A Case Study: IoT in logistics and supply chain management: Evaluating the adoption rate, associated challenges and impact on cost and business efficiency
The global business market of current century is characterized by strong competition. Globalization, development in information system based technologies is the primary reasons of this competitive business atmosphere. With its more than 1.2 billion population, India is a strategic area for any business entity. Rapid growth on information technology and proliferation of internet users has made the country even lucrative for business opportunities. Retail sector of India riding the wave of information technology boom, has ventured into the e-retailing space. The increasing adoption of internet among various strata of society and rapidly growing number of online shoppers have enabled steady growth of this sector. However, there is no dearth of challenges. Inventory management, warehousing, supply chain, customer relation are some of the many areas of e-retailing business that need constant improvement. Internet of things is one of the developments of present era information technology. Implementation of IOT to various segments of business processing can provide adequate solution wherever necessary. The present research will be conducted in the form of case study. It will focus on one e-retailing company of India and will analyze the process of IOT implementation in the supply chain management.
- Case Body
- IOT in Supply chain
Ping, Liu, Zhou & Wang (2011) conducted research on the application of Internet of Things for the supply chain management process of business organizations. They postulated that supply chain is the combined network of production units, warehouses, suppliers, distribution centers, end retailers and the customers. Supply chain is responsible for acquirement of raw materials, transfer of those material to the production unit, transfer of produced goods to the warehouses, to the retailers and finally to the customers. Thus the processes of supply chain are complex and its effective and efficient running depends on the material and information flows. Internet of things is the technological extension of internet. IOT can enable connectivity between objects and points. Thus real time monitoring of supply chain execution processes will be possible through application of IOT in various operational segments. The below table shows the activities of IOT in supply chain in comparison to the internet.
|Activity||Strategic Decision||Tactical & Operational Decision||Internet||IoT|
|Purchase||Supplier selection, Long term cooperation vs. short term deals||
Type and quantity of the material to be purchased; date, time and location of arrival
|E-procurement: Allows companies to use the internet for procuring materials; E Collaboration: allows companies to use the Internet for negotiating and sharing information, as well as handling value-added services like transportation, warehousing, customs clearing, payment, quality validation, and documentation||Like the Internet, eprocurement and e-collaboration can be implemented over the IoT; Ubiquitous information: allows companies to use the IoT for capture the real-time state of the material to be purchased.|
|Fabricate||Factory location; outsourcing vs. in-house making; mode of production||Scheduling production; allocating resources; due date||E-collaboration: Allows companies to use the Internet for coordinating the time of production, the allocation of resources, and the alternation of due date.||Like the Internet, e-collaboration can be implemented over the IoT; Optimization & surveillance: allows companies to use the IoT for optimizing and monitoring the process of production realtimely|
|Transport||Transportation network; outsourcing vs. in-house function||Planning optimal routes for vehicles||Ubiquitous information: allows to use the IoT for obtaining information about the state and location of products during the process of transporting|
|Store||Warehouse location; inventory management strategy selection||Loading/unloading operations; inventory level;||VMI/JMI (Vendor managed inventory/Joint managed inventory): allows vendors (and companies) to use the Internet for managing inventory (jointly).||Like the Internet, VMI/JMI can be implemented over the IoT; visual inventory management allows the dynamic information about the inventory to be collected automatically over the IoT|
|Market||Demand forecasting; Distribution network design||Order fulfillment; customer service||E-commerce: helps a network of supply chain partners to identify and respond quickly to changing customer demand captured over the Internet||Like the Internet, e-commerce can be implemented over the IoT and customers can understand the process of fabricating and transporting over the IoT|
Table 1: Activities of IOT in supply chain in comparison to internet
Source: Ping, Liu, Zhou & Wang (2011)
Li (2011) studied the application of Internet of Things in green agricultural products supply chain management in China. The study found that application of IOT in supply chain had become advantageous for green agricultural produce. It had benefited the agricultural information sector. The study also found gap between the applied research in the field of IOT and its practical applications with respect to supply chain management. The study found differences in applications of IOT to various green products. The supply chain management processes of all the green produces were not same and they needed different application methods.
