Group preference aggregation based on ELECTRE methods for ERP system selection

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Suzana Daher, Adiel Almeida, Group preference aggregation based on ELECTRE methods for ERP system selection

Suzana Daher, Adiel Almeida, Group preference aggregation based on ELECTRE methods for ERP system selection

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  • 1. Suzana de França Dantas Daher Adiel Teixeira de Almeida Group preference aggregationbased on ELECTRE methods for ERP system selection
  • 2. Agenda Introduction / Motivation Model Proposed Numerical application Final Remarks
  • 3. Motivation Enterprise resource planning (ERP) improves operational efficiency by integrating business processes and providing better access to integrated data across the entire enterprise Deciding which is the most suitable ERP solution is often a difficult task for many companies.  ERP not developed in-house
  • 4. Motivation Organizations select and implement ERP systems so as to obtain a variety of tangible and intangible benefits and for strategic reasons. The evaluation process of ERP systems needs to take many criteria into account  organizational factors such as the complexity of the business;  dealing with change management,  cost drivers,  its functional requirements,  system flexibility and system scalability,  external factors
  • 5. Motivation There is a strong possibility that in several organizations, an ERP system will be selected by a group. Multicriteria group decision making involves individuals who provide their preferences for a set of alternatives with respect to a set of attributes  Diverging opinions may arise
  • 6. Introduction This study deals with how support a group of individuals to achieve a collective decision when selecting an ERP system. The methodology adopted considered that DMs act in accordance with their own interests and there is no information about their relative importance to each other
  • 7. Introduction Which decision making method should be used? The selection of the most suitable decision making method should be based on the preference structures of the DMs
  • 8. Additive Model For instance, an additive model could be considered, such as in  Daher, S F D ; Almeida, A T (2012) The Use of Ranking Veto Concept to Mitigate the Compensatory Effects of Additive Aggregation in Group Decisions on a Water Utility Automation Investment. Group Decision and Negotiation Journal, v. 21, p. 185-204. In this case the additive model is considered for  aggregating the multiple criteria, and  Aggregating the decision makers’ preferences A veto concept is applied for the additive Aggregation of decision makers’ preferences
  • 9. Outranking methods An alternative approach is considered in this work:  Outranking methods Other properties are assumed for the decision maker preference
  • 10. Outranking methods Outranking methods are particulary suitable for decision-making through the notion of weak preference and incomparability. Outranking relations (S): “at least as good as”  aSb and not bSa a P b (a is strictly preferred to b)  bSa and not aSb b P a (b is strictly preferred to a)  aSb and bSa a I b (a is indifferent to b)  not aSb and not bSa a R b (a is incomparable to b)
  • 11. Outranking methods Construction of an outranking relation is based on 2 major concepts:  CONCORDANCE  Foran outranking aSb to be validated, a sufficient majority of criteria should be in favor of the assertion “a is at least as good as b”.  NON-DISCORDANCE  When the concordance condition holds, none of the criteria in the minority should oppose too strongly to the assertion aSb.
  • 12. ELECTRE Family methods ELECTRE ( Elimination Et Choix Traduisant la Realité / Elimination and Choice Expressing the Reality) This family seeks to obtain a set of N alternatives that outrank those which do not belong to the subset N. Choice problematic:  ELECTRE I, ELECTRE Iv, ELECTRE IS; Ranking problematic:  ELECTRE II, ELECTRE III, ELECTRE IV Sorting problematic:  ELECTRE A, ELECTRE TRI
  • 13. Model Proposed Based on a combination of two outranking methods: ELECTRE II and ELECTRE IV. Assumptions:  The decision problem is well structured  Prior definition of a set n alternatives  Prior definition of a set k criteria The model is organized in three steps Alencar, L.H., Almeida, A. T., Morais, D. C.: A Multicriteria Group Decision Model Aggregating the Preferences of Decision-Makers Based on ELECTRE Methods. Pesquisa Operacional 30, Issue 3, 687-702 (2010)
