Open AccessEvaluating the Impact of Performance Measurement Frameworks on Financial Management and Operational Efficiency in Fast Food Enterprises
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This case study evaluated the effectiveness of performance measurement framework (PMF) in elevating operational efficiency, with a primary focus on Simbisa Brands, the largest chain in Zimbabwe. The research on the fast food industry in this developing country investigated how the Balanced Scorecard (BSC) could be integrated to monitor the key performance indicators (KPIs) of an organization, in respect of financial performance, customer satisfaction, internal processes, and employee training. Using a mixed method approach, structured questionnaires were distributed to employees, and interviews were conducted with key employees and stakeholders at Simbisa Brands. Results indicated that while the PMF of Simbisa aligned with its strategic objectives, significant challenges and obstacles to operational effectiveness existed in data quality, employee engagement, and customer satisfaction. Moreover, the unstable economic environment in Zimbabwe further complicated financial reporting and cost management. The BSC framework, which aligned KPIs with strategic goals, could effectively track financial performance and customer loyalty in the industry to boost operational excellence and support sustainable growth. Recommendations to stakeholders were proposed to continuously improve data quality, enhance employee involvement, and refine performance metrics to deliver the best purchasing experiences. For Simbisa Brands and other similar organizations, this research offered valuable insights to assist them in gaining competitive advantages and long-term success in the face of challenging business environments.
1. Background of the Study
Performance measurement, central to the functionality of performance management systems (Zheng, 2024), plays an indispensable role in organizational success. According to Zheng (2024), performance measurement offered a simple and straightforward pathway to evaluate individual and organizational performance. Kumolu-Johnson (2024) reinforced this view by highlighting the positive correlation between business growth and performance tracking, which enabled organizations to monitor their most essential operational activities. Ogaji et al. (2019) added that performance assessment encouraged firms to refine their operations, align goals, and respond to unstable environments effectively. The fast food industry in Zimbabwe has been experiencing rapid growth in recent years. In a labor-intensive and highly specialized industry (Zheng, 2024), many utilized point-of-sale (POS) systems for managing businesses, especially in drive-through service. Yang et al. (2023) noted that, when managed effectively, fast-food businesses could be highly lucrative and even overtook hotels in market share. Besides, Zheng (2024) highlighted the emergence of new fast-food outlets and the increasing number of hotels that add fast-food items to their menus. Simbisa Brands Limited serves as a key player in this sector. Listed on the Zimbabwe Stock Exchange in 1998 and spun off from Innscor Africa in 2015, the company operates multiple fast-food brands, including Chicken Inn, Pizza Inn, Bakers’ Inn, Nando’s, Steers, Rocomamas, and Ocean Basket In view of its leading position, Simbisa must implement effective performance measurement systems to act proactively rather than reactively.
Simbisa Brands is currently utilizing the Balanced Scorecard (BSC) as its main performance measurement tool. As defined by Cignitas (2022), the BSC integrated financial and non-financial indicators into a framework that aligned a company’s strategies with operational actions and provided continuous feedback for strategic improvement. Gazi et al. (2022) explained that the BSC evaluated four main perspectives, i.e., financial, customer, internal processes, and learning and growth. This thorough structure allows firms to track performance across strategic objectives, promote teamwork, and drive continuous improvement. Financial measures remain a core element in evaluating business success.
However, the implementation and success of the BSC can vary by context. Khan (2012) noted that developed countries achieved higher BSC success rates due to enhanced data quality, robust management practices, and established organizational systems. These environments facilitate easier identification of performance metrics and more effective data analysis. Kumolu-Johnson (2024) and Zheng (2024) highlighted that in developed nations, the prevalence of strategic planning and data-driven cultures encouraged the adoption of the BSC. Cignitas (2022) also observed that developed markets benefitted from standardized industry benchmarks, which enabled the comparison of performance and learning from peers.
Employees may fear disruption, increased workloads, or reduced autonomy, especially when the benefits of the BSC are not explicitly communicated. In Zimbabwe, businesses like Simbisa Brands face several such challenges to implement performance measurement systems effectively in order to align with overall strategic goals. Simbisa has struggled with operational consistency, as customers have complained about slow service, inconsistent product quality, and limited menu variety. Moreover, Zimbabwe’s unstable economic environment, marked by hyperinflation and currency volatility, has compromised the reliability of financial reporting. These conditions increase the difficulty for Simbisa to gather accurate data on revenue, costs, and profitability, which undermines the financial component of the BSC. The result is reduced revenue, increased costs, and declining profitability due to inefficiencies and data challenges.
