1. Learning Objectives
Describe the major business intelligence (BI) implementation issues
List some critical success factors of BI implementation
Describe the importance and issues in integrating BI technologies and applications
Understand the needs for connecting BI systems with other information systems
Define on-demand BI and its advantages/limitations
List and describe representative privacy, major legal and ethical issues of BI implementation

2. Learning Objectives
Understand Web 2.0 and its characteristics as related to BI and decision support
Understand social networking concepts, selected applications, and their relationship to BI
Describe how virtual world technologies can change the use of BI applications
Describe the integration of social software in BI
Know how Radio Frequency Identification (RFID) data analysis can help improve supply chain management (SCM) and other operations
Describe how massive data acquisition techniques can enable reality mining

3. Opening Vignette… “BI Eastern Mountain Sports Increases
Collaboration and Productivity”
Company background
Problem description
Proposed solution
Results
Answer & discuss the case questions

4. Opening Vignette Collaborative Decision Making at Eastern Mountain Sports

5. Implementing BI – An Overview
Decisional Factors in BI Implementation
Reporting and analysis tools
Features, functionality, flexibility, scalability
Database
Scalability, performance, security
ETL Tools
Accessibility, efficiency, usability
Costs
Hardware/software, development/training
Benefits
Tangibles/intangibles - time saving, improved decisions/operations/customer satisfaction/

6. Implementing BI – An Overview
Critical Success Factors for BI Implementation
Business driven methodology and project management
Clear vision and planning
Committed management support and sponsorship
Data management and quality issues
Mapping the solutions to the user requirements
Performance considerations of the BI system
Robust and extensible framework

7. Managerial Issues Related to BI Implementation
System development and the need for integration
Cost–benefit issues and justification
Legal issues and privacy
BI and BPM today and tomorrow
Cost justification; intangible benefits
Documenting and securing support systems
Ethical issues
BI Project failures

8. BI and Integration Implementation
Types of Integration
Functional integration
different [physically separate] applications are provided/used as if it is a single system
Physical integration
packaging the hardware, software, and communication features required to accomplish functional integration
Primary focus in BI (and in this book) is functional-application integration

9. BI and Integration Implementation
Why integrate?
To better implement a complete BI system
To increase the capabilities of the BI applications
To enable real-time decision support
To enable more powerful applications
To facilitate faster system development
To enhance support activities such as blogs, wikis, RSS feeds, etc.

10. BI and Integration Implementation
Levels of BI Integration
Functional integration can be within the same BI or across different BI systems
Integration across different BI systems can be accomplished in a loosely coupled fashion – input output passing, messaging (SOA)
Integration within a BI system is more cohesive with several sub-systems constituting the whole
Embedded Intelligent Systems
Serving as the intelligent agents within BI

11. Connecting BI Systems to Databases and Other Enterprise Systems
Virtually every BI application requires database or data warehouse access
Multi-tiered Application Architecture

12. Connecting BI Systems to Databases and Other Enterprise Systems
Integrating BI applications and back-end systems
Web scripting languages (e.g., PHP, JSP, ASP)
Application integration servers (e.g., WebLogic)
Enterprise application integration – integration of large systems (BI to ERP, SCM, CRM, KM, etc.)
Integrating BI and ERP for DSS
ERP captures and stores data
BI converts data into information/knowledge
Middleware?

13. On-Demand BI The limitations of Traditional BI
Complex, time-consuming, expensive
The On-Demand Alternative
On-demand computing = Utility computing
SaaS (Software as a service)
Allows SMEs to utilize affordable BI
On-demand function alternatives
Internally sharing licenses within a firm
Sharing licenses with many firms via an ASP

14. Benefits of On-Demand BI
Ability to handle fluctuating demand
Flexible use of the BI technology pool
Reduced investment/cost
Hardware (servers and peripherals)
Software (more features for less)
Maintenance (centralized timely updates)
Embodiment of recognized best practices
Better flexibility and connectivity with other systems via SaaS infrastructure
Better RIO

15. The Limitations of On-Demand BI
Integration of vendors’ software with company’s software may be difficult
The vendor can go out of business, leaving the company without a service
It is difficult or even impossible to modify hosted software for better fit with the users’ needs
Upgrading may become a problem
You may relinquish strategic data to strangers (lack of privacy/security of corporate data)

16. Issues of Legality, Privacy and Ethics
Legal issues
Liability for the actions of advice provided by BI
Who is liable, if the software advice fails?
Privacy
Right to be left alone and the right to be free from unreasonable personal intrusions
Collecting information about individuals
The Web and information collection
Mobile user privacy
Homeland security and individual privacy

17. Issues of Legality, Privacy and Ethics
Ethics in Decision Making and Support
Electronic surveillance
Software piracy
Use of proprietary databases
Use of intellectual property such as knowledge
Computer accessibility for workers with disabilities
Accuracy of data, information, and knowledge
Protection of the rights of users
Use of corporate computers for non-work-related purposes (personal use of Internet while working)

