Approaching the ERP Project Cost Estimation Problem: an Experiment

Abstract

This poster reports on a solution to ERP project cost estimation and on results from its first experimental application. BackgroundEnterprise Resource Planning (ERP) projects have specific context factors, such as reuse levels, interdependent functionality, and use of a vendorspecific implementation methodology, which impose risks known to cause various degrees of project failure. We tackle this issue from a portfolio management perspective. Our solution rests on other authors' work [3] and our experience in ERP requirements engineering [2]. It combines: (i) the COCOMO II reference model [1] which lets ERP adopters account for specific cost drivers, (ii) a Monte Carlo simulation [4] which aids to handling the cost drivers' degrees of uncertainty, and (iii) a probability-based portfolio management concept [5] which lets quantify the chance for success with proposed interdependent deadlines for a set of related ERP projects. The Experimental StudyWe set out to apply our solution approach to reallife ERP project data, in order to learn if bundling ERP projects in a portfolio is advantageous over managing them separately. We call 'advantage' the ability to explicitly and systematically approach ERP context's uncertainty. We assumed that projects, with two different ratings for the same context factor, will differ in probability of success. We proceeded by three steps: First, we modeled the uncertainty of the COCOMO II five scale factors and the 17 cost drivers by means of a probability distribution based on literature sources [3,4] and uncertainty assessments provided by our ERP project stakeholders. Second, we run a Monte Carlo simulation process [4] with the COCOMO II factors and uncertainty values as input. It generated a population mean, standard deviation and confidence intervals. From each uncertain factor, we obtained possible effort and duration estimation values. Third, we applied the effort-and-deadline probability model in[8] to obtain (i) the probability of ERP portfolio's success with the proposed deadlines for each project in our portfolio, and (ii) a set of new deadlines which delivered a fixed probability of success. Our experiment's data came from 13 SAP projects implemented in a telecom service company. Results and Future ResearchOur calculations yielded that, when managing ERP projects as portfolio, the probability of success was 99.11% under effort constraints and 87.76% under time constraints. Next, for each cost driver/scale factor, we constructed two portfolios: the first had this driver/ factor rated 'very high' for all projects and the second had it rated 'very low' for all projects. We observed: (i) 13 out of the 17 drivers could be adjusted in a way that maximized the probability of success; and (ii) the probabilities of success for highly uncertain projects are greater when managed as a portfolio (Table 1) Although, this approach sounds an interesting solution alternative to ERP-adopters, our results are preliminary only and we acknowledge that related validity concerns are our mo...

Cost estimation for cross-organizational ERP projects: research perspectives

“…Although IS researchers have indicated the importance of investigating size/cost relationships in ERP settings, their published works (Daneva 2007;Morrison and Seaver 2007;Seaver 2005;Stensrud and Myrtveit 1998;Stensrud 2001;Stensrud and Myrtveit 2003;Vogelesang 2006) cite business needs in isolation and offer ''solution islands'' requiring theoretical integration in a number of areas. Our review of the literature and practice indicates that it is possible to find arguments which, when assembled, call for an integrated approach to sizing and estimation efforts that ERP adopters should consider in crossorganizational ERP projects.…”

“…Drawing on the early assessments of the authors of (Daneva 2007;Stamelos et al 2003;Stensrud 2001;Stensrud and Myrtveit 2003) and on a wide range of literature, we will, in the research proposed in Sect. 5, experiment with an integrated conceptual framework deploying a variety of models capable of assisting estimators in reflecting on why evaluations provided by one model might differ significantly from evaluations provided by another.…”

“…To the best of our knowledge, however, the suitability of these approaches to cross-organizational ERP projects has not been empirically investigated. A few authors (Stamelos et al 2003;Stensrud 2001;Stensrud and Myrtveit 2003;Daneva 2007) have investigated the applicability of these groups of methods to ERP projects. What Stensrud and Myrtveit found works well in the ERP context is to first use parametric regression models as an effort prediction system, and then to complement this with an analogy-based method for the purpose of exploratory data analysis (Stensrud 2001).…”

“…In our research, we make a conscious effort to fill a noticeable gap in the current discussion on ERP cost functions. Specifically, this means that our integrated approach will: (i) account for the possible changes in terms of coordination processes, business processes, and data handling procedures, and (ii) express them as complexity factors that are to be linked to the size/cost relationship (Daneva 2007;Vogelesang 2006). …”

“…Unlike Stensrud and Myrtveit (Stensrud and Myrtveit 2003), this author treated an ERP implementation as a portfolio of interdependent ERP projects. In this approach (Daneva 2007), the strengths of the three models were complementary: COCOMO II was used to capture some ERP-specific cost drivers, the Monte Carlo simulation was the vehicle selected to handle the degree of uncertainty of these cost drivers, and an effort-and-deadline-probability-based portfolio management model was used to quantify the chance of success with the proposed interdependent deadlines for a set of related ERP projects. Daneva wanted to see if such a combined approach would improve the ability of effort analysts to make sense of the uncertainties in ERP projects that arise due to volatile requirements.…”