This study aimed to evaluate the usefulness of the BSC in enhancing operational efficiency in developing countries, taking Simbisa Brands in Zimbabwe as a case study. It will enable the researcher to apply theoretical knowledge to a real-world context, thus bridging the gap between academic concepts and practical business applications. The findings will contribute to a larger body of literature and provide insights for both practitioners and scholars interested in performance measurement systems. The objectives of the study are as follows:
To assess how the integration of the BSC framework influences the monitoring of key performance indicators (KPIs) and the operational efficiency of Simbisa Brands in Zimbabwe; and
To identify the major challenges in implementing performance measurement systems in the fast-food industry in Zimbabwe and examine how these challenges affect strategic alignment and organizational performance.
2. Literature Review
BSC is a widely recognized performance measurement tool that has been broadly adopted in the fast-food industry It offers a holistic approach to assessing organizational performance by balancing four key perspectives: financial, customer, internal processes, and learning and growth (Hristov et al., 2024).
Empirical research supported the application of the BSC in the fast-food industry; according to Aluko & Kibuuka (2023), the BSC has been proved to improve operational efficiency, customer satisfaction, and financial outcomes. Their study of a large U.S. fast food chain revealed that the implementation of the BSC helped the company define strategic goals, align KPIs across departments, and promote data-driven decision-making. These efforts led to faster drive-through service, increased customer loyalty, and higher profitability. Similarly, a cross-sectional study by Kumar et al. (2024) found that fast food companies with a well-structured BSC outperformed competitors in revenue growth, profit margins, and customer retention.
Several challenges, such as the complexity of the framework, employee resistance to changes, and difficulties in aligning performance metrics with strategic objectives (Govindan et al., 2023) could hinder the adoption of the BSC in the fast-food sector. Additionally, the success of the BSC often depends on the context of an organization and the maturity of its performance management systems (Kumar et al., 2024). Organizations with an established culture of data-driven decision-making are more likely to benefit from the BSC (Aluko & Kibuuka, 2023).
BSC has been widely adopted across various sectors and countries, with both advantages and limitations depending on the contexts. In developed countries like the United States, the United Kingdom, and Germany, organizations have successfully implemented the BSC to align strategic goals with operational activities. Kaplan & Norton (1996), the creators of the BSC, illustrated its effective use in corporations such as Mobil Oil and Hilton Hotels, where it improved internal communication, clarified strategic direction, and enhanced performance monitoring. In Canada, Niven (2008) reported its successful application in healthcare settings, where hospitals achieved efficient service delivery and operational control. Malmi (2001) also discovered that Swedish manufacturing firms benefitted from using the BSC to connect strategic planning with day-to-day activities. Key advantages of the BSC include its integrated approach to performance measurement, combining financial indicators with the perspectives of customers, internal process, and learning and growth, thus supporting better decision-making and fostering organizational learning.
Conversely, the implementation of the BSC in developing countries often encounters significant barriers. Agyemang & Broadbent (2015) and highlighted that in regions such as Sub-Saharan Africa and the Middle East, organizations encountered challenges such as limited data reliability, lack of technical infrastructure, and resistance to changes. Rafiq et al. (2020) discovered that Egyptian firms struggled with poor alignment between strategic objectives and employee performance due to insufficient training and ambiguous communication. Similar issues were observed by Otley (2016) in Kenyan public institutions, where the application of the BSC was hampered by difficulties in tracking non-financial performance and maintaining staff engagement. Khan (2012) argued that weak organizational culture and immature performance systems in developing economies often reduced the effectiveness of the BSC. However, when adapted to local conditions and supported by capable leadership, the BSC could still drive improvements in operational efficiency, financial performance, and employee accountability.
While the multidimensional approach of BSC is advocated in performance measurement, the literature revealed a disparity in its effectiveness based on organizational maturity, industry type, and regional context. In developed economies, the BSC is consistently associated with enhanced strategic alignment, improved communication, and better financial and non-financial outcomes (Kaplan & Norton, 1996; Niven, 2008). However, even in these settings, successful implementation often hinges on strong leadership and a pre-existing culture of performance management. Conversely, in developing countries, empirical studies (Agyemang & Broadbent, 2015; Rafiq et al., 2020) showed that the complexity of the BSC, combined with infrastructural and cultural limitations, could severely hinder its practicality. This contrast underscored the importance of context-sensitive adaptation rather than direct transplantation of Western models into less developed settings.
