Transitioning to Agile: A Framework for Pre-adoption Analysis using Empirical Knowledge and Strategic Modeling
Notice bibliographique
Résumé
Transitioning to the Agile style of software development has become an increasing phenomenon among software companies. The commonly perceived advantages of Agile, such as shortened time to market, improved efficiency, and reduced development waste are among key driving motivations of organizations to Agile. Each year a considerable number of empirical studies are being published, reporting on successful or unfavorable outcomes of enacting Agile in various organizations. Reusing this body of knowledge, and turning it into a concise and reachable source of information on Agile practices, can help many software organizations which are at the edge of transition to Agile, dealing with the uncertainties of such a decision. \nOne of the early steps of transitioning to Agile (or any other process model) is to confirm the adaptability of new process with the current organization. Various Agile adoption frameworks have proposed different checklists to test the readiness of an organization for becoming Agile, or to identify the required adaptation criteria. Transitioning to Agile, as a significant organizational initiative, is a strategic decision, which should be made with respect to key objectives of the target organization. Having a reliable anticipation of how a new process model will impact the strategic objectives helps organizational managers to choose a process model, which brings optimum advantage to the organization. \nThis thesis introduces a framework for evaluating new Agile practices (compartments of Agile methods) prior to their adoption in an organization. The framework has two distinguishing characteristics: first, it acts strategically, as it puts the strategic model of organization at the center of many decision makings that should be performed during Agile adoption; and second, it is based on a repository of Agile practices that allows the framework to benefit from the empirical knowledge of Agile methods, in order to improve the reliability of its outcomes. This repository has been populated through an extensive literature review of empirical studies on Agile methods. \nThe framework was put in practice in an industrial case, at one of the R&D units of Ericsson Company in Italy. The target R&D unit was proposed with a number of Agile practices. The application of framework helped R&D unit managers to strategically decide on the new process proposal, by having a better understanding of its strategic shortcomings and strengths. A key portion of frameworkâs analysis results were evaluated one year after the R&D unit made the transition to Agile, showing that over 75% of pre-adoption analysis results came to reality after the enactment of new process into the organization.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
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