Business Process Analytics

  • Michael zur Muehlen
  • Robert Shapiro
Part of the International Handbooks on Information Systems book series (INFOSYS)


Business Process Management systems (BPMS) are a rich source of events that document the execution of processes and activities within these systems. Business Process Management analytics is the family of methods and tools that can be applied to these event streams in order to support decision making in organizations. The analysis of process events can focus on the behavior of completed processes, evaluate currently running process instances, or focus on predicting the behavior of process instances in the future. This chapter provides an overview of the different methods and technologies that can be employed in each of these three areas of process analytics. We discuss the underlying format and types of process events as the common source of analytics information, present techniques for the aggregation and composition of these events, and outline methods that support backward- and forward-looking process analytics.


Business process analytics Business activity monitoring Process controlling Process optimization Audit trail Process intelligence 


  1. Burmistrov I, Leonova A (1996) Effects of interruptions on the computerised clerical task performance. Human-computer interaction: human aspects of business computing. Proc EWHCI 96:21–29Google Scholar
  2. Golfarelli M, Rizzi S, Cella I (2004) Beyond data warehousing: what’s next in business intelligence? In: Proceedings of the 7th ACM international workshop on Data warehousing and OLAP, pp 1–6Google Scholar
  3. Grigori D et al. (2004) Business process intelligence. Comput Ind 53:321–343CrossRefGoogle Scholar
  4. Hackathorn R (2002) Minimizing action distance. DM Rev 12:22–23Google Scholar
  5. Leyer M, Heckl D, Moormann J (2014) Process performance measurement. In: vom Brocke J, Rosemann M (eds) Handbook on business process management, vol 2, 2nd edn. Springer Heidelberg, pp 227–241Google Scholar
  6. List B et al. (2001) Multidimensional business process analysis with the process warehouse. Kluwer International series in engineering and computer science, pp 211–228Google Scholar
  7. McCoy D (2002) Business activity monitoring: Calm before the storm. Gartner Research Note LE-15-9727Google Scholar
  8. McLellan M (1996) Workflow metrics – one of the great benefits of workflow management. In: Oesterle H, Vogler P (eds) Praxis des workflow-management. Vieweg, Braunschweig, pp 301–318CrossRefGoogle Scholar
  9. OASIS (2008a) Web services – Human task (WS-HumanTask) specification. 1.1 working draft, organization for the advancement of structured information standardsGoogle Scholar
  10. OASIS (2008b) WS-BPEL extension for people (BPEL4People) specification version 1.1. 1.1 working draft, organization for the advancement of structured information standardsGoogle Scholar
  11. Pau KC, Si YW, Dumas M (2007) Data Warehouse Model for Audit Trail Analysis in Workflows. In: Proceedings of the Student Workshop of 2007 IEEE International Conference on e-Business Engineering, (ICEBE)Google Scholar
  12. Rosemann M, Denecke T, Puettmann M (1996) PISA – process information system with access. Design and realisation of an information system for process monitoring and controlling (German). Arbeitsberichte des Instituts fuer Wirtschaftsinformatik. Universitaet Münster, GermanyGoogle Scholar
  13. Sayal M et al. (2002) Business process cockpit. In: Proceedings of the 28th international conference on very large data bases. pp 880–883Google Scholar
  14. Schiefer J, Jeng JJ, Bruckner RM (2003) Real-time workflow audit data integration into data warehouse systems. In: 11th European conference on information systemsGoogle Scholar
  15. van der WMP Aalst et al. (2007) Business process mining: an industrial application. Inf Syst 32:713–732CrossRefGoogle Scholar
  16. van der Aalst WMP (2014) Business process simulation survival guide. In: vom Brocke J, Rosemann M (eds) Handbook on business process management, vol 1, 2nd edn. Springer, Heidelberg, pp 337–370Google Scholar
  17. van Dongen BF, van der Aalst WMP (2005) A meta model for process mining data. In: J. Casto, E. Teniente (Eds.), Proceedings of the CAiSE'05 Workshops (EMOI-INTEROP Workshop), FEUP, Porto, Portugal, vol. 2, pp 309–320Google Scholar
  18. WfMC (1999) Audit data specification. Version 2. document number WFMC-TC-1015, available at
  19. WfMC (2009) Business process analytics format – Draft specification. 1.0, Document number WFMC-TC-1015 available at
  20. WfMC (2004) Wf-XML 2.0 – XML-based protocol for run-time integration of process engines. WfMC, Nov, WfMC-TC-1023, available at
  21. zur Muehlen M (2004) Workflow-based process controlling. foundation, design, and implementation of workflow-driven process information systems. Logos, BerlinGoogle Scholar
  22. zur Muehlen M, Klein F (2000) AFRICA: Workflow interoperability based on XML-messages. CAiSE 2000 International workshop on infrastructures for dynamic business-to-business service outsourcingGoogle Scholar
  23. zur Muehlen M, Rosemann M (2000) Workflow-based process monitoring and controlling – technical and organizational issues. Proceedings of the 33rd Hawai’i International Conference on System Sciences, IEEE, Waikoloa, HIGoogle Scholar
  24. zur Muehlen M, Ho DT (2008) Service Process Innovation: A Case Study of BPMN in Practice, Ralph Sprague, Jr., Proceedings of the 41st Hawai’i International Conference on System Sciences, IEEE, Waikoloa, HIGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Stevens Institute of TechnologyHobokenUSA
  2. 2.Process AnalyticaWellfleetUSA

Personalised recommendations