The impact of operations management practices in improving organisational performance
Anila Alam*
Assistant Professor, Savitribai Phule University, Pune, Maharashtra, India Email: anila.alam.r@gmail.com
Abstrac t- The primary focus of this research article is to investigate the significant influence that operations management strategies have in improving the performance of organizations. It elucidates the complex influence that operations management methods have on key performance indicators like as profitability, customer satisfaction, and competitive advantage by conducting a complete analysis of the relevant literature and empirical data. When it comes to boosting efficiency and innovation, the findings underline the value of simplified processes, technology integration, and strategic alignment with organizational goals. In addition, the research highlights the significance of cross-functional cooperation and the development of human capital in the process of cultivating a culture of operational excellence. In conclusion, the paper emphasizes how important it is to prioritize operations management as a strategic imperative in order to achieve a sustainable competitive advantage and long-term success in the dynamic business climate that exists today.
Keywords - Operations management, structure equation modeling supply chain management.
INTRODUCTION
Production and operations management (POM) and supply chain management (SCM) are two modern business essentials. One of the most important things that these occupations do is make sure that everything in an organization moves smoothly, from goods to information to resources. Production management, or POM, entails creating, organizing, and regulating production processes in order to convert inputs into outputs as efficiently as possible. Supply chain management (SCM), on the other hand, is concerned with the cooperative efforts of various businesses in meeting customer demand for goods and services. Merging POM and SCM processes is crucial for improved business performance, according to new research.
There are a number of reasons that can be provided for the connection that exists between POM and SCM. By incorporating these techniques, firms are able to improve their operational efficiency, optimize their production processes, and minimize their expenses. Supply chain management that is effective assures timely access to raw materials, saves expenses associated with inventories, and minimizes interruptions to production. The close cooperation between POM and SCM leads to improvements in demand forecasting, inventory management, and order fulfillment, which ultimately results in more revenue and improved customer satisfaction. For this reason, the financial performance of an organization, which includes measures like ROI and profitability, is a crucial indicator of the organization's future performance and viability. An improvement in a company's financial performance allows it to engage in innovation, expand its operations, and generate value for its stakeholders. After establishing a correlation between POM, SCM, and financial success, researchers have concentrated on understanding how these three areas may collaborate to boost a business's bottom line.
Even though there is a rising awareness of the connection between POM practices and financial success, there is still a need for more study to investigate the particular processes that are responsible for these kinds of correlations. The purpose of this research is to investigate how management of operations (POM) methods might improve organizational financial performance via the integration of supply chain management (SCM). The dearth of knowledge regarding the connection between financial performance, POM practices, and SCM integration is underscored by these research gaps. Combining POM and SCM has the potential to increase financial results, which is the goal of this study. This is achieved by drawing on well-established theories like the resource-based view (RBV) theory, which places an emphasis on unique resources and capabilities as a source of competitive advantage, and by exploring strategies for operations, which help to align operations with an overarching strategy in order to gain an advantage. Supply chain coordination, comprehensive quality management, and lean manufacturing are a few other concepts that help explain how this integration improved financial performance.
Our knowledge of the linkages between POM, SCM, and organizational financial performance is advanced by the synthesis of these theoretical viewpoints, which also provides companies with insights that can be put into practice in order to improve their financial results via integration.
More and more people are looking at POM integration with SCM processes as a means to improve organizational performance. As a result, we can see that the two fields are interdependent and that effective integration should result in better financial outcomes. The purpose of this research is to make a contribution to the current body of knowledge by exploring the processes and tactics that are responsible for the beneficial effect that POM practices have on the financial performance of organizations. The results will be of assistance to practitioners in the process of establishing and putting into practice efficient POM–SCM integration strategies in order to obtain better financial outcomes. The following are the research questions that will serve as the basis for our investigation:
- How does the organization's financial performance and the integration of supply chain management (SCM) change as a result of implementing POM techniques?
- How does SCM mediate the connection between POM practices and organizational performance?
The format will be maintained throughout this document. Here we will lay out the groundwork for our empirical investigation, describe our research methodology and hypotheses, and provide an overview of relevant theories and concepts. What follows is a description of the procedure that was used to carry out the research goals. Our study extensively discusses the theoretical and practical ramifications of our inquiry. A review of important limitations and a discussion of potential avenues for further study make up the last section of the article.
