Archive for the ‘Project Selection’ Category

A comprehensive model for selecting information system project under fuzzy environment (Chen & Cheng, in press)

Dienstag, Oktober 7th, 2008

A comprehensive model for selecting information system project under fuzzy environment (Chen & Cheng, in press)Chen, Chen-Tung; Cheng, Hui-Ling: A comprehensive model for selecting information system project under fuzzy environment; in: International Journal of Project Management, in press.doi:10.1016/j.ijproman.2008.04.001Update: this article has been published in:  International Journal of Project Management Vol. 27 (2009), No. 4, pp. 389–399.Upfront management is an ever growing body of research and currently develops into it’s own profession. In this article Chen & Cheng propose a model for the optimal IT project portfolio selection. They outline a seven step process from the IT/IS/ITC project proposal to the enterprise success

  1. IS/IT/ITC project proposal
  2. Project type classification
  3. Individual project analysis
  4. Optimal portfolio selection
  5. Portfolio adjustment
  6. Successfully selection
  7. Enterprise success

Behind the process are three different types of selection methods and tools – (1) crisp selection, (2) strategy development, and (3) fuzzy selection.The crisp selection is the first step in the project evaluation activities. It consists of different factual financial analyses, e.g. analysis of discounted cash flow, cost-benefits, total investment, payback period, and the return on investment.Strategy development is the step after the crisp selection, whilst it also impacts the first selection step by setting guidelines on how to evaluate the project crisply. Strategy development consists of a project strategic status analysis. According to Chen & Cheng’s framework a project falls in one of four categories – strategic, turnaround, factory, or support.The last step is the fuzzy selection. In this step typical qualitative characteristics of a project are evaluated, e.g., risk, feasibility, suitability, and productivity improvements. In this step lies the novelty of Chen & Cheng’s approach. They let the evaluators assign a linguistic variable for rating, e.g., from good to poor. Then each variable is translated into a numerical value, e.g., poor = 0, good = 10. As such, every evaluator produces a vector of ratings for each project, e.g., (0;5;7;2) – vector length depends on the number of characteristics evaluated. These vectors are then aggregated and normalised.[The article also covers an in-depth numerical example for this proposed method.]

Enterprise information system project selection with regard to BOCR (Liang & Li, in press)

Dienstag, September 23rd, 2008

 Enterprise information system project selection with regard to BOCR (Liang & Li, in press)

Liang, Chao; Li, Qing: Enterprise information system project selection with regard to BOCR; in: International Journal of Project Management, Article in Press, Corrected Proof
http://dx.doi.org/10.1016/j.ijproman.2007.11.001

Lots of consultants earn their money with selecting the right IT system. I have seen the most bizarre total-cost-of-ownership (TOC) calculations to get to it and witnessed the political madness which comes with buying-center decisions in never ending rounds of assessment workshops.

Liang & Li claim that „a comprehensive and systematic assessment is necessary for executives to select the most suitable project from many alternatives.“ Furthermore they claim that „This paper first proposes a decision method for project selection.“ However, the authors apply a analytical hierarchy/network process (AHP/ANP) to this decision-making predicament. They suggest breaking down the decision unsing their mulit-criteria BOCR framework, with the dimensions of benefits (B), opportunities (O), costs (C), and risks (R).

In the case of an manufacturing system, described in that article, the benefits consist of time gained, costs saved, service improvements, capacity increase, and quality improvements. The opportunities are an increased market share, fast ROI and payback period, and the ability for agile manufacturing. The risks associated with this MES are budget overruns, time delays, and several technological risks, e.g., reliability, flexibility, ease of use. Lastly Liang & Li break down the costs into software, implementation, taining, maintenance, upgrade, and costs for existing systems.

An Empirical Assessment of IT Project Selection and Evaluation Methods in State Government (Rosacker & Olson, 2008)

Mittwoch, August 13th, 2008

IT Project Selection Tools

Rosacker, Kirsten M.; Olson, David L.: An Empirical Assessment of IT Project Selection and Evaluation Methods in State Government; in: Project Management Journal, Vol. 39 (2008), No. 1, pp. 49–58.

Do project selection tools have an impact on project success? In order to answer this question Rosacker & Olson look into the usage of different quantitative and qualitative selection tools. As second step they try to link the tools to different success criteria.
Within their sample of 144 public IT projects (all in different U.S. states) the authors can only show limited correlations, using the F-Value [I don’t know about the distribution of the success variables, but if it isn’t normally distributed, the F-Test might have been to conservative and some effects which exist in real life, a classical example for the Type-2 Error or β-error].

  • NPV/IIR selected projects perform better in cost adherence
  • Projects selected based on ‚probability of completion‘ have a better overall performance
  • Projects selected due to ‚mandatory requirements‘ have a better overall performance
  • Projects selected with ’subjective assessment‘ perform better on their impact but perform weaker

A Framework for the Life Cycle Management of Information Technology Projects – ProjectIT (Stewart, 2008)

Donnerstag, Juli 17th, 2008

 ProjectIT

Stewart, Rodney A.: A Framework for the Life Cycle Management of Information Technology Projects – ProjectIT; in: International Journal of Project Management, Vol. 26 (2008), pp. 203-212.

Stewart outlines a framework of management tasks which are set to span the whole life cycle of a project. The life cycle consists of 3 phases – selection (called „SelectIT“), implementation (called „ImplementIT“), and close-out (called „EvaluateIT“).

The first phase’s main goal is to single out the projects worth doing. Therefore the project manager evaluates cost & benefits (=tangible monetary factors) and value & risks (=intangible monetary factors). In order to evaluate these the project manager needs to define a probability function of these factors for the project. Then these distribution functions are aggregated. Stewart suggests using also the Analytical Hierarchy Process Method (AHP) and the Vertex method [which I am not familiar with, neither is wikipedia or the general internet] in this step. Afterwards the rankings for each project are calculated and the projects are ranked accordingly.

The second phase is merely a controlling view on the IT project implementation. According to Stewart you should conduct SWOT-Analyses, come up with a IT diffusion strategy, design the operational strategy, some action plans on how to implement IT, and finally a monitoring plan.

The third stage („EvaluateIT“) advocates the use of an IT Balanced Score Card with 5 different perspectives – (1) Operations, (2) Benefits, (3) User, (4) Strategic competitiveness, and (5) Technology/System. In order to establish the Balanced Score Card measures for each category need to be defined first, then weighted, then applied and measured. The next step is to develop a utility function and finally overall IT performance can be monitored and improvements can be tracked.