Information Systems and e-Business Management

, Volume 14, Issue 3, pp 577–612 | Cite as

Analyzing inter-organizational business processes

Process mining and business performance analysis using electronic data interchange messages
  • Robert Engel
  • Worarat Krathu
  • Marco Zapletal
  • Christian Pichler
  • R. P. Jagadeesh Chandra Bose
  • Wil van der Aalst
  • Hannes Werthner
  • Christian Huemer
Original Article


Companies are increasingly embedded in B2B environments, where they have to collaborate in order to achieve their goals. Such collaborations lead to inter-organizational business processes that may be commonly supported through the exchange of electronic data interchange (EDI) messages (e.g., electronic purchase orders, invoices etc.). Despite the appearance of XML, traditional approaches to EDI, such as EDIFACT and ANSI X.12, still play an overwhelmingly dominant role. However, such traditional EDI standards lack a notion of process. In other words, the exchanged business documents are typically not embedded in the context of other exchanged business documents. This has two shortcomings: (1) the inability to apply proven business process management (BPM) methods, including process mining techniques, in such settings; and (2) the unavailability of systematic approaches to business intelligence (BI) using information from exchanged EDI messages. In this article, we present the EDImine Framework for enabling (1) the application of process mining techniques in the field of EDI-supported inter-organizational business processes, and (2) for supporting inter-organizational performance evaluation using business information from EDI messages, event logs and process models. As an enabling technology, we present a method for the semantic preprocessing of EDIFACT messages to exploit this potentially rich source of information by applying state of the art BPM and BI techniques. We show the applicability of our approach by means of a case study based on real-world EDI data of a German consumer goods manufacturing company.


Inter-organizational business processes Electronic data interchange Process mining Inter-organizational relationships Key performance indicators 


