Business Intelligence by zlPmEyM

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									  Business Intelligence:
Riding the Learning Curve




   Oti, Ashley, Brian, and Maggie   1
                                        1
Business Intelligence
What is BI and why is it important?
    Definition and history
    Primary approaches to BI
    Money Spent
    Best Practices
    Organizational types and BI needs
Case Studies
    Wild Track
    TALX
    Continental Airlines
    Sigma-Aldrich
Conclusions and interactive BI           2
What is Business Intelligence?




                             3
    What is Business Intelligence?

The gathering, storing, analysis, and dissemination of
data/information to facilitate informed business
decision-making.

  Enterprise Resource Planning
  Customer Relationship Management
  Data Warehousing
  Et Cetera

  Simply put, it is using information to succeed!
                                                         4
               What is Business Intelligence?




      Gathering                                  Storage                           Analysis         Distribution
“Business Intelligence-The Missing Link.” http://www.ittoolbox.com/peer/bi.pdf, Viewed 4/12/2006.           5
            History of Business Intelligence

            “Business Intelligence” (BI) was coined by Howard J
            Dresner in 1989 to describe how users could access and
            analyze company information stored in systems to better
            understand business and customers.
                                                                                      20 wheels last week
                                                                                         30 this week
                                                                                      next week make 40


    BI has existed in one form or another
    since the beginnings of trade.


“Business Intelligence Lies Beyond IT-Dresner.”
http://www.businessintelligence.com/ex/asp/id.631/xe/bimediadetail.htm, Viewed 4/4.
http://www.dollarway.org/caveman_carving_stone_hw.gif                                                 6
                 History of Business Intelligence
                   First appearance of modern concept of BI came from ex-soviet spy and
                   U.N. delegate Stevan Dedijer in the 1960’s

                        Applied principles of “political intelligence” to business
                        Believed strongly that BI should not be corporate espionage.
                        His research indicated that BI paralleled political intelligence as far
                         back as he looked (e.g. Swedish bank with >100-year old intelligence
                         dept., Dutch ceramics espionage in 1500’s (tech. stolen from China),
                         E. Indies spice trade, etc.)
                        “Intelligence he concluded was an integral and necessary part of any
                         self-maximizing system in conditions of competition.”




Marren, Patrick. ”The Father of Business Intelligence” The Journal of Business Strategy; 2004; 25, 6;   7
                History of Business Intelligence

                       Previous Names                                          Related Concepts

          o Decision Support Systems                                         Competitive Intelligence
          o Executive Information                                            Market Intelligence
            Systems                                                          Customer Intelligence
          o Online Analytic                                                  Competitor Intelligence
            Processing                                                       Strategic Intelligence
                                                                             Technical Intelligence

                                                                        • Knowledge Management
oGray, Paul. New Thinking about the Enterprise. Information Systems management; Winter 2005, 22,1, p. 91-94.
•Lonnqvist, Antti and Virpi Pirttimaki. “The Measurement of Business Intelligence.” Intelligence Systems Management; Winter 2006; 8 1, p.
                                                                                                                                  23,
32-40.
               History of Business Intelligence

            1960s - 1980s
            Only IT had access to data stored on computers. End users would request
            printed reports (usually regarding local needs). Long and tedious process
            that was used more to retroactively support decisions, not make them.

            1990s
            Employees began to think of corporation as a whole, requiring
            standardization, and resulting in Data Warehousing. “End user computing”
            also arrived on the scene, allowing each person to customize data analysis.

            2000s
            Systems are developed to analyze and present the data to end users (five
            general categories).
“Business Intelligence-Is it Really New?” http://www.pinndec.com/News/PressReleases/Press_Releases32.asp, viewed 4/11/2006.   9
                Five General Approaches to BI
                1. Scorecards and Dashboards
                             Scorecards present key performance indicators (e.g. ROI)
                             Dashboards present business performance in a condensed
                              and simple “dials and gauges” format




http://www.bixpert.hu/imgs/MANAGED/Report_Services/01.jpg
http://www.microstrategy.com/Solutions/5Styles/                                    10
               Five General Approaches to BI

           1. Scorecards and Dashboards
           2. Enterprise Reporting
                          Custom reports formatted to provide detailed information
                           to a variety of users. This is the most common approach
                           to BI. Less condensed than scorecards and dashboards.




http://www.microstrategy.com/Solutions/5Styles/                                   11
               Five General Approaches to BI

