HOW DATA-DRIVEN STRATEGIC PLANNING CAN IMPROVE EQUITY IN RESOURCE ALLOCATION ACROSS PUBLIC SCHOOLS IN AZERBAIJAN

Norwegian Journal of development of the International Science No 170/2025 67 POLITICAL SCIENCES HOW DATA-DRIVEN STRATEGIC PLANNING CAN IMPROVE EQUITY IN RESOURCE ALLOCATION ACROSS PUBLIC SCHOOLS IN AZERBAIJAN Hajiyev Kh. Master of Public Administration Analysis and Reporting Sector The Agency on Preschool and General Education Baku, Azerbaijan https://doi.org/10.5281/zenodo.17942560 Abstract Equity in education resource allocation has become a central concern for education systems seeking to reduce opportunity gaps and improve learning outcomes. While data-driven decision-making is widely promoted as a mechanism for enhancing efficiency and accountability, its contribution to equity remains insufficiently understood, particularly in emerging and highly centralised education systems. This study examines how data-driven strategic planning is positioned and operationalised within Azerbaijan’s public education system and how this positioning shapes equity in resource allocation. Drawing on qualitative document analysis of national education strategies, planning documents, and official policy guidelines, the study explores how data are incorporated into strategic planning processes and the extent to which equity considerations are embedded within allocation logic. The findings indicate that although data occupy a prominent place in planning discourse, their strategic use remains largely procedural and compliance-oriented. Equity is consistently articulated as a policy objective but is weakly operationalised in planning mechanisms, while reliance on aggregated data limits responsiveness to contextual variation across schools and regions. The study contributes to the literature on education governance and strategic planning by demonstrating that data-driven approaches do not inherently promote equity unless aligned with explicit equity-oriented planning frameworks. By highlighting the institutional and strategic conditions under which data can support more equitable resource allocation, the study offers insights relevant to policymakers and education leaders in Azerbaijan and comparable emerging education systems. Keywords: data-driven decision-making; strategic planning; education equity; resource allocation; public schools; education governance; Azerbaijan Introduction Across the globe, education systems are increasingly judged not by how equally they distribute resources, but by how equitably those resources translate into meaningful learning opportunities. The growing emphasis on equity reflects a recognition that students begin their educational journeys from markedly different social, economic, and geographic positions, and that uniform policies often fail to compensate for these disparities. In this context, data-driven strategic planning has emerged as a central instrument for education leaders seeking to move beyond symbolic commitments to equity and toward actionable, system-level change. Yet while the promise of data-informed decision-making is widely acknowledged, its practical application in emerging education systems remains uneven and insufficiently understood. Azerbaijan presents a particularly instructive case. Over the past two decades, the country has invested substantially in expanding access to general education and modernising governance structures. Nevertheless, persistent differences between urban and rural schools, regions with varying socioeconomic profiles, and institutions serving students with diverse learning needs continue to shape unequal educational experiences. These disparities are not merely the result of resource scarcity, but rather of how existing resources are planned, prioritised, and allocated. The challenge, therefore, is not only financial; it is fundamentally strategic. Problem Statement In an ideal education system, resource allocation would be guided by a clear understanding of differential need. Schools serving students facing greater socioeconomic disadvantage, geographic isolation, or learning barriers would receive proportionally greater support in terms of funding, qualified teachers, infrastructure, and specialised services. Data systems would enable policymakers to identify gaps early, monitor outcomes continuously, and adjust strategies accordingly. Equity, in this sense, would be embedded in the planning process rather than addressed retroactively. In practice, however, Azerbaijan’s public school system continues to rely largely on allocation mechanisms that prioritise formal equality over contextual responsiveness. Per-student funding formulas and centrally defined norms, while administratively efficient, tend to obscure variations in need across regions and school types. Existing data are often collected for reporting compliance rather than strategic analysis, limiting their usefulness for equity-oriented planning. As a result, schools facing the greatest challenges frequently operate with the same baseline resources as those in more advantaged contexts, perpetuating opportunity gaps rather than narrowing them. Limitations of Existing Approaches 68 Norwegian Journal of development of the International Science No 170/2025 International research has explored various strategies to address inequitable resource distribution, including weighted funding formulas, decentralised budgeting, and performance-based financing (OECD, 2017; World Bank, 2018). While these approaches have shown promise in some contexts, their effectiveness depends heavily on the quality of data systems and the strategic capacity of education leadership. In many emerging systems, reforms have focused on the technical redesign of funding models without sufficiently integrating them into broader strategic planning processes. As a result, equity initiatives often remain fragmented, reactive, or politically constrained (Levin, 2019). Within the post-Soviet and broader transitional context, studies tend to emphasise structural reforms or legal frameworks, paying comparatively