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The earliest and most pioneering work in the field of integrated supply chains was done by Forrester (1961). Over the years, numerous studies have followed on similar lines mostly on theoretical models to prove that poor Supply chain integration results in the “Bull whip” effect or the sequential buildup of inventories right from the downstream partners to up the Supply chain. Quite the opposite happens with an integrated Supply chain. With the advent of Information technology in the form of Internet, seamless integration has become very common. The main need for IT results from the following characteristics businesses have acquired since the 90s (Liljenberg, 1996) which includes (i) customer expectations are rising, (ii) complex businesses are relying on skills and knowledge of people increasingly and (iii) power of IT lies in the heart of businesses. All these consequences require the modern businesses to stay closer to the customer to be proactive in satisfying his needs. As planning instability grows backwards up the supply chain, controlling errors with the downstream partners becomes very important. The more integrated the flow of data between channel partners, the easier it is to balance the supply and demand across the entire network. An important trend in that direction is the use of internet for Supply chain integration. Pre- internet, real time demand information and inventory visibility were impossible to achieve. This has changed in the internet era and widely available web based technologies allow strong customer and supplier integration for inventory planning, demand forecasting, order scheduling and customer relationship management.
The basic notion of channel design is that efficiency can be improved sharing information among agents and plan jointly rather than distinctly (Raghunathan, 2001). In terms of relationships between manufacturers and distributors, in order to implement coordinating mechanisms and thus attain greater efficiency in supply chain management, the partners must share information, for a number of reasons, including the following as mentioned by Cachon and Fisher (2000).
- The mechanisms allow the manufacturers to understand each customer’s specific aspects and address them in a distinct manner, adding value to the line of products
- Characteristics such as segmentation of the points-of-sales and types of customers along the supply chain should be taken into account, especially in decisions to launch new products and in dealing with each store’s mix.
There are five innovative technologies which have had significant impact on supply chain integration seamlessly: Electronic data interchange (EDI), personal computers, artificial intelligence, communications systems, bar codes and scanners.
Greater Supply-chain visibility, as well as more accurate and timely information about supply-chain execution, allows for reduced safety stocks (thus optimizing cash-to-cash cycles and reducing inventory carrying cost) and increased on-time performance to customer commitments (thus driving additional revenue opportunities). Operating cost improves, as RFID (Radio Frequency Identification) significantly reduces the cost of cycle counting, receiving, picking and shipping.
The methodology of establishing the aforementioned hypotheses is by development of a survey tool. This survey tool is in the form of a questionnaire which is administered to a set of respondents who are part of organizations and work with technologies for interaction with the channel partners. The development of the questionnaire involved evaluation of the technologies and methodologies used in the industry for e-integration. Considering the same, a primary focus of the study was to focus on the demand visibility for channel partners. An important strategy in that direction is “Collaborative planning, forecasting and replenishment”.
This was administered to a mix of respondents from Industry and academicians. The sample size for the study was thirty. GlaxoSmithKline consumer health care and Marico Industries were two of the organizations mainly involved in this study from whose employees a major chunk of the industry related response was elicited.
The exact nature of value addition through Information technology is qualitative and cannot be measured by investments made on Information technology infrastructure or types of technologies used in organizations. There have been cases where authors have mentioned about the widespread view that Information technology has made the functions difficult for execution and there has been considerable resistance to IT. It has been proven that resistance to implementation of Information technology infrastructure is a major deterrent in improving the performance of Supply chains (Frohlich, 2002). Hence, instead of using explicit values of the variables of Study, data was measured on a 5-point Likert scale from 1- Strongly disagree to 5- Strongly agree. The questions were mainly used to measure perceived benefits (in form of inventory turns and Lead time reduction) through employment of Information technology infrastructure. This would aid in obtaining insight into the prospects of Information technology usage in organizations as the complexity of Supply chain grows.
The data obtained was fed into SPSS for analysis. The final analysis was to find out if there was any impact on the third variable through a mediating variable. This was done primarily to estimate the impact of “Product visibility” on “Lead time” through the impact “Product visibility” had on “Inventory turnover. The same was carried out for the “Vice versa” case.
