D8266118419 Advance Inventory Management

International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8, Issue-4, November 2019 Advance Inventory Management Practices and Its Impact on Production Performance of Manufacturing Industry Rashmi Ranjan Panigrahi, Jyoti Ranjan Das,Duryodhan Jena, Goutam Tanty Abstract: Inventory management is considered to be the most important function in every manufacturing firms. Steel industries in India are facing top competition in determining appropriate level of inventory that should be maintained by firms towards meeting at customer needs as well as smooth production process. Research paper aims to empirically examine the impact of Inventory Management Practices (IMP) on the Production Performances (PP) of the manufacturing industry. Due to various internal and external factors, inventory costs get volatile, which create scarcity of required inventory due to unexpected demand and supply. Looking at the global competition in recent days, the manufacturing industries are adopting various strategies related to different IMP like, ABC model, EOQ model, VMI Model, MRP, DFI etc. The present study comprises of 7 steel manufacturing firms of India and data were collected from 109 respondents selected at random by administer of structured questionnaires. The respondent selected for the study are production manager, purchase manager, warehouse manager etc. of IMP organizations. Different statistical tools were used for identification research problems. Findings revealed that selected 3 techniques of IMP have strong relationship with Production Performances. Study concludes that effective management of IMP will able to provide competitive advantages for manufacturing industry to survive in long run. Keywords: Inventory Management Practices, Production Performance, Manufacturing Firms I. INTRODUCTION As we know Inventory management is one of the key areas towards effective tool for cost reduction in business units. Effective Management of inventory will be the major function area of production and operation manager. Effective IM is critical to retailing industry because inventory has strong relationship between sales and customer service [4]. Now a day every companies trying to increase the productivity by reducing the production cost. Same can be possible by adopting scientific inventory management techniques. These techniques help to prepare strategy towards bringing continuous improvement in operational performances of manufacturing units. Revised Manuscript Received on November 08, 2019. * Correspondence Author Rashmi Ranjan Panigrahi *, Institute of Business and Computer Studies (IBCS) (Faculty of Management Science), Siksha ‗O‘ Anusandhan (Deemed to be University)Bhubaneswar, Odisha, India, Dr. Jyoti Ranjan Das, Institute of Business and Computer Studies (IBCS) (Faculty of Management Science), Siksha ‗O‘ Anusandhan (Deemed to be University) Bhubaneswar, Odisha, India, Dr. Duryodhan Jena, Institute of Business and Computer Studies (IBCS) (Faculty of Management Science), Siksha ‗O‘ Anusandhan (Deemed to be University) Bhubaneswar, Odisha, India, Dr. Goutam Tanty, School of Management, ICFAI University Jharkhand, Ranchi, India Retrieval Number: D8266118419/2019©BEIESP DOI:10.35940/ijrte.D8266.118419 To achieve this Operational efficiency, we have to fill the gap between inventory theory and practices, which was is highlighted [23] Inventory Management Practices (IMP) must be used by firm for optimum utilization of resources and adequate investment in inventory so that funds should not blocked in the form of stock [17]. IM refers to all activities in managing different levels of inventories and how supplies are available with low cost was discussed [13]. [7] Inventory are considered as ideal resources of having an economic value. Better management of inventories can help for to release capital for other productive use. Different techniques was adopted for effective management of inventory. Stochastic techniques one of the new techniques which is used to address the joint replenishment problem [17] for reducing cost structure of truck company. Cost reduction leads to profitability. [1] ABC (Always Better Control) is well accepted techniques for large manufacturing for efficient control greater amount of stock as per [9]. The reason of proper management of inventory is to reduce cost and increases the productivity. Inventory holding have significant cost in SCM [14]. A manufacturing firms always concern for proper management of materials by applying Inventory control techniques which can brings organizational productivity [19]. So, this paper was referred as conceptual cum