REVIEW OF LITERATURE
Salah A. et al. (2023) In this study, we look at manufacturing companies in Jordan to see how POM (production and operations management) approaches relate to organizational financial performance (OFP). Using concepts like the resource-based perspective, this study uses quantitative methods and survey data gathered from 209 managers. The results show that POM practices are favorably connected with both OFP and SCM integration. Integration of supply chain management (SCM) shows how POM practices may influence financial performance by mediating between POM practices and overall financial performance (OFP). This research contributes to the current literature by integrating POM and SCM methodologies; it elucidates the effects of these approaches on the bottom lines of Jordanian manufacturing companies.
Tan et al. (2022) In today's business world, competition is not about resources, but about the actual accumulation and utilization of knowledge within an organization. This paper investigates the impact of organizational learning and effectiveness on operations, employee productivity, and management performance, aiming to contribute to scholarly works and knowledge on organizational learning. The shift from acquiring wealth to focusing on knowledge and learning is crucial for organizational survival and continuous growth.
Iqbal (2020) This study aimed to examine the correlation between SMEs in Saudi Arabia and their competitive advantage as it pertained to supply chain management practises. The study mainly used Smart PLS with SEM and included 383 individuals from different sectors. Using supply chain management strategies as a moderator, the results demonstrated that SMEs greatly benefited from operations management methods in gaining a competitive edge. Nevertheless, it would have been beneficial for the study to expand its scope beyond SMEs in Saudi Arabia and take into account other elements and countries. Companies with less than 500 employees should prioritize developing products that address client demands by concentrating on what they do best.
Gadwe et al (2019) Operations management is crucial for organizations, but it cannot be isolated from other business functions. Each business manages unique aspects, and they must work together. Manufacturing firms often implement operations management activities, which positively impacts their performance. As service firms become more important and large, it is essential to develop and test theories related to their operational performance. Focusing on service operations management can provide a competitive edge in service organizations, making operations management activities essential for overall business success.
Chipwatanga et al. (2019) First National Bank - Zambia (FNBZ) operating model and its effect on performance are the subject of this research. The overarching goal of this study is to provide a novel paradigm for strategic operational excellence with the purpose of enhancing and maintaining organizational performance. Using preexisting organizational diagnostic models as well as research on operational performance-based criteria, the model was created. Important for managing and developing strategies, the research also investigates the link between operational excellence and innovation, as well as the link between performance assessment and organizational performance. The study's goals are to characterize operations, find obstacles to establishing a model for strategic operational excellence, and assess how well FNBZ is doing with its present model. A cross-sectional case study served as the basis for the research, which adhered to a pragmatic philosophical approach. In this mixed-method study, we used a random sample technique to choose 100 workers and 32 consumers, and we used a purposive selection technique to pick certain employees to interview.
METHODOLOGY
Data Gathering and Sample Process
To ensure representation across different sectors, this study's data was collected by creating a sample frame from a reputable database of manufacturing enterprises. Roughly 29.6 percent of all manufacturing enterprises were included in the sample, which included 100 firms. It was necessary to target a diverse range of manufacturing enterprises in order to achieve industry diversity. The manufacturing company served as the unit of analysis for this research. Each company had one representative from management who had a good grasp of POM and SCM chosen to take part in the research. As was common in SMEs, when specialized POM and SCM managers were not available, the managers responsible for critical operations such as purchasing, quality, and plant were consulted instead.
A basic random sampling approach was employed to select the participating businesses. One of the researchers went door-to-door to approach the selected companies. A cover letter outlining the study's aims and the necessity of responding anonymously for scholarly purposes was also sent to each company. Due to missing data, 10 of the 50 questionnaires were excluded, leaving only 40 usable for analysis.