18. Issues of Legality, Privacy and Ethics
A Model of Ethical Problem Formulation

19. Emerging Topics in BI – An Overview
Web 2.0 revolution as it relates to BI in (Section 6.7)
Online social networks (Section 6.8)
Virtual worlds as related to BI (Section 6.9)
Integration social networking and BI (Section 6.10)
RFID and BI (Section 6.11)
Reality Mining (Section 6.12)

20. Emerging Topics in BI – An Overview The Future of BI
Web 2.0 revolution as it related to BI (Section 6.7)
Online social networks (Section 6.8)
Virtual worlds as related to BI (Section 6.9)
Integration social networking and BI (Section 6.10)
RFID and BI (Section 6.11)
Reality Mining (Section 6.12)

21. Emerging Topics in BI – An Overview
In 2009, collaborative decision making emerged as a new product category that combines social software with business intelligence platform capabilities.
In 2010, 20 percent of organizations will have an industry-specific analytic application delivered via software as a service as a standard component of their business intelligence portfolio.
By 2012, business units will control at least 40 percent of the total budget for BI.
By 2012, one-third of analytic applications applied to business processes will be delivered through coarse-grained application mashups.
Because of lack of information, processes, and tools, through 2012, more than 35 percent of the top 5,000 global companies will regularly fail to make insightful decisions about significant changes in their business and markets.

22. The Web 2.0 Revolution
Web 2.0: a popular term for describing advanced Web technologies and applications, including blogs, wikis, RSS, mashups, user-generated content, and social networks
Objective: enhance creativity, information sharing, and collaboration
Difference between Web 2.0 and Web 1.x
Use of Web for collaboration among Internet users and other users, content providers, and enterprises

23. The Web 2.0 Revolution
Web 2.0: an umbrella term for new technologies for both content as well as how the Web works
Web 2.0 has led to the evolution of Web-based virtual communities and their hosting services, such as social networking sites, video-sharing sites
Companies that understand these new applications and technologies—and apply the capabilities early on—stand to greatly improve internal business processes and marketing

24. The Web 2.0 Revolution Characteristics of the Web 2.0
The ability to tap into the collective intelligence of users. The more users contribute, the better.
Data is made available in new or never-intended ways. Web 2.0 data can be remixed or “mashed up”.
Web 2.0 relies on user-generated and user-controlled content and data (enhanced collaboration).
Lightweight programming techniques and tools let nearly anyone act as a Web site developer.
The virtual elimination of software-upgrade cycles makes everything a perpetual beta or work-in-progress and allows rapid prototyping, using the Web as an application development platform.

25. The Web 2.0 Revolution Characteristics of the Web 2.0
Users can access and manage applications entirely through a browser.
An architecture of participation and digital democracy encourages users to add value to the application as they use it.
There is a major emphasis on social networks and computing.
Information sharing and collaboration is greatly supported.
This allows for rapid and continuous creation of new business models.
“dynamic content, rich user experience, metadata, scalability, open source, and freedom (net neutrality)”

26. The Web 2.0 Revolution Ajax (Asynchronous JavaScript and XML)
An enabling technology for Web 2.0, resulting in rich, interactive, fast-response, user-friendly GUIs
Makes Web pages feel more responsive by exchanging small amounts of data with the server behind the scenes (eliminated the need for reloading the complete Web page)
Leads to improved Web page interactivity, loading speed, and usability
Many companies and new business models have emerged based on Web 2.0

27. Online Social Networking – Basics and Examples
A social network is a place where people create their own space, or homepage, on which they write blogs; post pictures, videos, or music; share ideas; and link to other Web locations they find interesting.
The mass adoption of social networking Web sites points to an evolution in human social interaction
The size of social network sites are growing rapidly, with some having over 100 million members – growth for successful ones 40 to 50 % in the first few years and 15 to 25 % thereafter

28. Online Social Networking – Social Network Analysis Software
It is used to identify, represent, analyze, visualize, or simulate networks with
Nodes – agents, organizations, or knowledge
Edges – relationships identified from various types of input data (relational and non-relational)
Various input and output file formats exist
SNA software tools include
Business-oriented social network tools such as InFlow and NetMiner
Social Networks Visualizer, or SocNetV, which is a Linux-based open source package

29. Mobile Social Networking
Social networking where members converse and connect with one another using cell phones or other mobile devices
MySpace and Facebook offer mobile services
Mobile only services: Brightkite, and Fon11
Basic types of mobile social networks
Partnership with mobile carriers (use of MySpace over AT&T network)
Without a partnership (“off deck”) (e.g., MocoSpace and Mobikade)
Mobile Enterprise Networks
Mobile Community Activities (e.g., Sonopia)

30. Major Social Network Services
Facebook: The Network Effect
Launched in 2004 by Mark Zuckerberg (former Harvard student)
It is the largest social network service in the world with over 500 million active users worldwide
Initially intended for college and high school students to connected to other students at the same school
In 2006 opened its doors to anyone over 13; enabling Facebook to compete directly with MySpace.

