https://dinastipub.
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DOI: https://doi.
org/10.
38035/dijefa.
https://creativecommons.
org/licenses/by/4.
Analysis of Operational Key Performance Indicator and Management Control System on Employee Performance (Case Study: PT.
Modular Panel Erect.
Natahsya Novalica Gunaryo1* Universitas Trisakti Indonesia.
Jakarta.
Indonesia, 123012404021@std.
Corresponding Author: 123012404021@std.
Abstract: In a business environment, human resource effectiveness plays a critical role in ensuring the success of the company.
PT Modular Panel Erecta, a construction company, faces the challenge of aligning employee performance with its strategic goals.
Key Performance Indicators and Management Control Systems (MCS) are important instruments in improving employee performance and ensuring that they work in accordance with predetermined targets.
This study aims to analyze the effect of KPI and SPM on employee performance at PT Modular Panel Erecta.
The research method used is a quantitative approach with surveys and interviews.
Data was collected through questionnaires distributed to 30 employees selected using purposive sampling.
Data analysis techniques include validity, reliability, and multiple linear regression tests to measure the relationship between KPIAos.
SPM, and employee performance.
The results of the study are expected to show that effective KPI implementation and an optimal management control system have a significant influence on increasing employee productivity and work efficiency.
This study is expected to contribute to academics in the field of management accounting as well as to practitioners in improving the effectiveness of measuring and controlling employee performance, especially in the construction sector which faces complex challenges in labor management.
Keywords: Key Performance Indicators.
Management Control System.
Employee Performance.
Performance Management.
Construction.
INTRODUCTION
In an era of increasingly fierce business competition, the effectiveness of human resources (HR) is one of the factors in achieving success.
PT Modular Panel Erecta is one of the companies engaged in the construction industry and is facing similar challenges in ensuring employee performance in line with the company's strategic targets.
As a company operating in a highly competitive environment, the success of PT Modular Panel Erecta depends not only on its technical and operational capabilities, but also on managing the performance of its One of the instruments considered crucial in this performance management is the implementation of Key Performance Indicator (KPI) integrated with Management Control 3094 | P a g e https://dinastipub.
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System (MCS).
The observed phenomenon shows that many companies, including PT Modular Panel Erecta, still face obstacles in implementing KPIAos effectively.
KPIAos are often just a formality document without actually being implemented in daily operations.
Based on preliminary data obtained from interviews with the management of PT Modular Panel Erecta, there are several complaints related to the misalignment between the designed KPIAos and the actual performance results of employees.
In addition, the monitoring and evaluation system which is part of the Management Control System has not run optimally, making it difficult to ensure that KPIAos really drive employee performance.
The company's success in achieving its strategic goals is highly dependent on the effectiveness of KPI and SPM implementation.
According to Kaplan and Norton .
, wellstructured KPIAos are able to provide focus on strategic areas that require more attention.
On the other hand.
Simons .
emphasizes that an effective Management Control System can assist companies in ensuring that all organizational processes run in accordance with the predetermined direction.
Previous studies have discussed the influence of KPIAos and SPM on employee performance, but the majority of studies were conducted in the manufacturing and service sectors (Kaplan & Norton, 1996 .
Simons, 1.
Few studies have specifically addressed the implementation of KPIAos and MSS in the construction industry, which has unique challenges in workforce and project management.
Therefore, this study aims to fill the research gap by exploring the influence of KPIAos and MSS on employee performance in the context of the construction industry in Indonesia.
This research is based on Kaplan and Norton's .
Balanced Scorecard theory that emphasizes the importance of KPIAos in directing organizational strategy and Simons, 1995.
Levers of Control theory that highlights the role of SPM in ensuring alignment between strategic and operational goals.
Based on these two theories, this study proposes the following H1: The implementation of Key Performance Indicators (KPIAo.
has a positive and significant effect on employee performance at PT Modular Panel Erecta.
H2: Implementation of Management Control System (MCS) has a positive and significant effect on employee performance at PT.
Modular Panel Erecta.
H3: The implementation of KPI and SPM simultaneously has a positive and significant effect on employee performance at PT.
Modular Panel Erecta.
This research is expected to provide theoretical contributions in the field of management accounting as well as practical contributions for companies in developing more effective and integrated employee performance management strategies.
Figure 1.
Conceptual Framework 3095 | P a g e https://dinastipub.
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Key Performance Indicators According to Setiobudi .
KPIAos are specific measures of an organization's performance in its business area.
This measurement can be financial or non-financial and is used to measure the strategic effectiveness of the organization/company.
The use of KPIAos aims to measure employee performance more precisely and focused.
Meanwhile, according to Parmenter .
KPI is a collection of measurement tools created to direct some of the most important organizational factors to achieve success in the present and for the future.
