Towards Collecting Sustainability Data in Supply Chains with Flexible Data Collection Processes

  • Gregor Grambow
  • Nicolas Mundbrod
  • Jens Kolb
  • Manfred Reichert
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 203)


Nowadays, OEMs from many domains (e.g., electronics and automotive) face rising pressure from customers and legal regulations to produce more sustainable products. This involves the reporting and publishing of various sustainability indicators. However, the demands of legal entities and customers constitute a tremendous challenge as products in these domains comprise various components and sub-components provided by suppliers. Hence, sustainability data collection must be executed along the entire supply chain. In turn, this involves a myriad of different automated and manual tasks as well as quickly changing situations. In combination with potentially long-running processes, these issues result in great process variability that cannot be predicted at design time. In the SustainHub project, a dedicated information system for supporting data collection processes is developed. This paper provides three contributions: (1) it identifies core challenges for sustainable supply chain communication, (2) it reviews state-of-the-art technical solutions for such challenges, and (3) it gives a first overview of the approach we are developing in the SustainHub project to address the challenges. By achieving that, this comprehensive approach has the potential to unify and simplify supply chain communication in the future.


Process variability Data collection Sustainability Supply chain 


  1. 1.
    Fawcett, S.E., Osterhaus, P., Magnan, G.M., Brau, J.C., McCarter, M.W.: Information sharing and supply chain performance: the role of connectivity and willingness. Supply Chain Manage. Int. J. 12(5), 358–368 (2007)CrossRefGoogle Scholar
  2. 2.
    Gunasekaran, A., Ngai, E.W.T.: Information systems in supply chain integration and management. Eur. J. Oper. Res. 159(2), 269–295 (2004)CrossRefMATHMathSciNetGoogle Scholar
  3. 3.
    Pramatari, K.: Collaborative supply chain practices and evolving technological approaches. Supply Chain Manage. Int. J. 12(3), 210–220 (2007)CrossRefGoogle Scholar
  4. 4.
    Barnett, P.T., Braddock, D.M., Clarke, A.D., DuPré, D.L., Gimarc, R., Lehr, T.F., Palmer, A., Ramachandran, R., Renyolds, J., Spellman, A.C.: Method of semi-automatic data collection, data analysis, and model generation for the performance analysis of enterprise applications (2007)Google Scholar
  5. 5.
    Singh, R.K., Murty, H.R., Gupta, S.K., Dikshit, A.K.: An overview of sustainability assessment methodologies. Ecol. Ind. 9(2), 189–212 (2009)CrossRefGoogle Scholar
  6. 6.
    Ballou, B., Heitger, D.L., Landes, C.E.: The future of corporate sustainability reporting: a rapidly growing assurance opportunity. J. Account. 202(6), 65–74 (2006)Google Scholar
  7. 7.
    Adams, C.A., McNicholas, P.: Making a difference: sustainability reporting, accountability and organisational change. Account. Auditing Account. J. 20(3), 382–402 (2007)CrossRefGoogle Scholar
  8. 8.
    Pagell, M., Wu, Z.: Building a more complete theory of sustainable supply chain management using case studies of 10 exemplars. J. Supply Chain Manage. 45(2), 37–56 (2009)CrossRefGoogle Scholar
  9. 9.
    Gottschalk, F., van der Aalst, W.M.P., Jansen-Vullers, M.H., La Rosa, M.: Configurable workflow models. Int. J. Coop. Inf. Syst. 17(2), 177–221 (2008)CrossRefGoogle Scholar
  10. 10.
    Rosemann, M., van der Aalst, W.M.P.: A configurable reference modelling language. Inf. Syst. 32(1), 1–23 (2005)CrossRefGoogle Scholar
  11. 11.
    La Rosa, M., van der Aalst, W.M.P., Dumas, M., ter Hofstede, A.H.M.: Questionnaire-based variability modeling for system configuration. Softw. Syst. Model. 8(2), 251–274 (2009)CrossRefGoogle Scholar
  12. 12.
    Reinhartz-Berger, I., Soffer, P., Sturm, A.: Extending the adaptability of reference models. IEEE Trans. Syst. Man Cybern. Part A 40(5), 1045–1056 (2010)CrossRefGoogle Scholar
  13. 13.
    Hallerbach, A., Bauer, T., Reichert, M.: Configuration and management of process variants. In: vom Brocke, J., Rosemann, M. (eds.) Handbook on Business Process Management I, pp. 237–255. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  14. 14.
    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.) BPM Workshops 2012. LNBIP, vol. 132, pp. 560–572. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  15. 15.