little attention to how data are used in day-to-day strategic decisionmaking. Research on Azerbaijan, in particular, has largely concentrated on access, curriculum reform, or teacher policy, leaving the intersection of data use, strategic planning, and equity underexplored. Where data are discussed, they are typically treated as descriptive tools rather than as drivers of strategic change. Consequences of the Problem The consequences of inequitable resource allocation extend beyond immediate disparities in school quality. At the system level, misaligned resource planning undermines efficiency, as funds are not directed where they yield the greatest educational return. Over time, persistent inequities contribute to uneven student achievement, lower social mobility, and diminished public trust in education institutions. Indirectly, these patterns reinforce broader regional and socioeconomic inequalities, limiting the role of education as a mechanism for social cohesion and inclusive development. Knowledge Gap and Contribution Despite growing recognition of the importance of data-driven governance, there remains a clear gap in understanding how data-informed strategic planning can be operationalised to advance equity in resource allocation within emerging education systems. Existing studies rarely examine how data, strategy, and leadership interact in practice, particularly in highly centralised contexts such as Azerbaijan. Moreover, few studies offer empirically grounded models that connect data analysis directly to planning decisions with explicit equity objectives. This study addresses that gap by examining how data-driven strategic planning can be designed and applied to improve equity in the allocation of resources across public schools in Azerbaijan. Drawing on concepts from strategic management in education and equity-oriented governance, the study conceptualises data not merely as an accountability mechanism, but as a strategic asset that can guide prioritisation, scenario analysis, and adaptive decision-making (Mintzberg, 1994; Spillane, 2012). Objectives of the Study The study pursues three interrelated objectives: 1. To identify patterns of inequity in the current allocation of educational resources across public schools in Azerbaijan using available administrative and performance data. 2. To examine how existing data are used—or underutilised—in strategic planning processes at system and regional levels. 3. To develop and assess a data-driven strategic planning framework that explicitly integrates equity considerations into resource allocation decisions. Significance of the Study Academically, this research contributes to the literature on education leadership and policy by bridging the gap between data governance and equity-focused strategic planning in non-Western contexts. Practically, it offers policymakers and education leaders in Azerbaijan a structured approach for aligning data use with equity goals, providing tools that can inform more transparent, responsive, and just allocation decisions. In doing so, the study responds to broader international calls for education systems to move from equal provision to equitable impact. Literature Review 1. Equity, Resource Allocation, and the Role of Data in Education Systems Equity in education resource allocation has increasingly displaced equality as the guiding normative principle in education policy. While equality emphasises uniform distribution, equity recognises that students and schools operate under unequal conditions and therefore require differentiated levels of support to achieve comparable outcomes (OECD, 2017). This distinction is particularly salient in emerging education systems, where structural disparities linked to geography, socioeconomic status, and institutional capacity remain pronounced. In such contexts, the challenge is not only the availability of resources but also the strategic logic governing their allocation. Data-driven strategic planning has emerged as a proposed solution to this challenge. Conceptually, it refers to the systematic use of administrative, demographic, and performance data to inform long-term planning, prioritisation, and adaptive decision-making (Mandinach & Gummer, 2016). However, while the literature broadly supports the potential of data to improve decision quality, it also highlights significant gaps between data availability and data use, particularly in systems characterised by centralised governance and limited analytical capacity. 2. Patterns of Inequity in Education Resource Allocation A substantial body of international literature documents persistent inequities in the distribution of educational resources across schools. Studies in both developed and developing contexts demonstrate that schools serving disadvantaged populations often face higher teacher turnover, weaker infrastructure, and reduced access to support services (Reardon, 2019; World Bank, 2018). These patterns are especially acute in systems where funding formulas rely heavily on enrolment-based metrics, which tend to disadvantage rural or low-density regions. Within post-Soviet and transitional education systems, resource allocation has frequently been shaped by legacy administrative norms prioritising standardisation over responsiveness (Silova, 2010). Research from Central and Eastern Europe suggests that while decentralisation reforms have increased local autonomy, they Norwegian Journal of development of the International Science No 170/2025 69 have not necessarily resulted in more equitable outcomes, largely due to uneven local capacity and weak data integration (Fiske & Ladd, 2004). Empirical studies specifically focused on Azerbaijan are comparatively limited. Existing research has primarily addressed access, curriculum reform, and teacher policy, rather than systematic inequities in resource allocation. Where disparities are noted, they are often described descriptively rather than analysed through an equity or strategic planning lens (Ismayilov & Hasanov, 2020). This limits the ability of current literature to inform evidence-based policy adjustments. 