Measurements are gradual and quantitative and these measurements also have various points of view and are in the form of concrete data, and Key Performance Indicators are the beginning of determining company goals and strategizing.
(Sychrovy & imberovy, 2.
KPIAos are a tool for companies to assist in assessing the performance of their employees.
With KPIAos, companies will find it easier to provide assessments of employees, both those with positive and negative assessments.
According to Arlina et al .
Key Performance Indicator (KPI) is a variable used to quantitatively state the effectiveness and efficiency of a process or activity based on organizational goals, as a tool to evaluate the success of achieving organizational goals associated with certain metrics that are realized.
So far.
KPIAos have only been used for qualitative parameter measurements, for example such as measuring leadership quality, and also customer satisfaction.
But the thing to note is that not everything can be used as a KPI.
Management Control System (SPM) SPM is a system used to plan activities that support the achievement of the organization's mission through a predetermined mission (Sunarto 2017:.
Meanwhile, according to (Mulyadi 2016:.
a good control system in a company can create work procedures that are systematic and in accordance with the rules that apply in the organization, so that it will create a mutually supportive control environment in each company.
Sujarweni .
6: .
states that the management control system is a series of processes designed by the company to ensure that the company's resources are used effectively and efficiently, with the aim of achieving maximum performance in accordance with predetermined Management Control System is a process designed to direct and monitor employee actions in achieving organizational goals.
MCS not only focuses on financial control, but also includes control over behavior, information, and strategies implemented in the organization.
Employee Performance Employee performance refers to the results of an individual's work measured against certain criteria related to organizational goals and expectations.
This performance covers various aspects, including efficiency, effectiveness, quality, and productivity in completing assigned tasks and responsibilities.
Employee performance is also influenced by internal factors such as skills, motivation, as well as external factors such as organizational support and work environment.
Previous Research Asmoro & Nazar .
, showed that the implementation of clear KPIAos and an effective control system can increase employee productivity and motivation.
This study is relevant because it highlights the importance of performance measurement in ensuring the achievement of company goals.
Firnanda & Prasetya .
, show that KPIAos have a significant influence in improving employee productivity and efficiency.
Although conducted in the marketing sector, this study provides insight into how KPIAos can be adapted in various work environments.
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Laoli & Ndraha .
, the study highlights that a good control system should include continuous performance evaluation and constructive feedback for employees.
This finding is relevant in the context of this study because it emphasizes the importance of the control system in supporting the achievement of KPIAos.
These three studies provide the basis for this research in exploring how KPIAos and SPMs can be effectively applied to improve employee performance, particularly in the construction industry which has unique challenges in workforce management.
METHOD
This research uses a quantitative approach with survey methods.
The population in this study were all employees of PT Modular Panel Erecta, with a sample of 100 respondents selected using purposive sampling technique.
Sample criteria include employees who have worked for more than one year and have experience in implementing KPIAos and SPM.
The research variables consist of independent variables, namely Key Performance Indicators (KPIAo.
and Management Control Systems (MCS), and dependent variables, namely employee The operational definition of variables is set to ensure that each concept studied can be measured quantitatively.
The data used in this research is primary data obtained through distributing questionnaires and interviews to respondents.
The questionnaire was designed using a Likert scale to measure respondents' perceptions of KPIAos.
SPM, and employee performance.
Interviews were conducted to support the survey results by exploring more in-depth information related to the implementation of KPIAos and SPM in the company.
Data analysis techniques include validity and reliability tests to ensure that the research instruments are In addition, multiple linear regression analysis was used to test the relationship between the independent variables and the dependent variable.
The analysis model used in this study is as follows:
Y = 0 1X1 2X2 e Where:
= Employee Performance = Key Performance Indicators (KPI) = Management Control System (MCS) 0 = Constant 1, 2 = Regression Coefficients = Error term This research is expected to provide deeper insight into the effectiveness of KPIAos and SPM in improving employee performance, as well as providing recommendations for companies in developing more effective and structured performance management strategies.
RESULTS AND DISCUSSION
This chapter describes the results of data processing and analysis aimed at examining the effect of Key Performance Indicator (KPI) and Management Control System (MCS) on Employee Performance.
The analysis was conducted quantitatively using SPSS software and involved various statistical tests, including validity, reliability, classical assumption tests, multiple regression analysis, and hypothesis testing.
All tests were conducted based on primary data collected through questionnaires from 100 employee respondents.
Validity and Reliability Test 3097 | P a g e https://dinastipub.
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Before the main analysis, a validity test was conducted to ensure that the research instruments could measure the intended variables.
All questionnaire items were declared valid after item-total correlation tests showed significant values .
count > r tabl.
Subsequently, reliability testing was conducted using CronbachAos Alpha.
The results are:
KPI (X.
: CronbachAos Alpha = 0.
MCS (X.
