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Is it Worth the Effort?

A Decision Model to Evaluate Resource Interactions in IS Project Portfolios

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Abstract

The adequate consideration of resource interactions among IS projects is a challenging but important requirement within IS project portfolio selection. However, the literature does not mention any potential techniques for the identification and assessment of resource interactions. Moreover, the literature has so far neglected the question of the trade-off between time and effort invested in identifying and evaluating resource interactions caused by resource sharing among projects, compared to the benefits derived from this procedure. Hence, the paper’s contribution is twofold. First, a technique to support the identification and evaluation of potentially economically relevant resource interactions is suggested. Second, the paper proposes a decision model that allows to calculate a theoretical upper bound for the amount of effort that should be invested in improving estimates for identified interactions as part of the portfolio planning process.

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Notes

  1. In line with, e.g., Eilat et al. (2006) we use the term interaction synonymously to interdependency in this article.

  2. For comprehensive literature reviews see Chien (2002), Kundisch and Meier (2011a), or Müller et al. (2015).

  3. Alternatively to the fixed cost parameters introduced above, it is also possible to formulate parametric functions that represent the marginal cost decrease or increase for additional resource units.

  4. Please note that (8) and (9) implicitly assume that additionally acquired resources, and not just internally available resources, are able to contribute to synergies/cannibalization effects.

  5. The optimization model is part of a prototypically implemented decision support software; in the following referred to as system.

  6. For instance, the average number of projects in R&D and IT project portfolios in large and mid-sized firms, according to a cross industry study of Meskendahl et al. (2011), is 132. Obviously, the number of project proposals will typically be even much higher.

  7. To calculate PF, we assume that all input parameters necessary for our quadratically-constrained 0–1 program are known with certainty.

  8. Relaxing the contingency restrictions from the example of Lee and Kim (2001) enabled us to better illustrate the functionalities of our approach.

  9. Referring to the example in the introduction of Sect. 3.2.2, for 20 projects, five resources and only up to three projects (k = 3) per interaction, the potential number of interactions would be reduced from over 5 m to 6650.

  10. Please note that we have limited the number of projects participating in an interaction to k = 3 projects per interaction to keep the example comprehensible.

  11. We assume that existing resources generate fixed costs, even if they are not used to full capacity (e.g., personnel). If this assumption is relaxed, we have to introduce penalty costs to estimate the residual value of the reduced portfolio PF red i,s accordingly.

  12. For a triangular distribution, for example, the mode is set to the point estimate provided by the expert, while the upper and lower bounds derived by expert estimation provide the minimum and maximum values for the distribution, respectively. The probabilities for the occurrence of each realization s can then be calculated and serve as weights for the corresponding benefit differences d i,s . To calculate the probabilities for each individual s, the interval between the bounds has to be discretized into a number of subintervals. For each subinterval, its expected value serves as the realization of the interaction under investigation for the corresponding optimization step. The area defined by the interval and the triangle defining the distribution then serves as probability for the occurrence of this realization.

References

  • Aaker DA, Tyebjee TT (1978) A model for the selection of interdependent R&D projects. IEEE Trans Eng Manag 25(2):30–36

    Article  Google Scholar 

  • Aral, S, Brynjolfsson, E, Wu, DJ (2006) Which came first, IT or productivity? The virtuous cycle of investment and use in enterprise systems. In: Proceedings of the 27th International Conference on Information Systems, AIS, Milwaukee

  • Archer NP, Ghasemzadeh F (1999) An integrated framework for project portfolio selection. Int J Proj Manag 17(4):207–216

    Article  Google Scholar 

  • Bayney RM, Chakravarti R (2012) Enterprise project portfolio management: Building competencies for R&D and IT investment success. J. Ross Publishing, Plantation, FL

  • Beaujon GJ, Marin SP, McDonald GC (2001) Balancing and optimizing a portfolio of R&D projects. Nav Res Logist 48(1):18–40

    Article  Google Scholar 

  • Better M, Glover F (2006) Selecting project portfolios by optimizing simulations. Eng Econ 51(2):81–97

    Article  Google Scholar 

  • Bonham SS (2005) IT project portfolio management. Artech, Norwood

    Google Scholar 

  • Bradley G (2010) Benefit realisation management – a practical guide to achieving benefits through change, 2nd edn. Gower, Farnham

    Google Scholar 

  • Buhl HU (2012) The contribution of business and information systems engineering to the early recognition and avoidance of “Black Swans” in IT projects. Bus Inf Syst Eng 4(2):55–59

