Original Research

Assessing service delivery in Ugandan local governments: A composite indicator approach

Hillary Muhanguzi, James Wokadala

Received: 17 Apr. 2025; Accepted: 01 Dec. 2025; Published: 03 Feb. 2026

Copyright: © 2026. The Authors. Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Background: This study assesses service delivery within and among local governments in Uganda, utilising a composite indicator that aggregates elementary indicators under five dimensions: education, health, water, financial inclusion, and crime.

Aim: To devise and demonstrate the applicability of an alternative approach that holistically assesses local government service delivery performance using a singular indication as preferred to a plurality of disparate indicators.

Methods: Elementary indicators were collated from various secondary sources, normalised, weighted and aggregated to derive the composite indicator. The scores were correlated with selected local government characteristics to establish associations. External validity of the composite indicator was assessed.

Results: Uncertainty analysis shows that the min-max normalisation, budget allocation process (BAL) and additive aggregation produce the most stable rankings. Overall, Uganda’s performance stands at 45%. The composite indicator scores are positively correlated with population size and the age of the local government, but negatively correlated with the number of sub-counties and the distance from the capital city.

Conclusion: A composite indicator approach recognises the multidimensionality of the service delivery phenomenon. Rooted in a strong theoretical framework and quality data, it enables the application of objective statistical analyses that can empirically reveal drivers of service delivery in local governments.

Contribution: This article contributes to the literature by revealing what it would take to assess performance of a local government from a composite indicator perspective. Additionally, it has the potential to inform the rationalisation of the fragmented local governments and sector resource allocations for an equitable service provision experience throughout the four corners of Uganda.

Keywords: composite indicator; service delivery; local governments; performance assessments; Uganda.

Introduction

A well-functioning local government provides high-quality public services to individuals in alignment with their essential requirements and both national and global ambitions. The evolving nature of service planning and delivery requires continual assessment of service provision and corresponding adjustments by the service centres. Arena et al. (2025) observe that public administration is perpetually reforming towards organisational paradigms historically prevalent in the private sector. The contemporary information era, marked by complexity and data-driven dynamics, has enabled citizens to alter their service-seeking behaviours, thereby influencing the delivery and presentation of services. This aligns with Mofokeng, Ramolobe and Bogopa (2025), who noted that digital transformation in local governments offers opportunities to improve service delivery and governance. As a result, performance assessments are becoming important to institutional procedures in both central and local government sectors. Generally, the establishment of local governments in developing countries is primarily motivated by the pursuit of allocative and productive efficiency to enhance public service delivery (Bashaasha, Mangheni & Nkonya 2011). Allocative efficiency entails a superior alignment of governmental services with local desires, whereas productive efficiency encompasses enhanced accountability and reduced bureaucratic layers. In Uganda, local governments have a substantial mandate for the enhancement of individual and community well-being, lived experiences, and institutional trust. Local governments are required to enable devolution and decentralisation of authority, formulate their own development plans and budgets, and mobilise resources for service delivery (The Local Government Act 1997 (Uganda) 1997). This mandate designates local governments as the primary interface for service engagement among individuals, communities, and the government. This suggests: (1) that service requirements vary among different communities, necessitating tailored services for specific demographic groups, (2) the significant demand for public service accountability that should be imposed on local governments, (3) while each local government may have unique characteristics, the overarching principles of service delivery must not be overlooked. As noted by Satria et al. (2025), local governments play a crucial role in the effective anticipation, organisation, and provision of services, necessitating empirical study and comprehension of their performance. Service delivery serves as an indicator of the health of a nation’s governance, because effective service delivery signifies societal cohesiveness, mitigates public disturbance, ensures steady and equal resource access, and catalyses other governmental duties. It reinforces a ‘social contract’ between the citizens and the state. Collectively, these perspectives underscore the significance of enhancements in service delivery, as well as the necessity for a comprehensive framework for assessment, resonating with the positions of Byamugisha and Basheka (2015). Despite the significant utility of service delivery assessments, progress in this area is compromised. Amin and Chaudhury (2008) observed that although various tools and techniques are available for assessing ultimate welfare outcomes in service measurement, there is a lack of tools specifically designed to evaluate the services aimed at generating these outcomes, particularly those that measure the process of transforming inputs into outcomes. Bold et al. (2011) substantiated this claim, highlighting the lack of a complete, standardised set of indicators to assess service quality as perceived by citizens in Africa. Current indicators frequently lack cohesion, focusing solely on either end results or inputs, rather than on the essential processes that generate the outcomes or employ the inputs.