As mentioned earlier, the two main problems faced by Supply chains are demand uncertainty (Turban et al., 2004) and integration of Supply chain (Cooper et al. 1997; Burgess, 1998; Leeuwet al. 1999). The end result is the Lead time increase and inventory build-up. Product visibility was postulated as a factor to reduce the impact on Lead time and inventory turnover. The first step was to analyze the validity of responses obtained. The results considerably prove that accuracy was obtained for each of the three variables, (0.7 for Inventory turnover, 0.6 for Lead time, and 0.8 for Product visibility).
There is a significant influence of “Product visibility” on “Lead time” (sig<0.05). On the other hand “Product visibility” does not have a similar impact on Inventory turnover (sig>0.05). However, there seems to be a relation between the Lead time and Inventory turnover. The mode of impact, reduction of Lead time, would have on Inventory turnover is not very clear. While, there is no mention of this effect in the literature review, this may be an indirect impact of reduction of Lead time, as the number of times the inventory would be replenished may increase. To analyze the same, an analysis was carried out to investigate whether there was a significant impact on inventory turnover due to Lead time and vice versa.
The program tried to analyze the impact of a variable on another through a mediating variable. The impact of Lead Time on Inventory turnover and vice versa is ruled out. The results show that the significance level is about 0.17 or 83% confidence interval for the case when “Inventory turnover” is used as a mediating variable and 0.09 with 91% confidence interval for “Lead time” as a mediating variable. Each of these cases doesn’t fit the required confidence interval of 95%.
Hence, the next step was to analyze the impact of Product visibility on Inventory turnover and Lead time. The results show that “Product visibility” does impact Lead time as exhibited by the significance values (sig<0.05). However, the same is not observed about the “Inventory turnover” variable (sig>0.05).
The results as shown in the previous section show that Product visibility does have a performance enhancing impact. The impact it has on “Lead time” is proven by the significance values (sig<0.05 just about 0.01). However, the other result shows that there is no impact of Lead time on Inventory turnover which is evident from the significance value greater than 0.05 and lesser than the 95% confidence interval. This result is in line with the observations of certain studies done earlier. As mentioned earlier, reducing lead times has been cited as an important reason for adopting IT integration programs (Attaran, 1989; Schlie&Goldhar, 1995; McAfee, 2002).
On the other hand the impact of Product Visibility on Inventory turnover is not very clear. While, the final results show that the significance values are much higher than 0.05 and hence don’t fit in the confidence interval. Consequently, the improvement of demand information visibility across the Supply chain does not affect the inventory turnover of the Supply chain. The opposite has been the result of earlier studies based on mathematical models. It was shown that electronic data interchange (EDI) could reduce swings in inventory and safety stock levels. The simulation results of a study (Owens &Levary, 2002) showed that (among other improvements) the standard deviation of the stock level was reduced from 749 to 272 tons, leading to 400,000 $ annual savings. Also, the study on Bullwhip effect (Cachon& Fisher, 2000), shows that there is a considerable decrease in inventory build-up due to the visibility of demand information across the supply chain. The main feature of this study has been the mathematical modeling technique with four echelons built in the Supply chain. Similar models have been used in other studies too (Verwijmerenetal., 1996) to ascertain the performance enhancing effects of demand/product visibility on Inventory turnover.
At the same time the secondary impact of inventory turnover on Lead time due to improvement of “Product visibility” is also ruled out, thus, eliminating any mediation effect (sig>0.05).
The main focus of this study has been improvement of the performance of supply chain. The metrics chosen were Inventory turnover and Lead time. The transparency of supply chain i.e. the product visibility across the supply chain would lead to improvement of the performance was the expectation set by this study. The result ascertains these stated facts on the basis ofresponses from Industry. While, there have been widespread awareness and research in this area in US, Europe and other industrially developed nations, Asia has been growing its industries lately with reforms in the economic set up and governance. Hence, the percolation of Supply chain enhancements has taken time to set foot here. However, this study shows that certain sectors, primarily, FMCG goods industry are in the forefront in using technologies primarily Information technology to improve the Supply chain.
On the other hand, the other finding has been that impact is not adequate of Information technology on Inventory turnover. While, this is in contrast to earlier studies, the same is not evident by the study, enhancement effects on inventory turnover through Information technology cannot be brushed aside. However, an important outcome of the study has been the resistance observed in the industry in implementation of technology infrastructure. Since, the study is based on survey methods, the perceptions of the respondents reflect the lack of confidence in Information technology in improving the demand visibility and hence the inventory position of Supply chain partners.