...Business AnAlytics And intelligence Course Starting: 29 June 2014 Application Deadline: Early Decision 28 February 2014 Regular Decision 15 April 2014 (Batch 5) (Classes conducted on-campus as well as off-campus) Certificate Programme on Business Analytics and Intelligence BATCH 5 in god We trust, All Others Must Bring data - W edwards deming he theory of bounded rationality proposed by nobel laureate Herbert Simon is evermore significant today with increasing complexity of the business problems; limited ability of human mind to analyze alternative solutions and the limited time available for decision making. introduction of enterprise resource planning (eRP) systems has ensured availability of data in many organizations; however, traditional eRP systems lacked data analysis capabilities that can assist the management in decision making. Business Analytics is a set of techniques and processes that can be used to analyse data to improve business performance through fact-based decision making. Business Analytics is the subset of Business intelligence, which creates capabilities for companies to compete in the market effectively. Business Analytics is likely to become one of the main functional areas in most companies. Analytics companies develop the ability to support their decisions through analytic reasoning using a variety of statistical and mathematical techniques. thomas devonport in his book titled, “competing on analytics: the new science of winning”, claims...
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...Data Monetization: A Retailer’s Journey Mohammad S. Najjar University of Memphis Department of Management Information Systems 363 Fogelman Administration Building Memphis, TN 38152-3120 (901) 678 2478 msnajjar@memphis.edu William J. Kettinger1 University of Memphis Department of Management Information Systems 346 Fogelman Administration Building Memphis, TN 38152-3120 (901) 678 4547 bill.kettinger@memphis.edu A Paper submitted to the MISQ Executive special issue on “Big Data” Acknowledgements: The authors are indebted to Cynthia Beath and the special issue editors and reviewers for their advice on how to substantially improve this article. An earlier version of the paper was presented at the Pre-ICIS 2012 SIM Academic Workshop on “When Data is Ubiquitous: How to Succeed in a World of Big Data”. We are thankful to Omar El Sawy and other participants at the workshop for their insightful comments. We would also like to offer our sincere gratitude to the anonymous retailer and big data analytics company that provided so much time and insight concerning their experiences with monetization of big data. 1 Corresponding Author 1 Data Monetization: A Retailer’s Journey The ability to monetize a company’s data has been an elusive goal. However, in the era of big data, business intelligence and analytics, and cloud computing, this goal is becoming more achievable. The retail industry, with its exacting merchandising strategies and tight supply chain relationships...
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...Business Supply Chain Data Visualization by Mapping and Geographic Analytics (GA) Sandeep Kumar Karumuru 04/19/2016 Image1 Research Paper submission for Supply chain management (Spring 2016) To Distinguished Professor of Supply Chain Management Dr. Nada R. Sanders 1 Table of Contents Abstract 3 Overview 4 Background 5 Supply Chain Visualization 6 Supply Chain Mapping 7 Geographic Analytics 8-11 Business Example 12 Future Trends 13 Benefits and Challenges 14 Conclusion 15 Bibliography 16 2 Abstract The focus of this research paper in on the process of how workflow is handled in a typical supply chain environment. There are numerous areas of focus that come to mind when we talk about improvements for a supply chain but the process itself is not given enough significance. The research paper covers the most popular process in use, from spreadsheets to its immediate future evolution i.e. visualization tools for supply chain data. There are several tools that exist in the market, each of them have their advantages and disadvantages when used in a certain environment. Supply chain mapping is one such tool that many companies are already utilizing but the mapping tool which gives a visual representation of the entire supply chain network is only an abstract network map and so it has its shortcomings. In contrast, supply chain mapping can be utilized alongside geographic analytics giving...