Service delivery and assessments

Service delivery is described as any interaction with public administration in which individuals or enterprises seek or supply information, manage their affairs, or perform their obligations (Organisation for Economic Cooperation and Development 2009). Service delivery refers to the relationship between policymakers, service providers, and customers, including both the services and their supporting systems (Ministry of Local Government 2013). Uganda Women Network contends that service delivery means getting services as effectively and quickly as possible to the intended recipient with an objective to ensure physical, emotional and social needs are met and that people live and function as independently as possible within their own communities (Uganda Women’s Network 2014). These perspectives appear to culminate in the idea that service delivery transpires along a results chain from the service triggers to the outcomes. The quality of services is determined not only by outcomes but also by the governance, inputs, participants, and activities of everybody concerned. This aligns with the World Bank’s public administration function, which posits that an organisation’s productivity is contingent upon the quality and quantity of outputs in relation to inputs (World Bank 2023). The conversion of service inputs into outputs is facilitated by the organisational culture within the service centres. The primary contribution of this function is the incorporation of the mediating impact of public officials’ attitudes and behaviours. Consequently, we perceive service delivery as a multi-faceted process with causal connections from inception to receipt, which assessments must clearly acknowledge. Contemplating service delivery assessments along a results chain (Amin & Chaudhury 2008) allows analysts to comprehensively identify bottlenecks and comprehend the interrelations among various actors and actions. In accordance with Bold et al. (2011), we assert that service delivery is assessed through three interconnected dimensions: provider-recipient relationship, service quality, and governance of the services. At every phase of the outcomes chain, there are both forward and backward linkages, along with external and internal influences that impact the behaviours of the participants. The process includes both state and non-state actors, including professionals at the initiation stage and those at frontline delivery points. In this context, service delivery arises from particular triggers that guide governance decisions made by policymakers at both central and local government levels. We opine that assessments should consider service delivery as influenced by the dynamics of demand and supply. The quality and quantity of services at a given time and place are primarily influenced by the actions of the seekers and the resources available to the provider. During the search process, it is crucial to evaluate the internal or external factors that affect the user, generating a substantial demand for services. The interaction between providers and users, marked by equilibrium, asserts that satisfaction is fundamental to the service delivery process. The aforementioned viewpoints illustrate the complexities involved in accurately assessing service delivery. It is multi-dimensional as it includes various principles, acts, and interconnected components whose contributions must be recognised. Composite indicators (CIs) offer an effective approach by averaging multiple normalised indicators to yield a singular metric, rather than providing diverse individual indicators (Farrugia 2008). Composite indicators are frequently employed to elucidate complex constructs and possess considerable political allure, because they distil complicated issues into a singular metric, grounded in an underlying measurement paradigm (Cavicchia & Vichi 2021). In comparison, a local government provides services in accordance with the policies and objectives of the central government, through several departments or functions including health, education, infrastructure, and water. Moreover, the service centres encompass several types of service seekers, characterised by varied demographic advantages and requirements, hence intensifying the complexities within the local government’s service delivery function. In a nutshell, assessing the service delivery performance of a local government necessitates a singular metric that encompasses departmental contributions while also integrating inputs typically associated with central government decisions, as well as the outputs and outcomes resulting from these actions.

