1. © 2013, published by Flat World Knowledge 12-1 Information Systems: A Manager’s Guide to Harnessing Technology, version 2.0 John Gallaugher

2. © 2013, published by Flat World Knowledge Published by: Flat World Knowledge, Inc. © 2013 by Flat World Knowledge, Inc. All rights reserved. Your use of this work is subject to the License Agreement available here http://www.flatworldknowledge.com/legal. No part of this work may be used, modified, or reproduced in any form or by any means except as expressly permitted under the License Agreement.http://www.flatworldknowledge.com/legal 12-2

3. © 2013, published by Flat World Knowledge Chapter 12 The Data Asset: Databases, Business Intelligence, Big Data, and Competitive Advantage 12-3

4. © 2013, published by Flat World Knowledge Learning Objectives Understand how increasingly standardized data, access to third-party data sets, cheap, fast computing and easier-to-use software are collectively enabling a new age of decision making Be familiar with some of the enterprises that have benefited from data-driven, fact-based decision making 12-4

5. © 2013, published by Flat World Knowledge Data and Decision Making Big data: Massive amount of data available to today’s managers – Unstructured, big, and costly to work through conventional databases – Made available by new tools for analysis and insight Decision making is data-driven, fact-based and enabled by: – Standardized corporate data – Access to third-party datasets through cheap, fast computing and easier-to-use software 12-5

6. © 2013, published by Flat World Knowledge Data and Decision Making Business intelligence (BI): Combines aspects of reporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis Analytics: Driving decisions and actions through extensive use of: – Data – Statistical and quantitative analysis – Explanatory and predictive models – Fact-based management 12-6

7. © 2013, published by Flat World Knowledge Enterprises that Have Benefited from Data Mastery Walmart - Entered the top of the Fortune 500 list Harrah’s Casino Hotels - Grew twice as profitable as Caesars and rich enough to acquire it Capital One - Found valuable customers that competitors were ignoring – Its ten-year financial performance was ten times greater than the S&P 500 12-7

8. © 2013, published by Flat World Knowledge Learning Objectives Understand the difference between data and information Know the key terms and technologies associated with data organization and management 12-8

9. © 2013, published by Flat World Knowledge Organizing Data - Key Terms and Technology Database: Single table or a collection of related tables Database management systems (DBMS): Software for creating, maintaining, and manipulating data – Known as database software Structured query language (SQL): Used to create and manipulate databases 12-9

10. © 2013, published by Flat World Knowledge Organizing Data - Key Terms and Technology Database administrator (DBA): Job title focused on directing, performing, or overseeing activities associated with a database or set of databases – Database design and creation – Implementation – Maintenance – Backup and recovery – Policy setting and enforcement – Security 12-10

11. © 2013, published by Flat World Knowledge Key Terms Associated with Database Systems List of data, arranged in columns or fields and rows or records Table or file Column in a database table Represents each category of data contained in a record Column or field Row in a database table Represents a single instance of whatever the table keeps track of like student or faculty Row or record 12-11

12. © 2013, published by Flat World Knowledge Key Terms Associated with Database Systems Code that unlocks encryption Field or combination of fields used to uniquely identify a record, and to relate separate tables in a database like social security number Key Most common standard for expressing databases Tables or files are related based on common keys Relational database 12-12

13. © 2013, published by Flat World Knowledge Learning Objectives Understand various internal and external sources for enterprise data Recognize the function and role of data aggregators, the potential for leveraging third-party data, the strategic implications of relying on externally purchased data, and key issues associated with aggregators and firms that leverage externally sourced data 12-13

14. © 2013, published by Flat World Knowledge Transaction Processing Systems Record a transaction or some form of business- related exchange, such as a cash register sale, ATM withdrawal, or product return – Transaction: Some kind of business exchange Loyalty card: System that provides rewards in exchange for consumers allowing tracking and recording of their activities – Enhances data collection and represents a significant switching cost 12-14

15. © 2013, published by Flat World Knowledge Enterprise Software Firms set up systems to gather additional data beyond conventional purchase transactions or Web site monitoring Customer relationship management systems (CRM) - Empower employees to track and record data at nearly every point of customer contact Includes other aspects that touch every aspect of the value chain including SCM and ERP 12-15

16. © 2013, published by Flat World Knowledge Surveys Firms supplement operational data with additional input from surveys and focus groups Direct surveys can give better information than a cash register Many CRM products have survey capabilities that allow for additional data gathering at all points of customer contact 12-16

