Anand Final Project

8/8/2019 Anand Final Project

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Anand Vaneswaran

August 12, 2007

Summer Independent Study Business Intelligence

Final Report


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Table of Contents

Business Intelligence Report

1.0 Problem Statement 32.0 Purpose of this Report 3

3.0 Acronyms 34.0 Industry Applications of Business Intelligence (BI)

4.1 Background/Introduction 4

4.2 Measuring BI Benefits 54.3 BI & Data Warehousing (DW) Success Stories 7

4.4 BI Governance Model 84.5 BI The Operational Model 84.6 Current State of BI Solutions 9

5.0 Project Design5.1 The Company 125.2 Mission Statement 125.3 Company Operations 125.4 Process Diagram 13

5.5 Company Performance Tracking & Monitoring 135.6 Dashboard 145.7 E-R Diagram 18

5.8 Design Process 195.9 Design Implementation 195.10 Design Output 20

6.0 Conclusion 207.0 References 218.0 Acknowledgements 21


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Business Intelligence Report

1.0 Problem Statement

The scope of this project is to build a dummy corporation using real-world data from

organizations and explore the use of a tool that extracts data and converts it into useful

information for better management decision-making. The tool used will be NetCharts Designer 5.1.

2.0 Purpose of this Report

The purpose of this report is to describe the process and the approach used to provide

Business Intelligence for a dummy corporation using one of the available tools in the market.

3.0 Acronyms

IT Information Technology

BI Business Intelligence

DW Data Warehousing

IDC International Data Corporation

ROI Return-on-investment

TDWI The Data Warehousing Institute

OLAP Online Analytical Processing Technology

ODBC Open Database Connectivity

SQL Structured Query Language

DSN Database Source Name

HTML Hypertext Markup Language


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4.0 Industry Applications of Business Intelligence (BI)

4.1 Background/ Introduction

In the context of todays Information Age as opposed to the Industrialization age of

the past, heavy emphasis and reliance by most Corporations for data/information and the ability of

the systems to synthesize the same to enable better and quick decision-making is seen as a distinct

competitive edge in the marketplace.1 The fallout of this paradigm has resulted in the critical need

for establishing a strong nexus between the Business Processes in a company and the

corresponding Information Technology needs to provide the needed Business Intelligence that

would facilitate Corporations to arrive at informed decisions through Data Analysis and Synthesis.

In such a setting, Business Intelligence refers to various tools, in the form of applications

and technologies, used to gather, convert, and interpret data regarding the nature of the business,

such as metrics on sales, production, and internal operations. In this day and age, there is a need

for decision makers to receive accurate, actionable, and standardized information in a timely,

proactive, and automated manner. Organizations that make use of these applications and

technologies and implement them in their Business will gain an automatic competitive advantage

over those that have to manually build comprehensive financial and operational reports. When

things are done manually, it often results in a huge disparity in information availability and

accuracy.

Organizations in the US and across the globe have invariably moved towards the concept

of information democracy in todays global marketplace. This simply means that all users should

have access to the insight that they need to carry out their respective roles, and when information

is uniform and consistent across the enterprise. While companies look for ways to contain the costs

and complexity of managing data, the real goal is to leverage the information to make better

business decisions, to be more agile, and to gain insight into business performance. A recent


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survey of respondents constituting mostly IT and Business Professionals indicated that improving

data accuracy and integrity and gaining quick access to information is most important for their

organizations. Among other compelling findings in surveys, the need to find reliable business

intelligence (BI) strategies is becoming increasingly important. Currently, most organizations are

not taking full advantage of existing BI solutions. Benchmarks conducted on data warehouses (DW)

in organizations, small and large, across the United States revealed that companies are successful

in their BI & DW initiatives. While quick access to data and providing a repository of decision

support data scored high, completeness of data and improved communication scored low.