Some measures of local government performance

Worldwide, numerous local government performance measures exist; however, as suggested by Arena et al. (2025), this body of literature is fragmented because of varying methodological approaches and varied viewpoints. Historically, assessments of local government performance have concentrated on financial metrics, frequently neglecting broader implications of their actions (Satria et al. 2025). The World Bank established an innovative approach in the education and health sectors known as the Service Delivery Indicators (Wane & Martin 2013). This was a continent-wide initiative that gathered facility-based data utilising survey-based methodologies on a set of metrics related to service delivery, specifically: (1) the availability of essential infrastructure and resources, (2) the effort demonstrated by providers, and (3) the knowledge possessed by providers. This programme facilitated inter-country comparisons using a standardised set of measurements; nonetheless, it produced national figures and failed to link service performance to local governments, despite their significant responsibility in this area. While national-level statistics are more readily comprehensible for policymaking, they obscure the diverse service delivery contexts present within local governments. Additionally, the World Bank launched the Local Government Performance Index (LGPI) derived from six modules: education, health, physical security and dispute resolution, social assistance and welfare, citizen-state linkages and corruption, and social composition and culture (Kisunko et al. 2015). Nevertheless, literature regarding its adoption among local governments in Africa is limited, possibly because of the high costs associated with its implementation. In South Africa, as noted by Ngumbela and Juta (2025), the majority of government institutions are unable to assess their service delivery effectiveness. Nevertheless, the frontline service delivery monitoring programme aims to instigate improvements in service delivery by highlighting the importance of monitoring. The programme assesses service delivery quality by analysing public service facilities’ compliance with established standards. The Office of the Prime Minister (OPM) has led official local government performance assessments (LGPA) in Uganda. In the year 2021, this assessment was based on five dimensions: compliance with accountability standards, cross-cutting issues, education, health, and water (Office of the Prime Minister Uganda 2020). Notwithstanding the recent changes in the dimensions to incorporate agriculture and production services (Office of the Prime Minister Uganda 2024), it predominantly focuses on process indicators (from inputs to outputs), neglecting global service standards and the outcomes and experiences of users. This offers a limited view of the local government’s service delivery circumstances. The Ministry of Public Service and the National Statistics Office have recently conducted a 5-year cross-sectional national service delivery survey (UBOS 2021). The 5-year time lag is excessively lengthy to yield an accurate representation and generates multiple different indicators that lack convergence. This nationwide, multi-sectoral cross-sectional survey is limited in detail and depth, with responses indicative of the conditions at the time of data collection. The Action Coalition for Development (ACODE) has utilised the Local Government Councils Score Card to integrate the viewpoints of service recipients, as expressed by political leaders, in order to improve democratic decentralisation and address the problem of insufficient service delivery (Tumushabe et al. 2010). This scorecard, utilised by around 15% of local governments, comprises a series of characteristics and corresponding indicators intended to assess the performance of local government councils. This metric sheds light on the governance aspects of service delivery; yet, it is hardly used and directly overlooks critical sector outcomes. The measures reveal an irregular periodicity, resulting in a plethora of indicators that overlook numerous facets of the service delivery chain, hence offering a constrained depiction. Conversely, the CIs function as a holistic solution by amalgamating many aspects pertinent to service delivery (Marozzi & Bolzan 2018) channels and utilising defendable statistical methodologies and procedures. Nonetheless, the cumulative consequence of these assessments is that they exacerbate the lack of consensus on service delivery discussions, resulting in a perpetual loop of inadequate services despite robust national economic growth figures – this is a contradiction. We assert that local governance is significant, and the factors influencing local variance may differ from those at higher levels. In accordance with Kisunko et al. (2015), we acknowledge that local governments exhibit varying levels of performance in service provision; for example, they may deliver satisfactory health care while their educational institutions lag, or vice versa, in different contexts. Variations within the functional areas suggest that, regardless of whether the overall net effect is minimal or absent, the repercussions on particular sectors may still warrant attention. This national aggregation results in inaccurate conclusions, drawing assumptions about local processes by analysing consequences at higher governance levels – the ecological fallacy. Instead, we require a tool capable of assessing the variation both within and across local governments to pinpoint needs, ascertain causes of positive outcomes, develop pertinent programming, and assess results. This study constructs a composite indicator for local government service delivery, employing readily available elementary indicators across all tiers of the service delivery results chain. This is regarded as an innovative strategy that utilises effective data normalisation, aggregation, and weighting techniques to average various elementary indicators associated with different local government functions. This article’s introduction offers an overview of service delivery and metrics in Ugandan local governments, advocating for the development of a composite indicator. The second section delineates the methods, while the third section articulates the results. The fourth section comprises the discussion and conclusion of the article.

Research methods and design

Data and sources

This study collated official data from relevant state bodies, as is common with many composite indicators. The data were sourced from the 2024 Uganda National Population and Housing Census, the 2024 Uganda Police Force Annual Crime Report, the 2023–2024 Annual Health Sector Performance Report, the Ministry of Water and Environment Annual Sector Performance Report and the Master list of Education Institutions in Uganda. The utilisation of official statistics is beneficial because of its association with increased credibility, diminished data administration costs, and the presumption of superior quality stemming from the competent and unbiased handling of these statistics. Certain data points were derived, while others were retained in their original form, including the extraction of utopian and dystopian values for the variables. The initial 31 elementary indicators were classified into five dimensions of this composite indicator: education, health, water, financial inclusion, and crime, as illustrated in Online Appendix 1. According to Booysen (2002), two choices are presented, firstly the number and nature of the dimensions that will make up the composite indicator (CI) and secondly, the specific variables employed in estimating each of the dimensions. The selection of dimensions is typically grounded in the theoretical framework, empirical analysis, intuitive appeal, stakeholder input, or a mix thereof. In our analysis, the selection of the five is predicated on: (1) the availability and accessibility of official statistics for all district local governments, and (2) the perceived significance of the five local government functions in relation to the mandate. A crucial factor in verifying this selection is that alterations in dimensions must exhibit a discernible, linear relationship with the phenomenon (United Nations Economic Commission for Europe 2019). In light of the absence of a ‘light switch’ construction methodology for the CI, it is essential that all actions are meticulously documented and rationales are provided. Constructing a composite indicator necessitates the adoption of a validated methodology encompassing essential phases such as the theoretical framework, data normalisation, weighting, aggregation, and robustness testing, as advised by the Organisation for Economic Co-operation and Development (OECD) (European Commission. Joint Research Centre & Organisation for Economic Co-operation and Development 2008). The framework illustrated in Figure 1 depicts the relationship between the elementary indicators and dimensions leading to the composite indicator. Maggino (2013) asserts that the framework described by the indicators should focus on extracting information and facilitating explanations. Explanations are important, not only for comprehending phenomena, but also for planning eventual policy intervention. Relatedly, a proper comprehension of the link between the indicators and the CI enables the accurate identification of the technique for aggregating individual indicators.

