Abstract

The realities of the modern trend in which the need for the analysis of data is growing dictate the need for the transformation and modernization of the traditional approaches to developing statisticians, in this regard, the article considers the features of the competency-based approach to the learning and development process.
For the past few years the statistical training institute of the Statistics Centre Abu Dhabi, has been effective in bringing together an array of development interventions to build the capabilities within the government of Abu Dhabi. These interventions varied in process of delivery from online learning, which included synchronous and asynchronous methods, and Instructor-led trainings leading to series internationally recognized certificates from local and international universities.
The pillar role that STI is playing in the transformation to a data-driven public sector necessitated the continuous refinement of this approach in order to achieve several objectives including refining skills, reducing training load, enhance learner experience all while making the learning and development more relevant. This led to the adoption of a new competency-based approach which is further refined to the level of behavior indicators. By applying a systematic framework which describes the required knowledge and skills in specific statistical roles, we are able to evaluate employees’ competence and are able to build modular developmental programs that reduces irrelevant learning, the time required for learning and to increase the time used in applying learning as well as creating an ongoing snapshot of the overall knowledge and skills portfolio of the organization. However, this approach requires the availability of a competency dictionary, well defined job descriptions as well as the continuous revision of these two elements to ensure alignment with the organizational vision, mission and strategic objectives.
This paper describes the process of developing a comprehensive competency framework, job descriptions and modular learning with intermittent testing to ensure learning effectiveness and professional competence.