4.2 Measuring Business Intelligence benefits

To make the case for value, the International Data Corporation (IDC), a market research

and analysis firm, has found that organizations who successfully integrate Business Intelligence into

a Business Process can achieve a significant return on investment. IDCs Financial Impact of

Business Analytics study interviewed over 40 companies in a wide variety of industries in North

America and Europe. The study found that a Business Intelligence implementation generates a

median five-year return on investment (ROI) of 112% with a mean payback of 1.6 years on

average costs of $4.5 million. Of the organizations included in this study, 54% had an ROI of 101%

or more. The largest class of benefit was due to business process enhancement, where BI was

applied to operational decision in areas such as logistics, call centers, fraud detection, and

marketing campaign management. 2

Despite its promise, BI is not exactly delivering the ROI that C-level executives have

expected. The cause for most BI problems is not so much about the technology but actually about

the significant effects that BI has on the organizations and its people. Therefore, effective change

management as part of a BI program means putting in place a governance system to proactively

facilitate data integration for every change to the business architecture.


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One reason why organizations would be resistant toward change is because of the fact that

they never seem to be able to figure out the quality and relevance of data the starting point in a

BI initiative. One of the best ways to understand more about the current quality of data is to look

at how much the data is being used and how many users are actually using the data. Organizations

are now moving towards a pyramid that uses eight parameters as levels of data sophistication.

Data type & domain: looking at specific data type and attribute value domains to ensure

conformance. Non-printable characters, time zone ambiguities are a few examples.

Completeness:both logical and physical completeness of data.

Uniqueness & referential integrity:uniqueness applies within an entity. Referential integrity applies

to uniqueness in foreign-key/primary-key relations between entities.

Consistency:while referential integrity addresses entity relationships, consistency is concerned with

content overlaps and inconsistencies of data.

Freshness and timeliness:freshness addresses the currency of the content of the data. Timeliness

addresses when data becomes available to users.

Business rules conformance: it deals with whether data is used and transformed consistently with

its intent, definition, and semantics.3


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4.3 BI and DW Success Stories4

The table below covers a snapshot of Success Stories in the BI space from some Major

Corporations:

Business

Opportunities/ Benefits

Information needed Actions

WALMART: optimized

merchandising, promotion and

pricing, reduced stock by

20%, improved turnover by

2% to 5%

Items, costs, customer

behavior, inventory levels

Analysis of each cost and each

item for all 3500 suppliers,

quick response for inventory

levels and pricing

SONY THEATRES: improved

film scheduling/booking,

enhanced promotion

Detailed daily box office

information (number of tickets

sold, etc)

Forecasts of attendance and

potential sales and margins

HEWLETT PACKARD:

improved after sales service

Data on customers and after

sales services

Customer surveys (Satisfaction

ratings)

BANK OF AMERICA:

improved customer service,

65% increase in loan requests

Quick access to data on 36

million customers (profitability,

risk, needs)

Launch of a new loan by

phone product, development

of a comprehensive knowledge

of each customers needs

MTV NETWORKS:

programming changes in line

with customer services

Internal and external

(panels) data

Better reporting, monitoring

and decision support for

programming and ad planning


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4.4 Business Intelligence Governance Model

The fundamental components of governance are the mission statement, where the

organization or business unit provides and communicates overall purpose of the BI and DW

initiative; working definitions, which ensures common understanding between all parties involved;

and guiding principles, which provides specific direction to the project team. There will also be put

in place a Steering Committee, which will determine the mission and guiding principles, determine

the scope of each DW, establish quality standards, and sanction the governing data models.

The Data Warehousing Institute (TDWI) found in a recent survey that successful BI

initiatives are almost five times more likely to have project teams in which IT is very aligned with

the business. Organizations should ask some fundamental but pertinent questions when leading BI

initiatives:

Who are my customers?

Who are my profitable customers?

Who, what, and where am I on target to meet sales goals?

How do we manage our customer equity?

Which possibilities for additional business do we have with our current customers?

How should we handle our relationships with customers?