analytical for young researcher. II. STATEMENT OF THE PROBLEM From the past study it was observed that lots of mathematical model had been developed for managing Inventory effectively. Different well accepted techniques were being applied in past research paper, where effort is best fit as per situation [22]. They have used 8 Inventory Management techniques i.e. ABC, HML, VED, SED, GOLF, FSN, SOS, XYZ to address the issues related to proper management of inventory. In this line advanced technique Deterministic models (i.e. Economic Order Quantity, Discount and black order Model, Economic production / batch Qty Model) was also used [8] But in India limited literature have been found out in the area of effective IMP on Operational Performance no research had been find out till date in India towards measurement the performance of steel Manufacturing firms. [19] In India all the steel manufacturing firms are facing tough competition towards effective management of Stock/Material in their manufacturing units. 3875 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Advance Inventory Management Practices and Its Impact on Production Performance of Manufacturing Industry III. LITERATURE REVIEW Implementation of advanced inventory management practices techniques has positively impact on production performance related to consumer goods manufacturing firms [12]. Inventory control is deals with decision making strategy to identify time, quantity and optimum stock should maintain so that purchase cost and storage cost are minimized [16]. So, Management of Inventory depending upon planning and control function. [3] Effective IMS is very much required in operation of any business. Sl N o Author [1] 1 2 [15] [11] 3 4 [24] Volume, Issues, Journal Title, Objectives 23(2): 135-142 (2010) Journal of social Sciences A Tool of Optimizing Resources in a Manufacturing Industry A Case Study of Coca-Cola Bottling Company, Nigeria. The objective is to identify inventory is being maintained or not as per various existing optimization tool of IM in Coca-Cola bottling plant. 3(5):( 2013) International Journal of Business , Humanities and Technology Methodol ogy & Technique s Used Variance Analysis, EOQ Model, Chi-Squar e method The Impact of IMP on Financial Performance of Sugar Manufacturing firms Objectives is to find out impact of IMP on financial Performance How far firms can abe to adopt Lean Inventory system , technology and strategic supplier partnership in manufacturing process. Findings of Paper Gap of Paper This paper reveals that company doesn't follow EOQ model for Raw material order. Bottling plant made huge investment in IM. Usage of Inventory depends on Sales. Usage of Inventory should be focuses on sales and production cost. Next study can be based on forecasting model of Inventory Primary Data collected through Questionnai re, Descriptive analysis, Correlation analysis 1(4):392-40 6 (2015) International Journal of supply and operation management IMP and OP of Flour milling firms in Lagos. This study is based on impact of advance IMP on operational capabilities of flour mills. Quantitive Research Design, Descriptive analysis applied. Advanced IM techniques are tested i.e. ABC model, JIT model, Scientific Inventory Model etc. 5(5):82-89 (2016), Journal of Investment and Manageme nt Effect of I C Strategies on Inventory Record Accuracy in Kenya Power Company, Objectives is to find out the Effect of ICS (Cycle counting, inventory Coding and computerized Inventory Accuracy) on Inventory record Accuracy. Descriptive (correlation and Regression) and Inferential Analysis. Single t test also used to test the hypothesis Retrieval Number: D8266118419/2019©BEIESP DOI:10.35940/ijrte.D8266.118419 3876 Positive correlatio n between IMP with ROS and ROE. JIT , VMI & MRP can further be studied for better analysis it will helps in implementation of Advance IMP in manufacturing Industry. JIT, CIS, EOQ, are 3 effective IMP which have significance impact on OP of company. EPQ and MRP techniques need to adopted for measure effectiveness of IMP on OP of large Manufacturing Industry. Inventory Control Practices have positive impact on Inventory Record accuracy Gap is the study can be based on Role of Mgt. on ICP and its impact on Operational Performance of company. Published By: Blue Eyes Intelligence Engineering & Sciences Publication International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8, Issue-4, November 2019 5 [2] 5:(2018 ) Cogent Busines s and Manag ement The Impact of IMP on Firm's Competitiveness & Organizational Performances- Empirical evidence from micro and small enterprises in Ethiopia. This paper is based on what IMP