Task 1: Data Collection and Storage
The paper reflects on the importance of “Big Data for Supply chain and operation management”. According to Hazen et al. (2014), big data is one of the evolving term that helps in describing any voluminous amount of structured, unstructured as well as semi-structured data which has potential to be mined for information. Big data is utilized for managing supply chain as well as other operations of the organization. It is stated by Schoenherr and Speier (2015) that big data helps in making the supply chain of the organization much more efficient as well as better optimized for enhancing their bottom line. The utilization of big data in organization helps in improving responsiveness, demand planning, inventory planning and development that further assists in providing continual benefits in the field of supply chain management. On the other hand, it is opined by Tan et al. (2015) that with the adoption of big data, the various operations of organization are managed appropriately within the organization. It is identified that with the application of big data, the various operations are planned, organized as well as supervised in context to production, manufacturing and provision of services.
The report mainly elaborates the importance of big data in context to supply chain and operation management. The assignment illustrates data collection, storage, and importance of data in action. The paper also provides proper recommendation in order to solve online business problem in case of power outrage and other disasters.
1.1 Data Collection System
According to Chae (2015), data collection system is defined as a system that helps in aggregating and evaluating all sets of information in a very much consistent as well as efficient way. It is identified that modern data collection method generally relies on advanced technology that helps in taking huge amount of data for analyzing them appropriately. Big data plays an important in collecting various kinds of data by following proper techniques or methods. The different kinds of data that are collected are as follows:
Supply chain related data: It is identified that most of the business organizations are facing challenges due to absence of proper supply chain related data. Proper information as well as data related with supply chain must be collected for improving both service and efficiency of the organization. It is found that with the growth of appropriate digital technologies, companies are mainly able to collect massive amount of data, which subsequently needs powerful techniques (Christopher 2016). Analyzing the data of the customer generally helps in generating useful insights on pricing strategy, labor optimization, operational risk management and product placement. Some of the key benefits of using big data in collecting data related with supply chain include enhanced efficiency, improved productivity and edge with competitors.
Marketing data: The marketers utilize big data for collecting proper information related to the business. The marketing related information like purchase data, browsing behavior, social media interactions and more are collected from different organization. All this information that are collected with the help of the big data are integrated with proper marketing strategy for creating proper impact on customer engagement, customer retention as well as on marketing performance (Tachizawa et al. 2015). The information as well as data related with marketing are generally collected by analyzing the reviews of the customers, surveys, internet and government agencies.
1.2 Storage System
Financial data: It is identified that big data analytics engages in collecting as well as analyzing different types of data and information. The data that are collected can be a historical data, which is stored within a database, or the information that is being collected from bank, shopping centre as well as insurance company. Analyzing huge amount of data and information can occur in various ways. It is found that various types of algorithms and complex system are generally built for the same purpose (Agrahri et al. 2017). It is identified that data are mainly analyzed for various patterns that can be utilized for predicting the trends of the future, for calculating risks as well as for determining the prices. Big data collects information related to bank, credit cards as well as credit card unions for determining the level of risk. The financial companies are utilizing big data for improving their products, for reducing cost and for making the customers happy.
Operation management data: The data related with operation of the organization must be collected properly for increasing efficiency in context to expenditure and operations. It is identified that most of the organization utilizes big data for having appropriate data collection and analysis procedure for enhancing their profitability (Kwon, Lee and Shin 2014). The data related with the operations of the organization helps in organizing, planning as well as supervising in context to manufacturing as well as production.
It is found that in the traditional days, data are generally utilized for storing written documents, which are mainly managed with the help of marketing and management team of the organization. The written documents that are stored are not safe as they can be hacked or destroyed at anytime due to unavailability of appropriate security. In order to resolve this type of problem, big data is mainly introduced within the organization (Demirkan and Delen 2013). It is identified that big data helps in providing unlimited amount of storage capacity to the business owners so that both the operations as well as supply chain of the organization is managed appropriately. Additionally, various types of guidelines as well as rules are also present before the business organization after successful implementation of the big data analytics (Wixom et al. 2015). It is found that before the implementation of modern procedures of data collection, the data that are related with customer relationship management, supply chain management and other important information are stored with the help of manual procedure.