FIGURE 1: Conceptual framework for the composite indicator of local government service delivery.

Figure 1 illustrates the aggregation of sub-dimension components to produce the dimension components, also referred to as the sub-index. The five sub-indices are consolidated to obtain the final CI. This approach improves comprehension of the underlying impetus of the CI. Several assumptions pertinent to the formative measurement model (Terzi et al. 2021) adopted in this study include: (1) the dimensions are non-interchangeable, thus the exclusion of a dimension or elementary indicator results in the omission of a portion of the CI; (2) polarities and correlations are independent, allowing elementary indicators to exhibit both positive and negative correlations; and (3) alterations in the elementary indicators, corresponding to the dimensions, result in modifications to the service delivery CI values, although a change in one dimension does not inherently induce a change in another dimension.

Exploratory data analysis

Although official statistics may be regarded as reliable or comprehensible, it is imperative in any research to do exploratory data analysis (EDA) on any dataset as an essential preliminary step to establish a basis for further analyses. This is performed using measures of central tendency or dispersion. Particularly in composite indexing, the spread of the data caused by outliers affects the robustness of the final CI. An indicator heavily influenced by outliers may show large variations with slight changes in data, indicating high sensitivity and low reliability. Highly skewed, missing or data characterised by outliers is problematic in that it can make the CI less representative of the underlying data. At this stage, variables that were asymmetrical (|skewness coefficient|> 2 or |kurtosis coefficient|> 3) were winsorised. Winsorisation involves reassigning outlying points to the next highest point, or to a percentile value until the required kurtosis or skewness is obtained (Caperna & Smallenbroek 2023). Next was the detection of redundancy in the dataset using bi-variate analysis techniques. Redundancy may occur when variables within the same dimension exhibit high correlations, which is problematic in composite indexing as it leads to double-counting during the assignment of weights. As such, only less correlated variables are included (Mazziotta & Pareto 2013) in the subsequent analyses. Setting the thresholds using the Pearson correlation coefficient at −0.3 and 0.7 for negatively and positively correlated variables, respectively, three initially considered variables or elementary indicators were removed, thus the final CI is built using only 28 variables.

Normalisation, weighting, and aggregation

Taking into account the availability of diverse schemes, together with their advantages and disadvantages, we evaluated a combination of distinct conceivable and realistic scenarios to produce CI scores and rankings. It may be seen as an element of uncertainty analysis. This is crucial, as no single model is inherently superior to others; a CI merely reflects reality. Robustness tests are derived from these scenarios, as well as the selection of the optimal technique for the data. Table 1 presents a synthesis of the scenarios and the definitive changes in rankings. Normalisation is conducted to render local government data comparable prior to the application of weights, because of the disparate measurement units of the data. Four data normalisation strategies were evaluated: min-max, distance to reference point, z-score, and ranking. Min-max normalisation modifies the variable to a range of [0,1] by subtracting the minimum from the indicator value and dividing the outcome by the indicator range. Consequently, min-max normalised indicators possess identical ranges. This technique’s advantage resides in its simplicity and applicability to variables with positive, negative, and zero values (Terzi et al. 2021). The second approach involved the distance to a reference point, wherein the normalised indicator is articulated as a ratio of the subject value in relation to the reference value. This technique facilitates the integration of externally sourced service delivery targets and standards, illuminating the performance of local governments in relation to these benchmarks. Moreover, normalised indications possess the identical coefficient of variation as the original indicators, applicable solely to indicators with positive polarity. The third method employed was z-scoring or standardisation, which involves deriving normalised indicators by subtracting the mean from the original value and dividing by the standard deviation. The advantage is that the normalised values are centred around the mean and possess equal variances; nevertheless, this may result in the formation of negative values that are incompatible with the multiplicative aggregation method. The final method was ranking, which assigns a value’s rank based on its position relative to the variable’s series. Ranking reshapes the distribution of the variable. The application of weights to normalised variables signifies value judgements or local trade-offs for additive aggregation (Munda & Nardo 2005) and substitution rates for multiplicative aggregation. Weighting and aggregation procedures determine the extent to which dimensions can compensate for or substitute one another (Gan et al. 2017). In this context, it is plausible for variables or dimensions to provide complete, partial, or no compensation, as determined by the researcher’s paradigm. Weights may be obtained from the data or elsewhere. Our study evaluated three methodologies: equal weighting, principal component analysis (PCA), and the budget allocation process (BAL). Equal weighting indicates that all dimensions contribute uniformly to service delivery outcomes, resulting in each dimension being assigned a comparable weight that totals to 1. Principal Component Analysis seeks to reduce data dimensionality by generating linear combinations of the original variables. The weights can be computed from the factor loadings for the first principal component (PC1) using the values for each dimension. BAL is an external method for deriving weights, wherein a panel of experts allocates weights based on their intuitive judgement or established policy. Fifteen local government planners were enlisted to allocate weights to the dimensions based on the investment levels necessary to substantially enhance service delivery outcomes in that sector. Averagely, Education was allocated 25%, Health 25%, Water 25%, Finance 10%, and Crime 15%. Aggregation is typically conducted to derive sub-indices and CI values. This was executed in two phases, at a sub-dimensional level to derive sub-indices. At this juncture, a synthesis of equal weighing and additive aggregation was executed. This is justifiable in the formative measurement model, wherein the CI is characterised as a weighted linear aggregation of its normalised variables (Coltman et al. 2008). In the second stage, the derived sub-dimensional indices were aggregated by the application of the aforementioned weighting schemes and evaluating both additive and multiplicative methods to produce the final CI scores. The additive aggregation relies on the additive rule and entails summing the weighted normalised variables or sub-indices. Additive aggregation is entirely compensatory, allowing subpar performance of a local government in one area to be offset by superior performance in other dimensions. Multiplicative refers to the geometric aggregate of the weighted normalised sub-indices. Geometric aggregation is partially compensable, as it allocates greater weights to regions with better scores; nevertheless, it was not utilised for zero and negative values. Various CI values and ranks were derived from a mixture of distinct methodologies, hence facilitating robustness assessments through average rank shifts (Hudrliková 2013). This metric of ranking shifts is computed as the average of the absolute differences between each local government’s rank and a reference ranking (median rank) across all local governments. A smaller absolute shift in ranks indicates a rating more akin to the median, hence representing a more stable methodology. The values derived from this most stable approach were employed for subsequent analyses in this study.

