Approaches to Statistical Capacity Development in Myanmar Than Zaw Deputy Director General Central Statistical Organization

Part 1: Background Past situation of statistical capacity building initiatives in Myanmar’s NSS

Situation in the past Many different statistical training initiatives across statistical units of the NSS Not harmonized or coordinated Often ad-hoc and focused on specific statistical tasks  Resulted in very different level of capacities across the NSS, and this impeded cooperation within NSS

Assessments Various assessments and peer reviews of the National Statistical System (NSS) identified lack of systematic and continuous professional training for government statisticians as one of the key hindrances of statistical development.

New National Strategy for Development of Statistics NSDS acknowledges this and incorporates operational target: “training needs assessment conducted and training program for government statisticians developed”.

New Statistics Law Approved by Parliament October 25, 2017 New Statistics Law also acknowledges this and assigns the Central Statistical Organization (CSO) the responsibility to “upgrade statistical skills and competencies of staff engaged in statistical activities across the National Statistical System of Myanmar”.

Part 2: Recent initiatives Steps taken by CSO to improve the situation

Training Needs Assessment Started with comprehensive assessment of training needs across the NSS. Approach from two angles: interviewing statistical unit management about their needs but also individual-level testing of staff competencies (very different results!). Key findings: Need for more systematic and harmonized training across NSS Past training initiatives’ effectiveness and hindered by lack of common set of basic competencies of NSS staff  important to focus on this level first to make all statistical work and training more effective Also need to build skills of data users

Development of statistical training curriculum 29 course modules across 3 different certification levels for NSS statisticians: Level 1 focusses on basic competencies Level 2 focuses on core technical skills Level 3 focuses on advanced technical skills Course module for data users Seminar series: One for members of the NSS to present their recent work and achievements One for visiting international experts and NSS members that attended international conferences to share latest international trends and developments

Setting up Statistical Training Centre Delivering the training curriculum for the NSS New dedicated training annex constructed recently 1 main training room, 1 seminar room, 1 computer lab Dedicated training centre staff

Part 3: Lessons learnt Sharing of lessons learnt that may be of interest to other countries

What makes capacity development (CD) programmes successful? Conduct comprehensive training needs assessment first to know the full situation. Approach assessment from two angles, top-down and bottom-up. (If asked, statistical units will often request the most advanced trainings, “we need multivariate regression analysis training”, whereas staff may require basic competencies without which advanced training cannot be effective.) Based on needs assessment, tailor CD programme to specific context. Take existing recurring trainings into account to avoid overlap of certification systems. Include data users in statistical capacity development programmes if possible. Try to build communities of practice (e.g. seminar series). Move away from ad-hoc, donor-driven CD to systematic and harmonized CD across the NSS.

How can partnerships support the development of national statistics? Partnership with data producers of the NSS is important to ensure CD programme delivers to real needs and that there is NSS-wide buy-in to a programme. Partnership with data users is important. They need statistical capacity development, too. Partnership with Development Partners can help to start up a systematic CD programme, but the programme should be designed to run independently by the CSO/NSS in the medium term. Partnership with statistical training institutions outside the NSS is important to exploit synergies. However, academic training and professional training often requires very different approaches and content.

How do you prioritise between national statistical needs and international requirements? Prioritization should happen before the Capacity Building stage, so ideally not a problem when designing CD programmes. Prioritization of data needs Data production and analysis Data dissemination Data use Capacity Development for data producers Capacity Development for data users

Looking forward to closer cooperation in the statistical field!