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Reducing ambiguity during enterprise design

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Abstract

Requirements elicitation is one of the most important phases in the design process and applied by many engineering disciplines. A more recent application of the design process is to design the enterprise as an artefact, also called enterprise engineering (EE). Even though there are limits to formal enterprise design due to enterprise complexity, strategic intentions are not realised spontaneously or accidently. Intentional enterprise design is required, starting with the strategic context, eliciting enterprise intentions. Similar to the ad hoc evolution of enterprises, EE as a discipline also developed in a fragmented way with enterprise design knowledge mostly encapsulated in several enterprise design approaches. A previous study analysed eight different enterprise design/alignment approaches, inductively developing a common framework to represent and compare these approaches in terms of four main components. One of the components represents the scope of enterprise design/alignment in terms of three dimensions: design domains, intentions and constraints, and enterprise scope. Since existing approaches use inconsistent means of defining the first dimension, namely the design domains, previous work already provides some guidance on demarcating design domains in a more consistent way. This article focuses on the second dimension, i.e. intentions and constraints, and the need to distinguish between different intention-related concepts to reduce possible ambiguity. The study applies design science research to develop a method for enterprise intentions concept clarification (MEICC) as a theoretical contribution. The study also offers a practical contribution, demonstrating how the MEICC was used to clarify intention-related concepts that feature within a specific approach, namely Hoogervorst’s approach. A coding strategy (including coding conditions, a refined codebook and a coding method), developed for Hoogervorst’s approach via MEICC, is presented as a secondary contribution, since the coding strategy will also be useful to practitioners that use Hoogervorst’s approach.

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References

  1. Distanont A, Haapasalo H, Vaananen M, Letho J (2012) The engagement between knowledge transfer and requirements engineering. Int J Knowl Learn 1(2):131–156

    Google Scholar 

  2. Bentley LD, Whitten JL (2007) Systems analysis and design for the global enterprise, 7th edn. McGraw-Hill/Irwin, New York

    Google Scholar 

  3. Dym CL, Little P (2009) Engineering design, 3rd edn. Wiley, New York

    Google Scholar 

  4. Eggert RJ (2010) Engineering design, 2nd edn. High Peak Press, Idaho

    Google Scholar 

  5. Dietz JLG, Hoogervorst JAP, Albani A, Aveiro D et al (2013) The discipline of enterprise engineering. Int J Organ Des Eng 3(1):86–114

    Google Scholar 

  6. Boulding KE (1956) General systems theory: the skeleton of science. Manage Sci 2:197–207

    Article  Google Scholar 

  7. Hoogervorst JAP (2018) Practicing enterprise governance and enterprise engineering—applying the employee-centric theory of organization. Springer, Berlin

    Book  Google Scholar 

  8. Simon HA (1969) The sciences of the artificial, 3rd edn. MIT Press, Cambridge

    Google Scholar 

  9. De Vries M, Van der Merwe A, Gerber A (2017) Extending the enterprise evolution contextualisation model. Enterp Inf Syst 11(6):787–827

    Article  Google Scholar 

  10. Lapalme J (2012) Three schools of thought on enterprise architecture. IT Prof 14(6):37–43. https://doi.org/10.1109/MITP.2011.109

    Article  Google Scholar 

  11. De Vries M (2013) A classification schema for comparing business-IT alignment approaches. Int J Ind Eng Theory Appl Pract 20(3–4):111–126

    Google Scholar 

  12. De Vries M (2017) Towards consistent demarcation of enterprise design domains. In: De Cesare S, Frank U (eds) Advances in conceptual modeling. Springer, Switzerland, pp 91–100

    Chapter  Google Scholar 

  13. Giachetti RE (2010) Design of enterprise systems. CRC Press, Boca Raton

    Google Scholar 

  14. Hoogervorst JAP (2009) Enterprise governance and enterprise engineering. Springer, Diemen

    Book  Google Scholar 

  15. Hoogervorst JAP (2017) The imperative of employee-centric organizing and the significance for enterprise engineering. J Organ Des Eng 1(1):43–58. https://doi.org/10.1007/s41251-016-0003-y

    Article  Google Scholar 

  16. Kossiakoff A, Weet WN, Seymour S, Biemer SM (2011) Systems engineering principles and practice, 2nd edn. Wiley, New Jersey

    Book  Google Scholar 

  17. Douglas BP (2016) Agile systems engineering. Elsevier, https://app.knovel.com/hotlink/toc/id:kpASE00001/agile-systems-engineering/agile-systems-engineering. Accessed 11 July 2019

  18. Djouab R, Abran A, Seffah A (2016) An ASPIRE-based method for quality requirements identification from business goals. Requir Eng 21:87–106