  • 14. Model ProposedIndividual ranking of alternatives (ELECTRE II) Matrix of global evaluation Group ranking of alternatives (ELECTRE IV)
  • 15. Model ProposedFirst step ELECTRE II  Generation of individual rankings of alternatives For each Decision Maker:  Decision Matrix D  Concordance and discordance indices  Criteria weights (inter-criteria information)
  • 16. Model ProposedFirst step A concordance index C(a,b):  represents the coalition of arguments in favor of the statement “a is at least as good as b ” or in other words “a outranks b ” C (a, b) wj { j:g j ( a ) g j (b )} A discordance index D(a,b) :  is used to measure the arguments that may cast some doubt upon the latter statement. D ( a, b) max {g j (b) g j (a)} j: g j ( a ) g j ( b )  No veto condition: g j (a) v( g j (a)) g j (b), j J
  • 17. Model ProposedFirst step These indices are used to construct two pre-orders:  strong outranking relation (a SS b)  weak outranking relation (a Sw b) C ( a, b) c D ( a, b) d S iff aS b wj j: gj ( a ) gj (b ) wj j:gj ( a ) gj ( b ) C ( a, b) c D ( a, b) d aSW b iff wj wj j: gj ( a ) gj (b ) j: gj ( a ) gj ( b )
  • 18. Model ProposedSecond step Obtain a matrix of global evaluation Analyst must collect all individual ranking and compile them in a global evaluation matrix. DMs are considered as criteria and their rankings correpond to the evaluation of the alternatives (ranking position of the alternative)
  • 19. Model ProposedThird step ELECTRE IV  Obtain a group ranking ELECTRE IV is used in cases in which there is a pseudo-criterion family and its main feature is the absence of a weighting related to the relative importance of the criteria
  • 20. Numerical application Fictitious case study: ERP selection for a Brazilian airlines The company has to deal with inefficient operational procedures and an IT/IS legacy system. In order to improve its competitiveness, the company launch of several projects including, an ERP system and the reengineering of some business processes
  • 21. Numerical application Four decision makers:  the financial manager (DM1)  the IT/IS manager (DM2)  the operational manager (DM3)  the customer relation manager (DM4) Analyst should conduct the decision making process. Number of alternatives: 4
  • 22. Numerical application Criteria selection Based on: ISO/IEC 9126-1  a standard that addresses quality model definition and its use as framework for software evaluation Group of criteria:  functional, portability, maintainability, efficiency, vendor, cost
  • 23. Numerical applicationCriteria adopted Criteria Criteria group C1 Completeness Functional C2 Number of simultaneous users Functional C3 DBMS Standards Portability C4 Number of modules Maintainability C5 Time behavior Efficiency C6 Length of experience Vendor C7 License cost Cost Installation and implementation C8 Cost cost
  • 24. Numerical application Decision matrix C1 C2 C3 C4 C5 C6 C7 C8A1 4 5000 4 8 0.3 4 0.7 1.8A2 5 3000 5 12 0.6 5 0.5 1.3A3 3 4500 4 10 0.2 4 0.6 1.7A4 5 4000 3 5 0.7 5 0.4 2.0 Concordance and Discordance coefficients c+ c- d+ d- DM1 0.8 0.6 0.4 0.5 DM2 0.7 0.5 0.3 0.4 DM3 0.8 0.5 0.3 0.4 DM4 0.9 0.6 0.3 0.5
  • 25. Numerical application  Criteria weights C1 C2 C3 C4 C5 C6 C7 C8DM1 0.175 0.175 0.082 0.221 0.043 0.117 0.093 0.094DM2 0.081 0.101 0.086 0.333 0.005 0.081 0.188 0.125DM3 0.102 0.004 0.005 0.200 0.136 0.149 0.370 0.034DM4 0.035 0.035 0.198 0.167 0.056 0.232 0.211 0.066  Table of preorders for each DM Ranking DM1 DM2 DM3 DM4 1st A2 A2 A3,A4 A2 2nd A3 A1 A2 A3 3rd A1 A3 A1 A1,A4 4th A4 A4
  • 26. Numerical application Matrix of global evaluation DM1 DM2 DM3 DM4 A1 2 3 1 1 A2 4 4 2 3 A3 3 2 3 2 A4 1 1 3 1 Global ranking of alternatives Ranking Alternatives 1st A2 2nd A1, A3,A4
  • 27. Final remarks In general, decisions made in organizations involve a group of people, from different departments or sectors  Analyst should guarantee that client’s interest are as well represented as possible. An approach to support a group of decision makers to select na ERP system Different results could appear if ELECTRE IV be changed to another method such as Borda Count or Condorcet.
  • 28. Thank you. Suzana Daher Federal University of Pernambuco Brazil