The goal of any business is to increase its sale and hence the profit. Increase in sales can be achieved by attracting more and more customers and retaining as many of them as possible. This is possible only when the customers feel satisfied by the product or service offered by the business. Previously managements relied on customer feedback to improve their services. This is not a foolproof method as the feedback is not always accurate. The best way is to track the behaviour of individual customer and customize the service according to his or her needs. Big data offers this possibility to the managments to make efficient plans and decisions to cater to the diverse groups of customers by monitoring their likes and dislikes. By analysing the large volume of data collected through embedded sensors within a few seconds, big data can automate the process by which a particular service is rendered to a particular customer based on his or her behavioural attributes. Thus the way an enterprise is managed is drastically changed with the advent of big data. Instead of a group of C-level executives discussing and arriving at a decision, a machine employed to process user data decides what is best for the business.
Benefits for Industries : Industries that fail to make use of the vast potential offered by big data are doomed to lose big to their competitors who have already begun exploiting big data. A survey of 179 publicly traded firms in the US found that data-driven decision making accounted for 5-6% increase in output and productivity ( Brynjolfsson et. al. 5). What if a business can assure not only customer satisfaction but also customer safety? Consider an example of a vehicle’s safety system, that combines human signals with an algorithmic fatigue detector, that can warn the driver to stop driving and take a rest to avoid the risk of having an accident (Lomas, Sensors and Sensitivity). With ever increasing traffic and the number of accidents, such a model if implemented succesfully can radically transform automobile industry. This is just one example. When similar methods are adopted by different industries according to their own needs, their profitability can be increased multifold. The only concern here is the amount of time required to adopt data analytics and speeding up the process of analysis and decision making. With great advancements in technology made day after day, this can be achieved in the near future. By allocating a significant amount of funds towards big data analytics, businesses will no doubt deserve a pat on their back for providing themselves the opportunity to expand and grow.
Works Cited
Brynjolfsson, Eric, Lorin M Hitt, and Heekyung Hellen Kim. Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? 22 Apr 2011. Web. 1 Aug. 2016.
Lomas, Natasha. Sensors And Sensitivity. Techcrunch.com. 3 Aug. 2014. Web. 1 Aug. 2016.
