Big Data Analytics In Manufacturing Industry Case Solution & Answer

Big Data Analytics In Manufacturing Industry Case Solution 

Part A

Present and future role of data analytics for businesses

Big data analytics is the process of analyzing big data to drag information from the data. It involves the patterns of the data, correlations, trends in data and information about consumers’ preferences, this information help companies to make important decisions. Whereas in broader terms I can say that data analytics techniques allow organizations to analyze big data gathered from different sources and generate a meaningful information. In this system business intelligence help organizations in its business operations and performance. Big data analytics is considered as advanced analytics system that help to solve complex issues and different applications (target, 2020). We define business intelligence as the ability of an organization to use the data that organization collect from its day to day operations (Kimble & Milolidakis, 2015). Business intelligence help organizations to improve its overall business efficiency and help organization to identify potential business opportunities and threats. Along with this business intelligence also assists companies to make business level decisions (Xia  &  Gong,  2014). Business intelligence mainly focused on the structured and internal data of the organization but the unstructured and external data are unexplored so that have the potential to reduce the effectiveness of decision making due to less information about external environment (Heng 2014).

The trends of computing and new technology allow companies to deal with large data collection from multiple sources and it is a continuous process i.e. Wal-Mart generate 1 million transaction per hour (The Economist, 2010). Likewise twitter, YouTube and weibo also generate huge data daily. Due to its future potential in business, big data in under serious consideration of organizations. A survey about the adoption of big data stated that by 38% of the companies stated that they use advanced data analytics by 2008 and 85% of the companies stated that they are planning to adopt data analytics with three years (Russom, 2011). Big advanced data analytics help business to analyze the current data and predict the future consumer’s behaviors (Russom, 2011).   Big data analytics have potential to solve the business problems and challenges that companies face nowadays (Marín-Ortega et al., 2014).  Big data have three attributes i.e. velocity, volume and variety as big data have big data volume, different variety types and different data velocity (Russom, 2011). Like Nielsen can produce three lac rows per second and can depict one billion record per month through big data analytics (Prescott, 2014). Big data analytics can use structured and unstructured data and generate information that involves transaction information, inventory details, advertisement and consumer preferences (Schomm, Stahl & Vossen, 2013).

Big data analytics can help companies to improve consumer experience, meet consumers’ changing demand, analyze the changing trends, managing risks for the company, working on supply chain efficiency, allowing to use competitive intelligence and real time insights for decision making (Wang & Alexander, 2015). A study suggested that a retailor who can use big data properly have ability to increase its operating potential by 60% and can acquire market share and compete in the market (Tankard, 2012).This will allow company to build an efficient business management system and support overall business goals because it will allow company to generate sufficient useful information for the company (Srimani and Prathiba ;2016).

Big data analytics have major advantages for the organizations, big data analytics allow companies to get more visible version of the data available, big data analytics also help organizations to provide performance improvement and variability to collect the accurate data (Tao et al. ;2014). This allow companies to explore the changing needs of consumers and meet those changing demands. This also help companies in making decisions and support those decisions with algorithms of valuable insights of consumers and last but not least it help organizations to work on new business models, products and services (McKinsey,  2011).  A survey also stated that the big data analytics help organization to generate knowledge, developing new management rules and regulations. The data collected from different resources help company to information that is useful for internal and external environment of business along with that this information help management team to work on policies and strategies of the company (Zhang et al. ;2016). In future it is expected that every company will invest in big data analysis and there will be other resources available to support big data analytics firm.

Big data analytics help companies in improving the supply chain and also work for several other functions of supply chain i.e. supply chain planning, risk management, inventory management and personalized services (Vera-Baquero et al., 2015). Big data analytics can help companies in supply chain management and work on product innovation,      and new ideas of service deployment along with that it can help companies to work on the diverse collaborative associations of the companies and work on its cost effectiveness (Tan et al., 2015). Big data analytics help companies to work on the decision making process (Kościelniaka &  Puto,  2015). The use of big data analytics can be even more effective after using it with collaboration of decision makers and data analyst. Both can collectively use the big data effectively and make decisions accordingly. Big data analytics help companies in business revenues, customer’s services and other business operations. Organizations are actively using big data analytics to develop their capabilities in their respective business domain. The main objective behind the usage of this system is to comfortably communicate the decision making ( Constantiou & Kallinikos, 2015 ). Due to its past success companies are investing in using big data analytics systems in the organization. The potential of big data analyst and its power of data processing for its day to day data management has developed a need for organizations to adopt the big data analytic system. These management systems is now became the business domain of the companies.

It is stated that the data processing amount in future will get double and its potential to process big data will increase (Lee ; 2017). The report of 2025 for Seagate suggested that the range of big data analytics will increase. Big data analytics have potential to develop the competitive advantage of the companies but along with that big data analytics face challenges (Assunção  et  al.,  2015). The big data analytics have enough potential but there are less resources available, there is lack of analytics capabilities, there are no available network resources. Along with that there are data privacy issues (Ahmad & Quadri, 2015). It is stated that the big data analytics is expected to increase double by 2027. There are several challenges that big data is facing i.e. lack of resources but in future this number will increase and the efficiency of the data analysis will also increase (Zulkernine et al. ; 2013). It is expected that in future the use of data analytics will increase and companies work closely with big data analytics and information generated. Big data analytics allow companies to arrange the big data that companies collect from different sources and generate information from the data collected (Davis et al. 2012). Use this information for decision making and operational efficiency s (Chen, Mao, and Liu 2014). Big data analytics is expected to grow 103 billion by 2027 according to statista. And market size is expected to increase by more than double in 2018.

In future Artificial intelligence and will also play its role in making business more effective use of data and develop business process and make decisions. It can help companies in making business more efficient and help companies in predicting the consumer’s behavior (Lomotey and Deters 2014). Artificial intelligence and big data analytics will collectively allow business to find connections among the databases and generate useful information (Bonvillian 2013).

Part B

Role of Big Data Analytics in business

Big data analytics helps companies develop products and services based on customer needs. They can predict the future and make informed decisions. They can even help them discover new revenue streams. Those who are interested in marketing can also use big data to develop customized products. By analyzing big data, businesses can understand the market. This information helps them decide how to better target their audience. This, in turn, increases their profits.

Besides helping businesses make better decisions, big data can also help businesses increase their efficiency. If employees can make better decisions on the basis of data, they will feel more confident and proactive. Similarly, if you have more information, you can make better decisions as well. Having the right analytics in place will enable you to be more competitive and profitable in your market. The data is the most important resource in any business.

The role of big data analytics in business is increasing in India. It can also help companies with their digital infrastructure. With the help of big data analytics, companies can develop competitive pricing strategies and identify the best time to launch them. This will benefit their bottom line. Ultimately, the success of a business depends on the quality of its customer experience. Achieving this goal is vital for a company to survive and thrive in the world today………………….

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