followed in MSEs in Manufacturing sub sector, its impact on firm‘s competitiveness and organizational performances. Conceptual framework was tested through SEM model. Profitability, levels of output, and cost efficiency High level of IMP had leads to enhanced competitive advantages and helps in improving in organizational performances Study can be applied to large scale industry. Objective measure against profitability, level of output, cost efficiency will help to better representation of the concept. THEORY OF CONSTRAINTS (TOC) Theory of constraints (TOC) was based on stock management principle. For every organization it is very important to maintain good flow of inventory management throughout production systems. the reason of introducing theory of constraints (TOC) in this inventory management practices because it act as a tools that support continuous improvement in imp (inventory management programme). it is built as a conceptual model which acting as a chain, that advocate ―chain is only as strong as its weakest link‖ theory of constraints (TOC) was based on five steps such as, ― identify the system constraint, decide how to exploit the constraint, subordinate everything else, elevate the constraint, return to step one, but beware of inertia‖ . for developing reliable PPC (production planning and control) in inventory management through toc can help to reduce machine down time, tools breakage, lack of a component availability, scrap, reducing order timing. Three methods of TOC can help effective management of inventory are increase throughput, reduce inventory, reduce operating expense. Through TOC dependencies breaks by creating material buffer. TOC theory uses as a set of tools that act a change agent to manage constraints, whereby profit increases. It always focuses on achieving a reduction of organizational inventory. IV. OBJECTIVES AND HYPOTHESIS OF THIS STUDY This study is based on the objective to identify how manufacturing firms can make proper use of IM Practices for bringing their operational efficiencies. To hold the above statement, we have considered the following specific objectives 1. To know different AIM Practices adopted by steel manufacturing firms in Odisha. 2. To find out the significant relationship between Advanced IM techniques and operational efficiencies of manufacturing Industry in India. To achieve the above specific objectives, we have considered this specific Hypothesis: H01. Implementation of Advanced IM practices has a significant impact on production performance of manufacturing industry. Retrieval Number: D8266118419/2019©BEIESP DOI:10.35940/ijrte.D8266.118419 CONCEPTUAL FRAMEWORK [aimp of manufacturing units: economic order quantity of im, vendor managed inventory of im, abc model of im ,material requirement planning of im , demand forecast inventory of im , (production performance measurement items- rpc- reduction of production costs, rrw -reduction resource wastages, cip continuous improvement in production, rsr - reduce no of scrap and rejects, mdlt - minimization of delivery lead time, mmd -minimizing manufacturing downtime)] V. METHODOLOGY USED The research paper is based descriptive analysis and data were collected through structured questionnaire [11]. from key officials of the manufacturing industry. The cross-sectional survey design is also used in the study for collecting responses from a large population at a single point of time. This method helps to compare different variables at the same point of time. A Five-point Likert scale is used in the instrument to collect the data with respect to IMP adopted by manufacturing industries for improvement in operational efficiency. The questionnaire was piloted for checking its validity and test the reliability done on the basis of Cronbach‘s alpha coefficient for measurement scale. The result shows a coefficient value of 0.832, which is way ahead of minimum acceptable threshold limit of coefficient value 0.70 as [21]. Above 0. 