After the successful implementation of big data analytics tools, the data that are related with supply chain as well as operation management can be stored in any type of storage devices as per need. It is found that the method of automatic data collection is much more effective as compared to the procedure of manual data collection method. For supporting the various requirements of the business, it is very much significant to add appropriate values in context to various technological components (Papadopoulos et al. 2017). In order to support the needs as well as requirements of the business it is very much important to collect proper data with the help of appropriate procedure of data collection. Big data assists in providing proper amount of storage to the business organization and it is found that with the utilization of big data analytics, the procedure of data collection has become much more advanced in context to both business as well as consumers perspective.
It is identified that accessing data must be done as fast as possible. If the organizations are not able to access appropriate data in a timely manner then it is considered useless for the organization. In manual data management system, it is found that the data as well as information are not accessed properly and therefore the utilization of big data for the organization is one of the prior needs (Lu et al. 2013). The research domain of supply chain management is quite vast and therefore it can hold lot of technical approaches including finance, information technology as well as logistics. For managing both the relationship and the network between different units including facility providers, buyers as well as suppliers, big data is one of the significant tools. Big data is very much advantageous for both backward as well as forward service. The most important task before the management authority is to strengthen interface immunity by removing external attacks.
2.1 Consumer centric product design
Consumer centric product design is needed within the organization for driving the business appropriately. It is very much necessary to modify the existing system based on the demand of the consumers. It is identified that various types of advanced analytical technologies are required for improving the capacity of storage by providing appropriate security to the information that are mainly related with supply chain management as well as operation management. The components that are needed include collaboration, innovation, data driven technologies as well as consumer centric products (Ng et al. 2015). Consumer centricity not only helps in providing proper customer service but it also deals greater offerings on consumer experience for stage awareness. This is possible only due to the post purchasing as well as purchasing procedures. This approach of product design helps in putting the consumer at the first priority and the rest of the business to the nest priority level (Da, He and Li 2014). For improving the centricity of the consumer, there are number of components that are strictly required to be included are experience designing, consumer focused relationship, front line empowerment, metrics that matter and more.
It is quite important to consider the behavior, engagement, interest as well as demand of the people in order to help them. This also assists in identifying appropriate opportunities for developing various products and services, which further helps in grabbing more customers within the market. The management authority must consider the lifetime value of the consumer appropriately for customer segmentation (Martin 2015). Big data mainly assists in gathering, organizing as well as storing data in the server in a very much accurate manner for utilizing the information appropriately. For characterizing as well as addressing the information, it is very much important to comprehend the scenes in an accurate manner. Big data analytics have appropriate ability of connecting huge number of consumers to the business by considering various requirements as well as needs appropriately (Riggins and Wamba 2015).Consumers are helped by providing appropriate amount of support and for which utilization of big data by the organizations is one of the prior need. The workers of the organization must work properly for serving the goal of the organization and for resolving the difficulties and challenges associated both the organization. It is identified that extensive level of management knowledge is required for overcoming the challenges that the organizations are mainly facing due to inappropriate utilization of big data analytics (Whyte, Stasis and Lindkvist 2016). Thus, it is found that with the utilization of big data analytics, various challenges as well as risk associated with business organization can be resolved very much easily.
The big data analytics helps in improving the supply chain management and operation management of thee organization. It is found that based on the selected field of research, both the consumers and the workers who are working for the organization must be the centre of focus. It is identified that various information related with the buyers and suppliers must be stored as well as gathered within the data server of the organization (Wang and Ranjan 2015). The various customers can search their required products as well as services as per their requirement on the websites. Most of the medium to large small business organization utilizes big data analytics tool for storing as well as securing data from various external attackers.
The current supply chain management system of the organization are analyzed and it is identified that current supply chain management within the organizations faces number of challenges and difficulties due lack of proper utilization of big data software. However, the issues of traditional manual storage system get resolved after the implementation of big data within the organization (Sahebjamnia, Torabi and Mansouri 2015). The files are stored appropriately within the server by providing proper security to them from the external attackers after the big data tools are implemented. In order to solving the existing problems of the supply chain management, it is very much important to utilize MongoDB, Hadoop as well as Cloudera.