BI and DW will lead to development of additional and profitable sales, increased efficiency of sales

and marketing, improved customer service, decision support and monitoring, and cost reduction. 4


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4.5 Business Intelligence The Operational Model

The Typical Steps in institutionalizing and operationalizing a BI Program in a company would

tend to revolve around the following:

- Mission of the Program Statement of Purpose

- Strategic Objectives of the Program derived from the Mission Statement

- Strategic Measures / Critical Success Factors of the Program in line with the Strategic

Objectives

- Understanding Business Processes resulting in a Requirements Document

- Design/Code/integration testing resulting in a IT Platform for use by the Business

There are two major success constructs that have emerged from a recent survey of all the

important players in organizations BI and DW programs: product measures and development

measures.

Product Measures

Information quality:DW provides accurate, complete, and consistent information

System quality:DW is flexible, scalable, and able to integrate data

Individual impacts:quick and easy access to data; improves their decision-making

Organizational impacts: BI and DW should meet business requirements; support the

accomplished of strategic business objectives; enable improvements in business processes;

lead to high, quantifiable return on investment (ROI).

Development Measures

Development cost:cost of developing and maintaining DW

Development time:the time taken to develop DW5


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4.6 Current state of Business Intellige nce solutions

Business Intelligence Tools

Business Intelligence tools are interactive computer-based structures and subsystems

intended to help decision-makers use communication technologies, data, documents, knowledge,

and analytical models to identify and solve problems. During the 1990s, many organizations

around the US engaged in data warehousing projects. These activities included bringing together

the organizations legacy systems to developing user interface tools for analysis and reporting. The

data warehouse is the underlying structure from which reports and documents for analysis are

generated. Tools typically are in the form of dashboards and scorecards. Dashboards give

information seekers insight into day-to-day progress and performance data on a real-time and

integrated basis. The whole purpose of a dashboard is to integrate all the necessary data and

visualize it to the decision-makers. It is ideal because information is conveyed quickly and executive

managers think of it as eye candy. A Dashboard type user interface design allows presentation

of complex relationships and performance metrics in a format that is easily understandable and

digestible by time pressured managers. More specifically, such interface designs significantly

shorten the learning curve and thus increase the likelihood of effective utilization. A scorecard is a

custom user interface that helps optimize an organizations performance by linking inputs and

outputs both internally and externally through the use of metrics and graphs. To be effective, a

scorecard must link into the organizations vision. Typically, tools can be categorized as data-

driven and model-driven. Model-driven systems tend to utilize analytical constructs such as

forecasting, optimization algorithms, simulations, decision trees, and rules engines. Data-driven

systems deal with data warehouses, databases, and online analytical processing (OLAP)

technology.6


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One of the best ways to measure how well organizations utilize information/data

management solutions and from which vendors these products and services were obtained is

through the use of surveys.

As illustrated in the figure below, only 20% of respondents deploy BI tools widely

throughout the enterprise, followed by 32% whose deployment is limited to specific problems, and

another 30% who report scattered deployment. Nearly 15% roll out BI tools widely only after

initial deployment. These results indicate that only very few organizations take full advantage of BI

solutions for their business needs.

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Business Intelligence Systems

The survey also indicated that 68% of the respondents are using Microsoft Products for

their business intelligence and data management needs. 61% also use Oracle Products, while

about one-third use IBM.


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5.0 Project Design

5.1 The Company

SmartBiz, Inc. is a Telecommunications company based in Munich, Germany with employee

strength of roughly 5,000 and headquartered in Munich with field offices spread all across the

world. This company caters to the Telecom industry and primarily supplies products for the internet

market with stiff competition from other competitors, notably Allied, Inc and Tech Com. SmartBiz

is listed in the New York Stock Exchange (NYSE) as a publicly-held company and for the year

ending 2006 reported a net revenue of $1 million.

5.2 Mission Statement

To transform and enrich peoples lives through outstanding communications network and

growth of customers.


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5.3 Company Operations

Fundamentally operating on a customer-centric model, the following are some key

Business Processes:

1. Order administration and handling

2. Offer and contract management

3. Product lifecycle management

4. Manufacturing and volume production

5. Repair and Logistics

The process view model depicting the flow of the above processes is shown below.