90 % of the questionnaires that were administered & returned represent the reliability response rate of the study. The study considered the Independent variable as IMP (Inventory management practices) and PP (production performances) as the dependent variable. Respondent of this paper based on managers of different position i.e. production manager, store cum warehouse manager, operation manager, quality control manager, of five number of steel manufacturing Industries includes SAIL, TATA Steel, MESCO Steel. Sree Metaliks, MSP Steels. Descriptive statistics were used to find out the positive relationship of Advance Inventory Management techniques with production performance of manufacturing industry selected manufacturing industry. Correlation and regression 3877 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Advance Inventory Management Practices and Its Impact on Production Performance of Manufacturing Industry analysis used to measure the relationship between explanatory variables [6] and explained variable [9]. A purposive sampling technique was used to select 120 sample respondents from 5 manufacturing firms mentioned of Odisha. Out of which 109 samples respondents were found to be suitable for the study as per the response rate. strategies have corresponding change effect on OP of firms. (for details please refer Table-2) [refer with: Table 2 . Pearson Correlation Matrix of Relationship among AIMP and PP] VI. RESULT AND DISCUSSION This section deals with current state of IMP which based on ( Table -1) descriptive analysis of each 5IMP factors. It is clear ̄̄̄̄̅̅ from analysis that most accepted IMP were: EOQ (X =3.71, ̄̄̄̄̅̅ ̄̄̄̄̅̅ SD=1.012), VMI (X =3.16, SD=0.983), ABC (X =3.09, ̄̄̄̄̅̅ ̄̄̄̄̅̅ SD=1.102), MRP (X =3.09, SD=1.198), DFI (X=2.70, SD=1.084). The study shows that most common AMP among manufacturing firms are EOQ, MRP, ABC etc. while DFI and VMI model represent as least adopted method. analysis of different factors which used to measure the operational performance of manufacturing firms, based on mean and standard deviation values. Highly effective factors of OP are: Reduction of production costs (X̄̄̄̄̅̅ =3.08, SD=1.233), Minimization of delivery lead time (X̄̄̄̄̅̅ =3.27, SD=1.274), Reduction resource wastage (X̄̄̄̄̅̅ =3.36, SD=1.21), Reduce No of scrap and rejects (X̄̄̄̄̅̅ =3.19, SD=1.22), Minimizing manufacturing downtime (X̄̄̄̄̅̅ =3.21, SD=1.32), Continuous Improvement in production (X̄̄̄̄̅̅ =3.46, SD=1.21). Its mean deviation ranges from 3.71 – 2.70 and SD ranges lies between 1.320-0.983. It shows IMP has significant effect on OP of steel Manufacturing firms. Major effect of IMP on reduction of production cost, minimization of down time, less stock out and less will be the material shortage cost and also reduces the wastage. It will intern increase the moral of employees. [Refer with: Table 1 Calculation of Descriptive Statistics represent Advanced Inventory Management Practices & Production Performances parameters adopted] Source: Author’s Computation Hypotheses - H01(Advanced IM practices has a significant effect on the production performance of manufacturing firms) Table -2 shows that 5 number of contextual variables of AIMP have significant and positive relationship with 5 number of variables of PP. Economic Production Quantity, Vendor Managed Inventory, ABC Model, MRP Model, Demand Forecasting Inventory are independently as well as positively correlated with OP. it was tested with significant level of 1%. Analysis reveals that maximum correlation between (r=0.199, P<0.01) exist between EOQ and PP, followed by VMI (r=0.010, P<0.01), ABC (r=0.000, P<0.01), MRP (r=0.000, P<0.01) and DFI (r=0.000, P<0.01). This analysis suggests that as per the deployment of above IMP Retrieval Number: D8266118419/2019©BEIESP DOI:10.35940/ijrte.D8266.118419 *** significant level of Correlation is @0.01 level (2-tailed) * significant level of Correlation is @0.05 level (2-tailed) Source: Author’s Computation Implementation of AIMP (Advanced inventory management practices) has positive effect on PP (production performance0 of Indian steel Industry. [refer with: Table 3. Regression Result of IMP and Production] Regression analysis presented in Table 3 which is used to find out the relationship between IMP and PP by taking into variables. The value of R is positive (0.738). R2 (square)(0.545), which shows that 54.5 % of total variation in dependent variable (PP) on independent variable (AIMP). Durbin-Watson is a test for autocorrelation, have the test statistic range of 0 to 4 and according to D-W values ranges from 2 to 4 indicate negative autocorrelation so according to this condition analysis says D-W 2.145 which implies that there is no significant amount of auto correlation in the regression model. 