    Ayora, C., Torres, V., Weber, B., Reichert, M., Pelechano, V.: Vivace: a framework for the systematic evaluation of variability support in process-aware information systems. Information and Software Technology (2014, to appear)Google Scholar
  16. 16.
    van der Aalst, W.M.P., Weske, M., Grünbauer, D.: Case handling: a new paradigm for business process support. Data Knowl. Eng. 53(2), 129–162 (2004)CrossRefGoogle Scholar
  17. 17.
    Reijers, H.A., Liman, S.: Product-based workflow design. Manage. Inf. Syst. 20(1), 229–262 (2003)Google Scholar
  18. 18.
    Bhattacharya, K., Hull, R., Su, J.: A data-centric design methodology for business processes. In: Cardoso, J., van der Aaalst, W.M.P. (eds.) Handbook of Research on Business Process Management, pp. 503–531. IGI, Hershey (2009)Google Scholar
  19. 19.
    Müller, D., Reichert, M., Herbst, J.: A new paradigm for the enactment and dynamic adaptation of data-driven process structures. In: Bellahsène, Z., Léonard, M. (eds.) CAiSE 2008. LNCS, vol. 5074, pp. 48–63. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  20. 20.
    Künzle, V., Reichert, M.: PHILharmonicFlows: towards a framework for object-aware process management. J. Softw. Maint. Evol. Res. Pract. 23(4), 205–244 (2011)CrossRefGoogle Scholar
  21. 21.
    Dadam, P., Reichert, M.: The ADEPT project: a decade of research and development for robust and flexible process support - challenges and achievements. Comput. Sci. - Res. Dev. 23(2), 81–97 (2009)CrossRefGoogle Scholar
  22. 22.
    Sadiq, S., Marjanovic, O., Orlowska, M.: Managing change and time in dynamic workflow processes. Int. J. Coop. Inf. Syst. 9(1&2), 93–116 (2000)CrossRefGoogle Scholar
  23. 23.
    Weske, M.: Formal foundation and conceptual design of dynamic adaptations in a workflow management system. In: Proceedings of Hawaii International Conference on System Sciences (HICSS-34) (2001)Google Scholar
  24. 24.
    Lenz, R., Reichert, M.: IT support for healthcare processes - premises, challenges, perspectives. Data Knowl. Eng. 61(1), 39–58 (2007)CrossRefGoogle Scholar
  25. 25.
    Minor, M., Tartakovski, A., Bergmann, R.: Representation and structure-based similarity assessment for agile workflows. In: Weber, R.O., Richter, M.M. (eds.) ICCBR 2007. LNCS (LNAI), vol. 4626, pp. 224–238. Springer, Heidelberg (2007) CrossRefGoogle Scholar
  26. 26.
    Weber, B., Reichert, M., Wild, W., Rinderle-Ma, S.: Providing integrated life cycle support in process-aware information systems. Int. J. Coop. Inf. Syst. 18(1), 115–165 (2009)CrossRefGoogle Scholar
  27. 27.
    Minor, M., Tartakovski, A., Schmalen, D., Bergmann, R.: Agile workflow technology and case-based change reuse for long-term processes. Int. J. Intell. Inf. Technol. 4(1), 80–98 (2008)CrossRefGoogle Scholar
  28. 28.
    Müller, R., Greiner, U., Rahm, E.: AgentWork: a workflow system supporting rule-based workflow adaptation. Data Knowl. Eng. 51(2), 223–256 (2004)CrossRefGoogle Scholar
  29. 29.
    Lerner, B.S., Christov, S., Osterweil, L.J., Bendraou, R., Kannengiesser, U., Wise, A.E.: Exception handling patterns for process modeling. IEEE Trans. Softw. Eng. 36(2), 162–183 (2010)CrossRefGoogle Scholar
  30. 30.
    Zugal, S., Soffer, P., Haisjackl, C., Pinggera, J., Reichert, M., Weber, B.: Investigating expressiveness and understandability of hierarchy in declarative business process models. Softw. Syst. Model. (2013). doi:10.1007/s10270-013-0356-2
  31. 31.
    Pesic, M., Schonenberg, H., van der Aalst, W.M.P.: Declare: full support for loosely-structured processes. In: 11th IEEE International Enterprise Distributed Object Computing Conference, 2007, EDOC 2007, pp. 287–287. IEEE (2007)Google Scholar
  32. 32.
    Weber, B., Pinggera, J., Zugal, S., Wild, W.: Alaska simulator toolset for conducting controlled experiments on process flexibility. In: Soffer, P., Proper, E. (eds.) CAiSE Forum 2010. LNBIP, vol. 72, pp. 205–221. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  33. 33.
    Grambow, G., Mundbrod, N., Steller, V., Reichert, M.: Towards process-based composition of activities for collecting data in supply chains. In: 6th Central European Workshop on Services and their Composition (ZEUS 2014), February 2014Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2015

Authors and Affiliations

  • Gregor Grambow
    • 1
  • Nicolas Mundbrod
    • 1
  • Jens Kolb
    • 1
  • Manfred Reichert
    • 1
  1. 1.Institute of Databases and Information SystemsUlm UniversityUlmGermany

Personalised recommendations