    Article  Google Scholar 

  19. Horkoff J, Yu E (2013) Comparison and evaluation of goal-oriented satisfaction analysis techniques. Requir Eng 18:199–222

    Article  Google Scholar 

  20. Guizzardi RSS, Franch X, Guizzardi G, Wieringa RJ (2013) Ontological distinctions between means-end and contribution links in the i* framework. In: Ng W, Storey VC, Trujillo J (eds) ER 2013, LNCS 8217. Springer, Berlin, pp 463–470

    Google Scholar 

  21. Chung L, Nixon B, Yu E (1994) Using non-functional requirements to systematically select among laternatives in architectural design. In: Proceedings of 1st international workshop on architectures for software systems, pp 31–43

  22. Horkoff J, Yu E (2016) Interactive goal mode analysis for early requirements engineering. Requir Eng 21:29–61

    Article  Google Scholar 

  23. Horkoff J, Yu E (2009) Evaluating goal achievement in enterprise modeling—an interactive procedure and experiences. In: Proceedings of 2nd IFIP WG 8.1 working conference on the practice of enterprise modeling (PoEm’09), LNBIB, vol 39, pp 145–171

  24. Dimitrakopoulos G, Kavakali E, Loucopoulos P, Anagnostopoulos D et al (2019) The capability-oriented modelling and simulation approach for autonomous vehicle management. Simul Model Pract Theory 91:28–47

    Article  Google Scholar 

  25. The Open Group (2011) TOGAF 9.1. http://pubs.opengroup.org/architecture/togaf9-doc/arch/index.html. Accessed 15 Jan 2019

  26. Zachman JA (2009) The Zachman Framework for Enterprise Architecture™: A Primer for Enterprise Engineering and Manufacturing. http://zachmaninternational.com/index.php/home-article/15#maincol. Accessed 19 Nov 2009

  27. Gharajedaghi J (2011) Systems thinking: managing chaos and complexity, 3rd edn. Elsevier, Burlington, USA

    Google Scholar 

  28. Zachman JA (2008) John Zachman’s concise definition of the Zachman Framework. https://zachman.com/about-the-zachman-framework. Accessed 3 Apr 2019

  29. O’Rourke C, Fishman N, Selkow W (2003) Enterprise architecture using the Zachman framework. Thomson Course Technology, Boston

    Google Scholar 

  30. Smith KL (2019) The complete pragmatic family of frameworks. http://www.pragmaticea.com/display-show.asp?ShowName=PragmaticFamily&ModelName=POET.Methods.Overview.Phases.Strategising#entry. Accessed 3 Apr 2019

  31. Smith KL (2017) Enterprise DEBT: A pragmatic approach to enterprise transformation governance, V1.4. Pragmatic EA Ltd, Essex, England

  32. Smith KL (2019) Connecting the DOTS: The Death of “The Business & IT”, V1.0. Pragmatic EA Lmt, Essex, England

  33. Ferrari A, Spoletini P, Gnesi S (2016) Ambiguity and tacit knowledge in requirements elicitation interviews. Requir Eng 21:333–335

    Article  Google Scholar 

  34. Berry DM, Kamsties E (2005) The syntactically dangerous all and plural in specifications. IEEE Softw 22(1):55–57

    Article  Google Scholar 

  35. Gleich B, Creighton O, Kof L (2010) Ambiguity detection: towards a tool explaining ambiguity sources. Requir Eng Found Softw Qual Lect Notes Comput Sci 6182:218–232. https://doi.org/10.1007/978-3-642-14192-8_20

    Article  Google Scholar 

  36. Ashby WR (1958) Requisite variety and its implications for the control of complex systems. Cybernetica 1(2):83–99

    MATH  Google Scholar 

  37. Van der Meulen T (2017) Towards a useful DEMO-based enterprise engineering methodology, demonstrated at an agricultural enterprise. Dissertation, University of Pretoria

  38. Gause DC, Weinberg GM (1989) Exploring requirements: quality before design. Dorset House Publishing, New York

    MATH  Google Scholar 

  39. Dietz JLG (2006) Enterprise ontology. Springer, Berlin

    Book  Google Scholar 

  40. Theuerkorn F (2005) Lightweight enterprise architectures. Auerbach Publications, New York

    Google Scholar 

  41. Garrett JJ (2011) The elements of user experience: user-centered design for the web and beyond, 2nd edn. New Riders Press, Berkeley

    Google Scholar 

  42. Kuechler W, Vaishnavi V (2008) The emergence of design research in information systems in North America. J Design Res 7(1):1–16

    Article  Google Scholar 

  43. Winter R (2008) Design science research in Europe. European Journal of Information Systems 17:470–475

    Article  Google Scholar 

  44. Hevner AR, March ST, Park J, Ram S (2004) Design science in information systems research. MIS Q 28(1):75–105

    Article  Google Scholar 

  45. Owen C (1997) Design research: building the knowledge base. J Jpn Soc Sci Des 5(2):36–45

    Google Scholar 

  46. March ST, Smith G (1995) Design and natural science research on information technology. Decis Support Syst 15(4):251–266