5 IMP can explain around 66.9%(0.699)of total variation in production performance at a level of significant of 5%. [refer with: Table 4. ANOVA of the Regression Model] 3878 Published By: Blue Eyes Intelligence Engineering & Sciences Publication International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8, Issue-4, November 2019 VII. CONCLUSION, LIMITATION AND FUTURE WORK The ANOVA on regression model yield a F-value of 24.639, which explains the equation is significant at 5%(P<0.05%). The P -value is 0.0005, which is than 0.5%. and it indicates that overall regression model is statistically significant to predict the outcome variable i.e hypothesis deals with implementation of Advanced IMP have significant effect on Production Performance of manufacturing unit is justified. Table 5 - Deals with multiple regression analysis to know the status of IMP has significantly contributed mostly on OP of manufacturing firms. It is which variables included in the proposed model rightly contributed cum predicted to the dependent variables. Each independent variable in the study is compare on the basis of its contribution, by using Beta (β) values. Largest beta coefficient value is 0.550 or 55.0% which is the use of MRP of Inventory management practices. Next close to the above is 0.139 or 13.9% of ABC, 0.113 or 11.3% of VMII, 0.0016 or 1 % of EOQ, , 0.078 or 7.8% of DFI. it means above 1st three IMP (MRP, ABC and VMI) have positive and significant participation in determining dependent variables i.e. PP. [refer with: Table 5. Multiple Regression Equation for H02] The aim of this article is to calculate the contribution of AIMP on improving PP of steel manufacturing industry was represented by Hypothesis (H01). It proposes that IMP has no significance impact on OP of manufacturing firms, which become nullified by the result and analysis. It was hence proof from regression analysis, which represent IMP can represent .699 or 69.9% of total variation in OP. Analyzing study outcomes represent that relationship between AIMP and PP is highly significant in seven steel manufacturing firms. Apart from selected large manufacturing firms, it was observed from the study that Inventories strategy adopted by manufacturing firms are of totally different from a traditional well-accepted model i.e. EQO, MRP, VMI, etc. Manufacturing firms Advance IM Strategies, policies should be based on different factors i.e. current industry practices, altering customer preferences, right forecasting estimates and available production capacity of the manufacturing units. In recent times Performance dimension of flexibility, service, cost quality and innovation contributed immensely for good IMP [18]. AIMP in enhancing following factors Reduction resource wastage, Continuous Improvement in production, Reduce Number of scraps and rejects, minimizing manufacturing downtime, Reduction of production costs can be addressed by 5 highly positively significant techniques as per results. Many of the industry not aware about DFI and Barcoding techniques and their effective use in production units. If latest technology are adopted then production performances will increase. LIMITATION AND FUTURE WORK This study has several limitations. Instrument as a questionnaire for the measurement construct are not standardize one [2]. However, questionnaire is obtained through intensive literature review. Future research must re-validate measurement scale used under different situation and for small and medium scale Industry. Future research should seek to utilize multiple respondents from each participating enterprise to enhance the research finding. Another limitation of this study is the measurement of PP construct. The study is based on views of respondent to evaluate their operational performance regarding reduction of production cost, minimization of manufacturing down time, reduction resource wastage, Reduce Number of scrap and rejects is subjectively. Study can be extended to use of AIMP should applied towards reduction of caring cost and holding cost Subjective evaluation may increase measurement error due to relatively low reliability. Objective measurement will give more accurate information for better analysis. REFERENCES Background of the study represent the actual fact regarding most accepted variables of AIMP i.e. ABC, VMI, MRP, DFI and to some extent EOQ, which have significant contribution in manufacturing industry towards operational performance. It helps the firms to achieving competitive advantages. One of interesting fact is that the result of this article was supported by earlier researcher‘s literature reviews [John, N. E., Etim, J. J.et.al. (2015) and Velmathi, N., & Ganesan, R. (2012).] etc. Retrieval Number: D8266118419/2019©BEIESP DOI:10.35940/ijrte.D8266.118419 3879 1. Adeyemi, S. L., & Salami, A. O. (2010). 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A case study on inventory management using selective control techniques. Journal of The Association of Engineers, India, 82(1), 10-24. 17. Mustafa Tanrikulu, M., Şen, A., & Alp, O. (2010). A joint replenishment policy with individual control and constant size orders. International Journal of Production Research, 48(14), 4253-4271 18. Onyango, R. M. (2013). Lean enterprise and supply chain performance of pharmaceutical companies in Kenya. MBA Project. University of Nairobi. 