Transcript DSS Chapter 1 - Washburn University

Learning Objectives
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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
Learning Objectives
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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
Opening Vignette…
“BI Eastern Mountain Sports Increases
Collaboration and Productivity”
 Company background
 Problem description
 Proposed solution
 Results
 Answer & discuss the case questions
Opening Vignette
Collaborative Decision Making at Eastern Mountain Sports
Implementing BI – An Overview
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Decisional Factors in BI Implementation
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Reporting and analysis tools
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Database
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Accessibility, efficiency, usability
Costs
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Scalability, performance, security
ETL Tools
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Features, functionality, flexibility, scalability
Hardware/software, development/training
Benefits
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Tangibles/intangibles - time saving, improved
decisions/operations/customer satisfaction/
Implementing BI – An Overview
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Critical Success Factors for BI Implementation
Business driven methodology and project
management
b. Clear vision and planning
c. Committed management support and sponsorship
d. Data management and quality issues
e. Mapping the solutions to the user requirements
f. Performance considerations of the BI system
g. Robust and extensible framework
a.
Managerial Issues Related to BI
Implementation
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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
BI and Integration Implementation
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Types of Integration
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Functional integration
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Physical integration
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different [physically separate] applications are
provided/used as if it is a single system
packaging the hardware, software, and
communication features required to accomplish
functional integration
Primary focus in BI (and in this book) is
functional-application integration
BI and Integration Implementation
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Why integrate?
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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.
BI and Integration Implementation
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Levels of BI Integration
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Functional integration can be within the
same BI or across different BI systems
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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
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Serving as the intelligent agents within BI
Connecting BI Systems to Databases
and Other Enterprise Systems
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Virtually every BI application requires
database or data warehouse access
Multi-tiered Application Architecture
Connecting BI Systems to Databases
and Other Enterprise Systems
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Integrating BI applications and back-end
systems
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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
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ERP captures and stores data
BI converts data into information/knowledge
Middleware?
On-Demand BI
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The limitations of Traditional BI
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Complex, time-consuming, expensive
The On-Demand Alternative
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On-demand computing = Utility computing
SaaS (Software as a service)
Allows SMEs to utilize affordable BI
On-demand function alternatives
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Internally sharing licenses within a firm
Sharing licenses with many firms via an ASP
Benefits of On-Demand BI
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Ability to handle fluctuating demand
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Reduced investment/cost
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Flexible use of the BI technology pool
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
The Limitations of On-Demand BI
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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)
Issues of Legality, Privacy and Ethics
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Legal issues
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Liability for the actions of advice provided by BI
Who is liable, if the software advice fails?
Privacy
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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
Issues of Legality, Privacy and Ethics
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Ethics in Decision Making and Support
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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-workrelated purposes (personal use of Internet
while working)
Issues of Legality, Privacy and Ethics
A Model of Ethical Problem Formulation
“Unfolding” to control expansion
S
S
S
Typical problem
formulation
(T.O.P perspective)
Stakeholder
expansion
Problem
formulation
expansion
Typical problem
formulation
(T.O.P perspective)
S
Conversation
S
S
= Stakeholder
S
Integration of moral
intensity
components
Problem
definition
Emerging Topics in BI – An Overview
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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)
Emerging Topics in BI – An Overview
The Future of BI
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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)
Emerging Topics in BI – An Overview
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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 industryspecific 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.
The Web 2.0 Revolution
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Web 2.0: a popular term for describing
advanced Web technologies and applications,
including blogs, wikis, RSS, mashups, usergenerated 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
The Web 2.0 Revolution
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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
The Web 2.0 Revolution
Characteristics of the Web 2.0
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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-inprogress and allows rapid prototyping, using the Web
as an application development platform.
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)”
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The Web 2.0 Revolution
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Ajax (Asynchronous JavaScript and XML)
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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
Online Social Networking –
Basics and Examples
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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.
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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
Online Social Networking –
Social Network Analysis Software
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It is used to identify, represent, analyze,
visualize, or simulate networks with
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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
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Business-oriented social network tools such as
InFlow and NetMiner
Social Networks Visualizer, or SocNetV, which is a
Linux-based open source package
Mobile Social Networking
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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
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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)
Major Social Network Services
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Facebook: The Network Effect
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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.
Major Social Network Services
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Orkut: Exploring the Very Nature of Social
Networking Sites
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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
Implications of Business and
Enterprise Social Networks
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Business oriented social networks can go
beyond “advertising and sales”
Emerging enterprise social networking apps:
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Finding and Recruiting Workers
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Management Activities and Support
Training
Knowledge Management and Expert Location
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See Application Case 14.2 for a representative example
e.g., innocentive.com; awareness.com; Caterpillar
Enhancing Collaboration
Using Blogs and Wikis Within the Enterprise …>
Implications of Business and
Enterprise Social Networks
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Survey shows that best-in-class companies
use blogs and wikis for the following
applications:
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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%)
Virtual Worlds
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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:
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Second Life (secondlife.com)
Google Lively (lively.com)
EverQuest (everquest.com)
Avatars ?
Second Life as a DSS
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Advantages:
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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
Second Life as a DSS
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Disadvantages:
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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"
Virtual Tradeshows
See iTradeFair.com
Social Networks and BI:
Collaborative Decision Making
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Collaborative decision making (CDM) –
combines social software and BI
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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.
How CDM Works
RFID and BI
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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.
How does RFID work?
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RFID system
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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
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Active tag versus Passive tags
Data Representation for RFID
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RFID tags contain 96 bits of data in the form
of serialized global trade identification
numbers (SGTIN) [see epcglobalinc.org]
RFID for Supply Chain BI
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RFID in Retail Systems
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Functions in a distribution center
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receiving, put-away, picking, and shipping
Sequence of operations at a receiving dock
unloading the contents of the trailer
2. verification of the receipt of goods against
expected delivery (purchase order)
3. documentation of the discrepancy
4. application of labels to the pallets, cases, items
5. sorting of goods for put-away or cross-dock
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RFID for Supply Chain BI
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RFID in Retail Systems
RFID Data Sample
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RFID in Retail Systems
RFID for BI in Supply Chain
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Better SC visibility with RFID systems
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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
RFID + Sensors for Better BI
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Knowing the location and health of goods
(i.e., exception) during transportation
Reality Mining
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Identifying aggregate patterns of human
activity trends (see sensenetworks.com by
MIT & Columbia University)
Many devices send location information
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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, …
Reality Mining
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Citisense: finding people with similar interests
A map of an area of San
Francisco with density
designation at place of
interests
See
www.sensenetworks.com/city
sense.php for real-time
animation of the content.
End of the Chapter
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Questions, comments