    Article  Google Scholar 

  • Carazo AF, Gómez T, Molina J, Hernández-Díaz A, Guerrero FM, Caballero R (2010) Solving a comprehensive model for multiobjective project portfolio selection. Comput Oper Res 37(4):630–639

    Article  Google Scholar 

  • Chien CF (2002) A portfolio-evaluation framework for selecting R&D projects. R&D Manag 32(4):359–368

    Article  Google Scholar 

  • Colucci S, Di Noia T, Di Sciascio E, Donini FM, Mongiello M, Mottola M (2003) A formal approach to ontology-based semantic match of skills descriptions. J Univers Comput Sci 9(12):1437–1454

    Google Scholar 

  • Cooper RG, Edgett SJ, Kleinschmidt (2001) Portfolio management for new product development: results of an industry practices study. R&D Manag 31(4):361–380

    Article  Google Scholar 

  • Dickinson MW, Thornton AC, Graves S (2001) Technology portfolio management: optimizing interdependent projects over multiple time periods. IEEE Trans Eng Manag 48(4):518–527

    Article  Google Scholar 

  • Doerner KF, Gutjahr WJ, Hartl RF, Strauss C, Stummer C (2006) Pareto ant colony optimization with ILP preprocessing in multiobjective project portfolio selection. EJOR 171(3):830–841

    Article  Google Scholar 

  • Eilat H, Golany B, Shtub A (2006) Constructing and evaluating balanced portfolios of R&D projects with interactions: a DEA based methodology. EJOR 172(3):1018–1039

    Article  Google Scholar 

  • Engelstätter B (2013) Enterprise systems and labor productivity: disentangling combination effects. Int J Eng Res Appl 3(3):1095–1107

    Google Scholar 

  • Flyvbjerg B, Budzier A (2011) Why your IT project may be riskier than you think. Harv Bus Rev 89(9):601–603

    Google Scholar 

  • Fox GE, Baker NR, Bryant JL (1984) Economic models for R and D project selection in the presence of project interactions. Manag Sci 30(7):890–902

    Article  Google Scholar 

  • Gareis R (1989) ‘Management by projects’: the management approach for the future. Int J Proj Manag 7(4):243–249

    Article  Google Scholar 

  • Gareis R (1991) Management by projects: the management strategy of the ‘new’ project-oriented company. Int J Proj Manag 9(2):71–76

    Article  Google Scholar 

  • Gear TE, Cowie GC (1980) A note on modeling project interdependence in research and development. Decis Sci 11(4):738–748

    Article  Google Scholar 

  • Ghapanchi AH, Tavana M, Khakbaz MH, Low G (2012) A methodology for selecting portfolios of projects with interactions and under uncertainty. Int J Proj Manag 30(7):791–803

    Article  Google Scholar 

  • Ghasemzadeh F, Archer NP (2000) Project portfolio selection through decision support. Decis Support Syst 29(1):73–88

    Article  Google Scholar 

  • Ghasemzadeh F, Archer NP, Iyogun P (1999) A zero-one model for project portfolio selection and scheduling. J Oper Res Soc 50(7):745–755

    Article  Google Scholar 

  • Graves SB, Ringuest JL (2003) Models and methods for project selection: concepts from management science. Finance and Information Technology, Kluwer

    Book  Google Scholar 

  • Greene WH (2008) Econometric analysis, 6th edn. Prentice Hall, Upper Saddle River, New Jersey

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

    Google Scholar 

  • Howard RA (1966) Information value theory. IEEE Trans Syst Sci Cybern 2(1):22–34

    Article  Google Scholar 

  • Killen CP, Kjaer C (2012) Understanding project interdependencies: exploring the role of visual representation, culture and process. Int J Proj Manag 30(5):554–566

    Article  Google Scholar 

  • Kira DS, Kusy MI, Murray DH, Goranson BJ (1990) A specific decision support system (SDSS) to develop an optimal project portfolio mix under uncertainty. IEEE Trans Eng Manag 37(3):213–221

    Article  Google Scholar 

  • Kuechner W, Vaishnavi V (2012) A framework for theory development in design science research: multiple perspectives. J Assoc Inf Syst 13(6):395–423

    Google Scholar 

  • Kundisch D, Meier C (2011a) IT/IS project portfolio selection in the presence of project interactions – review and synthesis of the literature. In: Proceedings Wirtschaftsinformatik, Zurich, pp 477–486