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...(KVN-RENGANATHAN K) - S2647765D (Singapore I/C) ENTERPRISE STRATGEY, QUALITY, SOLUTIONS, DELIVERY, ANALYTICS HEAD kvnmangai@gmail.com / kv.nathan@hp.com Tel : +91 9176648555 Profile Summary Overall Experience of over 25+ years Currently leading Customer service and Warranty Analytics Delivery - Capabilities Build: Warranty Installed Base Analytics, Warranty Spend Analytics, Predictive, Fraud Analytics , Customer Research and Competitive Intelligence on warranty offerings Spearheading analysis of critical aspects of business using data mining, statistical models, dashboards and innovative visualization software. Establishing & driving consistent methodology for Transformation; building & socializing the Virtual team for Supply Chain and Volume operations with the focus. Lead Asia Pacific product returns policy, process re-engineering and on line claims system implementation across all distributors of APJ Managed defective supplies (ink cartridges and laser toners) warranty program across APJ region. Managed distribution compliance, logistics and SC distribution process for APJ Conversant with Multiple Project Methodologies and 6 Sigma methodologies Executed BIG Data , Un Structured data solutions and modeling Presented Warranty non compliance predictive modeling paper in PAW – Chicago 2013 Papers selected in INFORMS & WCM forums on the work done on analytics solution Managed Complex Cross Functional Teams (15+ years) in Customer service and warranty Executing...
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...Competing on Analytics By Thomas H. Davenport This article originally appeared in Harvard Business Review Article Reprint No. R0601H brought to you by Harvard Business Review articles are brought to you by Zurich HelpPoint as part of the Managing Risk Series. Zurich neither endorses nor rejects the information presented in the article. We do not guarantee the accuracy of this information or any results and further assume no liability in connection with this publication including any information or methods contained herein. Competing on Analytics The Idea in Brief It’s virtually impossible to differentiate yourself from competitors based on products alone. Your rivals sell offerings similar to yours. And thanks to cheap offshore labor, you’re hard-pressed to beat overseas competitors on product cost. How to pull ahead of the pack? Become an analytics competitor: Use sophisticated data-collection technology and analysis to wring every last drop of value from all your business processes. With analytics, you discern not only what your customers want but also how much they’re willing to pay and what keeps them loyal. You look beyond compensation costs to calculate your workforce’s exact contribution to your bottom line. And you don’t just track existing inventories; you also predict and prevent future inventory problems. Analytics competitors seize the lead in their fields. Capital One’s analytics initiative, for example, has spurred at least 20% growth in earnings...
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...intelligent systems, market demand for higher-end manufactures, and rise of new global markets. MANUFACTURING 19 Certain manufacturing segments are also adopting a services approach, which is a distinct breakaway from conventional manufacturing delivery. For example, Xerox is leasing out machines as a service. This approach spells a paradigm shift in the manufacturing sector’s strategic thinking. Over the next decade, manufacturing competitiveness, growth and development will increasingly hinge on the quality of inputs that go into the strategic planning. Towards this end, the importance of analytics can hardly be overstated. Analytics locates itself in the data that is related to the particular business. With the adoption of new network and communication technologies, companies have access to several terabytes of data about their customers, suppliers and operations. The amount of data in the manufacturing world currently tots up to nearly 1 exabyte per year and growing exponentially (compared to nearly 434 petabytes for healthcare and nearly 619 petabytes for banking). However, manufacturing firms in...
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...Khamassi Chief Data Scientist & Principal Consultant 1 © 2014 WIPRO LTD | WWW.WIPRO.COM | CONFIDENTIAL The Issue Environment: Outcomes Big data analytics is probably going to be remembered as a technological, if not, an industrial revolution Paralysis by analysis New technologies are rolling off the assembly line daily They keep revisiting the same issues over and over again New terminologies and approaches The delve into technological questions before answering the what and why questions. What matters seems to changes quite frequently I hear stories from my competitors, am I behind? Do I need this stuff? How do I know which are the new opportunities these technologies allow me to win? Skills are short Which skills do we need anyway? How do we organise them? How do we ensure we are compliant? 2 Many customers do not know where to start? Many organise several ‘vendor’ contests without a clear end insight They lack coherent approach that leads to faster results They involve either too many or too few stakeholders Where do I start and how do I plan for big data analytics? © 2014 WIPRO LTD | WWW.WIPRO.COM | CONFIDENTIAL Establishing An Analytical Capability Business Layer Principles: Analytics is a business outcome enabler What needs to be optimised, prioritisation, alignment with overall strategy, process changes etc. It bridges commercial management and IT expertise Analytical Layer There are four layers to be brought together successfully How analytics supports...
