Big Data and Analytics Retailing PDF

Added on - 15 Apr 2020

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Running Head: BIG DATA IN CONSUMER GOODS RETAILINGBig Data in Consumer Goods RetailingNameInstitutional affiliation
BIG DATA IN CONSUMER GOODS RETAILING2Big data in consumer goods retailingThe Big data is the convergence of many data from many sources and also it representsthe shift of culture on how retailers connect with the consumers in a meaningful way. The bigdata makes the business imperative and the retailers are leveraging it to transform their processesin industry and organizations. Companies of the consumer packed goods and retailers areexperiencing more pressure to gain the advantage of competition in every aspect of themarketplace. Both retailers and manufacturers are shining away from the broad, experimentaltactics of marketing in the search of the strategies to make the consumers pinpoint better whosetransactions happens online or through smartphones as they are in the physical stores. Modernconsumers are found along the digital way to shop where the information and data are critical toinformed decisions, loyalty and winning trials.The combination of the big data and analytics gives the companies of CPG and retailmany opportunities across the chain of value. In The strategy of the portfolio and thedevelopment of the product, companies can get the detailed understanding of the needs andattitude of the consumers and identify the segments of the consumers and improve their ability totarget the best value opportunity. They can measure the return on investment for the spentmarketing across newer and traditional marketing vehicles. Big data also enable the companies tomake better and faster decisions in their business and gives the improved performance. Big datahas expanded the retailers' boundaries and can improve the productivity of the employees'satisfaction, efficiency of operation, supply management of chain, and innovation of the productby using big data[ CITATION Akk16 \l 1033 ].Big data enable the retailers to concentrate on what the customers’ needs in terms ofservices and products. It gives the retailers agility to change the costs of goods in the demand
BIG DATA IN CONSUMER GOODS RETAILING3anticipation. Retailers can give customers specific discount and promotions and instruct theretailers on how the technology bridge devise traditional store and the integration level of thedesires of consumers[ CITATION Yuk17 \l 1033 ].How to make it happenExploiting data fully and analytics needs three capabilities:Companies must be able to choose the correct data and manage many sources of dataThey need the capability to turn the data into insight and they must combine commercialjudgement and deep talents of analytics.The management must undertake transformational program so that the insight yield bestdecisions for the business and translate to the best actions of the frontline[ CITATIONOme17 \l 1033 ].Managing the dataMany companies use the forward approach of data where they gather the data that theythink might be useful or use the existing data. The decision back approaches is recommendedwhich deals with the companies giving out answers to the related questions: what are thedecisions to improve? What are the analysis and data that will help improve those decisions? Theanswers to the following questions will be important during the late procedure of the journeywhen the experts of analytics are making decisions about how they can structure the data, whereto buy the software or invest in the proprietary buildings solutions, where to push for the 100%data accuracy. A retailer may seek better decisions about the spending of promotions where therange of the decisions can be broad: is there need of optimizing the design of the promotionalcirculars and the leaflets? Is there need of distributing the circulars?[ CITATION CTA14 \l 1033 ]In the identification, management of data.Problems of Big Data
BIG DATA IN CONSUMER GOODS RETAILING4The sheer transaction number and time needed for the analysis: the daily data points and thetransaction in retail are many: to become familiar with the trends, companies must capturemountains of data many years and they must invest in the database to enables decisionsmakers to get the required data. The capacity of the data storage is available at low costs andsome companies are turning to the software as the solution service to meet their needs of IT.Matching the data across the repositories: loyalty card database of the retailer does notmatch easily with the database with the cost of products which means the implications on therevenue will be straight but the gross margin implication will not. Leading companies arehaving the new application that matches dissimilar data types from the dissimilar database bypattern recognition[ CITATION Cha161 \l 1033 ].Reliability of the data: product information, sizes of packaging, description of the productsand the category of the product is lacking on the database of the retailers up do date becausedata, maintenance on the massive number consumes time and laborious effort.Lack of the history of some data: promotional; uplift depends on the in-store position of theproduct. Most of the companies lack products recordings making the analysis andinterpretation tricky and makes the retailers to create incomplete pictures since they lackrelevant data. Companies are overcoming this problem by crowdsourcing. There are someapps that the company can pay people to go to the local stores to take the pictures or collectdata which they can upload to the company online. Data management is the first step. Theanalytical tools and the sophisticated algorithms can be used be the companies to producerelevant data but the tools alone don’t constitute the advantage of competition. Companiesmust hire and retained the analysts with skills who can differentiate between the irrelevantfrom the relevant data, draw the correct hypothesis and translate the information to theinsights (Davenport, 2014).Implementation and Integration of Big Data into the Organization’s ArchitectureBig data can be implemented and integrated into the architecture of the organization withan aim of promoting high performance computing as well as automated report in numerous waysas explained below. Gathering the correct data and having best skills cannot yield good results ifthe company don't turn the driven data insights into the effective frontline action. When the
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