: CronbachAos Alpha = 0.
Employee Performance (Y): CronbachAos Alpha = 0.
These values indicate that each research instrument has good reliability ( > 0.
This aligns with the findings of Sari & Nugroho .
, which state that good reliability is essential for building a robust regression model, particularly in the context of performance management.
Classical Assumption Tests Normality Test One-Sample Kolmogorov-Smirnov Test Unstandardized Residual Normal Parameters Mean Std.
Deviation Most Extreme Differences Absolute Positive Negative Test Statistic Asymp.
Sig.
-taile.
Test distribution is Normal.
Calculated from data.
Lilliefors Significance Correction.
The Kolmogorov-Smirnov test showed a significance value of 0.
185 (> 0.
, indicating that the residual data is normally distributed.
This result is consistent with the findings of Fitriani .
, who emphasized that normally distributed residuals are a prerequisite for the validity of multiple linear regression models.
Heteroscedasticity Test Coefficientsa Model (Constan.
Key Performance Indicator Management Control System Dependent Variable: ABS_RES Unstandardized Coefficients Std.
Error Standardized Coefficients Beta Sig.
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This test was performed using the Glejser method.
The significance value for KPI was 631 and for MCS was 0.
555, both above 0.
This indicates that there is no heteroscedasticity, confirming the findings of Lestari .
, who noted that homogeneous data strengthens the validity of statistical inference.
Multicollinearity Test Coefficientsa Collinearity Statistics Tolerance VIF Key Performance Indicator Management Control System Dependent Variable: Employee Performance Model The tolerance values for KPI and MCS were 0.
816, and the VIF values were 1.
Since tolerance > 0.
1 and VIF < 10, it can be concluded that there is no multicollinearity.
This supports the findings of Prasetyo and Anggraini .
, who showed the importance of independence among independent variables in ensuring accurate estimation of regression Autocorrelation Test Model Summaryb Adjusted R Std.
Error of the Model R Square Square Estimate Durbin-Watson Predictors: (Constan.
Management Control System.
Key Performance Indicator Dependent Variable: Employee Performance The Durbin-Watson test result was 2.
This value is close to 2, indicating no autocorrelation in the data.
This is consistent with previous research by Hidayat .
, which stated that cross-sectional data tends to be free from autocorrelation.
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Multiple Regression Analysis Coefficientsa Unstandardized Coefficients Model Std.
Error (Constan.
Key Performance Indicator Management Control System Dependent Variable: Employee Performance Standardized Coefficients Beta Sig.
The resulting regression equation from the analysis is:
Y = 18.
233X1 0.
This means:
Every one-unit increase in KPI leads to a 0.
233 unit increase in employee performance.
Every one-unit increase in MCS leads to a 0.
357 unit increase in employee performance.
These findings align with research by Wardani and Santoso .
, which indicated that a good management control system has a stronger influence than KPI in improving human resource performance.
T Test (Partial Tes.
Coefficientsa Unstandardized Coefficients Model Std.
Error (Constan.
Key Performance Indicator Management Control System Dependent Variable: Employee Performance Standardized Coefficients Beta Sig.
The t-test results show that only the MCS variable has a significant partial effect on employee performance.
This reinforces the findings of Rahayu .
, who stated that a wellstructured management control system is more effective in driving employees to achieve performance targets than performance indicators alone.
F Test (Simultaneous Tes.
ANOVAa Sum of Squares Mean Square Regression Residual Total Dependent Variable: Employee Performance Predictors: (Constan.
Management Control System.
Key Performance Indicator Model Sig.
The F-test value was 8.
786 with a significance of 0.
000 (< 0.
, indicating that KPI and MCS simultaneously have a significant effect on employee performance.
This supports the study by Nuraini and Mulyadi .
, which concluded that the synergy between control systems and performance indicators contributes positively to overall employee productivity.
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Coefficient of Determination (R.
Model Summaryb Adjusted R Std.
Error of the Model R Square Square Estimate Predictors: (Constan.
Management Control System.
Key Performance Indicator Dependent Variable: Employee Performance The R Square value of 0.
153 indicates that the independent variables (KPI and MCS) 3% of the variation in employee performance.
The remaining 84.
7% is influenced by other factors outside the model, such as work environment, leadership, personal motivation, and organizational culture.
This is supported by the research of Putri & Halim .
, who stated that employee performance is a complex variable influenced by multiple dimensions.
Hypothesis Testing Results H1: KPI has a positive effect on employee performance Ie Rejected .
= 0.
119 > 0.
This finding contradicts Dewi .
, who found that KPI significantly improves performance in the manufacturing sector, but it may be explained by the respondents' characteristics being more influenced by systematic control than individual indicators.
H2: MCS has a positive effect on employee performance Ie Accepted .
= 0.
006 < 0.
This result is in line with Ananda and Yusuf .