  1. Barros A, Dumas M, Oaks P (2006) Standards for web service choreography and orchestration: status and perspectives. In: Bussler CJ, Haller A (eds) Business process management workshops, LNCS, vol 3812. Springer, Berlin, pp 61–74Google Scholar
  2. Berge J (1994) The EDIFACT standards. Blackwell Publishers, Inc, OxfordGoogle Scholar
  3. Brewer PC, Speh TW (2000) Using the balanced scorecard to measure supply chain performance. J Bus 21(1):75–93Google Scholar
  4. Casey M (2008) Partnership—success factors of interorganizational relationships. J Nurs Manag 16(1):72–83. doi: 10.1111/j.1365-2934.2007.00771.x Google Scholar
  5. Cheng J (2011) Inter-organizational relationships and information sharing in supply chains. Int J Inf Manag 31(4):374–384CrossRefGoogle Scholar
  6. Chia A, Goh M, Hum SH (2009) Performance measurement in supply chain entities: balanced scorecard perspective. Benchmarking Int J 16:605–620CrossRefGoogle Scholar
  7. de Leoni M, van der Aalst W (2013) Data-aware process mining: discovering decisions in processes using alignments. In: Proceedings of the 28th annual ACM symposium on applied computing. ACM, pp 1454–1461Google Scholar
  8. Ding Y, Fensel D, Klein MCA, Omelayenko B, Schulten E (2004) The role of ontologies in eCommerce. In: Handbook on ontologies, pp 593–616. Springer, BerlinGoogle Scholar
  9. Duffy R, Fearne A, Hornibrook S, Hutchinson K, Reid A (2013) Engaging suppliers in CRM: the role of justice in buyer–supplier relationships. Int J Inf Manag 33(1):20–27CrossRefGoogle Scholar
  10. Dustdar S, Gombotz R (2006) Discovering web service workflows using web services interaction mining. Int J Bus Process Integr Manag 1(4):256–266CrossRefGoogle Scholar
  11. Eckerson WW (2006) Performance dashboards. Wiley, New YorkGoogle Scholar
  12. Engel R, van der Aalst W, Zapletal M, Pichler C, Werthner H (2012a) Mining Inter-organizational business process models from EDI messages: a case study from the automotive sector. In: 24th international conference on advanced information systems engineering (CAiSE 2012), LNCS 7328, pp 222-237. Springer, BerlinGoogle Scholar
  13. Engel R, Krathu W, Pichler C, Zapletal M, Werthner H (2013a) Towards EDI-based business activity monitoring. In: Workshop on methodologies for robustness injection into business processes (MRI-BP’13) at the 17th IEEE international EDOC conference (EDOC 2013), September 9–13, Vancouver, Canada. IEEEGoogle Scholar
  14. Engel R, Krathu W, Zapletal M, Pichler C, van der Aalst W, Werthner H (2011) Process mining for electronic data interchange. In: 12th international conference on E-commerce and web technologies (EC-Web 2011), LNBIP, vol 85. Springer, Berlin, pp 77–88Google Scholar
  15. Engel R, Pichler C, Zapletal M, Krathu W, Werthner H (2012) From encoded EDIFACT messages to business concepts using semantic annotations. In: 14th IEEE international conference on commerce and enterprise computing (CEC’12), pp 17–25. IEEEGoogle Scholar
  16. Engel R, Prabhakara JR (2014) A case study on analyzing inter-organizational business processes from EDI messages using physical activity mining. In: 47th Hawaii international conference on system sciences (HICSS 2014). IEEEGoogle Scholar
  17. Engel R, Prabhakara JR, Pichler C, Zapletal M, Huemer C, Werthner H (2013b) Inter-organizational business processes: on redundancies in document exchanges. In: Effective, agile and trusted eServices co-creation, no 19 in TUCS lecture notes, pp 51–66. Turku Centre for Computer ScienceGoogle Scholar
  18. Engel R, Prabhakara JR, Pichler C, Zapletal M, Werthner H (2013c) EDIminer: a toolset for process mining from EDI messages. In: CAiSE’13 forum at the 25th international conference on advanced information systems engineering (CAiSE’13)., vol 998, pp 146–153Google Scholar
  19. Fensel D (2000) The role of ontologies in information interchange. In: Proceedings of the 2nd international scientific and practical conference on programming (UkrPROG 2000). Kiev, UkraineGoogle Scholar
  20. Fensel D (2004) Triple-space computing: semantic web services based on persistent publication of information. In: Proceedings of the IFIP international conference on intelligence in communication systems (INTELLCOMM), Bangkok, Thailand, 23–26 November 2004, LNCS 3283. Springer, pp 43–53Google Scholar
  21. Foxvog D, Bussler C (2005) Ontologizing EDI: first steps and initial experience. In: Data engineering issues in E-commerce, 2005. Proceedings. International workshop on, pp 49–58. doi: 10.1109/DEEC.2005.13