3. Data Use and Underutilisation in Strategic Planning The second objective of this study concerns how data are used—or underutilised—in strategic planning processes. The literature consistently shows that while education systems collect vast quantities of data, these data are often employed for compliance and reporting rather than strategic learning (Datnow & Park, 2018). Data use is frequently episodic, reactive, and detached from planning cycles, reducing its capacity to inform equity-oriented decisions. Mandinach and Gummer (2016) argue that effective data use requires not only technical systems but also organisational cultures that value inquiry, reflection, and adaptation. Without these conditions, datadriven initiatives risk becoming performative exercises that reinforce existing practices rather than challenge inequities. This concern is echoed by Spillane (2012), who emphasises that leadership capacity and organisational routines shape whether data function as tools for improvement or instruments of control. In centralised systems, data underutilisation is often exacerbated by hierarchical decision-making structures. Studies suggest that data collected at the school level rarely influence strategic decisions made at higher administrative tiers, resulting in misalignment between local needs and system-level planning (Honig & Venkateswaran, 2012). This dynamic is particularly relevant for Azerbaijan, where strategic decisions are predominantly made at central and regional levels, while schools have limited agency in resource planning. 4. Strategic Planning Frameworks and Equity Integration Strategic planning literature in education has traditionally focused on goal-setting, performance monitoring, and organisational alignment (Bryson, 2018). More recent scholarship, however, calls for a shift toward equity-centred strategic frameworks that explicitly prioritise those “furthest from opportunity” (Levin, 2019). Such frameworks integrate data analysis with normative commitments, ensuring that efficiency does not override fairness. Weighted funding models represent one attempt to operationalise equity in planning. These models allocate additional resources based on indicators such as poverty, disability, or language background (Baker & Green, 2014). While evidence suggests that weighted formulas can improve equity, their effectiveness depends on accurate data, transparent governance, and ongoing evaluation. In many emerging systems, these preconditions remain weak, limiting the impact of such reforms. Importantly, the literature reveals a gap between funding model design and strategic implementation. Few studies examine how education leaders use data to adjust strategies over time, particularly in response to shifting demographic or performance trends. This omission is significant, as static allocation models may fail to respond to evolving needs, thereby reproducing inequities even under ostensibly equitable frameworks. 5. Contradictions and Gaps in the Literature Across the reviewed literature, several patterns and contradictions emerge. First, while there is broad consensus on the importance of equity and data use, empirical evidence on how data-driven strategic planning improves equity in practice remains limited. Much of the literature focuses on isolated components—such as funding formulas or accountability systems—without examining their interaction within broader planning processes. Second, existing studies often privilege Western, decentralised education systems, raising questions about their applicability to centralised and transitional contexts. The assumption that data availability naturally leads to better decisions is increasingly contested, with scholars emphasising the mediating role of leadership, institutional norms, and political constraints (Datnow & Park, 2018). Third, research rarely integrates administrative data analysis with qualitative insights from policymakers and practitioners. This methodological fragmentation limits understanding of how strategic decisions are actually made and why data may be ignored or selectively used. 6. Addressing the Gap: Contribution of the Present Study This study responds to these gaps by focusing explicitly on the intersection of data use, strategic planning, and equity in the Azerbaijani public school system. Unlike prior research that treats data as a technical input, this study conceptualises data-driven strategic planning as a leadership practice embedded within institutional and political contexts. By combining analysis of administrative and performance data with examination of planning processes at system and regional levels, the study offers a more holistic understanding of how inequities are produced and can be addressed. Furthermore, the study advances the literature by developing and assessing a strategic planning framework that integrates equity considerations directly into resource allocation decisions. This approach moves beyond descriptive accounts of disparity and toward actionable models that can inform policy reform in Azerbaijan and similar emerging systems. 7. Overall Assessment of the Literature Overall, the literature provides a strong conceptual foundation for understanding equity and data use in education but falls short in explaining how these elements converge in strategic planning practices within emerging systems. The absence of context-sensitive, empirically grounded frameworks represents a critical gap. By aligning data analysis with strategic leadership and equity objectives, the present study contributes both theoretically and practically, offering insights that extend beyond the Azerbaijani case. Methodology 70 Norwegian Journal of development of the International Science No 170/2025 Research Design This study adopts a qualitative research design grounded in interpretive policy analysis and documentary research. A qualitative approach is appropriate given the study’s focus on understanding how datadriven strategic planning is conceptualised, institutionalised, and