Although multiple studies highlighted the positive impact of the BSC on key outcomes such as customer satisfaction, employee engagement, and operational efficiency (Aluko & Kibuuka, 2023; Kumar et al., 2024), there was a lack of consensus on how to effectively overcome the challenges of its implementation. Govindan et al. (2023) and Otley (2016) emphasized that barriers such as employee resistance, inferior data quality, and unclear KPIs could undermine the potential benefits of the BSC. This suggested that to deploy the BSC, one needs a more dynamic and iterative approach that incorporates feedback from the stakeholders, ongoing training, and continuous performance evaluation. Additionally, the literature often treated the BSC as a technical tool rather than a change management instrument. A more critical view recognized that performance measurement was not just about metrics but also about influencing behavior and organizational culture. Therefore, future applications of the BSC particularly in the fast food and other service-driven sectors should integrate change management strategies and capacity-building efforts to maximize its effectiveness.
In the Zimbabwean context, the barriers to implementing BSC are significantly amplified by the volatile economic environment, infrastructural limitations, and challenges arising from human capital. Unlike more stable developing economies, Zimbabwe faces persistent inflation, currency instability, and inconsistent policy frameworks, which undermine long-term strategic planning as an essential component of the BSC in practice. These macroeconomic challenges not only curtail the reliability of financial data, but also limit investment in the infrastructure of performance management targeting data collection and analysis. Furthermore, high employee turnover, shortages of skills, and low morale exacerbated by economic uncertainty all adversely affect employee engagement and buy-in, which are critical factors determining the success of the BSC (Rafiq et al., 2020; Otley, 2016). Cultural resistance to formal performance tracking, compounded by weak accountability systems in both public and private sectors, often leads to poor alignment between strategic goals and actual operations (Agyemang & Broadbent, 2015). These unique socio-economic dynamics in Zimbabwe not only intensify the barriers identified in broader literature, but also call for locally adapted BSC models that account for resource scarcity, institutional weaknesses, and the necessity for inclusive stakeholder engagement.
3. Methodology
To effectively explore the research questions, this study employed a quantitative methodology with structured questionnaires to gather measurable data from a broad and varied participant base, thereby strengthening its validity. This approach was particularly appropriate to meet the objectives in this study, as it provided impartial and quantifiable insights into the influence of performance measurement frameworks (PMF) on financial management and operational efficiency within fast food enterprises. The adoption of quantitative methods allows unbiased measurement and comparison across organizations, hence supporting the development of generalizable and dependable conclusions that can inform strategic decision-making, particularly in developing economies.
Participants in the study were asked to complete questionnaires on their own and returned them one week later. To maintain confidentiality, the questionnaires were either emailed to participants or administered in person. This method of data collection outperforms others owing to its cost-effectiveness, efficiency, and convenience, as it allowed respondents to complete the survey at a time that suited them most, ultimately leading to a higher rate of participation. The use of closed-ended and structured interview questions helped streamline responses and ensured that participants had relevant knowledge of the research topic.
The questionnaire was carefully designed based on key constructs identified in the existing literature on performance measurement, financial management, and operational efficiency within small and medium-sized enterprises. Each section of the questionnaire targeted a specific dimension, such as financial decision-making, resource utilization, and performance evaluation, with multiple items under each dimension to capture all-encompassing responses. A five-point Likert scale was applied to quantify attitudes and perceptions, ranging from “strongly disagree” to “strongly agree”, and it allowed consistency in responses and ease of analysis. The development process included expert review to ensure the validity of content; the questions were structured to be clear, concise, and contextually appropriate for respondents familiar with the operation of fast-food enterprises.
The sample size of 21 respondents was determined based on targeted sampling within Simbisa Brands’ management and operational staff, who were directly involved in performance measurement activities. Given the specificity of the study focus and the limited number of relevant personnel, the sample provided depth over breadth. While the small size may limit generalizability, it enables in-depth insights from key informants closely aligned with the research objectives.
Data analysis was conducted using advanced statistical tools to uncover significant patterns, correlations, and trends. Regarding data analysis, the study followed a systematic approach beginning with descriptive statistics to summarize participant demographics and general trends. Inferential statistical techniques, including correlation and multiple regression analysis, were employed to explore relationships between key variables and to determine the extent to which PMF influence financial management and operational efficiency. The choice of these methods was guided by the need to identify significant patterns, test hypotheses, and draw objective conclusions based on the empirical data. Prior to the analysis, data screening procedures were employed to check for completeness and outliers, followed by assumption testing for normality, linearity, and multicollinearity to guarantee the validity of results. All statistical procedures were conducted using specialized software to facilitate the production of precise, reliable, and replicable analysis.