19. Panigrahi, R. R., & Jena, D. (2020). Inventory Control for Materials Management Functions—A Conceptual Study. In New Paradigm in Decision Science and Management (pp. 187-193). Springer, Singapore. 20. Sah, A. N. (2009). Data Analysis Using Microsoft Excel. Excel Books India. 21. Santos, J. R. A. (1999). Cronbach‘s alpha: A tool for assessing the reliability of scales. Journal of extension, 37(2), 1-5. 22. Swarup, k. Gupta. p. k. & Manmohan, Operations Research, Sultan Chand ... Wiley and Sons, 2003 23. Tiwari, V., & Gavirneni, S. (2007). ASP, the art and science of practice: Recoupling inventory control research and practice: guidelines for achieving synergy. Interfaces, 37(2), 176-186. 24. Tundura, L., & Wanyoike, D. (2016). Effect of Inventory Control Strategies on Inventory Record Accuracy in Kenya Power Company, Nakuru. Journal of Investment and Management. Vol, 5, 82-92 25. Velmathi, N., & Ganesan, R. (2012). Inventory management of commercial vehicle industry in India. Ijemr, 2(1), 34-45. 26. Zanakis, S. H., Austin, L. M., Nowading, D. C., & Silver, E. A. (1980). From teaching to implementing inventory management: Problems of translation. Interfaces, 10(6), 103-110 papers in National and International journals. He is also served as University-approved faculty of Sikkim Manipal University (DE) and also a registered as a faculty of BPUT, Rourkela, Odisha. He was received best paper presenter award in National and international conferences for the year 2016, 2018 and 2019. He was also an author of 1 book ―corporate Strategy‖. He is a life member of OCA (Orissa Commerce Association) & (ORSI) Operational Research Society of India. He has attended many FDP, Seminars in & around Odisha, Jharkhand, Indore etc. Prof. Jyoti Ranjan Das [PhD, MBA, M.Phil., MDJEC, LLB] is working as Professor in the Institute of Business and Computer Studies (IBCS) (Faculty of Management Science), under Siksha ‗O‘ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India. He has 20 years of vast experience in academics. he has more than 25 number of research publication in international journals Dr. JRD of repute. He had already guided 7 PhD scholar. He is well known as a young management expert in the state of Odisha. he was being invited as Resources Person, Chief Guest and as a delegate to various institution in national level. Dr. Duryodhan Jena [(MSC, M.Phil. and PhD in Statistics), MBA] is working as Associate Professor in the Institute of Business and Computer Studies (IBCS) (Faculty of Management Science), under Siksha ‗O‘ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India. He has 16 years of vast experience in academics. and 3 years of Research experience (NCDS, Dr. D. Jena NABARD chair, SOHUM foundation). 4 number of PhD scholars are pursuing PhD under his guidance. He is an active member in different Industry Associations. Dr. Jena has several publications in national and international journal of repute. He is a life member of Operational Research Society of India (ORSI). Dr. Goutam Tanty [MBA, PhD} Is Currently Working as An Associate Professor in Faculty of Management Studies at ICFAI University, Jharkhand. He Has 1 Year of Industry Experience And 13 Years of Academics Experience in The Area of Financial Management, Insurance Management, Banking Management, Security Analysis and Dr. G Tanty Portfolio Management. He Has Published Around 8 Research Papers in Various National and International Journals and Also Presented Research Papers in Both National and International Conferences. 5 number of PhD scholars are pursuing PhD under his guidance His Research Interest Includes Stock Market, Financial Derivative, Insurance, Banking and Financial Accounting. He has guided 3 PhD scholar. AUTHORS PROFILE Rashmi Ranjan Panigrahi [MBA, M.Com, PhD(Contin…)] is a Research Scholar in the Institute of Business and Computer Studies (IBCS) (Faculty of Management Science), under Siksha ‗O‘ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India. Prior to joining as doctoral student, he was headed the position as a Principal of Rajdhani College of Science, technology & Management (Affiliated to Utkal University) under Rajdhani Mr. RRP Group of Institution, Near Mancheswar, Bhubaneswar, Odisha. He has 8 years of academic as well as administrative experience and 1 year of corporate experience. He has presented 7 papers in National & International Seminars & published 9 odd Retrieval Number: D8266118419/2019©BEIESP DOI:10.35940/ijrte.D8266.118419 3880 Published By: Blue Eyes Intelligence Engineering & Sciences Publication