17. © 2013, published by Flat World Knowledge External Sources Organizations can have their products sold by partners and can rely heavily on data collected by others Data from external sources might not yield competitive advantage on its own – Can provide operational insight for increased efficiency and cost savings – May give firms a high-impact edge 12-17

18. © 2013, published by Flat World Knowledge Data Aggregators Firms that collect and resell data One has to be aware of the digital tracking of individuals – Possible by the availability of personal information online 12-18

19. © 2013, published by Flat World Knowledge Learning Objectives Know and be able to list the reasons why many organizations have data that can’t be converted to actionable information Understand why transactional databases can’t always be queried and what needs to be done to facilitate effective data use for analytics and business intelligence Recognize key issues surrounding data and privacy legislation 12-19

20. © 2013, published by Flat World Knowledge Reasons for Poor Information Incompatible systems – Legacy systems: Older information systems that are incompatible with other systems, technologies, and ways of conducting business Operational data cannot always be queried – Most transactional databases are not set up to be simultaneously accessed for reporting and analysis – Database analysis requires significant processing 12-20

21. © 2013, published by Flat World Knowledge Learning Objectives Understand what data warehouses and data marts are and the purpose they serve Know the issues that need to be addressed in order to design, develop, deploy, and maintain data warehouses and data marts 12-21

22. © 2013, published by Flat World Knowledge Data Warehouses and Data Marts Set of databases designed to support decision making in an organization Structured for fast online queries and exploration Collects data from many different operational systems Data mart: Database or databases focused on addressing the concerns of a specific problem or business unit 12-22

23. © 2013, published by Flat World Knowledge Data Warehouses and Data Marts Marts and warehouses may contain huge volumes of data Building large data warehouses can be expensive and time consuming Large-scale data analytics projects should build on visions with business-focused objectives 12-23

24. © 2013, published by Flat World Knowledge Figure 12.2 - Information Systems Supporting Operations and Analysis 12-24

25. © 2013, published by Flat World Knowledge Maintaining Data Warehouses and Data Marts Firms can address the broader issues needed to design, develop, deploy, and maintain its system through data: – Relevance – Sourcing – Quantity and quality – Hosting – Governance 12-25

26. © 2013, published by Flat World Knowledge Insights from Unstructured Big Data Hadoop - Made up of half-dozen separate software pieces and requires the integration of these pieces to work Advantages – Flexibility – Scalability – Cost effectiveness – Fault tolerance 12-26

27. © 2013, published by Flat World Knowledge E-Discovery Identifying and retrieving relevant electronic information to support litigation efforts – Firm should account for it in its archiving and data storage plans – Data can be used later and therefore should be stored in order 12-27

28. © 2013, published by Flat World Knowledge Learning Objectives Know the tools that are available to turn data into information Identify the key areas where businesses leverage data mining Understand some of the conditions under which analytical models can fail Recognize major categories of artificial intelligence and understand how organizations are leveraging this technology 12-28

29. © 2013, published by Flat World Knowledge Business Intelligence Toolkit Provide regular summaries of information in a predetermined format Canned reports Puts users in control so that they can create custom reports on an as- needed basis By selecting fields, ranges, summary conditions, and other parameters Ad hoc reporting tools Heads-up display of critical indicators that allow managers to get a graphical glance at key performance metrics Dashboards Takes data from standard relational databases, calculates and summarizes the data, and then stores the data in a special database called a data cube Data cube: Stores data in OLAP report Online analytical processing (OLAP) 12-29

30. © 2013, published by Flat World Knowledge Data Mining Using computers to identify hidden patterns in, and to build models from, large data sets – Customer segmentation and market basket analysis – Marketing and promotion targeting – Collaborative filtering and customer churn – Fraud detection, financial modeling, and hiring and promotion Prerequisites – Organization must have clean, consistent data – Events in that data should reflect trends 12-30

31. © 2013, published by Flat World Knowledge Problems in Data Mining Firm is overexposed to risk Using bad data can give wrong estimates When the market does not behave as it has in the past, computer-driven investment models are not effective Historical consistency Build a model with so many variables that the solution arrived at might only work on the subset of data used to create it Over-engineer 12-31

32. © 2013, published by Flat World Knowledge Skills for Data Mining Information technology Statistics Business knowledge 12-32

33. © 2013, published by Flat World Knowledge Artificial Intelligence (AI) Computer software that seeks to reproduce or mimic human thought, decision making, or brain functions – Data mining has its roots in AI Neural network: Examines data and hunts down and exposes patterns, in order to build models to exploit findings Expert systems: Leverages rules or examples to perform a task in a way that mimics applied human expertise 12-33