External validation

The external validation of the composite indicator involves juxtaposing the results with recognised metrics of the analogous phenomenon. The OECD asserts that these connections can be employed to assess the explanatory capacity of the composite indicator. The OPM in Uganda has been aggregating the annual LGPA scores, which illustrate the quality of service delivery at that level. The 2024 LGPA values were correlated with our CI scores for the corresponding local government as a means of external validation.

Ethical considerations

This article followed all ethical standards for research without direct contact with human or animal subjects.

Results

The findings of absolute rank shifts indicate that the most stable approach was minimax normalisation within the BAL weighting and additive aggregation, as it yielded the lowest values. Consequently, the CI scores and rankings derived from this methodology were employed for subsequent analyses. They are additionally depicted in the choropleth in Figure 2.

FIGURE 2: Map of service delivery composite indicator performance for local governments in Uganda, 2024.

According to Figure 2, the local governments in the lighter-coloured areas exhibit superior service delivery performance compared to those in the darker areas. The local governments in the central-southern region, closer to the capital city, are depicted in lighter colours compared to those in the northeastern region of the country. Coincidentally, these locations in the central-southern region are comparably more urbanised. The results suggest an unequal distribution of service delivery outcomes related to the geographical closeness of local government to Kampala, implying the influence of urbanisation. Urbanisation is an unavoidable consequence of progress, exerting considerable pressure on service providers to meet the demands of an expanding, educated, and predominantly employed populace. This situation aligns with the findings of Stren (2012), indicating that throughout Africa, decentralisation and democracy resulted in a transition of primary service supply from the state and its agencies to private providers, influenced by market forces. Privately-owned hospitals and schools are predominantly located in urban areas rather than rural regions. The least performing local governments are predominantly situated in the northeastern region, particularly in the Karamoja area. This region has long suffered from droughts that devastate livelihoods and security issues that deter significant investment and engagement in social services. These observations align with various socio-economic indicators of the region, as noted by Mayanja (2021) and UNPFA (2018), who contend that the challenges in the Karamoja region primarily stem from a blend of enduring structural problems and pressing issues, including a legacy of insecurity and disarmament that undermines the appeal of essential services in the area.

Performance of district local governments

Figure 3 is a heat map showing the list of 10 best performing and 10 worst performing district local governments, by the constructed composite indicator.

FIGURE 3: Heat map for the list of 10 best performing and 10 worst performing local governments, 2024.

