Évaluation et amélioration du rendement de la formation en entreprise : vers une démarche basée sur la gestion des processus d’affaires
Training is a key strategy to develop employees’ skills. Businesses continue to invest in training and development, but they rarely have data to evaluate the results of this investment. Most companies use the Kirkpatrick/Phillips model to evaluate the training. However, it emerges from the literature that companies have difficulties in using this model. There are three main barriers to the evaluation of training. The first barrier is the difficulty of isolating learning as a factor that affects the results. Another barrier is the lack of a useful assessment IT tool with the learning management system and the third barrier is the lack of standardized data to compare various learning functions. In this thesis, we propose a model to manage training projects in enterprises (Analysis, Modelling, Monitoring and Optimization - AM2O), based on Business Process Management (BPM). Such a scenario considers the training activities as business processes. Our model is inspired by the BPM method through the definition and monitoring of performance indicators for managing all aspects of training. It is based on the analysis and modeling of training needs to ensure alignment between training activities and business objectives. It allows the monitoring of training projects as well as the calculation of tangible and intangible benefits (without additional cost). In addition, it allows us to classify training projects according to criteria relative to the enterprise. Thus, our approach could be used to optimize the yield of the training through a series of simulations using the machine learning algorithms logistic regression, neural network and co-training. Finally, we develop an IT tool, Enterprise Training Programs Evaluation and Optimization System - ETREOSys, to manage training programs in enterprises and for decisionmaking support. ETREOSys is aWeb platform which uses cloud services such as virtual machines, data centers, Content Delivery Network and NoSQL databases. AM2O and ETREOSys resolve the main problems related to the management and evaluation of training in enterprises namely: the difficulty of isolating the effects of training and the lack of IT tools.
Monitoring Evaluation Organizational learning Business analysis Modelling Monitoring Assessment Optimization Machine learning algorithms