    Article  Google Scholar 

  47. Niehaves B (2007) On epistemological diversity in design science—new vistas for design-oriented IS research? In: 28th International conference on information systems. Montreal

  48. Klein HK, Myers MD (1999) A set of principles for conducting and evaluating interpretive field studies in information systems. MIS Q 23(1):67–94

    Article  Google Scholar 

  49. Peffers K, Tuunanen T, Niehaves B (2018) Design science research genres: introduction to the special issue on exemplars and criteria for applicable design science research. Eur J Inf Syst 27(2):129–139. https://doi.org/10.1080/0960085X.2018.1458066

    Article  Google Scholar 

  50. Gregor S, Jones D (2007) The anatomy of a design theory. J Assoc Inf Syst 8(5):312–335

    Google Scholar 

  51. Peffers K, Tuunanen T, Rothenberger M, Chatterjee S (2008) A design science research methodology for information systems research. J MIS 24(3):45–77

    Google Scholar 

  52. Gregor S, Hevner A (2013) Positioning and presenting design science research for maximum impact. MIS Q 37(2):337–355

    Article  Google Scholar 

  53. Guest G, MacQueen KM, Namey EE (2012) Applied thematic analysis. Sage, Thousand Oaks

    Book  Google Scholar 

  54. Siau K (2004) Informational and computational equivalence in comparing information modelling methods. J Database Manag 15(1):73–86

    Article  Google Scholar 

  55. Sheer A-W, Hars A (1992) Extending data modelling to cover the whole enterprise. Commun ACM 35(9):166–172

    Article  Google Scholar 

  56. Wand Y, Weber RA (2002) Research commentary: information systems and conceptual modelling—a research agenda. Inf Syst Res 13(4):363–376

    Article  Google Scholar 

  57. Karagiannis D, Mayer HC, Mylopoulos J (2016) Domain-specific conceptual modeling: concepts, methods and tools. Springer, Berlin

    Book  Google Scholar 

  58. Grüninger M, Atefi K (2000) Fox MMS ontologies to support process integration in enterprise engineering. Comput Math Organ Theory 6(4):381–394

    Article  Google Scholar 

  59. Honderich T (2006) The Oxford companion to philosophy. Oxford University Press, Oxford

    Google Scholar 

  60. Corea C, Delfmann P (2017) Detecting compliance with business rules in ontology-based process modeling. In: Leimeister JM, Brenner W (eds) Proceedings der 13. Internationalen Tagung Wirtschaftsinformatik (WI 2017). St. Gallen, pp 226–240

  61. Wand Y, Weber RA (1993) On the ontological expressiveness of information systems analysis and design grammars. Inf Syst J 3(4):217–237

    Article  Google Scholar 

  62. Verdonck M, Gailly F, Pergl R, Guizzardi G et al (2019) Comparing traditional conceptual modeling with ontology-driven conceptual modeling: an empirical study. Inf Syst 81:92–103

    Article  Google Scholar 

  63. Guizzardi G, Falbo RA, Guizzardi RSS (2008) Grounding software domain ontologies in the unified foundational ontology: The case of the ODE software process ontology. In: Proceedings XI Iberoamerican workshop on requirements engineering and software environments, Recife, Brazil. pp 244–251

  64. Krueger RA, Casey MA (2015) Focus groups: a practical guide for applied research, 5th edn. SAGE, Thousand Oaks

    Google Scholar 

  65. MacQueen KM, McLellan-Lemal E, Bartholow K, Milstein B (2008) Team-based codebook development: Structure, process, and agreement. In: Guest G, MacQueen KM (eds) Handbook for team-based qualitative research. AltaMira, MD, Lanham, pp 119–135

    Google Scholar 

  66. Saldana J (2009) The coding manual for qualitative researchers. Sage Publications, London

    Google Scholar 

  67. De Vries M, Gerber A, Van der Merwe A (2015) The enterprise engineering domain. In: Aveiro D, Pergl R, Valenta M (eds) Advances in enterprise engineering IX. Springer, Berlin, pp 47–63

    Chapter  Google Scholar 

  68. Perinforma APC (2015) The essence of organisation. Sapio, www.sapio.nl

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Acknowledgements

We would like to thank all participants of this study for their active participation and willingness to contribute towards the development of a method for enterprise intentions concept clarification.

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Correspondence to Marné de Vries.

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de Vries, M. Reducing ambiguity during enterprise design. Requirements Eng 25, 231–251 (2020). https://doi.org/10.1007/s00766-019-00320-1

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