Ugandan local governments collectively achieve a performance level of 45% on a scale of 0% – 100%. This performance is mostly driven by a moderately favourable outcome in the water sector at 65%, followed by education at 61%. The sector with the lowest performance is financial inclusion, at 36%. The most notable result is the disparity in performance across dimensions and sectors. This is not mere random disparity; it likely signifies profound structural, institutional, and historical influences. Kampala, the capital city, rates as the highest performer in service delivery. Among the top 10 performing local governments, six are situated in the south-central region of the country. Notably, the only local government in the central or western region included in the lowest rankings is Kakumiro district. Amudat district local government, located in a border area with a semi-arid environment, ranks lowest in service delivery performance. The Karamoja area comprises four districts that are among the 10 lowest-ranked district local administrations. A national average of 45% indicates that local governments are actively involved in service delivery, surpassing a zero baseline. It establishes a benchmark from which progress can be measured. More critically, it underscores a significant performance shortfall. This indicates that, on average, over half (55%) of the anticipated service delivery results are unmet. This performance gap is substantial and may exacerbate enduring regional inequality, impede human development, and incite citizen discontent. The average score acts as an essential diagnostic instrument, signalling that the existing local governance model necessitates substantial enhancement and strategic re-prioritisation to provide comprehensive service delivery. The average absolute rank shifts resulting from various potential techniques are displayed in Table 1 as part of the uncertainty tests.

The definitive alteration in rankings quantifies the extent to which local governments fluctuate in their rankings when the normalisation, weighting scheme, or aggregation is modified. A value approaching zero indicates enhanced stability of the combination of the methods, and vice versa. Table 1 indicates that the BAL-min-max. Additive method yields the minimal absolute rank shift (6.43), hence deemed the most stable. This indicates that, on average, each local government’s rank under this set of methods changes by 6.43 spots. The equal weighting – Z score – additive aggregation method is the most unstable, with local governments typically altering their rank by an average of 20.24 positions when methodologies are altered.

Correlation analysis

The computation of CI scores facilitates bivariate and multivariate statistical analyses that elucidate the associated components or predictors, respectively. The correlation analysis investigated the relationship between the composite indicator of service delivery and selected district-level attributes, including population size, geographical area, age, distance from the capital city, and the number of sub-counties. The findings reveal both positive and negative correlations, with differing degrees of statistical significance as shown in Table 2.

A statistically significant positive relationship was identified between local government population size (r = 0.2301, p = 0.0070) and district age (r = 0.2858, p = 0.0007) with the composite service delivery indicator score. This indicates that local governments with greater populations and more extensive institutional memory typically have superior service delivery performance. In contrast, the distance from the capital city (r = −0.3135, p = 0.0002) and the number of sub-counties (r = −0.4282, p < 0.0010) exhibited a strong negative correlation with service delivery. This suggests that distant (from the capital city) local governments and those with a greater number of sub-counties generally exhibit diminished service delivery outcomes. The relationship between the geographical size of the local government and service delivery (r = −0.1321, p = 0.1251) was negative and not statistically significant. This indicates that, when considering other variables, the geographical size of a local government does not exhibit a significant correlation with the overall level of service delivery. Taken together, this analysis underscores the significance of demographic and regional factors in influencing service delivery outcomes. More populous and established local governments appear to be more capable of providing services successfully, whereas geographic distance from the central business district and administrative fragmentation continue to pose significant obstacles to equitable and efficient service delivery.

External validation of the composite indicator

The comparative results are depicted in the cross-plot in Figure 4, with each point symbolising a pair of observations. The data points demonstrate increased dispersion while still reflecting an overarching trend, as their slope rises, indicating a positive correlation between the two variables. The correlation coefficient is 0.17, signifying a low positive and statistically insignificant correlation (p-value = 0.052 > 0.0500) between the two metrics of service delivery. These results may be attributed to the substantial variations in methodology, including the dimensions and elementary indicators utilised. Moreover, the standard practices of aggregation, balancing, and normalising inherent in composite indexing are not strictly followed in the computation of LGPA scores by the OPM.

FIGURE 4: Cross-plot of the local government performance assessment scores, 2024 and the composite indicator scores.

