Contributions of Information Technology Tools to Project's Accounting and Financing
Bibliographic record
Abstract
“According to the Standish Group CHAOS Report 2003, each year in the USA there are approximately 175,000 projects in IT application development that spends $250 Billion. Among these, 31.1% of projects will be cancelled, 52.7% of projects will cost 189% of their original estimates, only 52% of required features and functions make it to the released product, and time overruns occur in 82% of the cases. In financial terms $55 billion dollars is wasted in these projects.” (Madpat, 2005). This chapter suggests an innovative platform to analyze software projects in order to overcome the difficulties that are shown through the statistics. The first layer of the platform is based on costing theories in order to handle the cost overruns. At the second layer are the project management tools, and on the third layer is the software engineering. The last two layers give the needed information on the project scope and the development efforts. Connecting those three layers gives a better perspective on the projects, which is the best platform for decision making. Cost management of a project is defined by the PMBOK (project management body of knowledge) (PMI, 2004) as one of the nine core activities of projects management. This activity is defined as an assembly of processes that include planning, estimating, budgeting, and controlling of project costs so that the process will be executed within the budget framework that has been designated for it. However, although it defines costing as a core activity, it does not provide the methodologies for the application mode of the costing (Kinsella, 2002). The challenge in project management is described as “the effective allocation of resources within the framework of time, cost and delineation constraints that are balanced against the quality demands and nature of relations with the customer” (Kerzner, 2003. p.5). Hence, cost management should be viewed as part of the project management challenge. Software projects can be analyzed through software engineering tools, CASE (computer-aided software engineering tools), that assist in the analysis and characterization of the software project and in the evaluation and measurement of the work productivity in the project. Cooper and Kaplan (1998) analyze the integration between costing systems and operational systems. The integration that Cooper and Kaplan introduce, like the classic costing methods, does not provide a response to the project structure and the features of a software project (such as estimation difficulties, risk management, and lifecycle). This chapter recommends integrating costing systems and operational systems of software projects; the projects management tools and the software engineering tools.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.026 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".