Table 1. Characteristics of the questioned sector and its participants
Variables | Measures | Frequency | Percentage (%) |
Gender | Male | 64 | 30.6 |
| Female | 36 | 17.2 |
Age | Less than 30 years old | 3 | 1.4 |
| 31–40 | 30 | 14.4 |
| 41–50 | 33 | 15.8 |
| 51–60 | 8 | 3.8 |
| Over the age of 60 | 6 | 2.9 |
Position on the Job | Operations manager | 29 | 13.9 |
| Supply chain manager | 26 | 12.4 |
| Plant manager | 20 | 9.6 |
| Quality manager | 18 | 8.6 |
| Others | 7 | 3.3 |
Work Experience | Less than 5 years | 16 | 7.7 |
| 5–less than 10 | 20 | 9.6 |
| 10–less than 15 | 13 | 6.2 |
| 15–less than 20 | 11 | 5.3 |
| 20 and above | 7 | 3.3 |
sector Industry | Pharmaceutical and medical | 5 | 2.4 |
| Chemical and cosmetic | 12 | 5.7 |
| Food and beverages | 17 | 8.1 |
| Leather and garment | 6 | 2.9 |
| Plastic and rubber | 7 | 3.3 |
| Electrical and IT | 12 | 5.7 |
| Machinery and hardware | 10 | 4.8 |
| Others | 3 | 1.4 |
No. of employees | Less than 100 | 16 | 7.7 |
| 100–less than 200 | 34 | 16.3 |
| 200–less than 300 | 4 | 1.9 |
| 300 and above | 4 | 1.9 |
Total | | 100 | 100 |
Top of Form
Measurement
To ensure that all participants could understand and take part in the survey, it was first prepared in English and then translated into Hindi. Thanks to the revised scales, we have content validity for the elements. The questionnaire was examined by ten academics with skills in POM and SCM and five managers with experience in manufacturing businesses. The authors distinguished three aspects: Total Quality Management (TQM), Joint Initiation and Control (JIT), and Production Cost Disparity (PCD). A scale measuring POM behaviors was developed using twelve items that were adapted from previous studies. Using a 10-item scale, we assessed the organization's degree of SCM integration. Of the three questions used to measure OFP, one had participants rank their own performance relative to their opponents' on a five-point Likert scale.
Variance in Common Methods
The study used Harman's single-factor test in an effort to address the issue of common method variance (CMV) in data collection. The data came from self-reporting questionnaires administered to a single point of contact inside each participating organization. The analysis of variance reveals a single component that explains over half of the data variance. The absence of a single component and the fact that the largest factor only explained 33% of the variance are both concerning. The 50% cutoff point is far higher. It seems that CMV did not cause any significant issues based on the data that was collected.
Methods Based on Statistics and Analysis
This study used structural equation modeling (SEM) to unravel the complex network of interconnections among the latent components of operations management research. Due to its unified framework for evaluating direct and indirect consequences, structural equation modeling (SEM) is an ideal statistical tool to use for researching complicated phenomena like the impact of POM practices on OFP via SCM integration. When dealing with measurement error or unobservable components, SEM is also an excellent choice. Structural equation modeling (SEM) was used to investigate the relationships between OFP, SCM integration, POM practices, and latent components in accordance with social science standard method. Because of its comprehensive nature and ability to evaluate model fit, SEM may help conduct a more complete and trustworthy empirical investigation.
RESULTS AND ANALYSIS
Evaluation of the Measurement Model
To ensure the study's validity and reliability, the researchers used structural equation modeling (SEM) and Amos 24.0. To further ensure the variables' convergent validity, they used a confirmatory factor analysis (CFA). All of the measuring scale items were statistically significant (p < 0.01), therefore meeting the convergent validity criterion. Table 2 details the results and last aspects of the evaluation.