Discussion

The assessment of multi-dimensional constructs necessitates high-quality data and precise definitions of the foundational theoretical frameworks. The evaluation of service delivery at the local government level is complex and multifaceted, largely because of the intricate nature of service operations, governance, and the numerous stakeholders involved. In this study, we build a composite indicator for local government service delivery encompassing five dimensions: health, education, water, financial inclusion, and crime. This decision arises from a review of the methodologies presently employed by local governments in Uganda, which inadequately regard service delivery standards, causal relationships within the service delivery framework, and the multiple interconnected pillars that support service delivery at that level. Consequently, precisely assessing local government performance using a meticulously crafted composite indicator represents a significant shift from anecdotal evidence to empirical data. Indeed, as suggested by Heintzman and Marson (2005), accurate assessments are crucial to performance management systems that enhance the public service value chain. A composite indicator consolidates various performance metrics into a unified, comprehensive measure, thereby offering stakeholders streamlined communication tools essential for decision-making. Local governments do not operate in a vacuum (Berevoescu 2017); hence, a CI acknowledges this complexity while also enabling benchmarking, comparisons, healthy competition, and the establishment of a common language. Although the design of the CI is essential, it is not a universal solution for all measurement issues at the local government level because of intrinsic challenges, including: (1) determining what to measure, (2) the impact of weighting various dimensions on the final score and rankings, (3) the oversimplification of reality, and (4) the quality of data significantly influencing the score’s quality. This study contributes to the expanding knowledge on service delivery assessments at the local government level by employing empirical statistical methods to analyse this multifaceted phenomenon. The recognition of tested CI building techniques, culminating in robustness tests conducted in this study, indicates the reliability of the results. This analysis identifies the various sources of service performance that influence the service delivery experience at the local government level. The thorough assessment of the diverse activities of local governments is essential for their objectives, transforming the abstract notion of ‘bringing services closer to the people’ into a tangible, quantifiable, and improvable reality, advantageous for both citizens and leaders. These results allow users to conduct inter- and intra-local government comparisons that elucidate the variances in service delivery. During the construction phase, several methodological issues emerge, including the polarity of elementary indicators, integration of service delivery targets, and the assignment of weights to the dimensions. Polarity denotes the sign of the link between the indicator and the measured phenomena (latent variable), specifically if an increase in the indicator’s value results in an increase in the value of the CI. In our context, crime serves as a negative indication, with a reduced incidence being preferable. The majority of indicators within the crime dimension exhibited positive polarity with the CI, necessitating their inversion throughout the data normalisation process. The integration of service delivery targets based on international standards is justified because it facilitates the monitoring of local governments’ success in this area. This was executed during the data normalisation phase, although the methodology was not the most robust. Thus, this perspective facilitates the ‘globalization’ of the CI in local government service delivery. Our most effective method employed the weights assigned via the BAL, an externally determined factor. This approach allows for the allocation of value judgements to service sectors or dimensions in a participative manner or according to any explicitly defined process (Jimenez-Fernandez & Ruiz-Martos 2020). This stage offers stakeholders the opportunity to engage in the construction process for the CI, which is advantageous, as Heintzman and Marson (2024) assert that the involvement of service recipients in establishing targets and measurements enhances service delivery, as indicated by service satisfaction. The overall composite score for service delivery is moderate with superior performance in the education and water dimensions. These findings present a complex portrayal of a developing nation, such as Uganda. A national average of 45% is a significantly revealing statistic. It does not denote systemic failure, but rather reflects a condition of transitional development. It indicates that although essential services (education, water, and health) are being delivered, a considerable segment of the population remains inadequately served. Service delivery outcomes are contingent upon substantial financial inputs, which, as posited by the World Bank (2013), have been inadequate in Uganda; this may elucidate the current performance condition. The data indicate a binary service supply scenario – modest and low performance. The modest performance in the education and water sectors aligns with development literature and can be ascribed to multiple converging factors: firstly, the elementary indicators employed are at the input level, linked to physical infrastructures. Results in these areas are significantly dependent on physical assets at primary service delivery locations, including schools and water points. These projects are prominently visible and politically advantageous, often warranting attention by politicians. Secondly, these sectors might be characterised as historical or institutionalised since the onset of colonialism in Africa. These service departments have been integral to the operations of local governments since time immemorial. They generally possess well-defined departments, explicit financial allocations, and consistent protocols. The institutional memory and clarity of mandate for these sectors establish a robust platform for execution. Thirdly, numerous development frameworks have increasingly prioritised outcomes in these areas, resulting in the alignment of investments by local governments. For decades, programmes such as the Millennium Development Goals (MDGs) and the Sustainable Development Goals (SDGs) have emphasised the importance of inclusivity through universal primary education and access to clean water. This approach has directed substantial aid, technical expertise (Archer et al. 2010), and national focus into these areas, enhancing local capacity and resource flows. The low outlier score for financial inclusion (36%) is indicative and highlights a distinct array of issues. It indicates that local governments are inadequately prepared to address this contemporary, systemic aspect of service delivery. Financial inclusion remains an abstract idea; it results from a complex ecosystem that includes private banking institutions and telecommunications corporations. The involvement of local governments in this context is predominantly indirect, poorly comprehended, and operationally challenging. Consequently, local governments in Uganda may possess inadequate regulatory ability to successfully impact market dynamics in this sector. The health dimension operates marginally below the national average, positioned between the high-performing sectors and financial inclusion. The health sector possesses historical and institutional strengths akin to those of the education sector; nonetheless, its subpar performance may be ascribed to the fact that infrastructure and its equitable allocation throughout the country remain inadequate in meeting service standards (Uganda Women’s Network 2014). In the Ugandan local government framework, crime prevention is led by national security entities, including the police and intelligence services. The lower local government councils have little responsibility at the community level, rendering service delivery in this context a complex governance function rather than a direct supply of services. The elementary indicators employed concentrated mostly on crimes reported to the authorities, therefore depicting a complex scenario as they do not address prosecuted, investigated, or verified incidents. This may result in an exaggerated portrayal of the situation compared to reality. Alternatively, it may indicate the significant institutional trust placed in the law enforcement system because individuals often report any suspicious cases for intervention. Although correlation does not imply causation, the findings from the bivariate analyses are both enlightening and persuasive. The favourable correlation with population size may be ascribed to economies of scale in service delivery, enhanced fiscal capability, and more robust advocacy for public resources (Kibirige et al. 2023), which may result in increased service provision. Likewise, older local governments are poised to gain from accumulated institutional expertise, more sophisticated governance frameworks, and well-established infrastructure, which collectively improve service delivery performance. Local governments in regions situated at a considerable distance from urban or administrative centres sometimes encounter logistical difficulties, inadequate connectivity, inefficient oversight, and diminished access to central government assistance. Similarly, districts with a greater number of sub-counties may have coordination inefficiencies and increased administrative burdens. This aligns with the perspectives of Steffensen and Ssewankambo (2011) that the administrative fragmentation of local government systems in Uganda significantly impedes service delivery because of the consequent strains on administrative capability and the finance framework. According to Fellows, Dollery and Marques (2022), geographical remoteness, characterised by significant distances between administrative centres and restricted access to public services, remains a persistent issue in Australian local governments. This study parallels ours, because it found a negative link between geographical size and the CI, but it was not statistically significant. This indicates that the physical dimensions of a local government do not exhibit a significant correlation with service delivery success when other structural and demographic variables are taken into account. However, Enid et al. (2003) assert that local governments in distant regions generally lack the capacity to leverage economies of scale in service delivery, and because of their limited and less varied revenue base, they are unable to compete with those in proximity to urban centres. These results underscore the intricate interaction of demographic, regional, and administrative factors in influencing local government service delivery outcomes. More populous and established districts seem better prepared to deliver successful services, but geographical isolation and excessive administrative fragmentation continue to pose substantial obstacles to equitable service delivery. These findings correspond with extensive empirical research highlighting the significance of spatial accessibility, institutional maturity, and governance competence in influencing public service delivery (Organisation for Economic Cooperation and Development 2009). External validation is an essential process for evaluating the construct validity and practical applicability of a newly developed composite indicator (European Commission. Joint Research Centre & Organisation for Economic Co-operation and Development 2008). It demonstrates that the CI corresponds with theoretically associated notions or recognised metrics encompassing analogous domains. The observed correlation coefficient signifies a weak positive relationship between the two metrics. This conclusion indicates that the new CI, although significantly overlapping with the established LGPA measure, also encompasses distinct aspects of service delivery performance. From a validation standpoint, this positive correlation can be deemed acceptable, as it upholds both convergent and discriminant validity: the indicator aligns with theoretical predictions while being non-redundant.