4. Results
The strategic objectives in this study encompassed geographic and brand portfolio expansion, operational efficiency and customer experience, financial performance, and social responsibility.
N | Minimum | Maximum | Mean | Standard Deviation | |
The PMF is clearly aligned with the overall strategy in an organization. | 21 | 2 | 5 | 3.57 | 0.978 |
The KPIs used in the framework are relevant to the key success factors in an organization. | 21 | 1 | 5 | 3.33 | 1.111 |
The framework effectively measures progress towards achieving strategic goals. | 21 | 1 | 5 | 3.19 | 1.123 |
Valid N (list wise) | 21 |
Overall speaking, employees generally believed that the Performance Management Framework (PMF) aligned with the strategy of the organization, as reflected by a mean score of 3.57 as reflected in Table 1 above, though there was potential for further improvement. Their perception of the relevance of the KPIs within the framework was neutral to slightly positive, with a mean of 3.33, indicating some alignment with key success factors but also room for better integration with strategic objectives. Additionally, employees viewed the effectiveness of the framework in monitoring progress toward strategic goals as slightly positive, with a mean score of 3.19, suggesting that it was only effective to a certain context.
In this study, the quality of the data was categorized based on factors such as accuracy, completeness, timeliness, relevance, and consistency, while the availability of data was defined in terms of accessibility, storage, and integration.
N | Minimum | Maximum | Mean | Standard Deviation | |
The data used in the PMF is accurate and reliable. | 21 | 1 | 4 | 3.33 | 1.065 |
The data is collected in a timely and consistent manner. | 21 | 1 | 4 | 2.62 | 1.284 |
The organization has sufficient resources to collect and analyze data. | 21 | 2 | 5 | 3.57 | 0.978 |
Valid N (list wise) | 21 |
According to Table 2, the average score of 2.62 (SD = 1.284) reflects a slightly negative perception concerning the timeliness and consistency of data collection, thus pointing to possible issues such as delays in gathering data. Meanwhile, a mean score of 3.57 (SD = 0.978) signifies a somewhat positive outlook among employees regarding the availability of resources for data collection and analysis. This implied that most employees did not consider the limitation of resources as a major obstacle, although there remains room for optimized resource allocation.
In this study, employee engagement and buy-in were defined by the comprehension of the framework, participation in design and execution, clarity and openness in communication, acknowledgment and incentives, provision of training and assistance, presence of feedback, and its channels for expression.
N | Minimum | Maximum | Mean | Standard Deviation | |
Employees understand the purpose and objectives of the PMF. | 21 | 1 | 5 | 3.48 | 1.03 |
Employees are involved in the design and implementation of the framework. | 21 | 1 | 5 | 2.38 | 1.564 |
Employees believe that the framework is fair and equitable. | 21 | 1 | 4 | 2.05 | 1.071 |
Valid N (list wise) | 21 |
Table 3 reflects that the average score of 3.48 (SD = 1.03) indicates that employees generally have a somewhat positive view of their understanding of the purpose and goals of the PMF. Nonetheless, most employees did not see the framework as entirely unclear nor irrelevant. On the other hand, a mean score of 2.38 (SD = 1.564) reflects a slightly negative perception regarding employees’ involvement in the design and implementation of the framework. This might be due to a top-down approach, insufficient communication, and a perceived lack of influence. In addition, a mean score of 2.05 (SD = 1.071) indicates a negative perception concerning the fairness and equity of the framework, indicating that most employees considered it to be unfair or inequitable.
The financial perspective under this study included revenue growth, profitability, cost management, and cashflow.
N | Minimum | Maximum | Mean | Standard Deviation | |
The organization has experienced a satisfactory increase in revenue over the past year. | 21 | 1 | 4 | 3.0 | 1.095 |
The current net profit margin is adequate to support our strategic goals. | 21 | 2 | 5 | 3.57 | 0.978 |
Valid N (list wise) | 21 |
A mean score of 3.0 with a standard deviation of 1.095 indicates a neutral perception among employees about the revenue growth in an organization over the past year. Mixed opinions with both positive and negative viewpoints were involved. In contrast, Table 4 shows that a mean score of 3.57 with a standard deviation of 0.978 reflects a somewhat positive perception regarding the adequacy of the current net profit margin in supporting strategic objectives. While not a strong endorsement, this implied that most employees did not see the profit margin as entirely insufficient.
The perspective of customers under this study included customer satisfaction, customer retention, market share, and customer loyalty.