  22. Foxvog D, Bussler C (2006) Ontologizing EDI semantics. In: Roddick JF, Richard Benjamins V, Si-said Cherfi S, Chiang R, Claramunt C, Elmasri RA, Grandi F, Han H, Hepp M, Lytras MD, Mišić VB, Poels G, Song I-Y, Trujillo J, Vangenot C (eds) Advances in conceptual modeling—theory and practice, LNCS, vol 4231. Springer, Berlin, pp 301–311Google Scholar
  23. Grigori D, Casati F, Castellanos M, Shan M, Dayal U, Sayal M (2004) Business process intelligence. Comput Ind 53(3):321–343CrossRefGoogle Scholar
  24. Hevner AR, March ST, Park J, Ram S (2004) Design science in information systems research. Manag Inf Syst Q 28(1):75–106Google Scholar
  25. Hill N, Ferguson D (1989) Electronic data interchange: a definition and perspective. EDI Forum J Electron Data Interchange 1:5–12Google Scholar
  26. Hornix PTG (2007) Performance analysis of business processes through process mining. Master’s thesis, Technische Universiteit Eindhoven, Department of Mathematics and Computer ScienceGoogle Scholar
  27. Janssens G (2011) Electronic data interchange: from its birth to its new role in logistics information systems. Int J Inf Technol Secur 3:45–56Google Scholar
  28. Johnston D, McCutcheon D, Stuart F, Kerwood H (2004) Effects of supplier trust on performance of cooperative supplier relationships. J Oper Manag 22(1):23–38CrossRefGoogle Scholar
  29. Kaplan R, Norton D (2004) Focusing your organization on strategy-with the balanced scorecard. Harvard Business School Publishing, WatertownGoogle Scholar
  30. Kaplan RS, Norton DP (1992) The balanced scorecard - measures that drive performance. Harvard Bus Rev 70(1):71–79Google Scholar
  31. Kleijnen J, Smits M (2003) Performance metrics in supply chain management. J Oper Res Soc 54(5):507–514CrossRefGoogle Scholar
  32. Krathu W, Engel R, Pichler C, Zapletal M, Werthner H (2014) Identifying inter-organizational key performance indicators from EDIFACT messages. In: Proceedings of the 2014 IEEE 16th conference on business informatics (CBI), vol 1, IEEE, pp 17–24Google Scholar
  33. Krathu W, Pichler C, Engel R, Zapletal M, Werthner H (2012) Semantic interpretation of UN/EDIFACT messages for evaluating inter-organizational relationships. In: International conference on advances in information technology (IAIT 2012), CCIS, vol 344. Springer, Berlin, pp 81–93Google Scholar
  34. Krathu W, Pichler C, Engel R, Zapletal M, Werthner H, Huemer C (2014a) A framework for inter-organizational performance analysis from EDI messages. In: Proceedings of the 16th IEEE conference on business informatics (CBI 2014). IEEEGoogle Scholar
  35. Krathu W, Pichler C, Xiao G, Werthner H, Neidhardt J, Zapletal M, Huemer C (2014b) Review of success factors in inter-organizational relationships: a cause and effect model. Inf Syst E-Bus ManagGoogle Scholar
  36. Krathu W, Pichler C, Zapletal M, Werthner H (2012b) Semantic inter-organizational performance analysis using the balanced scorecard methodology. In: 35th Jubilee international convention on information and communication technology, electronics and microelectronics (MIPRO 2012). IEEEGoogle Scholar
  37. Krause D, Handfield R, Tyler B (2007) The relationships between supplier development, commitment, social capital accumulation and performance improvement. J Oper Manag 25(2):528–545CrossRefGoogle Scholar
  38. Lehmann F (1996) Machine-negotiated, ontology-based EDI (electronic data interchange). In: Proceedings of the workshop at NIST on electronic commerce, current research issues and applications, pp 27–45. Springer, BerlinGoogle Scholar
  39. Li S, Lin B (2006) Accessing information sharing and information quality in supply chain management. Decis Support Syst 42(3):1641–1656CrossRefGoogle Scholar
  40. Liegl P, Zapletal M, Pichler C, Strommer M (2010) State-of-the-art in business document standards. In: 8th IEEE international conference on industrial informatics (INDIN 2010). IEEE, pp 234–241Google Scholar
  41. Nezhad HRM, Saint-paul R, Benatallah B, Casati F (2008) Deriving protocol models from imperfect service conversation logs. IEEE Trans Knowl Data Eng 20(12):1683–1698CrossRefGoogle Scholar
  42. Nezhad HRM, Saint-paul R, Casati F, Benatallah B (2011) Event correlation for process discovery from web service interaction logs. VLDB J 20(3):417–444CrossRefGoogle Scholar
  43. Omelayenko B (2001) Ontology integration tasks in business-to-business E-commerce. In: Engineering of intelligent systems, LNCS 2070. Springer, Berlin, pp 119–124Google Scholar
  44. Pauw WD, Lei M, Pring E, Villard L, Arnold M, Morar J (2005) Web services navigator: visualizing the execution of web services. IBM Syst J 44(4):821–845CrossRefGoogle Scholar
  45. Peltz C (2003) Web services orchestration and choreography. Computer 36:46–52. doi: 10.1109/MC.2003.1236471 CrossRefGoogle Scholar