           1. Scorecards and Dashboards
           2. Enterprise Reporting
           3. On-line Analytical Processing (OLAP) Analysis
                          Relates subsets of data (e.g. time, customer, revenues) for
                           “cube” analysis. Allows access to some primary data.




http://www.microstrategy.com/Solutions/5Styles/                                      12
                Five General Approaches to BI

           1.    Scorecards and Dashboards
           2.    Enterprise Reporting
           3.    On-line Analytical Processing (OLAP) Analysis
           4.    Advanced and Predictive Analysis
                          Similar to OLAP, but allows users full access to primary
                           data. Provides the maximum analysis potential.




http://www.microstrategy.com/Solutions/5Styles/                                       13
                Five General Approaches to BI

           1.    Scorecards and Dashboards
           2.    Enterprise Reporting
           3.    On-line Analytical Processing (OLAP) Analysis
           4.    Advanced and Predictive Analysis
           5.    Alerts and Proactive Notification
                          Automated generation of reports with user subscriptions
                           and “alerts” to problems and/or opportunities.




http://www.microstrategy.com/Solutions/5Styles/                                      14
                    Business Intelligence Spending

                                                    Global BI Spending


                                   6
                                  5.8
                 US$ (billions)




                                  5.6
                                  5.4
                                  5.2
                                   5
                                  4.8
                                         03




                                                        04




                                                                               05




                                                                                                    06
                                        20




                                                      20




                                                                            20




                                                                                                  20
•Gile, K., Russom, P., Moore, C., and Fossner, L. “Business Intelligence Driven By Compliance, Standardization, And Performance Initiatives.”
Market Research Report. 2005.
                                                                                                                                   15
•Whiting, Rick. “BI Spending to Increase.” Information Week, March 6, 2006.
              Business Intelligence Spending

                  In a Merrill Lynch survey of 100 CIOs, BI
                  ranked as the #1 spending priority for 2006
   Top Spending Priorities                             % respondents ranking in top 5
(1) BI/DW                                                           53
(2) Application Integration                                         33
(3) Corporate Portals                                               29
(4) Security                                                        27
(5) Supply Chain Management                                         26



Kash Rangan et al. Merrill Lynch Survey October 2005                              16
 Best Practices

Clearly define goals (both short and long-
term) and expectations
Know your unknowns and unknowables
Match strategy with company BI needs
Simplify
Plan to use BI for prediction rather than
reporting
Real-time


                                             17
              Best Practices cont.
             “…best practice BI today relies not only on
             technology, but on strategic plans and
             predictive insights.”
                   Relies on a broad portfolio of software tools for data,
                    process, data extraction and quality, integration,
                    analysis, forecasting, and visualization
             This helps organizations to monitor business
             operations and events, measure performance, and
             drive the newly updated process changes.

Rinaldi, Damian V. Best Practice BI Relies on Broad Portfolio. SoftwareMag.com. The IT Software Journal. July 2005. Pg. 1-6   18
The BI Learning Curve

                                                                    Sigma
 Complexity of Business Needs
                                High



                                                      Continental
                                Medium




                                                  TALX



                                         Wild Track
                                Low




                                            Low           Medium        High

                                            Implementation Difficulty          19
                              Case study
Small company, simple needs

         Background Information
         Business Problem
           Old Method
           New Method

         Business Intelligence Solution




                                           20
                                                         Background
Small company, simple needs

            A wildlife conservation non-profit organization, spin-off
            from Rhinowatch
            Founded by Zoë Jewell and Sky Alabhi in 2004
            Situated in Sub-Saharan Africa; main headquarters in
            Namibia’s Waterberg Plateau Region

            In the business of conserving rhinos
            Not the average business ($$$) but has created substantial
            ROI for indigenous workers

Swoyer, Stephen. ”BI Case Study: Tracking Business Intelligence Success.” Business Intelligence Journal.; Spring   21
2005; 10, 2; ABI/INFORM Global pg.15
                                                     Business Problem
 Small company, simple needs

                Attrition of Rhinos
                Black Rhino
                White Rhino
                Old Method
                New Method




http://www.rhinos-irf.org/technicalprograms/afrsg/                      22
                                                           Rhino Attrition
 Small company, simple needs
                                                                                  Southern White Rhino
                                                                                  11,100
                                                                                  Northern White Rhino-
                                                                                  only 30 remain
                                                                                  Found only in the
                                                                                  Democratic Republic of
                                                                                  Congo