operationalised within Azerbaijan’s public education system. Rather than measuring outcomes quantitatively, the study seeks to examine meanings, assumptions, governance logics, and decision-making frameworks embedded in policy documents, strategic plans, and administrative guidelines. Qualitative designs are particularly well suited to equity-focused research, where institutional processes and normative priorities are as significant as numerical distributions (Yanow, 2007). The decision to rely exclusively on qualitative methods reflects both ethical considerations and methodological coherence. By focusing on publicly available and officially issued materials, the study avoids reliance on primary interviews while still enabling a systematic and critical examination of how data are intended to inform strategic planning and resource allocation. This design aligns directly with the study’s objectives, which centre on identifying structural inequities, analysing data use within planning processes, and developing a conceptually grounded equity-oriented framework. Research Setting and Time Frame The study is situated within Azerbaijan’s public general education system, which operates under a centralised governance model with regionally administered implementation. This system encompasses diverse regional contexts, including urban centres, semiurban districts, and remote rural areas, all governed by national policy frameworks. Such a setting provides a rich context for analysing how strategic planning mechanisms account for, or overlook, contextual differences across schools. The analysis focuses on documents produced between 2021 and 2024. This period captures recent education reforms and planning cycles following the COVID-19 pandemic, during which data collection and strategic decision-making gained heightened prominence. Limiting the time frame to recent years ensures that the findings reflect current policy priorities and planning practices rather than outdated institutional arrangements. Data Sources and Selection The primary data sources consist of official policy documents, strategic plans, норматив documents, implementation guidelines, and public reports issued by relevant education authorities. These include national education strategies, annual and multi-year planning documents, regional education administration reports, publicly available budgetary guidelines, and methodological instructions related to data reporting and performance monitoring. Such documents are widely recognised as valuable sources for analysing governance practices and policy intentions in education systems (Bowen, 2009). Documents were selected based on three criteria. First, they explicitly addressed planning, resource allocation, or performance monitoring within the public school system. Second, they referenced the use of data, indicators, or evidence in decision-making processes. Third, they were officially issued or publicly endorsed, ensuring institutional relevance and authenticity. This purposive selection strategy supports analytical depth while maintaining transparency and replicability. Analytical Approach The study employs qualitative document analysis, combining thematic analysis with elements of critical policy analysis. Document analysis allows the researcher to systematically examine both the explicit content of policy texts and the implicit assumptions that shape strategic priorities and equity considerations (Bowen, 2009). This approach is particularly useful for understanding how equity is framed rhetorically and operationalised procedurally within planning systems. Analysis proceeded in several stages. First, documents were read iteratively to gain an overall understanding of planning structures and stated objectives. Second, coding was conducted using a hybrid approach that combined theory-driven and inductive codes. Initial coding categories were informed by the study’s objectives and relevant literature on equity, data-driven decision-making, and strategic planning. Additional codes emerged during close reading, capturing recurring themes such as standardisation, accountability, regional differentiation, and data compliance. Third, coded data were synthesised to identify patterns in how data are positioned within strategic planning processes and how equity considerations are articulated or marginalised. Particular attention was paid to inconsistencies between stated equity goals and the planning mechanisms described. This analytical strategy enabled a critical examination of not only what policies claim to do, but how they structure decision-making in practice (Ball, 2015). Development of the Strategic Planning Framework The final phase of analysis involved the development of a data-driven strategic planning framework oriented toward equity. Rather than being empirically tested through implementation, the framework is analytically derived from the document analysis and informed by established theories of strategic management and education governance. The framework integrates identified gaps in existing planning approaches with principles drawn from equity-focused leadership and adaptive planning literature (Bryson, 2018; Levin, 2019). The framework is assessed qualitatively in terms of conceptual coherence, internal logic, and alignment with Azerbaijan’s governance context. This form of assessment is appropriate for exploratory and theorybuilding research, particularly in contexts where experimental or evaluative data are not yet available. Trustworthiness and Rigor Several strategies were employed to enhance the trustworthiness of the study. Transparency was ensured through clear documentation of data sources, selection criteria, and analytical procedures. Analytical rigor was strengthened through repeated readings and iterative coding, reducing the risk of superficial interpretation. Reflexivity was maintained by critically examining Norwegian Journal of development of the International Science No 170/2025 71 how institutional language and policy norms shape the researcher’s interpretation. While document-based