I. Background

Inequalities are widening across Asia and the Pacific, not only in terms of income and wealth, but also for opportunities and services, such as education, health and employment despite their guarantee by international legal and normative frameworks on human rights. Children, women, youth, older persons, persons with disabilities, migrants, and minority groups are often disproportionately affected. They also are disproportionately vulnerable to climate change, economic shocks, and health crises. In the face of new and emerging risks, countries in Asia and the Pacific need to accelerate policy action to tackle poverty and inequality through evidence-based and inclusive policies. This is crucial for delivering on the Leave No One Behind (LNOB) pledge of the 2030 Agenda on Sustainable Development.

To accelerate policy action and achieve positive impact, countries should use data and rigorous methodologies to design inclusive and evidence-based policies. As a first step, they must identify populations in vulnerable situations across specific sectors and locations. This requires disaggregated data analysis to identify who is excluded or discriminated against and capture intersecting vulnerabilities along age, gender, disability, and location among others. While an increasing number of countries are generating LNOB evidence and including them in their Voluntary National Reviews (VNR) to track progress in SDGs, there is a need to actively use LNOB evidence in policy and programme design as well as national development plans. Moreover, it would be ideal to use innovative digital tools and technologies to demonstrate LNOB evidence in a user-friendly and accessible manner to wider public.

Against this background, ESCAP developed a technical assistance project entitled “Innovative and digital technologies for inclusive policymaking that leaves no one behind in Asia and the Pacific” to respond to the need for more detailed and policy-specific in-depth analysis in five target countries, including Indonesia. The project, to be implemented in 2026-2029 period, aims to strengthen capacity among target countries to inform their national policies with LNOB evidence thereby contributing to inclusive and evidence-based national policies and plans from design phase to monitoring and evaluation phase. Accordingly, the project will build capacity among policymakers and technical specialists to actively use scientific methodologies and digital tools that analyze and disaggregate nationally appropriate data and present evidence online or offline in a customizable and visually accessible manner. ESCAP’s LNOB Platform and methodology will be actively used throughout this project featuring more results from alternative data sources from Indonesia.

One of the key outputs of this project in Indonesia is to integrate the ESCAP LNOB analysis and evidence into the national SDG Dashboard which is developed and maintained by the SDG Secretariat at the Ministry of National Development Planning (BAPPENAS) with the support of United Nations Children’s Fund (UNICEF) and the United Nations Resident Coordinator’s Office (RCO). In this context, ESCAP has provided technical assistance to Indonesia throughout 2026 in terms of generating preliminary analysis and delivering a virtual capacity-building workshop to review the methodology and preliminary analysis. This work has exclusively relied on 2024 editions of SUSEANS and SAKERNAS. Since the 2025 editions of these rich surveys became recently available, the SDG Sekretariat requested ESCAP to provide a two-day in-person technical capacity-building workshop so that statisticians and technical specialists in Indonesia could independently carry out the LNOB analysis with the latest available data. The final results from this engagement will be featured in the SDG dashboard in early November 2026 and inform policy discussions during the the inception meeting of ESCAP’s technical cooperation project in late November 2026. This two-day technical capacity-building workshop is being organized by the SDG Sekretariat with the generous financial support of UNICEF Indonesia and coordination from RCO.

II. Meeting Objectives

The technical capacity building workshop introduced a supervised machine learning algorithm, which forms the basis of ESCAP LNOB methodology, and build local capacity to run the algorithm independently using the latest available survey data. In this way, the workshop participants generated LNOB evidence through hands-on group work using the latest available SUSENAS and SAKERNAS and prepared final inputs to be presented at the national SDG Dashboard. The workshop also provided an opportunity to discuss the way LNOB evidence should be featured in the SDG dashboard and explored long-term standard operating procedure for regularly updating the evidence at national and provincial levels

The workshop helped participants:

1. understand how the ESCAP LNOB algorithm works in action with nationally representative household surveys with a specific emphasis on SDG indicators;

2. improve their data analysis and visualization skills using a new machine learning algorithm using an open-source statistical software programme;

3. generate tailored and up-to-date LNOB evidence by disaggregation SDG indicators at national and provincial levels across Indonesia;

4. explore short-term and long-term solutions to featuring regularly updated LNOB evidence in the SDG Dashboard.

III. Target Audience

The technical capacity building workshop convened 30 participants targeting statisticians and technical specialists targeting BAPPENAS and BPS along with colleagues from the United Nations Country team including UNICEF and UN RCO. 

IV. Organization and Participation

The technical workshop was organized in person at ibis Styles Bogor Pajajaran in Bogor on 6-7 October 2026 with the generous financial support of UNICEF. The meeting was conducted in English with interpretation to Bahasa.