     Black rhino is most endangered
     70,000 in the 1970s
     3,600 remain today




Swoyer, Stephen. ”BI Case Study: Tracking Business Intelligence Success.” Business Intelligence Journal.; Spring 2005; 10, 2;
ABI/INFORM Global pg.15
                                                                                                                                23
http://www.wildtrack.org/
                                                           Old Method
 Small company, simple needs

                     Invasive monitoring techniques
                     Tagging, radio collaring, etc.
                     Negative impact
                          Expensive
                          Highly involved




Swoyer, Stephen. ”BI Case Study: Tracking Business Intelligence Success.” Business Intelligence Journal.; Spring 2005; 10, 2; ABI/INFORM
Global pg.15
                                                                                                                                    24
http:/www.wildtrack.org/
                                                          New Method
Small company, simple needs

              Footprint
              Identification
              Technique (FIT)
              Paper, pencil, and
              ruler
              Positive impact
                    Cheaper
                    Less involved

Swoyer, Stephen. ”BI Case Study: Tracking Business Intelligence Success.” Business Intelligence Journal.; Spring 2005; 10, 2; ABI/INFORM
Global pg.15
                                                                                                                                   25
http:/www.wildtrack.org/
                                                           BI Solution
Small company, simple needs



               Footprints photographed (digital), then optimized on
               Adobe Photoshop
               Fed into NiSAS, which uses custom input algorithm to
               identify derived points from landmark cues in the photos
               NiSAS generates 93 different measurements based on the
               distance and angles between those points
               Database is loaded with measurements
               JMP takes over
               Footprint library of each rhino is presented as a circle
Swoyer, Stephen. ”BI Case Study: Tracking Business Intelligence Success.” Business Intelligence Journal.; Spring 2005; 10, 2;
ABI/INFORM Global pg.15
                                                                                                                                26
http:/www.wildtrack.org/
                                                           BI Solution
Small company, simple needs

          Tracks are photographed, then analyzed using JMP statistical
          software




Swoyer, Stephen. ”BI Case Study: Tracking Business Intelligence Success.” Business Intelligence Journal.;
Spring 2005; 10, 2; ABI/INFORM Global pg.15
                                                                                                            27
http:/www.wildtrack.org/
                                                           Results and Conclusion
Small company, simple needs
                                                     The Footprint
                                                     Identification
                                                   Technique won the
                                                  Environment, Energy
                                                 and Agriculture award
                                                       in the 2002
                                                    Computerworld
                                                         Honors
                                                    program…were
                                                   nominated by SAS,
                                                   whose software we
                                                 use. Full details of the
                                                 award are available at
                                                   www.cwheroes.org
http://www.rhinos-irf.org/technicalprograms/afrsg/
Swoyer, Stephen. ”BI Case Study: Tracking Business Intelligence Success.” Business Intelligence Journal.; Spring 2005; 10, 2;   28
ABI/INFORM Global pg.15
                        Case Study
  Medium company,
somewhat simple needs

        Corporate HQ in St. Louis
        HR and Payroll BPO for the verification of
        employment and income, unemployment
        cost management, and tax credits and
        incentives
        Houses over 75 million employee records
        FY06 Revenues estimated at $200 million
        1,800 employees
                                                     29
                                                                                                              CRM
                                            Problem
    Medium company,
                                                                            SalesLogix
  somewhat simple needs                                                       (CRM)


               Much of growth in
               recent years from
               acquisitions                                                  Solomon
                                                                             (Acctng)
               Multiple information
               platforms
               Different data on each                                        Oracle
                                                                                                 Business
                                                                                                 Reporting
               platform                                                    (TWN apps)
                                                                                                 & Analysis

               Multiple reporting
               structures
•Browder, Laura, Senior Business Analyst for The Work Number, Interviewed March 9, 2006.   Mgt
•Farrell, Craig, Data Warehouse Technical Lead, Interviewed March 9, 2006.                                    30
                                             Solution
    Medium company,
  somewhat simple needs

               Laura Browder-Project/Business Sponsor
               Craig Farrell-IT Project Manager
               Data Warehouse (Quilogy)
               Use OLAP-Online Analytical Processing
               (ProClarity/Einstein)
               Expected ROI 200% ($1 million)
                  Time Savings
                  Data mining

