Size does matter. Say goodbye to your sizing estimation woes with package points
Today many organizations undertake IT-enabled transformation programs or enterprise resource planning (ERP) implementations to drive business, increase profitability, and enhance operational efficiency. The nature of these programs is such that their success or failure can have a direct impact on the company's financial performance. These programs are often built with off-the-shelf application packages; but there is no industry standard to measure the size of these package implementations. Further, in enterprise solutions projects, estimating the effort in package implementation with reasonable accuracy is crucial since inaccurate estimation results in substantial time and cost escalation.
Estimation for such projects is a major challenge in the absence of a well-established and scientific framework or an industry benchmark. Moreover, due to the inherent nature of work involved in package implementation, universally accepted techniques such as Lines of Code and Function Points cannot be applied to derive an effort estimate.
Infosys Package Points, a patent-pending solution, is a methodology for package implementation sizing that helps enterprises derive consistent and repeatable estimates. Our methodology helps in estimating the size of an implementation project in terms of 'Package Points,' based on factors like solution size, tasks, and complexity.
Based on our Package Points methodology, we have designed the Enterprise Solution Package Implementation (ESPI) sizing tool. Developed with the Oracle eBusiness suite of products, the tool makes an implementation predictable, resulting in better accuracy in terms of effort estimation. In addition, it improves customer confidence in project estimates.
Watch our expert speak about Package Points methodology
There are several challenges in estimating the package implementation size when trying to execute your ERP projects within the budget and deadline. Critical aspects, such as the scope, tasks, and complexity of the project, should be taken into account to define a scientific methodology that will lead to consistent implementation.