N | Minimum | Maximum | Mean | Standard Deviation | |
Customers’ feedback indicates a high level of satisfaction with our products/services. | 21 | 1 | 3 | 1.9 | 0.768 |
Are customers loyal to the organization and likely to repeat purchases? | 21 | 1 | 5 | 3.19 | 1.123 |
Valid N (list wise) | 21 |
A mean score of 1.9 (SD = 0.768) as shown in Table 5 indicates a predominantly negative perception among employees concerning customer satisfaction with the products or services of Simbisa Brands. This suggested that most employees believe customer satisfaction was relatively low. In contrast, a mean score of 3.19 (SD = 1.123) reflects a somewhat positive perception regarding customer loyalty and repeated business. This implied that most employees did not view customer loyalty particularly low, though not highly enthusiastic, in the organization.
In this study, the internal process perspective encompassed aspects such as operational efficiency, quality, innovation, and supply chain management.
N | Minimum | Maximum | Mean | Standard Deviation | |
The average time taken to fulfill customers’ orders is acceptable and meets company standards. | 21 | 1 | 4 | 3.05 | 1.117 |
The number of quality issues reported is within an acceptable range. | 21 | 1 | 4 | 1.95 | 0.973 |
Valid N (list wise) | 21 |
A mean score of 3.05 with a standard deviation of 1.117 indicates a neutral perception among employees concerning the time required to complete customer orders as reflected in Table 6. This reflected a mix of both positive and negative views on this aspect of operational performance. Conversely, a mean score of 1.95 with a standard deviation of 0.973 points to a predominantly negative perception among employees regarding the frequency of quality issues reported. This suggested that most employees believed the number of quality issues was unacceptably high.
The learning and growth perspective in this study covered aspects such as employee satisfaction, employee competencies, information technology, and innovation.
N | Minimum | Maximum | Mean | Standard Deviation | |
Employees receive sufficient training hours to enhance their skills and performance. | 21 | 2 | 5 | 3.57 | 0.978 |
Employee engagement levels are satisfactory and contribute to a positive work environment. | 21 | 1 | 5 | 2.67 | 1.155 |
Valid N (list wise) | 21 |
Table 7 shows that the average score of 3.57 with a standard deviation of 0.978 indicates that employees generally have a somewhat positive view of the adequacy of training hours provided to improve their skills and performance. Although not strongly endorsed, this suggested that most employees did not see the training hours as entirely inadequate. Conversely, the average score of 2.67 with a standard deviation of 1.155 reflects a somewhat negative perception among employees regarding employee engagement levels and their role in fostering a positive work environment. While this was not a strongly negative view, it pointed to some concerns about employee engagement within the organization.
The findings suggested that motivating employees was essential for reaching organizational objectives, with a mean score of 3.05 and a standard deviation of 1.071 as shown in Table 8. Communication methods, such as face-to-face meetings and electronic messaging, effectively illustrated causal links with employee relations, as reflected by a mean of 3.57 and SD of 0.978. The company regularly complied with the regulatory bodies, with a mean of 3.38 and SD of 1.071. Understanding stakeholders’ attitudes remained challenging, with a mean of 3.48 and SD of 1.167, thus highlighting the importance of these attitudes to enhance operational performance. Close interactions with customers were less frequently measured, as indicated by a mean of 2.38 and SD of 1.322, whereas objective congruence was sometimes measured, with a mean of 3.24 and SD of 1.179, and recognized as a necessary condition for formalization. Overall, consistent monitoring of regulatory compliance within the company contributed positively to its operational performance.
N | Minimum | Maximum | Mean | Standard Deviation | |
Managing stakeholders’ attitudes can be a challenging endeavor. | 21 | 1 | 5 | 3.48 | 1.167 |
Considering regulatory bodies can positively influence company performance. | 21 | 1 | 4 | 3.38 | 1.071 |
Motivating employees to work towards the company’s objectives and goals is a crucial component. | 21 | 1 | 4 | 3.05 | 1.071 |
Communication channels such as face-to-face meetings and electronic messages can effectively explain causal relationships with employee relations. | 21 | 1 | 5 | 3.57 | 0.978 |
Objective congruence is emphasized as a fundamental requirement for formalization. | 21 | 1 | 5 | 3.24 | 1.179 |
Companies that maintain strong customer relationships tend to experience successful development. | 21 | 1 | 5 | 2.38 | 1.322 |
Valid N (list wise) | 21 |
A correlation analysis was performed to examine the connection between the PMF and its impact on operational efficiency.
