Methodological Framework to Guide the Development of Continual Evolution Methods - SIGMA
Chapitre D'ouvrage Année : 2019

Methodological Framework to Guide the Development of Continual Evolution Methods

Résumé

Companies live in a fast-changing environment imposing to constantly evolve in order to stay competitive. Such an evolution is carried out through continuous improvement cycles or radical changes often based on innovation that concern their products, their processes, their internal organization, etc. We refer to this situation as continual evolution. There are two implications of such continual evolution from our viewpoint: (a) the instillation of the “no end point” philosophy in organizations and (b) the use of methods based (1) on continual evolution cycles (by opposition to project-based approaches that have delimited budget and dates) and, (2) on autonomous and collective implication of the organization’s actors. This article presents a methodological framework, called As-Is/As-If framework to support method engineers in handling such continual evolution. The framework offers a process model and a product meta-model that are both reusable instruments, aiming to guide the construction of continual evolution methods. The process model and product meta-model can be seen as prototypical examples to be adapted in each situation at hand using heuristics proposed as part of the framework. The usefulness of the framework is illustrated through two methods adaptations
Fichier principal
Vignette du fichier
AsIs-AsIf_Caise19_Cela et al_authorVersion.pdf (1.13 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-02059792 , version 1 (22-06-2021)

Identifiants

Citer

Ornela Çela, Mario Cortes-Cornax, Agnès Front, Dominique Rieu. Methodological Framework to Guide the Development of Continual Evolution Methods. Paolo Giorgini; Barbara Weber. Advanced Information Systems Engineering. 31st International Conference, CAiSE 2019, Rome, Italy, June 3–7, 2019, Proceedings, 11483, Springer, pp.48-63, 2019, Lecture Notes in Computer Science, 978-3-030-21290-2. ⟨10.1007/978-3-030-21290-2_4⟩. ⟨hal-02059792⟩
161 Consultations
241 Téléchargements

Altmetric

Partager

More