34. © 2013, published by Flat World Knowledge Artificial Intelligence Genetic algorithms: Model building techniques where computers examine many potential solutions to a problem – Modifies various mathematical models that have to be searched for a best alternative 12-34

35. © 2013, published by Flat World Knowledge Learning Objectives Understand how Walmart has leveraged information technology to become the world’s largest retailer Be aware of the challenges that face Walmart in the years ahead 12-35

36. © 2013, published by Flat World Knowledge Walmart - Data-Driven Value Chain Largest retailer in the world – Source of competitive advantage is scale Efficiency starts with a proprietary system called retail link – Retail link - Records a sale and automatically triggers inventory reordering, scheduling, and delivery – Inventory turnover ratio: Ratio of a company’s annual sales to its inventory Back-office scanners keep track of inventory as supplier shipments come in 12-36

37. © 2013, published by Flat World Knowledge Data Mining Prowess Gets data from varying environmental conditions Protects the firm from a retailer’s twin nightmares – Too much inventory – Too little inventory Helps the firm tighten operational forecasts – Enables prediction Data drives the organization – Reports form the basis of sales meetings and executive strategy sessions 12-37

38. © 2013, published by Flat World Knowledge Sharing Data and Keeping Secrets Walmart shares sales data with relevant suppliers – Stopped sharing data with information brokers – Custom builds large portions of its information systems to keep competitors off its trail – Other aspects of the firm’s technology remain confidential 12-38

39. © 2013, published by Flat World Knowledge Challenges Finding huge markets or dramatic cost savings – To boost profits and continue to move its stock price higher Criticisms – Accusations of sub par wages and a magnet for union activists – Poor labor conditions at some of the firm’s contract manufacturers – Demand prices so aggressively low that suppliers end up cannibalizing their own sales at other retailers 12-39

40. © 2013, published by Flat World Knowledge Learning Objectives Understand how Caesars has used IT to move from an also-ran chain of casinos to become the largest gaming company based on revenue Name some of the technology innovations that Caesars is using to help it gather more data, and help push service quality and marketing program successaa 12-40

41. © 2013, published by Flat World Knowledge Caesars’ Solid Gold CRM for the Service Sector Caesars Entertainment provides an example of exceptional data asset leverage in the service sector – Focus on how this technology enables world-class service through customer relationship management Leveraged its data-powered prowess to move: – From a chain of casinos – To largest gaming company by revenue 12-41

42. © 2013, published by Flat World Knowledge Collecting Data Caesars’ collects customer data on everything one might do at their properties – Used to track preferences and see if a customer is worth pursuing Total rewards loyalty card system – Opt-in: Marketing effort that requires customer consent – Opt-out programs - Enroll all customers by default 12-42

43. © 2013, published by Flat World Knowledge Most Valuable Customers Customer lifetime value (CLV): Present value of the likely future income stream generated by an individual purchaser Tracks over ninety demographic segments – Each responds differently to different approaches – Iterative model of mining the data to identify patterns – Creates and tests a hypothesis against a control group – Analyzes to statistically verify the outcome – Profits come from locals and people 45 years and older 12-43

44. © 2013, published by Flat World Knowledge Data Driven Service Identifies the high value customers and gives them special attention Customers could obtain reserved tables and special offers Tracks gamblers suffering unusual losses and provides feel-good offers to them CRM effort monitors any customer behavior changes Customers come back as they feel they are treated better than competitors 12-44

45. © 2013, published by Flat World Knowledge Data Driven Service Focuses on service quality and customer satisfaction – Embedded in its information systems and operational procedures Employees are measured on metrics that include speed and friendliness – Compensated based on guest satisfaction ratings Changed the corporate culture at Caesars – From very-property-for-itself mentality – To a collaborative, customer-focused enterprise 12-45

46. © 2013, published by Flat World Knowledge Innovation and Strategy Innovation Has new innovations that help it gather more data Push service quality and marketing program success Firm launched: Interactive bill boards RFID-enabled poker chips and under-table RFID readers Incorporation of drink ordering to gaming machines Strategy Data advantage creates intelligence for a high-quality and highly personal customer experience Data gives the firm a service differentiation edge Loyalty program represents a switching cost Firm’s technology is unique and holds many patents 12-46

47. © 2013, published by Flat World Knowledge Challenges Gaming is a discretionary spending item, and when the economy tanks, gambling is one of the first things consumers will cut – Taken private: Publicly held company has its outstanding shares purchased by an individual or by a small group of individuals who wish to obtain complete ownership and control Has been through a risky overly optimistic buyout 12-47