Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Business & Information Systems Engineering
Published in: Business & Information Systems Engineering 2/2017

05-09-2016 | Research Paper

Is it Worth the Effort?

A Decision Model to Evaluate Resource Interactions in IS Project Portfolios

Authors: Dr. Christian Meier, Prof. Dr. Dennis Kundisch, Jochen Willeke

Published in: Business & Information Systems Engineering | Issue 2/2017

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

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.
previous article Business Analytics and Data Science: Once Again?
next article Service-Channel Fit Conceptualization and Instrument Development

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now
Show more products
Footnotes
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 i,s red 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.
 
Literature
Aaker DA, Tyebjee TT (1978) A model for the selection of interdependent R&D projects. IEEE Trans Eng Manag 25(2):30–36CrossRef
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):207–216CrossRef
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):18–40CrossRef
Better M, Glover F (2006) Selecting project portfolios by optimizing simulations. Eng Econ 51(2):81–97CrossRef
Bonham SS (2005) IT project portfolio management. Artech, Norwood
Bradley G (2010) Benefit realisation management – a practical guide to achieving benefits through change, 2nd edn. Gower, Farnham
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):55–59CrossRef
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):630–639CrossRef
Chien CF (2002) A portfolio-evaluation framework for selecting R&D projects. R&D Manag 32(4):359–368CrossRef
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
Cooper RG, Edgett SJ, Kleinschmidt (2001) Portfolio management for new product development: results of an industry practices study. R&D Manag 31(4):361–380CrossRef
Dickinson MW, Thornton AC, Graves S (2001) Technology portfolio management: optimizing interdependent projects over multiple time periods. IEEE Trans Eng Manag 48(4):518–527CrossRef
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):830–841CrossRef
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):1018–1039CrossRef
Engelstätter B (2013) Enterprise systems and labor productivity: disentangling combination effects. Int J Eng Res Appl 3(3):1095–1107
Flyvbjerg B, Budzier A (2011) Why your IT project may be riskier than you think. Harv Bus Rev 89(9):601–603
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):890–902CrossRef
Gareis R (1989) ‘Management by projects’: the management approach for the future. Int J Proj Manag 7(4):243–249CrossRef
Gareis R (1991) Management by projects: the management strategy of the ‘new’ project-oriented company. Int J Proj Manag 9(2):71–76CrossRef
Gear TE, Cowie GC (1980) A note on modeling project interdependence in research and development. Decis Sci 11(4):738–748CrossRef
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):791–803CrossRef
Ghasemzadeh F, Archer NP (2000) Project portfolio selection through decision support. Decis Support Syst 29(1):73–88CrossRef
Ghasemzadeh F, Archer NP, Iyogun P (1999) A zero-one model for project portfolio selection and scheduling. J Oper Res Soc 50(7):745–755CrossRef
Graves SB, Ringuest JL (2003) Models and methods for project selection: concepts from management science. Finance and Information Technology, KluwerCrossRef
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
Howard RA (1966) Information value theory. IEEE Trans Syst Sci Cybern 2(1):22–34CrossRef
Killen CP, Kjaer C (2012) Understanding project interdependencies: exploring the role of visual representation, culture and process. Int J Proj Manag 30(5):554–566CrossRef
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):213–221CrossRef
Kuechner W, Vaishnavi V (2012) A framework for theory development in design science research: multiple perspectives. J Assoc Inf Syst 13(6):395–423
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):111–118CrossRef
Lourenco JC, Morton A, Bana e Costa CA (2012) PROBE – a multicriterial decision support system for portfolio robustness evaluation. Decis Support Syst 54(1):534–550CrossRef
Marsden JR, Pingry DE (1993) Theory of decision support systems portfolio evaluation. Decis Support Syst 9(2):183–199CrossRef
Maylor H, Brady T, Cooke-Davies T, Hodgson D (2006) From projectification to programmification. Int J Proj Manag 24(8):663–674CrossRef
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):346–359CrossRef
Nemhauser GL, Ullmann Z (1969) Discrete dynamic programming and capital allocation. Manag Sci 15(9):494–505CrossRef
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):51–68CrossRef
Praviz FR, Levin G (2006) Project portfolio management tools and techniques. IIL, New York
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
Santhanam R, Kyparisis GJ (1996) A decision model for interdependent information system project selection. EJOR 89(2):380–399CrossRef
Schniederjans MJ, Wilson RL (1991) Using the analytic hierarchy process and goal programming for information system project selection. Inf Manag 20(5):333–342CrossRef
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):175–183CrossRef
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):403–413CrossRef
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
Wehrmann A, Heinrich B, Seifert F (2006) Quantitatives IT-portfoliomanagement. Wirtschaftsinformatik 48(4):234–245CrossRef
Weingartner HM (1966) Capital budgeting of interrelated projects: survey and synthesis. Manag Sci 12(7):485–516CrossRef
Metadata
Title
Is it Worth the Effort?
A Decision Model to Evaluate Resource Interactions in IS Project Portfolios
Authors
Dr. Christian Meier
Prof. Dr. Dennis Kundisch
Jochen Willeke
Publication date
05-09-2016
Publisher
Springer Fachmedien Wiesbaden
Published in
Business & Information Systems Engineering / Issue 2/2017
Print ISSN: 2363-7005
Electronic ISSN: 1867-0202
DOI
https://doi.org/10.1007/s12599-016-0450-4

Other articles of this Issue 2/2017

Business & Information Systems Engineering 2/2017 Go to the issue

Catchword

Quantified Vehicles

Research Paper

Service-Channel Fit Conceptualization and Instrument Development

Research Paper

Retained Organizations in IT Outsourcing

Call for Papers

Call for Papers – Issue 5/2018

Editorial

Business Analytics and Data Science: Once Again?

Premium Partner

    Image Credits