The World Bank Group considers itself a “Knowledge Bank.” It pursues its vision of a world free of poverty on a livable planet by supporting developing countries with funding and knowledge. Since the 1990s, it has increasingly cast itself as a Knowledge Bank, even more so than as a lending institution. The World Bank’s knowledge work contributes to development outcomes both by informing clients in various policy and reform areas and by informing staff and clients on the selection, design, and implementation of lending operations.

The Bank Group’s knowledge work has strengths and limitations. External assessments, client surveys, and Independent Evaluation Group (IEG) reports consistently show that member countries and development partners value the depth and breadth of the World Bank’s knowledge work. However, client surveys highlight a gap in tailoring its knowledge to country contexts (figure 1.1). Moreover, the World Bank’s lending delivery model does not readily support projects’ adaptation and course corrections to circumstances that emerge during implementation (World Bank 2019a, 2020b). The transaction costs of designing solutions from the best available evidence remain high, which is part of a bigger limitation—namely, that the World Bank does not systematically and consistently learn from its own projects and programs (World Bank 2016, 2020d; World Bank Group 2021). A Knowledge Bank’s greatest asset is its ability to embed, create, and share knowledge. The World Bank achieves this but has room to improve the methods, predictability, and consistency with which it does so, as discussed in Realizing the World Bank Group’s Knowledge Potential for Effective Development Solutions: A Strategic Framework (World Bank Group 2021).

Over the years, the World Bank has sought to improve its approach to being a Knowledge Bank. These efforts focused on two themes. First, the World Bank optimized its organizational structure to remove the geographical silos that impeded the flow of knowledge. There have been various initiatives, including more recently in 2014 with the creation of Global Practices (GPs). These GPs were designed to provide globally integrated technical knowledge and oversee various mechanisms to move staff and knowledge across countries. The World Bank revised the GP model in 2019 and 2020 by moving most GP staff to the Regions. Second, the World Bank enacted strategies, action plans, mechanisms, and incentives to better carry out its knowledge mandate. Two prominent recent initiatives demonstrate this. The 2021 Strategic Framework for Knowledge aimed to improve the Bank Group’s knowledge contributions by adjusting its knowledge systems, creating staff incentives, and enhancing staff expertise through hiring practices and other means (World Bank Group 2021). Similarly, the 2024 Knowledge Compact for Action is part of a larger Bank Group reform known as the evolution (World Bank Group 2023). This Knowledge Compact emphasizes using new technologies to deliver knowledge to clients with greater speed, quality, and impact (World Bank Group 2024). It proposes specific changes to the Bank Group’s knowledge products, processes, budgeting, systems, partnerships, and capacity building.

Figure 1.1. Regional Results of the Two-Minute Client Survey

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Figure 1.1. Regional Results of the Two-Minute Client Survey

Source: Independent Evaluation Group, based on the two-minute client surveys the World Bank does for all lending projects.

Note: The number of projects in the sample is 1,374 for country context question and 1,378 for global expertise question. The data are for projects approved during FY14–23.

Four issues affected the World Bank’s past efforts to improve the Knowledge Bank. First, senior management largely left decisions about the World Bank’s knowledge architecture to the GPs. Second, the World Bank’s past efforts lacked continuity because management discontinued certain strategies and approaches, as well as a previous central knowledge management team. This instability limited the time that business units and the organizational culture had to adjust to new knowledge management approaches. Third, these past efforts have often focused on creating databases and other formal knowledge management mechanisms and have not seriously embraced World Bank staff’s revealed preference for informal knowledge sharing. Fourth, the World Bank has room to improve how it manages the balance between its traditional country-based model and its newer and growing role as a convener and knowledge provider on global issues. The World Bank engages primarily through a country-based model, conducting country diagnostics, working with government to establish a program based on strategic priorities and Bank Group comparative advantage, and using lending and knowledge to pursue country development goals. This engagement model has several advantages, chiefly in promoting a country-owned development agenda, which is critical for development effectiveness. However, the model faces challenges in addressing regional and global issues because it focuses the program on those national priorities for which governments demand support, which do not necessarily align with global and regional challenges and global public goods.

