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Alignment of planning instruments with the National Strategic Development Plan, in accordance with the results chain


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Added by:   OECD analyst
Added on:   27 Oct 2026
Updated by:   OECD analyst
Updated on:   27 Oct 2026

This initiative uses advanced AI (embeddings, FAISS and OpenAI) to align SINAPLAN instruments with the National Development Strategic Plan (PEDN). By analysing 27 national objectives against 43 public policies, it detects gaps and misalignments within the results chain. This ensures State actions respond to strategic priorities, strengthening evidence-based decision-making and public value generation through coherent national planning.

Name in original language

Articulación de los instrumentos del planeamiento con el Plan Estratégico de Desarrollo Nacional, conforme a la cadena de resultados

Initiative overview

The initiative involves using artificial intelligence tools to analyse and align the Peruvian State's planning instruments within the SINAPLAN framework, in accordance with the results chain established in the Guide for Institutional Planning. 

According to the regulatory framework, policies and plans must be vertically aligned to implement the national objectives of the National Strategic Development Plan (PEDN), which embodies the country's strategic development priorities and guides State action. However, in practice, this alignment is not always systematically verified or based on evidence. 

To address this challenge, a methodology was developed that combines semantic embeddings, vector indexing (FAISS), re-ranking and structured validation using advanced language models (OpenAI API). This identifies levels of alignment between: Objectives and Strategic Actions of the PEDN (27 Strategic Objectives and 163 Strategic Actions); and Priority Objectives of the 43 National Policies approved as of 2025 (209 Priority Objectives).

The tool enables the detection of clusters, gaps and potential misalignments between strategic instruments, ensuring that National Policies—and progressively, other planning instruments—effectively respond to the priorities defined in the PEDN. This strengthens the coherence and effectiveness of national planning, directly impacting the quality of public policy monitoring and evaluation, evidence-based decision-making and the State's capacity to direct its interventions towards the effective achievement of national priorities and the generation of public value.

Results, outcomes and impacts

The benefits of the AI initiative are: 

a. Systematic and Visual Identification of the level of alignment between the PEDN (Strategic National Development Plan) and National Policies. 

b. Detection of Strategic Actions with low levels of implementation within National Policies (indicating potential implementation gaps, insufficient programmatic alignment or the need to strengthen interventions to ensure consistency with national priorities). 

c. Identification of Priority Objectives with high thematic concentration. 

d. Significant Reduction in Time required for manual comparative analysis, transforming a process that previously took approximately three months into one that can be completed in about three weeks.

Other relevant details

Challenges and lessons learned: The main challenges in implementing the AI initiative are: a. Massive volume of POs and SAs (Priority Objectives and Strategic Actions) in separate databases without sectoral or thematic alignment. b. Diverse alignment scenarios between the analysed databases. c. Semantic ambiguity and breadth in regulatory and strategic texts. d. Structural and drafting differences among various planning instruments. e. Risk of false positives in automated similarity matching, which necessitated the use of multiple AI tools for more rigorous analysis, as well as programming expertise to enhance process precision. f. Need to ensure governance and specialised human oversight throughout the process to guarantee appropriate linkage between instruments. g. Institutional adaptation to the use of artificial intelligence tools for strategic analysis.

About the policy initiative


Category:

  • AI policy initiatives, programmes and projects

Initiative type:

  • AI use cases/projects in the public sector

Status:

  • Active

Start Year:

  • 2025

Target Sectors:


OECD AI Principles:

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Other relevant urls:

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