According to the research of Cortes, Boza, Perez & Cuenca (2015) Sensing Enterprises (SE) was an characteristic of information technological process that reacted to stimulus from the internet sources. The research study focused on the application of similar internet based technologies in supply chain management processes. Their study pointed that there were three prominent pillars of IOT. Those were: to be identifiable, to communicate and to interact. All these three activities could be achieved either among the IOT devices, or among networks of interconnected objects, or amongst the IOT devices and end users or with other entities present in the network. The study pointed out three specific applications of IOT implementations in supply chain management of fresh agricultural products. The first benefit was the monitoring of quality and food security of fresh agricultural products. Involvement of IOT enabled gathering of information through the whole process, starting from raw materials procurement to production, processing, distribution and finally sales. The second benefit was the establishment of management information system that could results in increased integration of supply chain processes to the overall systems of companies dealing with fresh agricultural produces. Information collection and dissemination among all the stakeholders of the processes would help the companies in connecting and coordinating all the nodes of business. The third prominent benefit was the reduction in cost of overall supply chain procedure along with improvement in efficiency of the system. Application of internet of things could reduce the cost of physical links of supply chain management processes and increase the efficiency of the channel.
- Applications and Challenges to IOT implementation in Supply Chain Management
Li (2013) in his research on use of technology to combat fraud in global supply chain found that internet of things could be used as a countermeasure. IOT models can be used to create check counterfeiting products. Authentication technology can include physical examination of products as well as communication between concerned parties. Users and sellers can be verified and the same information can be shared with all involved stakeholders.
Qiu, Luo, Xu, Zhong 7 Huang (2014) conducted a study on public logistics services of Supply Hub in Industrial Park. The study proposed an IOT enabled supply chain system for the area. The process envisaged upgradation of traditional model of supply chain into an information technology enabled model. The proposed IOT enabled model was intelligent, real-time and highly collaborative. Another information infrastructure was also proposed in the study that would match various divisions of departments or nodes within the supply chain processes. Implementation IOT model in the logistics services system enabled proper flows of physical goods along with information from one node to another.
According to Lee & Lee (2015) internet of things has a host of applications in supply chain management system of business organizations. The study broadly classified the applications into three segments. Those segments are represented in the below table.
|1||Monitoring and control||Collect data on equipment performance, energy usage, and environmental conditions, and allow managers and automated controllers to constantly track performance in real time anywhere, anytime. Advanced monitoring and control technologies such as smart grid and smart metering reveal operational patterns, spot areas of potential improvement, or predict future outcomes and optimize operations, leading to lower costs and higher productivity|
|2||Big data and business analytics||IoT devices and machines with embedded sensors and actuators generate enormous amounts of data and transmit it to business intelligence and analytics tools for humans to make decisions. These data are used to discover and resolve business issues such as: changes in customer behaviors and market conditions to increase customer satisfaction, and to provide value-added services to customers. Business analytics tools may be embedded into IoT devices, such as wearable health monitoring sensors, so that real-time decision making can take place at the source of data|
|3||Information sharing and collaboration||Information sharing and collaboration in the IoT can occur between people, between people and things, and between things. Sensing a predefined event is usually the first step for information sharing and collaboration. In the supply chain area, information sharing and collaboration enhance situational awareness and avoid information delay and distortion|
Table 2: IOT categories for enterprises applications
Source: Lee & Lee (2015)
The implementation process of internet of things in supply chain management in not smooth as there exist many challenges. Gartner (2014) pointed that IOT systems were prone to multiple challenges with respect to security, consumer privacy, the enterprise, data self, server technologies, storage management and networking. Table 3 represents the challenges to IOT in terms of technical and managerial challenges.
|1||Data Management Challenge||IoT sensors and devices are generating massive amounts of data that need to be processed and stored. The current architecture of the data center is not prepared to deal with the heterogeneous nature and sheer volume of personal and enterprise data. Consequently, they will prioritize data for operations or backup based on needs and value. Data centers will become more distributed to improve processing efficiency and response time as IoT devices become more widely used and consume more bandwidth.|
|2||Security Challenge||IoT devices have vulnerabilities due to lack of transport encryption, insecure Web interfaces, inadequate software protection, and insufficient authorization. On average, each device contained 25 holes, or risks of compromising the home network. Devices on the IoT typically do not use data encryption techniques.|
|3||Data Mining Challenge||As more data are available for processing and analysis, the use of data mining tools becomes a necessity. Data consist not only of traditional discrete data, but also of streaming data generated from digital sensors in industrial equipment, automobiles, electrical meters, and shipping crates. These streaming data are about location, movement, vibration, temperature, humidity, and even chemical changes in the air. Data need to be tamed and understood using computer and mathematical models. Traditional data mining techniques are not directly applicable to unstructured images and video data. Coupled with the need for the advanced data mining tools to mine streaming data from sensor networks and image and video data, there is a shortage of competent data analysts.|
|4||Privacy Challenge||IoT devices can provide a vast amount of data on IoT users’ location and movements, health conditions, and purchasing preferences–—all of which can spark significant privacy concerns. Protecting privacy is often counterproductive to service providers in this scenario, as data generated by the IoT is key to improving the quality of people’s lives and decreasing service providers’ costs by streamlining operations.|
|5||Chaos||The evolution of IoT technologies (e.g., chips, sensors, wireless technologies) is in a hyper accelerated innovation cycle that is much faster than the typical consumer product innovation cycle. There are still competing standards, insufficient security, privacy issues, complex communications, and proliferating numbers of poorly tested devices.|
Table 3: Challenges to IOT
Source: Source: Lee & Lee (2015)
The present research study will try to figure out following research questions.