This evaluation is timely because it supports ongoing efforts to improve the Knowledge Bank. Similar to the Strategic Framework for Knowledge and the Knowledge Compact, this evaluation’s broad purpose is to help the World Bank improve learning in (and from) World Bank–financed operations. Specifically, it aims to identify actions that the World Bank could take to ensure impactful learning in all its financing operations. This includes improving learning with clients and partners, enhancing staff incentives and managerial signals for knowledge, revitalizing the World Bank’s knowledge and learning staff, and generating the knowledge required for scaling and replicating impactful projects. The evaluation’s purpose and scope were informed by the Strategic Framework for Knowledge and the Knowledge Compact; the internal discussions surrounding the preparation of these documents, in which IEG participated; and discussions with managers and directors from the Regions, Practice Groups, and Development Economics Vice Presidency.

Approach and Scope

This evaluation is guided by the high-level question, How can the World Bank create optimal conditions for learning in and from its financing operations? Past IEG evaluations, described in appendix B, have covered different aspects of the Knowledge Bank and established the positive links between knowledge and outcomes. This evaluation examines the “production function,” or the enablers and processes, that World Bank teams and managers use to ensure that knowledge is impactful and contributes to granular insights and actionable recommendations to systematically foster multidimensional learning to improve operations and, ultimately, development outcomes.

The evaluation’s scope is knowledge and learning in and from World Bank financing. First, the evaluation covers the World Bank, which includes the International Bank for Reconstruction and Development and the International Development Association. It centers more on learning for its staff and management and less on learning for clients and partners. Second, the evaluation focuses on the World Bank’s unique value proposition as an institution that functions between global dynamics and local development. This unique value proposition comes together in lending operations, from project preparation to completion (figure 1.2). The evaluation therefore looks at the timing, purpose, and types of knowledge surrounding development projects and assesses how “learning enablers”—or factors associated with more knowledge inputs and better conditions for learning—fit and extract knowledge during certain milestones in the project life cycle and how these pieces of knowledge fit together to contribute to learning in lending. Third, the evaluation covers both country knowledge and sector knowledge, formal and informal knowledge processes, and tacit and explicit knowledge (for definitions, see the Conceptual Framework and Definitions section). Fourth, the evaluation period is 2014–23, coinciding with the creation of the GPs. Fifth, the evaluation considers knowledge as both an input to action and an output or result from action. Consequently, the evaluation focuses on how the World Bank applies and expands its knowledge (knowledge as a process) rather than on how it compiles and organizes its knowledge (knowledge as a resource). For example, the evaluation examines World Bank projects’ use of advisory services and analytics (ASA) but not the volume, topic, or quality of ASA.

Figure 1.2. The Linear Model: Knowledge Entry Points in the Project Life Cycle

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Figure 1.2. The Linear Model: Knowledge Entry Points in the Project Life Cycle

Source: Independent Evaluation Group.

This evaluation’s underlying assumption is that effective management of knowledge resources and processes facilitates continuous learning, contributes to performance, and ultimately yields better outcomes. Managing for outcomes requires having credible, operationally relevant knowledge that can feed into the choice and design of operations and inform course correction during project implementation. Past research and evaluations have found a positive role of ASA, staff quality, monitoring and evaluation quality, and other aspects of knowledge on measures of the World Bank’s effectiveness (appendix B). The link has also been documented in other industries (Davenport and Prusak 1998; Goldhar et al. 1976; Orpen 1985). Strategy documents over the years have repeatedly highlighted that knowledge generated by World Bank–financed operations is an important part of the World Bank’s value proposition. For example, the 2018 Capital Increase Package highlighted the vast amount of knowledge embedded in operations and the World Bank’s role in creating and transferring knowledge as part of its financing, and framed knowledge as a way to create greater impact. This evaluation focuses on the factors associated with knowledge inputs and learning conditions and does not attempt to link knowledge inputs to projects’ outcomes.