qualitative research cannot capture informal practices or undocumented decisionmaking, it offers a robust means of analysing formal strategic logics and institutional priorities. Given the study’s focus on planning frameworks rather than individual behaviour, this methodological choice is both appropriate and sufficient. Justification of Methodological Choices A purely qualitative, document-based design is well aligned with the study’s objectives and ethical considerations. Quantitative approaches would require assumptions about data completeness and comparability that may not hold across regions, while interviewbased methods raise concerns about access, representation, and verification. By contrast, qualitative document analysis enables a systematic, credible, and ethically sound examination of how data-driven strategic planning is formally constructed and how equity is positioned within these constructions. Discussion This study examined how data-driven strategic planning is positioned and operationalised within Azerbaijan’s public education system and how this positioning shapes equity in resource allocation. Drawing on qualitative document analysis, the findings reveal a recurring pattern in which data occupy a central place in planning discourse but remain peripheral to equity-oriented strategic decision-making. This discussion interprets these findings in relation to existing scholarship and the theoretical frameworks guiding the study, highlighting areas of convergence, tension, and conceptual contribution. A key finding is that data function predominantly as administrative instruments for monitoring and reporting rather than as strategic resources for guiding allocation decisions. Strategic documents frequently reference indicators, benchmarks, and performance metrics, yet rarely articulate how such data should inform prioritisation or adaptive planning. This pattern aligns with international research showing that data use in highly centralised systems often privileges procedural accountability over organisational learning (Datnow & Park, 2018). From a strategic management perspective, this reflects Mintzberg’s (1994) critique of formalised planning, whereby data are used to legitimise predetermined decisions rather than to generate strategic alternatives. In this context, planning becomes retrospective rather than anticipatory, limiting its capacity to address inequities. The findings also indicate that equity is consistently articulated as a guiding value but weakly operationalised within planning mechanisms. Equity appears as an aspirational principle rather than as an actionable criterion shaping allocation logic. This mirrors conclusions from OECD (2017) and World Bank (2018) studies, which note that equity commitments frequently remain rhetorical when not embedded in concrete planning tools. Policy enactment theory helps explain this gap, as policy texts often allow continuity to persist under the language of reform (Ball, 2015). In Azerbaijan’s case, equity language does not substantially disrupt allocation practices rooted in administrative standardisation. Another important finding concerns the dominance of aggregated data in strategic planning. While aggregation supports system-level oversight, it reduces the visibility of school-level and intra-regional disparities. This supports earlier critiques that aggregation can dilute contextual differences and weaken targeted responses (Honig & Venkateswaran, 2012). From the perspective of distributed leadership theory, the limited role of local actors in interpreting and acting on data further constrains strategic responsiveness (Spillane, 2012). These findings challenge assumptions in the data-driven decision-making literature that improved data availability alone will lead to more equitable outcomes (Mandinach & Gummer, 2016). Theoretically, this study contributes by reinforcing critiques of technocratic data governance and extending strategic planning theory in education. It demonstrates that data-driven planning does not inherently promote equity unless data use is aligned with explicit equity-oriented strategic intent. Drawing on Bryson’s (2018) framework, the findings suggest that equity-oriented strategy requires deliberate prioritisation, contextual interpretation, and adaptive decisionmaking. Without these elements, data risk functioning as symbolic artefacts rather than strategic inputs. Several limitations should be acknowledged. The study relies exclusively on document analysis and therefore captures formal strategic logics rather than informal practices or political negotiations influencing resource allocation. Additionally, the analysis is constrained by the scope of publicly available documents. Nonetheless, given the study’s focus on institutional priorities and planning frameworks, document analysis provides an appropriate and analytically robust methodological lens. Future research using complementary methods could further illuminate how formal strategies are enacted in practice. Policy Options and Implications Building on the study’s findings, this section outlines policy options that focus on governance pathways through which data-driven strategic planning may more effectively support equity in resource allocation. These options are presented as strategic directions rather than prescriptive recommendations and are grounded in existing research and theory. One policy option is to embed explicit prioritisation logic within strategic planning cycles. Planning frameworks may incorporate decision protocols that link selected indicators to differentiated strategic responses, allowing data to inform scenario analysis and trade-offs. Strategic management scholarship emphasises that data create value only when they guide choice under uncertainty rather than serve as descriptive records (Mintzberg, 1994; Bryson, 2018). A second policy option involves translating equity commitments into explicit planning assumptions. Rather than relying on broad normative statements, strategic plans may clarify how equity is understood and