•Browder, Laura, Senior Business Analyst for The Work Number, Interviewed March 9, 2006.
•Farrell, Craig, Data Warehouse Technical Lead, Interviewed March 9, 2006.                 31
                                              Data Warehouse
    Medium company,
                                                Data Sources                          Data Warehouse
  somewhat simple needs

            6 months for                           SalesLogix                              Sales
            data cleansing                           (CRM)                                 Data Mart
                                                                                                                             CRM
            “Putting out                                             Extract,
            fires” (Farrell)                                         Transform,            Finance
                                                                                           Data Mart
            2 months of                                              & Load
                                                    Oracle
            Parallel reporting                    (TWN-Apps)
            (test)                                                                         Client
                                                                                           Data Mart                        Business
            Frequency of                                                                                                    Reporting &
            data loads                                                                                                      Analysis

            Data Marts-                              Solomon
                                                                                           Records
                                                                                           Data Mart
            ”subject-specific                      (Accounting)
            data stores”

                                                                                                                          Management

•Browder, Laura, Senior Business Analyst for The Work Number, Interviewed March 9, 2006.
•Farrell, Craig, Data Warehouse Technical Lead, Interviewed March 9, 2006.                                                           32
•Adapted from Vitt, Elizabeth, Luckevich, Michael, and Misner, Stacia. Business Intelligence: Making Better Decisions Faster. 2002, 51.
                                              Data Warehouse Users
    Medium company,
  somewhat simple needs


                                                               Power Analysts
                                                                2 Developers


                                                           Information Consumers

                                                                     30
                                                              Business Analysts
                                                                Management
                                                                    CRMs


                                                              Information Users

                                                               Eventual Users:
                                                           1,800 TALX Employees
                                                            Limited Client Access




•Browder, Laura, Senior Business Analyst for The Work Number, Interviewed March 9, 2006.
•Farrell, Craig, Data Warehouse Technical Lead, Interviewed March 9, 2006.                                                           33
•Adapted from Vitt, Elizabeth, Luckevich, Michael, and Misner, Stacia. Business Intelligence: Making Better Decisions Faster. 2002, 56.
                                              BI Gaps
    Medium company,
  somewhat simple needs

                Project Champion
                Change Management okay…
                ROI from time/cost savings
                Need more data mining-REVENUE
                GENERATION
                “We need to think like plumbers, fixing
                holes, finding those industries where we
                don’t have 100% market share.” (Farrell)
•Browder, Laura, Senior Business Analyst for The Work Number, Interviewed March 9, 2006.   34
•Farrell, Craig, Data Warehouse Technical Lead, Interviewed March 9, 2006.
                               Continental Airlines
                               Case Study
   Large company,
somewhat complex needs




                       “Continental Airlines is a
                  LEADER in real-time BI and the
                  fifth largest airline in the US and
                      the seventh in the world!”


Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business
Intelligence: Best Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.   35
                              “Real-time BI”
   Large company,
somewhat complex needs

              Real-time BI is like “regular” business intelligence
              as far as an organization performing an analysis on
              strategic information for making effective
              business decisions
              BUT, real-time BI focuses more on current
              business decisions that are made for “customer
              facing applications, like those found at check-in
              processes, and helps firms become more customer
              centric”.
Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business                36
Intelligence: Best Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.
                              Background
   Large company,
somewhat complex needs

               Background
                  Established in 1934
                  Experienced financial problems in 1990
                           The CEO and the Board developed the “Go Forward
                            Plan”
                                  Fly to Win, Fund the Future, Make Reliability a Reality,
                                   and Working Together
                    In 2001, Continental Airlines provided real-
                     time BI in their organization along with
                     developing a data warehouse
Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business                37
Intelligence: Best Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.
                               BI approach
   Large company,
somewhat complex needs

               The Process of utilizing real-time BI in their
               organization…
                  Focusing on five categories of real-time BI
                   applications
                  Developing their data warehouse
                           The architecture and process of their data warehouse
                    Establishing their Flight Management
                     Dashboard
Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business                38
Intelligence: Best Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.
                              Categories of Real-time BI
   Large company,
somewhat complex needs

       1.        Revenue Management
                      Maximizing revenue in an organization
       2.        Customer Relationship Management
                      Improving customer service to increase profits
       3.        Crew Operations and Payroll
                      Providing employees with strong pay and benefits
       4.        Security and Fraud
                      Supporting airline security efforts
       5.        Flight Operation
                      Providing customers with a great “flying” experience
Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business                39
Intelligence: Best Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.
                               Data Warehouse
                               Architecture




Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business                40
Intelligence: Best Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.
                             Flight Management
                             Dashboard




                                                                                                                              41
Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business Intelligence: Best
Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.
                             Continental’s Vision
   Large company,
somewhat complex needs


             An automated data warehouse system that
             can run several tests at once and receive
             loads of accurate information immediately
             in return
             A Service Bureau was created to help gather
             all real-time information as soon as it
             becomes available
 Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business                42
 Intelligence: Best Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.
                            Continental Airlines
                            Conclusion
   Large company,
somewhat complex needs

                Continental Airlines saw the problem and
                 found the best solution
                Using real-time BI, Continental Airlines
                 generated “more than $500 million in revenue
                 and an ROI greater than 1,000 percent”
                Went from “first to favorite airline”
                Moved to a third generation of decision support
                 and became an example of success to
                 organizations in this situation

Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. Real-time Business Intelligence:43
Best Practices at Continental Airlines. Information Systems Management. Boston: Winter 2006. Vol. 23, Iss. 1.
                 Sigma-Aldrich (SIAL)
                 Case Study
Large company, complex needs

          BI in a global corporation




                                        44
                 Background
Large company, complex needs

            Operates   in 35 countries
            > 6,800 employees

            $2 billion/year in revenues
                Fine Chemicals
                Life Sciences products

                Stable isotopes

                Oligonucleotide synthesis

                Pharmaceuticals

                                             45
                    Problem
Large company, complex needs

              No centralized Data Warehouse or formal
               BI processes
                 Various informal processes ranging from
                  technology conference summary documents
                  stored on common hard drives to archived
                  market research reports
                 Knowledge/data were not globally accessible;
                  the company’s left hand didn’t know what its
                  right was doing, resulting in lost time, duplicated
                  efforts, and inefficient processes
                                                                        46
                 Problem
Large company, complex needs



                                       Research and
         Sales                         Development



                               Legal


                                         Human
      Marketing                         Resources

                                                      47
                   Solution
Large company, complex needs

            New corporate motto “One Company”
            Centralize operations data and provide
             analysis tools with SAP and overlying
             systems
                  Examples of overlying systems include
                       Business Warehouse (SWOT and financial analyses)
                       Over Quota (opportunities database)
                       Sales Database (Track and analyse sales patterns)



                                                                            48
                  Solution
Large company, complex needs


                                Analysis           Research and
                                                   Development
      Sales


                         Centralized Storage and          Legal
                              Analyzation

                                  SAP
                                                      Human
      Marketing                                      Resources
                                                                  49
                        Solution
Large company, complex needs

  Interviewed upper level IT exec (CIO recently left SIAL) to better
  understand BI strategy.
   – 1998 Sales and Distribution
     mod.
                                                                     1999 predicted budget
   – 2001 Business Warehouse                                        Category Cost (Millions)
   – 2003 Purchasing mod.                                            Training        5
                                                                     Software       10
   – 2004 Production Planning mod.                                  Hardware        15
   – 2005 Profitability Analysis mod.                               Consulting      20
                                                                       Total        50
   – 2006 Human Resources mod.
                                                                                                    50
“E-comm end to end.” http://www.networkworld.com/ecomm2000/ecomm-endtoend.html, Viewed 4/17/2006.
                  Solution
Large company, complex needs




 Brian: So, we’re in the middle of a transition to SAP . . .how
 long will this last?
 IT exec.: FOREVER . . . You never finish the transition, we will
 always be implementing SAP!!



                               WHY?


                                                                  51
        SAP Module “Map”
         FI/CO Module
                         QM Module
       Executive
     Management          QC
PA Module
                    IC Module            WM Module
                                     Inventory Control
  SD Module     Sales
                 Production               PO Module
                   PP Module
    HR Module
       Human Resources
                                                      52
                 SAP Module “Map”
                 FI/CO Module
                                       QM Module


         PA Module
                                              •In stock?
                     •In stock?   IC Module                WM Module
                                                •No
•Order
           SD Module                    •Make some
                                                            PO Module
                                  PP Module     •Order components
         HR Module

                                                                        53
                  SAP Module “Map”

   PA Module
Profitability Analysis (Marketing, Sales,
Management, Corp. Strategic Planning)
•Market segment analyses
    •Products
    •Customers
    •Orders
    •Business units

