An empirical validation of software cost estimation models
Communications of the ACM
Software engineering metrics and models
Software engineering metrics and models
Function point analysis
Estimation of information systems development efforts: a pilot study
Information and Management
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
An assessment and comparison of common software cost estimation modeling techniques
Proceedings of the 21st international conference on Software engineering
Function point analysis: measurement practices for successful software projects
Function point analysis: measurement practices for successful software projects
Software Engineering Economics
Software Engineering Economics
Experience With the Accuracy of Software Maintenance Task Effort Prediction Models
IEEE Transactions on Software Engineering
Quantifying the value of IT-investments
Science of Computer Programming
Software Measurement and Estimation: A Practical Approach (Quantitative Software Engineering Series)
Software Measurement and Estimation: A Practical Approach (Quantitative Software Engineering Series)
Estimating Software Costs
Software Estimation: Demystifying the Black Art
Software Estimation: Demystifying the Black Art
A General Empirical Solution to the Macro Software Sizing and Estimating Problem
IEEE Transactions on Software Engineering
Quantifying the yield of risk-bearing IT-portfolios
Science of Computer Programming
Quantifying IT estimation risks
Science of Computer Programming
Quantifying IT forecast quality
Science of Computer Programming
Software Estimation Best Practices, Tools & Techniques: A Complete Guide for Software Project Estimators
The Rise and Fall of the Chaos Report Figures
IEEE Software
The IT Measurement Compendium: Estimating and Benchmarking Success with Functional Size Measurement
The IT Measurement Compendium: Estimating and Benchmarking Success with Functional Size Measurement
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This article discusses how to quantify the forecasting quality of IT business value. We address a common economic indicator often used to determine the business value of project proposals, the Net Present Value (NPV). To quantify the forecasting quality of IT business value, we develop a generalized method that is able to account for asymptotic cases and negative valued entities. We assess the generalization with real-world data of four organizations together consisting of 1435 IT assets with a total investment cost of 1232+ million Euro for which 6328 forecasts were made. Using the generalized method, we determine the forecasting quality of the NPV, along with the benefits and cost using real-world data of another 102 IT assets with a total business value of 1812 million Euro. For the real-world case study, we will find that the quality of the forecasted NPVs is lower than the forecasted benefits, which is again lower than the forecasting quality of the cost. Also, we perform a sensitivity analysis to investigate the impact on the quality of an asset's forecasted NPV when the forecasting quality of benefits or cost improves. Counterintuitively, it turned out in this case study that if the quality of cost forecasts would improve, the overall quality of its NPV predictions would degrade. This underlines the importance of both accurate cost and benefit predictions. Finally, we show how to use the quantified forecast information to enhance decision information using two simulation examples.