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...hbr.org Some companies have built their very businesses on their ability to collect, analyze, and act on data. Every company can learn from what these firms do. Competing on Analytics by Thomas H. Davenport Reprint R0601H Some companies have built their very businesses on their ability to collect, analyze, and act on data. Every company can learn from what these firms do. Competing on Analytics COPYRIGHT © 2005 HARVARD BUSINESS SCHOOL PUBLISHING CORPORATION. ALL RIGHTS RESERVED. by Thomas H. Davenport We all know the power of the killer app. Over the years, groundbreaking systems from companies such as American Airlines (electronic reservations), Otis Elevator (predictive maintenance), and American Hospital Supply (online ordering) have dramatically boosted their creators’ revenues and reputations. These heralded—and coveted—applications amassed and applied data in ways that upended customer expectations and optimized operations to unprecedented degrees. They transformed technology from a supporting tool into a strategic weapon. Companies questing for killer apps generally focus all their firepower on the one area that promises to create the greatest competitive advantage. But a new breed of company is upping the stakes. Organizations such as Amazon, Harrah’s, Capital One, and the Boston Red Sox have dominated their fields by deploying industrial-strength analytics across a wide variety of activities. In essence, they are transforming their organizations into armies of...
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...Introduction to Big data Every day, 2.5 quintillion bytes of complex, every changing data are generated. (IBM) Data comes from social sites, digital images, transaction records, and countless unknown resources. The amount of data we generate daily is enormous, and the rate it is being generated is accelerating. As we head into a future where technology dominates the global market, this pace will only continue accelerate. Businesses and other entities are aware of this data and its power. In a survey taken by Capgemini and the Economist, over 600 global business leaders identified their companies as data driven and identified data analytics as an integral part of their business. Big Data solutions are considered the answer for handling this data converting it into useful information. According to the O'Reilly Radar Team (Big Data Now), Big Data consists of three variables – size, velocity and variety. Data is considered big if conventional systems cannot handle its size. It is not only that size of Big Data that matters, but also the volume of transactions that come with it. The second issue is how fast the data is generated and how fast if it changes (velocity). New data and updated data is constantly generated, and it must be processed and analyzed quickly to create real value for an organization. The final issue is data structure (variety). Data is typically collected in raw form, unstructured, from a variety of sources. To acquire useful information, data needs to be processed...
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...HBR Article: Diamonds in the Data Mine March 31, 2010 By Gary Loveman This is a pretty nice and short yet highly effective article that outlines the importance of providing an exceptional customer service in today’s service industry, especially in the gaming industry as it is the case of Harrah’s Entertainment casino. Actually, from its inception, Harrah’s former CEO Phil Satre had instituted this policy of “changing Harrah’s from an operations-driven company that viewed each casino as a stand-alone business into a marketing-driven company that built customer loyalty to all Harrah’s properties”. In doing so, Satre asked Gary Loveman to head a strategy to affect this change in all Harrah’s organizations, and so Loveman did follow through on this task. He effectively focused on delivering customer service and on understanding and marketing effectively to the customer. This is the secret to Harrah’s success, which allows him and Harrah’s to maintain loyalty from its customers based on the database they had collected over the years, as they were able to identify their customers’ needs and wants as well as to have good reward and incentive programs in place to recognize their clientele according to the time and money they spend gambling over their facilities. Yet, for their workforce, Harrah’s instituted a bonus system tied to job satisfaction. “Rewards hinge on everyone’s performance at a casino- and on customer satisfaction, not a property’s financial performance”. Also...
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...INTRODUCTION Big data is described as complex data collections that has very large size beyond the capability of traditional tools to capture, manage and process it efficiently. It is also use in many ways where it usually refers to both of data that being managed and used to store and process it by the technology which it helps to deduce different types of results using the same data that being stored intentionally or unintentionally. There are three characteristics of big data which are volume, velocity and variety. When it comes to volume, the name of big data itself indicates that it is related to its enormous size. Nowadays, data is being produced by networks, machine as well as system such as social media which this is use by human...