                                               SD Module
                                            Sales and Distribution
                                                              54
                 Outcome
Large company, complex needs


     • Success was gauged through employee interviews
       (e.g. Sales, Operations, Marketing, Technical
       Service, Management, Production, and R&D)
         • Answers mainly depended on the individual’s role
           within the company, but for the most part, people were
           either unaware of the systems in place, or they were
           confused by them.
       No one person understood SAP in its entirety . . . . Even
       one of the primary SAP “architects” was limited in their
       ability to explain it to me
                                                                    55
                 Conclusion
Large company, complex needs


     • Integration of DW/BI within Sigma has been
       extremely difficult and slow due its large size and
       operational diversity/complexity
     • Most business units still operate in isolation from
       others, not many understand the systems in place.
     • Much work remains before we’ll really be able to
       gauge success/failure


                                                             56
 The Need for Business
 Intelligence

WildTrack-business need (simple) identified,
solution clear
TALX-business need unclear, solution not
utilized
CA-business need (complex) identified,
solution clear
SIAL-business needs (complex), many
solutions needed


                                               57
        Interactive BI




                                                               Management
                                                               IS6800 Firm
     Data Warehouse
Ashley, Maggie, Oti, Brian

                                                                IS 6800 Dashboard



                             Business Need Complexity

                                                        High
     BI Software
        Audience                                        Low

                                                                      Low          High
                                                                 Implementation Difficulty58
       IS6800 Dashboard for BI Success
          Complexity of Business Needs
                                         High

 GOOD




CAUTION
                                         Low




 BAD                                            Low                   High

                                                Implementation Difficulty    59
   References
Browder, Laura, Senior Business Analyst for The Work Number, Interviewed March 9, 2006.
“Business Intelligence-Is it Really New?”
http://www.pinndec.com/News/PressReleases/Press_Releases32.asp, viewed 4/11/2006.
“Business Intelligence Lies Beyond IT-Dresner.”
http://www.businessintelligence.com/ex/asp/id.631/xe/bimediadetail.htm, Viewed 4/4.
“Business Intelligence-The Missing Link.” http://www.ittoolbox.com/peer/bi.pdf, Viewed 4/12/2006.
“E-comm end to end.” http://www.networkworld.com/ecomm2000/ecomm-endtoend.html, Viewed 4/17/2006.
Farrell, Craig, Data Warehouse Technical Lead, Interviewed March 9, 2006.
Gile, K., Russom, P., Moore, C., and Fossner, L. “Business Intelligence Driven By Compliance,
Standardization, And Performance Initiatives.” Market Research Report. 2005.
“Five Styles of BI”. http://www.microstrategy.com/Solutions/5Styles/
Gray, Paul. “New Thinking about the Enterprise.” Information Systems Management; Winter 2005, 22,1, p.
91-94.
Kash Rangan et al. Merrill Lynch Survey October 2005
Quilogy-”Choose right BI partner”, http://www.quilogy.com/page.aspx?page=1719, viewed 3/14/2006.
Lonnqvist, Antti and Virpi Pirttimaki. “The Measurement of Business Intelligence.” Intelligence Systems
Management; Winter 2006; 23, 1, p. 32-40.
Marren, Patrick. ”The Father of Business Intelligence” The Journal of Business Strategy; 2004; 25, 6;
ABI/INFORM Global pg. 5.
Rinaldi, Damian V. Best Practice BI Relies on Broad Portfolio. SoftwareMag.com. The IT Software Journal.
July 2005. Pg. 1-6
Swoyer, Stephen. ”BI Case Study: Tracking Business Intelligence Success.” Business Intelligence Journal.;
Spring 2005; 10, 2; ABI/INFORM Global pg.15
Vitt, Elizabeth, Luckevich, Michael, and Misner, Stacia. Business Intelligence: Making Better Decisions
Faster. 2002, 51.
Watson,Hugh J, Barbara H Wixom, Jeffrey A Hoffer, Ron Anderson-Lehman, Anne Marie Reynolds. “Real-
time Business Intelligence: Best Practices at Continental Airlines.” Information Systems Management.
Boston: Winter 2006. Vol. 23, Iss. 1.
Whiting, Rick. “BI Spending to Increase.” Information Week, March 6, 2006.
                                                                                                            60

								
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