  46. Pham TT (2003) Mining of EDI data for performance measurement of a supply chain (unpublished). DICentral CorporationGoogle Scholar
  47. Pham TT (2004) Quantitative approach to using e-commerce data to monitor and control the performance of a supply chain. In: e-Technology, e-Commerce and e-Service, 2004. EEE’04. 2004 IEEE international conference on. IEEE, pp 157–162Google Scholar
  48. Provan K, Sydow J (2008) Evaluating inter-organizational relationships. The Oxford handbook of inter-organizational relations, pp 691–718Google Scholar
  49. Saunders C, Wu Y, Li Y, Weisfeld S (2004) Interorganizational trust in B2B relationships. In: 6th international conference on electronic commerce (ICEC 2004). ACM, pp 272–279Google Scholar
  50. Seppänen R, Blomqvist K, Sundqvist S (2007) Measuring inter-organizational trust—a critical review of the empirical research in 1990–2003. Ind Market Manag 36(2):249–265CrossRefGoogle Scholar
  51. Song M, van der Aalst W (2007) Supporting process mining by showing events at a glance. In: 17th annual workshop on information technologies and systems (WITS 2007), pp 139–145Google Scholar
  52. Storerl C, Quaddus M (2003) Preliminary evaluation of inter-organizational information systems and relationships. In: PACIS 2003 proceedingsGoogle Scholar
  53. Verbeek H, Buijs J, van Dongen B, van der Aalst W (2011) XES, XESame, and ProM 6. In: Information systems evolution, LNBIP, vol 72. Springer, pp 60–75Google Scholar
  54. Vollmer K, Gilpin M, Stone J (2007) B2B integration trends: message formats. Forrester Res 6Google Scholar
  55. van der Aalst W (2011a) Intra-and inter-organizational process mining: discovering processes within and between organizations. In: Johannesson P, Krogstie J, Opdahl AL (eds) The practice of enterprise modeling. Springer, Berlin, pp 1–11Google Scholar
  56. van der Aalst W (2011b) Process mining: discovery, conformance and enhancement of business processes. Springer, BerlinCrossRefGoogle Scholar
  57. van der Aalst W, Adriansyah A, van Dongen B (2012) Replaying history on process models for conformance checking and performance analysis. Wiley Int Rev Data Min Knowl Disc 2(2):182–192CrossRefGoogle Scholar
  58. van der Aalst W, Dumas M, Ouyang C, Rozinat A, Verbeek E (2008) Conformance checking of service behavior. ACM Trans Internet Technol 8(3):29–59CrossRefGoogle Scholar
  59. van der Aalst W, Reijers HA, Weijters AM, van Dongen B, Alves de Medeiros A, Song M, Verbeek H (2007) Business process mining: an industrial application. Inf Syst 32:713–732CrossRefGoogle Scholar
  60. van der Aalst W, Ter Hofstede AHM, Weske M (2003) Business process management: a survey. In: Business process management (BPM 2003), Lecture notes in computer science, vol 2678. Springer, Berlin, pp 1–12Google Scholar
  61. van der Aalst W, Verbeek H (2008) Process mining in web services: the WebSphere case. IEEE Bull Tech Comm Data Eng 31(3):45–48Google Scholar
  62. van der Aalst W, Weijters A, Maruster L (2004) Workflow mining: discovering process models from event logs. IEEE Trans Knowl Data Eng 16(9):1128–1142CrossRefGoogle Scholar
  63. van der Aalst W et al (2012) Process mining manifesto. In: Daniel F, Barkaoui K, Dustdar S (eds) Business process management workshops. Springer, Berlin, pp 169–194Google Scholar
  64. van der Werf JME, van Dongen BF, Hurkens CA, Serebrenik A (2008) Process discovery using integer linear programming. In: van Hee KM, Valk R (eds) Applications and theory of Petri nets. Springer, Berlin, pp 368–387Google Scholar
  65. W3C (2009) OWL 2 web ontology language document overview. (last visited May 7, 2012)
  66. Weijters A, van der Aalst W, De Medeiros AA (2006) Process mining with the heuristics miner-algorithm. Technische Universiteit Eindhoven, Tech. Rep. WP 166Google Scholar
  67. Wetzstein B, Ma Z, Leymann F (2008) Towards measuring key performance indicators of semantic business processes. In: Abramowicz W, Fensel D (eds) Business information systems, LNBIP, vol 7. Springer, Berlin, pp 227–238Google Scholar
  68. Zaheer A, Harris J (2006) Interorganizational trust (March 10, 2005). In: Shenkar O, Reuer JJ (eds) Handbook of strategic alliances, chap 10. Sage Publications, pp 169–197Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Robert Engel
    • 1
  • Worarat Krathu
    • 1
  • Marco Zapletal
    • 1
  • Christian Pichler
    • 1
  • R. P. Jagadeesh Chandra Bose
    • 1
  • Wil van der Aalst
    • 1
  • Hannes Werthner
    • 1
  • Christian Huemer
    • 1
  1. 1.Vienna University of TechnologyViennaAustria

Personalised recommendations