The application of various types of big data tools are utilized for saving both time and money at the same time. The various types of business insights that have never been revealed could be exposed proper after the utilization of big data within the supply chain management and operation management. Additionally, it helps in providing strategic future layout for the consumers who are generally working within the business organizations (Ellison 2014). It is identified that appropriate big data must be adopted for improving the relationship between the various buyers as well as suppliers of the organization (Xing and Zio 2016). Big data is quite advantageous in the field of extraction, mining, data storage, analyzing as well as visualizing. Big data is one of the most widely utilized analytic tools for handling power of various types of limitless jobs and concurrent tasks that are related with the business organizations.
The open source software is very much needed for the distributed storage. It is found that the supply chain management related with the business organization always holds distributed nature of data. If hardware failure does not occur then big data generally works very much efficiently. There are number of components within the recommended system that must be improved for both developing the consumer centric model include role of suppliers, customers, technology, finance and tax property (Arenas et al. 2015). The supply chain strategy can be developed properly even after the implementation of bug data analytics tool. The recommended model must consist of supply chain operating model, data based assets, strategic risk resolving approaches. It is identified that both data driven innovation as well as product requirement must be easily served by considering both the ethical as well as sustainable factors while product designing. Proper products must be developed with appropriate approaches of process management and product improvement. The other important features that are possible due to big data are:
Enhanced visibility: Big data analytics helps in increasing the overall visibility of inventory level, demands, manufacturing as well as the capacity of the business organizations (Xing and Zio 2016). Thus, it is found that big data analytics utilization in business organization helps in enhancing the entire production level of the organization.
Real time operation: The utilization of big data analytics helps in making the real time operation much easier. The data server which is associated with both B2B as well as B2C business models have become easier after big data analytics is implemented in the real time operation (Arenas et al. 2015). Big data helps in adding values to both the supply chain management procedure as well as operation management. Additionally big data helps in taking proper decision by applying appropriate technique.
Business continuity is defined as one of the procedure or capability that assists in either organizing or continuing the delivery approach of business procedure in context to improvement. For measuring the success as well as sustainable revenue from the market, it is very much necessary to plan the business improvement for the organization appropriately. There are generally that are required to be implemented by various owners of the business in order to deploy the plan of improvement.
In order to improve both the supply chain model as well as operation management, there are number of phases that are required to be exposed with the help of the organization. The phases include:
Process selection: This is the initial phase for improving the continuous business. Various technology-based procedures might effectively affect the business organization either positively or negatively (Podaras, Antlova and Motejlek 2016). However, it is identified that based on the product as well as service requirement of the consumers, appropriate model must be selected. Selection as well as implementation of accurate procedure helps in generating the scope for continuous improvement.
Process evaluation and standardization: It is very much important to select the most accurate procedure for implementing them in the real world. It is identified that big data tools are the most appropriate tools that must be applied for improving the big data analytics because of its security approach, accessibility power as well as timelines.
Improvement of procedure: After identification of accurate procedure, they must be implemented accurately. The procedure that is evaluated should be implemented after considering all the different aspects of improvement plan as well as security. For improving the supply chain management, it is quite important to identify the basic issues (Ellison 2014). After that proper challenging procedures as well as tools must be applied for mitigating the preliminary problems. For this specific phase, the lifecycle event that is mainly followed is known as PDCA cycle.
Conclusion
It can be concluded from the entire assignment that big data analytics plays an important role in managing both supply chain management as well as operation management related with the business organization. It is identified that big data tool help in shaping the entire supply chain of the business organization. The volumes of both data and information that are related with each other must affect both the cost as well as time management either negatively or positively. The various components of supply chain that are generally identified include scheduling, forecasting, delivering, distributing as well as inventory planning. It is found that big data analytics plays an important role within the business organization by managing both operation management and supply chain management. The utilization of big data also help in creating some difficulties as well as challenges for the business organization and it is very much important to resolve the challenges properly. The methods that are mainly utilized for resolving those challenges include:
Security implementation in various data transmission channel: It is very much necessary to implement appropriate security within the channel of data transmission. The information that is transmitted between the suppliers must be kept ways from unauthorized access by the external attackers.
Privacy problems: Privacy is one of the significant issues that must be resolved effectively. It is identified that proper encryption as well as decryption approaches must be developed for making the server secured from various attackers. After analyzing the social network appropriately, it is very much necessary to adopt proper privacy policies in order to resolve the issues that are related with data access. Both authentication and authorization must be adopted so that the external attackers are not able to caches data from the server.
References
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