The Shapiro-Wilk test was employed to determine whether the data collected from the 21 eligible respondents in this study followed a normal distribution. This test is commonly used to assess the normality of a dataset, as it effectively evaluates if the sample originates from a normally distributed population. Its popularity stems from its sensitivity and efficiency, especially when dealing with small sample sizes such as the one in this study.
Since most of the variables do not meet the assumptions of normal distribution, nonparametric methods will be necessary for analysis to ensure accurate results. The Shapiro-Wilk test showed that Operational Efficiency, Alignment with Strategic Objectives, Employee Engagement and Buy-in, Financial Perspective, Customers’ Perspective, and Internal Process Perspective all have p value less than or equal to 0.05, indicating they were not normally distributed. In contrast, Data Quality and Availability (p = 0.061) and Learning and Growth Perspective (p = 0.075) have p value just above the significance threshold, suggesting they might be normally distributed but should be interpreted with caution.
Tests of Normality | ||||||
Kolmogorov-Smirnova Test | Shapiro-Wilk Test | |||||
Statistic | df | Sig. | Statistic | df | Sig. | |
Operational efficiency | 0.188 | 21 | 0.051 | 0.891 | 21 | 0.023 |
Alignment with strategic objectives | 0.238 | 21 | 0.003 | 0.837 | 21 | 0.003 |
Data quality and availability | 0.193 | 21 | 0.040 | 0.912 | 21 | 0.061 |
Employee engagement and buy- in | 0.218 | 21 | 0.010 | 0.898 | 21 | 0.032 |
Financial perspective | 0.248 | 21 | 0.002 | 0.849 | 21 | 0.004 |
Customers’ perspective | 0.316 | 21 | < 0.001 | 0.687 | 21 | < 0.001 |
Internal process perspective | 0.238 | 21 | 0.003 | 0.821 | 21 | 0.001 |
Learning and growth perspective | 0.178 | 21 | 0.080 | 0.917 | 21 | 0.075 |
Performance measurement | 0.206 | 21 | 0.020 | 0.879 | 21 | 0.014 |
Since most of the variables do not meet the assumptions of normal distribution, nonparametric methods will be necessary for analysis to ensure accurate results. According to Table 9, the Shapiro-Wilk test showed that Operational Efficiency, Alignment with Strategic Objectives, Employee Engagement and Buy-in, Financial Perspective, Customers’ Perspective, and Internal Process Perspective all have p value less than or equal to 0.05, indicating they were not normally distributed. In contrast, Data Quality and Availability (p = 0.061) and Learning and Growth Perspective (p = 0.075) have p value just above the significance threshold, suggesting they might be normally distributed but should be interpreted with caution.
This research used Spearman’s correlation because it is appropriate for examining relationships between variables that might not satisfy the assumptions needed for parametric tests, such as normality and linearity. Employing Spearman's correlation allowed the study to accurately identify associations between variables without relying on the normal distribution of the data, resulting in more dependable and meaningful insights into the underlying relationships within the dataset.
The correlation matrix above (Table 10) indicates significantly positive relationships between operational efficiency and each of the three independent variables, i.e., alignment with strategic objectives, data quality and availability, and employee engagement and buy-in. These results emphasized the critical role of aligning the PMF with strategic goals, maintaining high data quality and accessibility, and promoting employee engagement and support to enhance operational efficiency.
Spearman’s rho | 1 | 2 | 3 | 4 |
Operational efficiency | ||||
Alignment with strategic objectives | 0.75** | |||
Data quality and availability | 0.85** | 0.60** | ||
Employee engagement and buy-in | 0.86** | 0.71** | 0.64** |
The analysis indicated a strong relationship between operational efficiency and the financial and customers’ perspectives, (Table 11) hence suggesting that enhancing these areas could greatly boost the overall performance. The connection with the internal process perspective was moderate but still implied that optimizing internal processes could positively impact the operational efficiency. Furthermore, the positive correlation with the learning and growth perspective underscored the significance of investing in employee development and fostering a supportive organizational culture to achieve operational excellence.
Spearman’s rho | 1 | 2 | 3 | 3 | 4 |
Operational efficiency | |||||
Financial perspective | 0.65** | ||||
Customers’ perspective | 0.77** | 0.27 | |||
Internal process perspective | 0.24 | 0.02 | 0.22 | ||
Learning and growth perspective | 0.55* | 0.28 | 0.33 | 0.3 |
The correlation matrix (Table 12) indicated a significantly positive relationship between operational efficiency and performance measurement. This strong correlation implied that effective performance measurement was closely linked to improved operational efficiency. In essence, organizations that adopt and utilize robust performance measurement systems tend to attain superior operational results.