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............................................................................3 SWOT Analysis.....................................................................................................4 Woolworths Limited © MarketLine Page 2 Woolworths Limited Company Overview COMPANY OVERVIEW Woolworths Limited (Woolworths or 'the company') owns and operates retail stores that sell food, liquor, fuel, general merchandise and home improvement products in Australia and New Zealand. It is headquartered in Bella Vista, Australia, and employs more than 197,000 people. The company recorded revenues (excluding financial income) of A$58,921.7 million (approximately $60,506.7 million) during financial year ended June 2013 (FY2013), an increase of 6.9% over FY2012. The operating profit of the company was A$3,594.6 million (approximately $3,691.3 million) during FY2013, an increase of 7.4% over FY2012. The net profit was A$2,259.4 million (approximately $2,320.2 million) in FY2013, an increase of 24.4% over FY2012. KEY FACTS Head Office Woolworths Limited 1 Woolworths Way Bella Vista New South Wales 2153 AUS 61 2 8885 0000 Phone Fax Web Address http://www.woolworthslimited.com.au Revenue / turnover 58,921.7 (AUD Mn) Financial Year End Employees Australian Stock Exchange Ticker June 197,000 WOW Woolworths Limited © MarketLine Page 3 Woolworths Limited SWOT Analysis SWOT ANALYSIS...
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...Review of Three Business Analytical Articles Kevin Johnson Grand Canyon University: MGT-820-O101 Using Business Analytics for Competitive Advantage November 26, 2014 Introduction The intent of this paper is to provide doctoral learners an opportunity to analyze three articles of literature as it correlates to the principles of business analytics. This doctoral learner chose the following three articles to review: A New Business Dimension – Business Analytics by Pavel Năstase and Dragos Stoica, The Collaborate / Integrate Business Technology Strategy by Stephen J. Andriole, and Evolving From Information to Insight by Glover Ferguson, Sanjay Mathur and Baiju Shah. A New Business Dimension – Business Analytics by Pavel Năstase and Dragos Stoica This is article focuses on the achievement of the appropriate business outcomes through the utilization of business analytics. According to Năstase and Stoica (2011), to ensure these results necessitates a holistic perspective to evaluate analytic factors and ensure that the appropriate elements are utilized. The methodology of business analytics offers an organization a complete and current data that can improve planning. Therefore; it provides managers with an enhancement of abilities to manage costs and to wisely use sparse funds. Furthermore, it allows managers the capability to leveraging staff resources, placing very valuable, expensive resources to on projects that clearly support organizational goals (Năstase and Stoica...
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...era of ‘big data’? Brad Brown, Michael Chui, and James Manyika Radical customization, constant experimentation, and novel business models will be new hallmarks of competition as companies capture and analyze huge volumes of data. Here’s what you should know. The top marketing executive at a sizable US retailer recently found herself perplexed by the sales reports she was getting. A major competitor was steadily gaining market share across a range of profitable segments. Despite a counterpunch that combined online promotions with merchandizing improvements, her company kept losing ground. When the executive convened a group of senior leaders to dig into the competitor’s practices, they found that the challenge ran deeper than they had imagined. The competitor had made massive investments in its ability to collect, integrate, and analyze data from each store and every sales unit and had used this ability to run myriad real-world experiments. At the same time, it had linked this information to suppliers’ databases, making it possible to adjust prices in real time, to reorder hot-selling items automatically, and to shift items from store to store easily. By constantly testing, bundling, synthesizing, and making information instantly available across the organization— from the store floor to the CFO’s office—the rival company had become a different, far nimbler type of business. What this executive team had witnessed first hand was the gamechanging effects of big data. Of course...
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...The Impact of “Cloud Computing”-based Information Sharing on Supply Chain Li YiPeng, Zhongnan University of Economics and Law, School of Information and Safety Engineering, Wu Han, China, Lyp2357@163.com The research presented in this publication uses both analytical and methodological approach through mathematical models to exploit a real time information sharing based on “Cloud Computing”. The author has clearly provided type, limitation and limited orientation to the following terminologies with respect to the scope of is research and publication: Type of Information Shared, The pertaining definitions of Information Measurement, Quantitative and Qualitative Measurement of Information, Accelerating Physical Flow, Scope of Uncertainty in the Supply Chain, Building Cloud Computing Platform in Supply Chain. The methodological approach is also provided to find the optimal solution for information sharing in a cloud computing scenario, the study uses a mathematics optimization model by including variables such as Product, Consumer (computed through Poisson Process, Auto Regression, ARIMA and Stationary Demand), Retailer and Manufacturer. The results of this study are very important to supply chain practitioners. It can be used as benchmark to assess the impact and value of cloud computing in the supply chain. It is the cloud computing platform’s task to make the partners using the information service more easily and conveniently. To those middle and small-sized companies...
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