Customization effort estimation of Microsoft ERP projects

Abstract

Abstract The enterprise resource planning (ERP) software market is rapidly growing due to its potential in aiding organizations to streamline their business processes and enhance workforce productivity. However, ERP customization projects often encounter delays in schedules and exceed budgets mainly because estimations of project customization effort and duration are typically carried out using ad-hoc methods. This study aims to construct and validate a customization effort estimation (CEE) model tailored for ERP projects employing Microsoft Dynamics 365 (D365) customization. To achieve this, six critical factors that impact CEE in D365 projects are identified. Subsequently, an industry-wide survey is conducted to determine the relative significance of these factors and to establish their weights for both simple and complex variants. The proposed model D365CustomizePro is created through the application of stepwise multiple linear regression and then validated through the leave-one-out cross-validation technique based on data collected from 21 real-life D365 projects undertaken at a software house. The estimation accuracy of D365CustomizePro is compared with the estimation accuracy achieved by using two different well-known effort estimation techniques, i.e. expert judgment and COCOMO II (algorithmic estimation model). Results reveal that D365CustomizePro exhibits better estimation accuracy vis-á-vis both expert judgment and COCOMO II.