Conceptual Framework and Definitions

The evaluation defines learning as the ability of World Bank staff to identify, transfer, and transform knowledge to benefit development outcomes. This definition supports the evaluation’s examination of the processes that inform lending operations and capture the lessons of implementation in a continuous learning loop. The focus is on staff learning. Box 1.1 defines the terms related to multidimensional learning in lending.

Multidimensional learning results from using multiple dimensions of knowledge. Learning is elicited through the lending project life cycle by the knowledge ecosystem. This knowledge ecosystem provides positive or negative learning enablers, some within the World Bank’s control and some not. Learning comes from and leads to knowledge, which spans multiple dimensions, including operational, sectoral, and country knowledge, coming in two forms: explicit or tacit. This knowledge can come from inside or outside the World Bank. The World Bank can use this knowledge for strategic, instrumental, and conceptual purposes. Hence, multidimensional learning encompasses all types and forms of knowledge. Effective learning in lending can lead to faster project preparation, faster adaptation to changing circumstances and emerging issues, faster scaling of projects and acceleration of results, more systematic replication of successes and innovations, better avoidance and building on past failures and mistakes, and more effective capacity building and joint learning with clients and partners. In other words, effective learning in lending is closely linked to managing for outcomes.

Methods

The evaluation applies a mixed methods, phased approach to the conceptual framework. IEG used case-based methods to review a sample of 34 World Bank operations approved between 2014 and 2023 (appendix A). IEG selected these cases—20 investment project financing (IPF), 8 development policy financing (DPF), and 6 Program-for-Results (PforR) operations mapped to 10 GPs and covering all Regions—through a combination of stratified random and purposive sampling. The sample included 16 active and 18 closed operations to allow for analysis of knowledge inputs used through the project cycle, from design and appraisal to completion. IEG collected data on the 34 case operations’ knowledge inputs from project documents and semistructured interviews with past and current task team leaders (TTLs). The case study data collection focused on analytic work (including ASA, to the extent these were used to inform projects), lessons from other projects, review processes, team composition, learning with clients and partners, and other internal knowledge management mechanisms. In addition, the evaluation conducted a desk review of 34 learning agendas in a sample of Multiphase Programmatic Approach (MPA) operations approved between 2017 and 2024. The evaluation did not deeply analyze learning from the self-evaluation systems and the country engagement cycle but drew on prior IEG evaluations on this.

IEG generated and further tested the emerging findings. As shown in figure 1.3, IEG’s case analysis generated findings and hypotheses about what types of knowledge inputs are used, in what stage of the project cycle, how they are used depending on the financing instrument, and what factors enable learning. IEG further explored the emerging findings and hypotheses using quantitative analysis of project peer reviews, project document references, and TTL turnover; reviews of financing instrument guidance and other documents; direct observations of review meetings; a questionnaire for knowledge and learning professionals; and interviews with practice managers from both sides of the matrix. The evaluators discussed early findings emerging from triangulating findings across all qualitative and quantitative methods in a series of meetings with staff and managers.

Figure 1.3. Methods

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Figure 1.3. Methods

Source: Independent Evaluation Group.

Note: AI = artificial intelligence; K&L = knowledge and learning; MDB = multilateral development bank; MPA = Multiphase Programmatic Approach; TTL = task team leader.

Report Structure and Overarching Finding

The report is structured as follows. Chapter 2 describes how the World Bank structures knowledge inputs along major project milestones. Chapter 3 discusses how the World Bank’s knowledge ecosystems enable effective learning beyond the standard project processes. Chapter 4 presents conclusions and recommendations. Overall, the evaluation finds that the World Bank’s formal, linear approach to embedding knowledge in its lending processes strongly supports knowledge inputs and learning opportunities at specific entry points of the project cycle, especially at the preparation stage, but that it also has imbalances, weak lesson learning, and fragmented institutional support.