➢ What was the state of supply chain management process of the E-Retail company before IOT implementation?
➢ What were the challenges faced by the company during IOT implementation in supply chain management process?
➢ What are the impacts of IOT implementation to the business and operational cost of the E-Retail company?
➢ What are the impacts of IOT implementation to the business efficiency of the E-Retail company?
➢ What are the other benefits of IOT implementation to the E-Retail company?
- Research Notes
The current research study will follow case study method of research. One particular E-Retail company of India will be selected as the case and the research will be carried through proper prior permission from concerned authorities. The research will follow following processes.
The research study will cover below mentioned management issues with respect to implementation of IOT in supply chain processes of one E-Retailing company.
➢ Efficiency through improved inventory management
➢ Real time supply chain management
➢ Increased logistics transparency
➢ Impact on the cost of business
➢ Physical challenges to IOT implementation
➢ Logical Challenges to IOT implementation
➢ Technological challenges to IOT implementation
The present case study will focus on implementation of IOT to the supply chain management process of one E-Retail company. The result of the study will help the concerned organization in evaluating its position and processing practices with respect to IOT implementation. The cost and business efficiency analysis will provide cognizance regarding its business standing. The company can evaluate its own policies and working procedures with respect to IOT in supply chain and reframe its business practices so as to optimize its business efficiency and productivity. Improved logistics management, transparency, real time supply chain management and reduction in cost of operations are some of the advantages the company will get by considering the results of this study. Other e-retailing companies can also benefit from the present study in similar manner by adopting the research procedure followed in this study.
- Objectives of the Case Study
The present case study is situational in nature as it will evaluate implementation rate of IOT in supply chain and will also analyze the associated challenges and impact on cost and business efficiency of the organization. Following are the objectives of the present case study.
➢ To assess the state and implementation rate of IOT in supply chain management process of E-Retail industry in India
➢ To analyze the challenges faced by E-Retail companies while implementing IOT in supply chain
➢ To assess the impact of IOT implementation on the operational cost of E-Retail companies
➢ To analyze the impact of IOT implementation on the business efficiency of E-Retail companies
- Data Collection and Analysis
Information for the current case study will be collected from one E-Retail company. Both quantitative and qualitative data will be collected from the organization. For quantitative data collection a set of close ended questionnaire will be prepared and distributed among selected respondents from the studied company. Qualitative data will be collected through interviews. Judgmental sampling method will be employed to select few high ranking employees of the organization working in the field of IOT implementation and supply chain. The interviews will be semi structured in nature so that the respondents can give detailed information of the research subject. Secondary data will be collected through journals, past literatures, annual reports, and internal reports relating to IOT implementation in supply chain.
The collected data will be analyzed using two methods. Qualitative data will be analyzed through thematic analysis. Quantitative data will be analyzed by the use of various statistical tests. SPSS software will be used for those statistical tests.
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- Li, L. (2011, March). Application of the internet of thing in green agricultural products supply chain management. In Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on (Vol. 1, pp. 1022-1025). IEEE.
- Cortés, B., Boza, A., Pérez, D., & Cuenca, L. (2015). Internet of Things Applications on Supply Chain Management. World Academy of Science, Engineering and Technology, International Journal of Computer and Information Engineering, 2(12).
- Li, L. (2013). Technology designed to combat fakes in the global supply chain. Business Horizons, 56(2), 167-177.
- Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431-440.
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- Gartner. (2014, March 19). Gartner says the Internet of Things will transform the data center. Retrieved from http://www. gartner.com/newsroom/id/2684616
- Pang, Z., Chen, Q., Han, W., & Zheng, L. (2015). Value-centric design of the internet-of-things solution for food supply chain: Value creation, sensor portfolio and information fusion. Information Systems Frontiers, 17(2), 289-319.