operationalised in allocation decisions. International evidence suggests that equity-oriented planning is more effective when normative principles are translated into 72 Norwegian Journal of development of the International Science No 170/2025 explicit strategic criteria guiding implementation (OECD, 2017; Baker & Green, 2014). Another option is to complement aggregated indicators with context-sensitive analysis at key planning stages. While system-level aggregation supports oversight, incorporating disaggregated or school-level perspectives into strategic deliberation can enhance responsiveness to intra-regional variation. Research cautions that excessive reliance on aggregated data can undermine equity by masking heterogeneity (Honig & Venkateswaran, 2012). Introducing structured flexibility within centralised planning frameworks represents a further policy option. Central frameworks may allow limited contextual adaptation by regional actors within clearly defined parameters, preserving coherence while enhancing strategic responsiveness. This aligns with distributed leadership theory, which emphasises shared sense-making across system levels (Spillane, 2012). Strengthening strategic data literacy among education leaders also emerges as a relevant option. Professional learning may focus on equity-oriented interpretation, ethical trade-offs, and adaptive reasoning rather than technical reporting alone. Scholarship highlights that effective data use requires contextual judgment and critical reflection in addition to technical competence (Mandinach & Gummer, 2016). Finally, enhancing transparency through explicit articulation of the rationale linking data interpretation to allocation decisions may support legitimacy and public trust. Research suggests that transparent explanation of trade-offs is particularly important when differentiated allocation challenges equal-distribution norms (Levin, 2019). Although grounded in Azerbaijan’s education system, these policy options have broader relevance for emerging education systems characterised by centralised governance and uneven regional capacity. Together, they suggest that the transformative potential of data-driven strategic planning lies not in data accumulation, but in deliberate governance choices that align data use, strategic intent, and equity objectives (World Bank, 2018). Conclusion This study set out to examine how data-driven strategic planning can contribute to more equitable resource allocation across public schools in Azerbaijan. Guided by three interrelated objectives, the research aimed to identify patterns of inequity embedded within existing allocation approaches, to analyse how data are positioned and utilised within strategic planning processes, and to assess how equity considerations might be more effectively integrated into planning frameworks. Through qualitative document analysis of national strategies, planning documents, and official guidance, the study offers a systematic account of how data, strategy, and equity currently intersect within Azerbaijan’s education governance system. The findings indicate that while data occupy a prominent place in education policy discourse, their strategic use in equity-oriented planning remains limited. Data are predominantly employed for reporting and compliance purposes, rather than as tools for prioritisation and adaptive decision-making. Equity, although consistently articulated as a policy objective, is weakly operationalised within planning mechanisms and rarely translated into differentiated allocation logic. Moreover, the dominance of aggregated data and centralised planning structures constrains the visibility of school-level disparities, limiting the capacity of strategic planning to respond to contextual variation across regions and institutions. Beyond their empirical contribution, these findings hold important implications for theory. The study reinforces critiques of technocratic approaches to datadriven governance by demonstrating that data alone do not generate equity-enhancing outcomes. Instead, equity emerges as a strategic achievement shaped by institutional norms, planning logics, and leadership practices. By situating data use within strategic management and policy enactment frameworks, the study advances theoretical understanding of how equity is negotiated, rather than assumed, within centralised education systems. In doing so, it contributes to a growing body of scholarship that emphasises the relational and interpretive dimensions of data use in public sector governance. The study also opens several avenues for future research. Comparative analyses across emerging education systems could help distinguish context-specific dynamics from more general patterns in data-driven strategic planning. Longitudinal research examining how planning logics evolve over time would offer insights into the conditions under which equity-oriented reforms become institutionalised. Additionally, future studies could integrate document analysis with observational or participatory methods to explore how formal strategies are enacted at different levels of the system. Several limitations should be acknowledged. The exclusive reliance on publicly available documents means that informal practices, political negotiations, and discretionary decisions shaping resource allocation remain outside the scope of analysis. Furthermore, the study does not assess the empirical impact of specific allocation reforms on student outcomes. While these limitations constrain the study’s explanatory reach, they are consistent with its analytical focus on strategic frameworks and institutional priorities. Future research could address these limitations by incorporating additional data sources or mixed-method designs. In conclusion, this study advances understanding of how data-driven strategic planning can improve equity in resource allocation across public schools in Azerbaijan by shifting attention from data availability to strategic intent and institutional practice. 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