  • Kundisch D, Meier C (2011b) A new perspective on resource interactions in IT/IS project portfolio selection. In: Proceedings ECIS 2011, Helsinki, paper 174

  • Lee JW, Kim SH (2001) An integrated approach for interdependent information system project selection. Int J Proj Manag 19(2):111–118

    Article  Google Scholar 

  • Lourenco JC, Morton A, Bana e Costa CA (2012) PROBE – a multicriterial decision support system for portfolio robustness evaluation. Decis Support Syst 54(1):534–550

    Article  Google Scholar 

  • Marsden JR, Pingry DE (1993) Theory of decision support systems portfolio evaluation. Decis Support Syst 9(2):183–199

    Article  Google Scholar 

  • Maylor H, Brady T, Cooke-Davies T, Hodgson D (2006) From projectification to programmification. Int J Proj Manag 24(8):663–674

    Article  Google Scholar 

  • Meskendahl S, Jonas D, Kock A, Gemünden HG (2011) The art of project portfolio management. TIM Working Paper 4(1), Technische Universität Berlin

  • Müller M, Meier C, Kundisch D, Zimmermann S (2015) interactions in IS project portfolio selection – status quo and perspectives. Proceedings Wirtschaftsinformatik, Osnabrück, Paper 64

  • Nelson C (1986) A scoring model for flexible manufacturing systems project selection. EJOR 24(3):346–359

    Article  Google Scholar 

  • Nemhauser GL, Ullmann Z (1969) Discrete dynamic programming and capital allocation. Manag Sci 15(9):494–505

    Article  Google Scholar 

  • Phillips LD, Bana e Costa CA (2007) Transparent prioritisation, budgeting and resource allocation with multi-criteria decision analysis and decision conferencing. Ann Oper Res 154(1):51–68

    Article  Google Scholar 

  • Praviz FR, Levin G (2006) Project portfolio management tools and techniques. IIL, New York

    Google Scholar 

  • Pries-Heje J, Baskerville R (2008) Strategies for design science research evaluation. In: Proceedings ECIS 2011, Galway, pp 1–12

  • Project Management Institute (2008) The standard for portfolio management, 2nd edn. PMI, Pennsylvania

    Google Scholar 

  • Santhanam R, Kyparisis GJ (1996) A decision model for interdependent information system project selection. EJOR 89(2):380–399

    Article  Google Scholar 

  • Schniederjans MJ, Wilson RL (1991) Using the analytic hierarchy process and goal programming for information system project selection. Inf Manag 20(5):333–342

    Article  Google Scholar 

  • Stummer C, Heidenberger K (2003) Interactive R&D portfolio analysis with project interdependencies and time profiles of multiple objectives. IEEE Trans Eng Manag 50(2):175–183

    Article  Google Scholar 

  • Tian Q, Ma J, Liang J, Kwok RCW, Liu O (2005) An organizational decision support system for effective R&D project selection. Decis Support Syst 39(3):403–413

    Article  Google Scholar 

  • Toppila A, Liesiö J, Salo A (2011) A resource allocation model for R&D investments: A case study in telecommunication standardization. International Series in Operations Research & Management Science. Springer, New York, pp 241–258

    Google Scholar 

  • Wehrmann A, Heinrich B, Seifert F (2006) Quantitatives IT-portfoliomanagement. Wirtschaftsinformatik 48(4):234–245

    Article  Google Scholar 

  • Weingartner HM (1966) Capital budgeting of interrelated projects: survey and synthesis. Manag Sci 12(7):485–516

    Article  Google Scholar 

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Authors and Affiliations

  1. Chair for Business Information Systems, esp. Digital Markets, Department for Business Information Systems, University of Paderborn, Warburger Str. 100, 33098, Paderborn, Germany

    Christian Meier &  Dennis Kundisch

  2. Arvato Systems GmbH, An der Autobahn 200, 33333, Gütersloh, Germany

    Jochen Willeke

Authors
  1. Christian Meier
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  2. Dennis Kundisch
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  3. Jochen Willeke
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Correspondence to Christian Meier.

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Accepted after three revisions by Prof. Dr. Bichler.

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Meier, C., Kundisch, D. & Willeke, J. Is it Worth the Effort?. Bus Inf Syst Eng 59, 81–95 (2017). https://doi.org/10.1007/s12599-016-0450-4

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