Conclusion

In conclusion, the service delivery composite indicator offers a comprehensive assessment of the performance of specified sectors or functions within local government, while also highlighting the underlying factors influencing the performance scores. The developed composite indicator is externally valid, highlighting conceptual alignment while maintaining the indicator’s unique contribution to evaluating service delivery in a more thorough and contextually pertinent way. The performance of local governments is moderately satisfactory, exhibiting modest performance in traditional sectors such as education and water, which reflects a firm foundation of public service. Nonetheless, the inadequate scores in financial inclusion reveal insufficient adaptation by local governments to the requirements of contemporary governance. This composite indicator and performance status serve as a call to action: to re-evaluate service delivery assessments at the local government level to enhance the comprehensiveness of service functions, promote investments that ensure inclusive and equitable service distribution among and within local governments, and establish a standardised list of elementary indicators mirroring global service standards, accompanied by the generation of high-quality data. Future research should formulate a composite indicator encompassing additional local government service sectors and elementary indicators, employ multivariate statistical methods such as beta regression to analyse service differentials, conduct a concurrent qualitative module to elucidate the rationale behind the findings, and examine correlations among the dimensions or sectors.

Acknowledgements

This article is based on research originally conducted as part of Hillary Muhanguzi’s doctoral thesis titled ‘Methodological Aspects in the Construction of a Composite Indicator of Service Delivery in Uganda’ submitted to the Directorate of Research and Graduate Training, Makerere University, School of Statistics and Planning library in 2025. The thesis was supervised by James Wokadala. The thesis was reworked, revised, and adapted into a journal article for publication. The author confirms that the content has not been previously published or disseminated and complies with ethical standards for original publication.

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Hillary Muhanguzi: Conceptualisation, Methodology, Writing – original draft, Writing – review & editing. James Wokadala: Supervision. All authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication, and take responsibility for the integrity of its findings.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

The data that support the findings of this study are available from the corresponding author, Hillary Muhanguzi, upon reasonable request.

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency, or that of the publisher. The authors are responsible for this article’s results, findings, and content.

References