, who found that a management control system is a primary tool in ensuring alignment between company strategy and individual H3: KPI and MCS simultaneously affect employee performance Ie Accepted .
= 0.
This reinforces empirical evidence from a longitudinal study by Taufik .
, which showed that the combination of KPI and control systems creates a positive synergy for organizational efficiency.
CONCLUSION
This chapter presents an in-depth discussion of the research findings outlined in Chapter IV by connecting them with the theoretical framework and previous empirical studies.
Additionally, this chapter provides the implications of the findings, limitations of the study, and recommendations for future research.
The research aimed to examine the influence of Key Performance Indicator (KPI) and Management Control System (MCS) on Employee Performance.
The results indicate that the MCS variable has a significant effect on employee performance, whereas the KPI variable does not have a statistically significant partial effect.
This suggests that a structured and integrated control system plays a more vital role in directing employee behavior and achieving performance targets than the mere application of KPI The lack of a significant effect of KPI on employee performance might stem from the way it is implemented within the organization.
While KPIs may exist, their ineffective internalization or lack of consistent monitoring could weaken their impact on performance Meanwhile, the significant role of MCS highlights the necessity of having comprehensive control mechanisms such as planning, performance feedback, continuous evaluation, and clear accountability.
These findings align with the contingency theory of management control, which posits that the success of control systems is contingent upon how well they fit the organization's needs, strategies, and operating environment.
This theory supports the importance of contextual factors in determining the effectiveness of any management control framework.
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In accordance with previous studies, such as that by Ananda and Yusuf .
, effective management control systems foster coordination, clarify performance expectations, and motivate employees to deliver optimal results.
Their research emphasizes that robust control mechanisms enhance not only compliance but also motivation, innovation, and alignment with organizational goals.
Additionally, the fact that KPI and MCS simultaneously affect performance suggests that when combined, they can complement one another in improving While KPI serves as a performance measurement tool.
MCS ensures that such measurements are aligned with strategic intentions and operational goals.
The R-squared value of 15.
3% reflects that the model explains a modest proportion of the variance in employee performance.
This level is acceptable in behavioral studies, which often deal with complex human-related variables.
It also implies the need to investigate other potential contributing factors.
The remaining 84.
7% variance may be attributed to various elements outside the model, including leadership style, organizational culture, job satisfaction, personal motivation, training, career development, and technological infrastructure.
This reinforces the understanding that employee performance is influenced by a broad spectrum of Similar findings have been reported by Putri and Halim .
as well as Nuraini and Mulyadi .
, who both concluded that employee performance is multifaceted and cannot be wholly explained by managerial tools alone.
Their recommendations highlight the inclusion of psychological and environmental variables in performance assessment models.
From a managerial standpoint, these findings suggest that organizations should focus more on developing and refining their management control systems.
These systems serve as the backbone for strategy implementation and operational monitoring, especially in dynamic organizational environments.
While KPI remains an important tool for tracking outcomes, its effectiveness is enhanced when embedded in a broader control process that aligns with the organizationAos vision, communicated clearly to employees, and evaluated regularly.
Organizations are encouraged to not rely solely on KPI metrics without establishing a context that supports and sustains them.
One practical recommendation is to involve employees in the KPI-setting process.
Their participation could increase the sense of ownership, motivation, and understanding of performance expectations.
This approach aligns with participative management principles, which have been shown to improve employee engagement and satisfaction.
In addition, training sessions and workshops should be conducted to educate both managers and staff on how to interpret and use KPIs effectively.
Without adequate understanding, even the most welldesigned indicators may fail to influence behavior as intended.
Technology also plays a crucial role in supporting performance management.
Organizations should consider adopting digital tools and performance dashboards that offer real-time feedback and integrate seamlessly with their MCS infrastructure.
Such systems enable timely interventions and foster a culture of continuous improvement.
However, this study is not without limitations.
The use of a cross-sectional design restricts the ability to observe changes over time, and the reliance on self-reported questionnaire data may introduce common method bias.
These limitations should be considered when interpreting the results.
Future research could adopt a longitudinal design to explore how the influence of KPI and MCS on employee performance evolves over time.
It is also advisable to utilize mixed-method approaches to gain deeper insights into the behavioral and contextual factors influencing performance.
Expanding the scope of research to include multiple organizations across different industries would enhance the generalizability of the findings.
Comparative studies could reveal how industry-specific dynamics affect the implementation and impact of performance management tools.
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In conclusion, this study reaffirms the central role of the management control system in improving employee performance.
While KPI can be a valuable measurement tool, its effectiveness increases when integrated within a comprehensive and well-functioning control Therefore, the strategic integration of KPI and MCS, supported by technology and participatory practices, offers a holistic approach to managing performance in dynamic, competitive organizational environments.
REFERENCES