|Almira Lavina Sambowo||System Engineering, Modeling, and Simulation Laboratory, Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia|
|Akhmad Hidayatno||System Engineering, Modeling, and Simulation Laboratory, Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia|
The manufacturing industry has always been one of
the most significant GDP contributors globally, accounting for approximately
15% of the global GDP. However, with unknown future challenges, the industry
must begin to consider and improve its underlying resilience capability in
order to survive. This study offers a
fundamental resilience index that can be applied to different manufacturing
industries to guide them in developing a strategy to increase their resiliency.
Resilience refers to a company’s ability to bounce back to its original or
targeted state after being disrupted or exposed to a risk. In this study,
resilience has four main factors: robustness, resourcefulness, redundancy, and
rapidity. This study combines these four factors with the four typical
organizational functions in most organizations: operations, finance, strategy,
and human resources. Each resilience factor has a set of indicators obtained
through literature studies and in-depth interviews with experts. This study
indicates that the most influential factor and resilience indicator are
redundancy and reserve funds, respectively. Furthermore, this study found that reserve funds,
customer satisfaction, and demand forecasts are the top three indicators in
terms of the highest weighted value.
Business organizational functions; Business resilience; Manufacturing industry; Performance resilience index
Indonesia currently ranks 15th in the world’s gross domestic market, and the UK-based Center for Economics and Business Research (2020) predicted that Indonesia will become the eighth strongest economy in the world by 2035, with a predicted gross domestic product (GDP) of USD 4.03 billion and a market share of 3.17%. This shows that the Indonesian economy will continue to strengthen from year to year. Manufacturing currently dominates Indonesia’s GDP, with a contribution of 19.7% (Badan Pusat Statistik [BPS], 2020). With the growing contribution of this industry, it is hoped that better attention will be paid to its progress to improve Indonesia’s economic growth in the future.
In reality, the projection of economic growth faces many challenges. One such challenge was the financial crisis and the increase in the world’s economic instability in 2008. In two years, this crisis caused a 9.14% decrease in the number of processing and manufacturing industries in Indonesia, with around 2,349 businesses becoming bankrupt, closing, or merging with other companies (BPS, 2020). Another challenge to Indonesia’s current economic growth projections was the economic crisis of 2020 that resulted from the COVID-19 pandemic. As a result, Indonesia’s GDP fell due to decreased economic activities, such as household consumption and investment in Indonesia. Similar to the 2008 economic crisis, the sector most affected by this economic crisis was the manufacturing industry. Data from the central statistics agency show that the manufacturing industry had the most extensive layoffs (BPS, 2020).
These challenges show that the manufacturing industry was the sector most affected by these crises and thus has the greatest need to prepare for future crises by developing resilient capacity. Strong resilience-supporting factors are necessary for industries to withstand the impacts of crises. This research aims to determine a resilience indicator in the product industry, which starts with understanding the organizational function and general business model of the manufacturing industry. This simple and unique approach has not been found in the many studies on company resilience. By understanding the manufacturing industry’s business model, we can identify critical points to increase its ability to survive in the face of disturbances. These critical points can then be translated into a resilience index to give complete and balanced views to guide strategy development and prioritize resources to strengthen the industry itself.
Several indicators were eliminated from the final assessment of resilience performance based on the average values obtained. Regarding the operational functions, the experts felt that seven indicators were too many. Thus, an indicator with a value above 3.0 was taken as an indicator of the operational organizational functions. Regarding the financial organizational function indicators, the total cost and inventory holding cost indicators were considered to overlap because the total cost is the sum of the inventory holding cost and other expenses. For indicators under human resources organizational functions, well-being and job satisfaction had high values. However, the data for these indicators can only be generated through separate assessments by workers.
Based on in-depth interviews and weighing the resilience performance of business systems in the manufacturing industry, we found that the most critical resilience factor was redundancy. Meanwhile, rapidity was the factor that had the lowest weight. In terms of organizational functions, the most critical resilience factor was the operational function, followed by the strategy and finance functions, while the human resources function was the factor with the lowest weight. Based on the global weighted values, reserve funds, customer satisfaction, and demand forecasts were the top three indicators in terms of the highest weighted values. The indicators with the lowest weighted values were supplier delivery lead time, customer delivery lead time, and manufacturing lead time.
As this research is still in its conceptualization stage, future research is expected to increase or reduce the number of assumptions used, thus providing more representative results. On a larger scale, the performance index can be used as the basis of a company’s resilience performance framework by creating a dynamic model that can foresee the possible resilience outcome for the industry and combine it with the resilience performance index as a quantitative score. Research can also be carried out to expand the scope of this study by including experts who work for large-scale companies, such as multinational corporations.
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