., Milani, F.P.: Business process variability modeling: A survey. Report, ACM Digital Library (2013)
Torres, V., Zugal, S., Weber, B., Reichert, M., Ayora, C., Pelechano, V.: A qualitative comparison of approaches supporting business process variability. In: La Rosa, M., Soffer, P. (eds.) Business Process Management Workshops. LNBIP, vol. 132, pp. 560–572. Springer, Heidelberg (2012)
Lodhi, A., Koppen, V., Wind, S., Saake, G., Turowski, K.: Business process modeling language for performance evaluation. In: 47th Hawaii International Conference on System Sciences (HICSS), pp. 3768–3777 Jan 2014
del Río-Ortega, A., Resinas, M., Cabanillas, C., Ruiz-Cortés, A.: On the definition and design-time analysis of process performance indicators. Inf. Syst. 38(4), 470–490 (2013)
Milani, F., Dumas, M., Matulevičius, R.: Identifying and classifying variations in business processes. In: Bider, I., Halpin, T., Krogstie, J., Nurcan, S., Proper, E., Schmidt, R., Soffer, P., Wrycza, S. (eds.) EMMSAD 2012 and BPMDS 2012. LNBIP, vol. 113, pp. 136–150. Springer, Heidelberg (2012)
Cognini, R., Corradini, F., Polini, A., Re, B.: Extending feature models to express variability in business process models. In: Persson, A., Stirna, J. (eds.) CAiSE 2015 Workshops. LNBIP, vol. 215, pp. 245–256. Springer, Heidelberg (2015)
Rolland, C., Nurcan, S.: Business process lines to deal with the variability. In: 43rd Hawaii International Conference on System Sciences (HICSS), pp. 1–10 (Jan 2010)
Machado, I., Bonifácio, R., Alves, V., Turnes, L., Machado, G.: Managing variability in business processes: An aspect-oriented approach. In: Proceedings of the 2011 I Workshop on Early Aspects. EA 11, pp. 25–30. ACM, New York, NY, USA (2011)
Hallerbach, A., Bauer, T., Reichert, M.: Capturing variability in business process models: the Provop approach. J. Softw. Maintenance Evol. Res. Pract. 22(6–7), 519–546 (2010)
Rosemann, M., van der Aalst, W.M.P.: A configurable reference modelling language. Inf. Syst. 32(1), 1–23 (2007)
Razavian, M., Khosravi, R.: Modeling variability in business process models using UML. In: Fifth International Conference on Information Technology: New Generations, ITNG 2008, pp. 82–87 (April 2008)
del-Río-Ortega, A., Cabanillas, C., Resinas, M., Ruiz-Cortés, A.: PPINOT tool suite: a performance management solution for process-oriented organisations. In: Basu, S., Pautasso, C., Zhang, L., Fu, X. (eds.) ICSOC 2013. LNCS, vol. 8274, pp. 675–678. Springer, Heidelberg (2013)
Strecker, S., Frank, U., Heise, D., Kattenstroth, H.: MetricM: a modeling method in support of the reflective design and use of performance measurement systems. Inf. Syst. e-Bus. Manage. 10(2), 241–276 (2011)
Popova, V., Sharpanskykh, A.: Modeling organizational performance indicators. Inf. Syst. 35(4), 505–527 (2010)
Suhartono, D.: Variability model implementation on key performance indicator application. Int. J. Innov. Manage. Technol. 6(1), 77–80 (2015)
Vianden, M., Lichter, H.: Variability model towards a metric specification process. In: Proceedings of the International Conference on Computer Science and Information Technology, pp. 76–79 (2011)
Apics, S.C.C.: Supply Chain Operations Reference Model: SCOR Version 11.0. Supply Chain Council APICS, CCOR, CPIM, CSCP, DCOR, SCOR, and SCORmark are all registered trademarks of APICS. All rights reserved (2015)
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Estrada-Torres, B., del-Río-Ortega, A., Resinas, M., Ruiz-Cortés, A. (2016). Identifying Variability in Process Performance Indicators. In: La Rosa, M., Loos, P., Pastor, O. (eds) Business Process Management Forum. BPM 2016. Lecture Notes in Business Information Processing, vol 260. Springer, Cham. https://doi.org/10.1007/978-3-319-45468-9_6
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