Spearman’s rho | 1 | 2 |
Operational efficiency | 0.97** | |
Performance measurement | 0.97** |
Respondent 1: The PMF aligns well with strategic goals like market growth, customer satisfaction, and profitability.
Respondent 2: Generally aligned but suggests more focus on sustainability and social responsibility.
Respondent 3: The focus of some KPIs are short-term; recommends a broader framework that includes long-term value creation.
Summary: The PMF is mostly aligned with strategic goals, but there is a need to incorporate long-term and sustainability-focused KPIs.
Respondent 1: Finds that the PMF is motivating due to clear goals and performance-based rewards.
Respondent 2: Views it useful for tracking, but not personally motivating; suggests more focus on development and recognition.
Respondent 3: Motivated by feedback but wants more frequent recognition and engagement.
Summary: The PMF can motivate employees, but effectiveness varies depending on the design, frequency of feedback, and opportunities for development.
Respondent 1: Focus is mainly on financial KPIs; recommends more customer and operational metrics.
Respondents 2 & 3: PMF includes financial, customer, and operational KPIs, but lacks learning and growth metrics like employee engagement and training.
Summary: Simbisa used a broad range of KPIs, but there was a gap in learning and growth measures that required attention.
Respondent 1: Positive impact; improved inventory management and reduced food waste.
Respondent 2: Helpful, but data collection is time-consuming and sometimes inconsistent.
Respondent 3: Mixed impact; improved processes but overemphasis on short-term results can harm morale.
Summary: PMF has improved some operational areas, but challenges exist in data quality, time demand, and short-term focus.
Respondent 1: Lack of employee buy-in and resistance to changes.
Respondents 1 & 2: Owing to the complexity of the framework, it is hard for some employees to use it effectively.
Respondents 2 & 3: Time-consuming and resource-intensive, especially for smaller units.
Summary: Major barriers include limited employee engagement, complexity, and resource demands, thus affecting effective implementation.
5. Discussion
The research on the PMF of Simbisa Brands underscored its alignment with the company’s strategic aims, the quality and accessibility of data, and employee involvement. The results indicated a moderate level of employee perception regarding the extent to which the PMF aligned with organizational objectives, with average scores suggesting room for improvement regarding the relevance of the KPIs and their effectiveness in tracking the progress toward goals. This highlighted the importance of ensuring that performance measurement was closely linked to strategic priorities, as Neely et al. (2005) emphasized the need for integrating performance metrics with organizational strategy to boost overall effectiveness. Although employees see the potential of the PMF, there remains a gap in fully leveraging its capacity to support strategic aims, which is particularly crucial in the fast-paced fast-food industry.
Data quality and accessibility are critical factors influencing operational performance, as revealed by the study. Employees expressed concerns about delays and inconsistencies in data collection, which are essential for making informed decisions. Supporting this, recent literature has noted that high-quality data is vital for the implementation of successful performance measurement system (Dumond, 1994). While employees generally agree to the sufficiency of data collection, issues with data timeliness can impede operational efficiency. Moreover, a strong association between data quality and operational performance suggests that enhancing the practices of data management could lead to better results, in terms of performance management emphasizing the requisite for ongoing investment in data systems and procedures (Bourne et al., 2003).
The correlation analysis in the study showed robust connections between operational efficiency and various elements of the PMF, such as employee engagement and measurement practices. Specifically, Spearman’s correlation revealed very strong positive relationships between operational efficiency and data quality and availability (r = 0.85), employee engagement and buy-in (r = 0.86), and alignment with strategic objectives (r = 0.75). These high correlation coefficients (all significant at the 0.01 level) suggested that improvements in these aspects of the PMF were often expected to produce notable gains in operational efficiency. This highlighted the importance of involving and motivating employees to achieve organizational goals, to align with Kaplan & Norton (1996), who argued that employee commitment was vital for the successful deployment of performance measurement systems.