Table 2. Results from the measurement model
1st Constructs | 2ndConstructs | Items | Mean | Std. dev. | Factor Loadings | Cranach’s
Alpha Values | CR | AVE |
Management of Total Quality (TQM) | | | | | | 0.72 | 0.75 | 0.52 |
| | TQM1 | 3.72 | 0.91 | 0.74 | | | |
| | TQM2 | 3.76 | 0.99 | 0.65 | | | |
| | TQM3 | 3.60 | 0.98 | 0.67 | | | |
| | TQM4 * | 3.77 | 2.38 | - | | | |
| | TQM5 | 3.69 | 1.04 | 0.66 | | | |
The JIT method of inventory management | | | | | | 0.71 | 0.73 | 0.54 |
| | JIT1 | 3.18 | 1.14 | 0.78 | | | |
| | JIT2 | 3.19 | 1.17 | 0.60 | | | |
| | JIT3 | 3.13 | 1.09 | 0.61 | | | |
Designing Processes and Capacity (PCD) | | | | | | 0.74 | 0.77 | 0.53 |
| | PCD1 | 4.01 | 1.01 | 0.64 | | | |
| | PCD2 * | 2.57 | 1.42 | - | | | |
| | PCD3 | 4.02 | 1.05 | 0.90 | | | |
| | PCD4 | 3.61 | 1.06 | 0.69 | | | |
| Management of Production and Operations (POM) | | | | | 0.73 | 0.76 | 0.53 |
| | TQM | 3.71 | 0.87 | 0.92 | | | |
| | JIT | 3.16 | 0.90 | 0.67 | | | |
| | PCD | 3.55 | 0.75 | 0.51 | | | |
Integration of Supply Chain Management (SCI) | | | | | | 0.92 | 0.93 | 0.57 |
| | SCI1 | 3.00 | 1.09 | 0.68 | | | |
| | SCI2 | 3.30 | 1.11 | 0.79 | | | |
| | SCI3 | 3.41 | 1.09 | 0.76 | | | |
| | SCI4 | 3.44 | 1.05 | 0.75 | | | |
| | SCI5 | 3.39 | 1.14 | 0.85 | | | |
| | SCI6 | 3.29 | 1.15 | 0.83 | | | |
| | SCI7 | 3.26 | 1.08 | 0.78 | | | |
| | SCI8 | 3.28 | 1.01 | 0.63 | | | |
| | SCI9 | 3.29 | 1.10 | 0.77 | | | |
| | SCI10 | 3.36 | 1.07 | 0.79 | | | |
Financial Performance of the Organization (OFP) | | | | | | 0.80 | 0.82 | 0.56 |
| | OFP1 | 3.01 | 1.19 | 0.78 | | | |
| | OFP2 | 3.29 | 1.06 | 0.75 | | | |
| | OFP3 | 3.62 | 1.16 | 0.71 | | | |
Note(s): Low factor loading is the reason for the item-related * composite reliability (CR) and average variance extracted (AVE).
The research used a measurement model that achieved a reasonable level of fit, with indices like χ2 = 405.736, df = 193, χ2/df = 2.102, CFI = 0.911, TLI = 0.900, IFI = 0.912, SRMR = 0.069, and RMSEA = 0.073. The model seems to be capturing the connections between the observable variables and latent components correctly, according to these fit indices. All of the assessment scales showed convergent validity, with average variance extracted (AVE) values higher than the suggested cut-off value of 0.50.
The measuring scales' internal consistency and reliability were evaluated by reliability studies. Overcoming the proposed criterion of 0.70, both Cronbach's alpha and composite reliability (CR) demonstrated internal credibility, dependability, and consistency. In order to evaluate discriminant validity, the researchers followed the guidance of Fornell and Larcker and made sure that the square root of the AVE value for each construct was greater than its correlation with other components. This demonstrated that the scales accurately differentiated between different concepts, a quality known as discriminant validity.
Table 3. Discriminant validity findings
Factors | 1 | 2 | 3 |
1Management of the supply chain with integrated | 0.746 | | |
2. The financial success of the organization | 0.556 *** | 0.748 | |
3. Operations and production management | 0.555 *** | 0.724 *** | 0.721 |
Significant information: the square root of the average variance extracted (AVE) is shown on the bolded diagonal of the matrix, inter-construct correlations are shown off-diagonal, and the threshold of significance is 0.001.
DISCUSSION AND IMPLICATIONS
The structural model assessment findings explain previously unexplained connections between supply chain management (SCM) integration, product lifecycle management (POM) procedures, and financial performance. Notable results show how important POM techniques are for improving financial performance and encouraging SCM integration. With this data, we can better understand how POM and SCM procedures may improve a business's bottom line. While POM practices do impact OFP immediately, the partial mediation effect shows that SCM integration also plays a role in transmitting some of this effect. This mediation technique may help businesses enhance their financial performance and integrate POM and SCM more efficiently. The mediation study has helped us better grasp the intricate relationship between OFP, SCM integration, and POM processes.
According to this study, organizations that excel in Product-Oriented Management (POM) tend to have supply chains that are more connected and efficient. When it comes to SCM integration, POM techniques are advantageous. This evaluation is in line with the RBV theory's, which holds that unique assets are critical to a company's success. Incorporating POM methods into SCM has the potential to enhance supply chain coordination, reaction times, and reactivity to customer demands. Firms may distinguish themselves with this special ability.
In addition, the research shows that POM techniques have a favorable effect on operational performance (OFP), which highlights the monetary gains that firms may make by concentrating on effective production and operations. This provides further evidence that efficient production management and operational excellence are key factors in an organization's capacity to succeed and make money.
