Software Project Estimation Errors in Traditional SDLC Models

Abstract

Software project estimation errors are common in traditional SDLC models where cost, schedule, effort, resources, and delivery scope are planned early in the project lifecycle. In enterprise software projects, inaccurate estimation can lead to schedule delays, budget overruns, resource shortages, reduced quality, and pressure on development and testing teams. This article discusses how estimation errors occur due to incomplete requirements, weak historical data, unrealistic assumptions, changing scope, poor risk analysis, and limited understanding of system complexity. It explains the role of effort estimation methods, work breakdown structures, function points, lines of code, productivity rates, milestone planning, and variance tracking in improving estimation accuracy. The article also highlights common challenges such as stakeholder pressure, underestimated testing effort, integration complexity, delayed defect correction, and poor change control. A structured estimation review approach is presented to improve planning accuracy, support early risk identification, and strengthen project monitoring. The study concludes that effective management of estimation errors improves project predictability, reduces cost and schedule deviation, and supports controlled delivery in traditional SDLC-based enterprise software projects.