31. Major Social Network Services
Orkut: Exploring the Very Nature of Social Networking Sites
The brainchild of a Turkish Google programmer
It was to be Google's homegrown answer to MySpace and Facebook
Format is similar to others: a homepage where users can display every facet of their personal life they desire using various multimedia applications
A major highlight of Orkut – ability to create and control communities
Also supports many languages

32. Implications of Business and Enterprise Social Networks
Business oriented social networks can go beyond “advertising and sales”
Emerging enterprise social networking apps:
Finding and Recruiting Workers
See Application Case 14.2 for a representative example
Management Activities and Support
Training
Knowledge Management and Expert Location
e.g., innocentive.com; awareness.com; Caterpillar
Enhancing Collaboration
Using Blogs and Wikis Within the Enterprise …>

33. Implications of Business and Enterprise Social Networks
Survey shows that best-in-class companies use blogs and wikis for the following applications:
Project collaboration and communication (63%)
Process and procedure document (63%)
FAQs (61%)
E-learning and training (46%)
Forums for new ideas (41%)
Corporate-specific dynamic glossary and terminology (38%)
Collaboration with customers (24%)

34. Virtual Worlds
Virtual worlds have existed for a long time in various forms — stereoscopes, Cinerama, simulators, computer games, …
They are artificial worlds created by computer systems in which the user has the impression of being immersed
Examples:
Second Life (secondlife.com)
Google Lively (lively.com)
EverQuest (everquest.com)
Avatars ?

35. Second Life as a DSS Advantages: Easy access and low cost
Experienced and dedicated designer/builders
Tools and venues for communications-driven decision support (DecisionSupportWorld.com)
A large, dedicated user base
Impression management / creativity enhancement
Time compression
Easy data integration from real life using RSS feeds
Encourages active participation and experiential learning

36. Second Life as a DSS Disadvantages: Learning time and training costs
Distractions are numerous
Pranksters and spam are common
Technology problems persist
Chat is a very slow communication tool
Resistance to use
Addiction
Participation in most of these virtual environments requires downloading of a "plug-in"

37. Virtual Tradeshows
See iTradeFair.com

38. Social Networks and BI: Collaborative Decision Making
Collaborative decision making (CDM) – combines social software and BI
CDM is a category of decision-support system for non-routine, complex decisions that require iterative human interactions.
Ad hoc tagging regarding value, relevance, credibility, and decision context can substantially enrich both the decision process and the content that contributes to the decisions.
Tying BI to decisions and outcomes that can be measured will enable organizations to better demonstrate the business value of BI.

39. How CDM Works

40. RFID and BI Wal-Mart's RFID mandate in June 2003
DoD, Target, Albertson's, Best Buy,…
RFID is a generic technology that refers to the use of radio frequency waves to identify objects.
RFID is a new member of the automatic identification technologies family, which also includes the ubiquitous barcodes and magnetic strips.

41. How does RFID work? RFID system Tags
a tag (an electronic chip attached to the product to be identified)
an interrogator (i.e., reader) with one or more antennae attached
a computer (to manage the reader and store the data captured by the reader)
Tags
Active tag versus Passive tags

42. Data Representation for RFID
RFID tags contain 96 bits of data in the form of serialized global trade identification numbers (SGTIN) [see epcglobalinc.org]

43. RFID for Supply Chain BI
RFID in Retail Systems
Functions in a distribution center
receiving, put-away, picking, and shipping
Sequence of operations at a receiving dock
unloading the contents of the trailer
verification of the receipt of goods against expected delivery (purchase order)
documentation of the discrepancy
application of labels to the pallets, cases, items
sorting of goods for put-away or cross-dock

44. RFID for Supply Chain BI
RFID in Retail Systems

45. RFID Data Sample
RFID in Retail Systems

46. RFID for BI in Supply Chain
Better SC visibility with RFID systems
Timing/duration of movements between different locations – especially important for products with limited shelf life
Better management of out-of-stock items (optimal restocking of store shelves)
Help streamline the backroom operations: eliminate unnecessary case cycles, reorders
Better analysis of movement timings for more effective and efficient logistics

47. RFID + Sensors for Better BI
Knowing the location and health of goods (i.e., exception) during transportation

48. Reality Mining
Identifying aggregate patterns of human activity trends (see sensenetworks.com by MIT & Columbia University)
Many devices send location information
Cars, buses, taxis, mobile phones, cameras, and personal navigation devices
Using technologies such as GPS, WiFi, and cell tower triangulation
Enables tracking of assets, finding nearby services, locating friends/family members, …

49. Reality Mining Citisense: finding people with similar interests
A map of an area of San Francisco with density designation at place of interests
See for real-time animation of the content.

50. End of the Chapter
Questions, comments