The research also shows that SCM integration mediates the good benefits of POM practices on OFP, providing empirical proof for this claim. Previous studies have shown that supply chain integration may improve organizational performance, so this makes sense. Increased operational efficiency, decreased lead times, and increased customer satisfaction are the results of improved cooperation, communication, and coordination made possible by SCM integration across supply chain participants.
Since SCM integration acts as a mediator between POM techniques and OFP, it is clear that a holistic approach to managing production, operations, and the supply chain is essential. Organizations should be aware that POM practices and supply chain integration are interdependent and should be strategically linked in order to optimize performance.
Implications for Theory
There have been major holes in the literature about the connections between Operational Financial Performance (OFP), Supply Chain Management (SCM) integration, and Product Management (POM) techniques; this research addresses those gaps. By offering a thorough examination of the interaction between POM practices and SCM integration, it fills a crucial need in our understanding of how these two factors affect the financial performance of organizations. The research shows that good POM practices have a good impact on SCM integration, which improves financial results.
Finding out whether SCM integration mediates the relationship between POM practices and OFP is an unmet need, and this study aims to address that. While many earlier research failed to take this into account, the current investigation reveals an important pathway via which POM behaviors affect financial results. This finding provides further context for the processes at play and emphasizes the need of supply chain management integration in converting POM practices into better financial performance for businesses.
The study confirms and develops theoretical frameworks such as the RBV and the concept of operation strategy within the contexts of POM practices, SCM integration, and OFP. Researchers found that POM practices positively affect SCM integration and financial performance, with SCM integration moderating this link. This lends validity to these theoretical ideas.
Finally, the study fills a contextual gap in the literature by focusing on manufacturing firms. While previous research has largely centered on Western contexts, this study offers valuable insights into how the proposed relationships hold in a unique geographical and industrial context.
Managerial Implications
This study emphasizes the need of enhancing operational responsiveness and efficiency via the combination of Supply Chain Management (SCM) and Production Order Management (POM). It recommends that in order to maximize efficiency and cut down on waste, managers should coordinate production with supply chain strategy. Supply chain partners and departments working together may boost customer happiness, efficiency, and the flow of information. Supply chain and manufacturing may run more smoothly with the help of cross-functional teams and real-time information exchange.
Improving OFP and guaranteeing quality all the way through production may be achieved by strategic investments in POM techniques. You may enhance production flexibility and decrease inventory costs by using TQM concepts, JIT manufacturing processes, and PCD procedures. Financial results may be improved via strategic investments in these practices, which can result in cost savings and a competitive advantage.
The transmission of the influence of POM techniques to OFP is greatly facilitated by SCM integration. A well-integrated supply chain allows all partners to communicate and collaborate seamlessly, which is the emphasis of managers. Modern data systems, programs to integrate suppliers, and efficient transportation and logistics management may accomplish this.
Limitations and Directions for Future Research
The research's unclear causality is due, in part, to its cross-sectional design, which only looks at the associations between variables at one moment in time. This is only one of several limitations of the study. Future research may use a longitudinal approach to follow these variables over time to learn more about the dynamics of the connections between POM practices, SCM integration, and financial performance. This would provide stronger evidence of causative relationships. Furthermore, no other possible mediators were considered; the research just looked at SCM integration as a mediator in the connection between POM practices and financial success. To further understand the processes via which POM practices affect financial performance, future studies should look at other mediators like corporate culture, innovative skills, or IT adoption. To get a more detailed picture of how SCM integration affects financial performance, it would be helpful to measure it in a more holistic way that takes into account different dimensions and levels.
CONCLUSION
Overall, this study has looked at how OFP, SCM integration, and POM processes interact with each other in a manufacturing company scenario. Our results confirm the importance of POM practices as key contributors to operational effectiveness and financial success by highlighting their considerable impact on OFP and SCM integration. Specifically, our study identifies SCM integration as a mediating factor, emphasizing its critical role in converting efficient POM procedures into improved financial outcomes. These observations provide insightful advice to professionals working in manufacturing industry, highlighting the significance of coordinating supply chain integration initiatives with production goals in order to gain long-term competitive advantage and better financial results. In addition to advancing knowledge in academia, this research offers a useful foundation for businesses looking to optimize their supply chain and manufacturing processes in order to prosper in the cutthroat business environment of today.
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