Besides, the significant correlation between the PMF and operational efficiency (r = 0.97, p < 0.01) indicated that an integrated performance measurement approach directly impacted organizational performance. The strength of this correlation implied that performance measurement was not merely supportive but integral to operational outcomes. Practically, it suggested that refining the PMF by enhancing data quality, improving alignment with strategy, and increasing employee engagement could lead to measurable and significant improvements in operational results. Therefore, fast food companies like Simbisa Brands should prioritize the improvement of PMF by boosting employee involvement, ensuring data quality, and aligning metrics with strategic objectives to better adapt to market changes and foster operational excellence. The analysis of the perspectives adopted in the BSC further supported these conclusions. Operational efficiency was strongly correlated with the customers’ perspective (r = 0.77) and the financial perspective (r = 0.65), indicating that the performance in these areas was closely linked to efficient operation. This suggested that enhancing customer satisfaction and financial health could directly improve operational outcomes. The learning and growth perspective also showed a moderate correlation (r = 0.55), reinforcing the value of employee training and engagement. In contrast, the internal process perspective had a weak correlation (r = 0.24), indicating that the metrics currently employed to measure internal processes might not effectively capture the drivers of operational efficiency, or that these processes were not yet optimized.
Despite offering valuable insights into the PMF of Simbisa Brands, this study had several limitations as follows. First, the research relied heavily on self-reported data collected by questionnaires, which might be subject to bias in response, as participants might provide socially desirable answers rather than accurate reflections of their perceptions. Second, the study was confined to a single company within the fast-food industry in Zimbabwe, thus restricting the generalizability of the findings to other sectors or regions with different economic, cultural, and organizational dynamics. Apart from this, constraints related to time and access to internal company documents might have limited a more in-depth exploration of the technical components of the PMF, such as specific KPIs or data management systems. Lastly, while the quantitative approach enabled statistical analysis, it might have overlooked nuanced qualitative factors such as employee attitudes, informal practices, or managerial insights that could further explain the effectiveness of the PMF. Future research incorporating mixed methods and broader industry comparisons would help address these gaps and provide a thorough understanding.
Beyond organizational performance, improving the PMF at Simbisa Brands and in the fast-food sector on the whole has wider social and economic implications, particularly in developing economies like Zimbabwe. A more effective PMF could help stabilize employment by fostering a performance-driven culture that supports employee development, recognition, and retention. Improved measurement of customer satisfaction and service quality could enhance consumer trust and brand loyalty, which are crucial for competitiveness in saturated markets. Furthermore, incorporating KPIs related to sustainability and social responsibility could align business practices with environmental and community goals, thus contributing to long-term economic resilience. By reinforcing accountability, operational transparency, and strategic alignment, robust performance measurement systems could ultimately support more inclusive and sustainable growth across the sector.
6. Conclusions
In summary, the evaluation of Simbisa Brands’ PMF highlighted both its strengths and opportunities for improving the alignment with the strategic goals of the company. Employees generally considered the framework aligned with the overall strategy to a certain degree and reported adequate resources for data collection and analysis. However, there were notable concerns regarding employee engagement, fairness, and relevance of KPIs. Specifically, employee feedback pointed to a lack of involvement in the design and implementation of the framework and fostered perceptions of unfairness. Issues related to data quality and availability, such as inconsistencies in timeliness and accuracy should be addressed to attain superior operational results.
The correlation analysis confirmed the vital link between effective performance measurement and operational efficiency, thus demonstrating that alignment with strategic objectives and high-quality data significantly influenced performance outcomes. Strongly positive relationships between operational efficiency, financial performance, and customer satisfaction indicated that focusing on these areas could generate considerable benefits for the organization. Taken as a whole, improving the framework with strengthened employee participation, increased KPIs with relevancy, and enhanced data quality will promote trust, transparency, and operational excellence of Simbisa Brands and the fast-food industry in Zimbabwe. The research findings suggested that by tracking key metrics like food waste, labor costs, and customer satisfaction, the organization was able to identify areas for improvement and implement targeted initiatives. Considering regulatory bodies is a crucial part of performance measurement to ensure operational efficiency.
7. Recommendations
Based on the findings in this study, the following recommendations were proposed to improve the PMF of Simbisa Brands and enhance its contribution to the operational efficiency in the fast-food sector:
Fast food enterprises should ensure that their performance measurement systems are directly connected to the broader strategic visions of their organizations, including goals related to sustainability and corporate social responsibility. These systems should be reviewed and revised periodically to remain in sync with the evolving business priorities.
To enhance the effectiveness of the PMF, it is essential to foster a culture of employee engagement. This can be achieved by clearly communicating the purpose and benefits of the framework, offering training of its application, and creating more opportunities for staff recognition, development, and participation in the evaluation process.
Adequate financial, human, and technological resources should be allocated to support the application and ongoing management of the performance measurement system. Where internal capacity is limited, outsourcing specific tasks such as data processing or performance reporting should be taken into consideration in order to optimize efficiency.
The data used to support the research findings are available from the corresponding author upon request.
The authors declare no conflict of interest.
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