5.4 Process Diagram

OrderReceipt

OrderEntity

OrderValidation

Customer

Inputs

Customer

Outputs

FactoryManufacturing*

R & D Design

Transportation- Logistics*

Installation

Customer Satisfaction*

ContractClosure

Delivery*

RepairedProduct

DefectiveProduct*

* - Points of

Measurement

Suppliers


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5.5 Company Performance- Tracking and M onitoring

The Organization tracks and monitors its performance around the processes listed above

through a scorecard approach refereed to as the Balanced Scorecard. The Executive Management

chaired by the Chief Executive Officer and his direct reports review the performance on a monthly

basis and work on corrective actions for underperforming measures.

5.6 Dashboard

The most recent Business Scorecard performance for the month of June 07 is given below.

Repair Performance

NodeNumber

Repair/turnaround time(# daysactual) Target Status

1 10 15

2 15 15

3 13 15

4 22 15

5 11 156 16 15

7 9 15

8 14 15

9 13 15

10 12 15

Order Fulfillment Lead Time Performance

Item # Lead Time Actual Status

1 10 152 10 17

3 10 18

4 10 9

5 10 12

6 10 8

7 10 13


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8 10 16

9 10 10

10 10 7

Delivery Quality Performance

Month # of items shipped # of defective items # allowed Status

1 40 4 4

2 40 8 4

3 40 9 4

4 40 2 4

5 40 0 4

6 40 6 4

7 40 12 4

8 40 6 4

9 40 5 410 40 3 4

11 40 7 4

12 40 10 4

Customer Critical Issue (CCI) Performance

Item Number CCI - # of customer critical issuesper month Target Status

1 24 20

2 35 20

3 44 20

4 42 20

5 55 20

6 17 20

7 16 20

8 11 20

9 9 20

10 18 20

Financial Revenue Performance

Quarter Revenue (in millions) Target Status

1 20 20

2 22 20

3 19 20

4 16 20

5 17 20

6 18 20


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7 26 20

8 24 20

Gross Margin Outlook Performance

Quarter Gross Margin (%) Target (%) Status

1 12 15

2 14 15

3 16 15

4 16 15

5 17 15

6 11 15

7 15 15

8 13 15

Product Cost Reduction for a single product - Performance

Month Unit Price Target ($) Status

1 35 40

2 38 40

3 45 40

4 40 40

5 42 40

6 50 40

7 36 40

8 35 409 30 40

10 45 40

11 55 40

12 40 40

First Pass Yield Performance

Item Number FPY (Factory) Target (%) Status

1 82 90

2 88 903 87 90

4 95 90

5 93 90

6 100 90

7 91 90

8 80 90

9 75 90


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10 90 90

Supplier Audit Corrective Action Closure Performance

Month # of findings Target Status

1 22 10

2 15 10

3 13 10

4 10 10

5 17 10

6 14 10

7 10 10

8 8 10

9 9 10

10 12 10

11 16 10

12 14 10

Customer Satisfaction Performance

Quarter Customer Loyalty Index(CLI) Target CLI Status

1 8 8.5

2 7.5 8.5

3 7.7 8.5

4 9.2 8.5

5 8.6 8.5

6 8.5 8.5

7 7.8 8.5

8 6.9 8.5


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5.7 E-R Diagram

Repair Performance

PK Serial Number

Location Performance

Turnaround time

Target

Status

FK1 Month

Delivery Performance

PK Item number

Lead Time

Actual

Status

FK1 Month

Delivery Quality Performance

PK,FK1 Month

Number of items shipped

Number of defective items

Number allowed

Status

Customer Satisfaction Performance

PK,FK3 Month

Customer Loyalty Index (CLI)

Target

FK1 Serial Number

FK2,FK4 Item numberStatus

FK5 Quarter

Customer Critical Issue Performance

PK Item Number

CCI

Target

Status

FK1 Month

Financial Revenue Performance

PK Quarter

Revenue

TargetStatus

Gross Margin Outlook Performance

PK Quarter

Gross Margin

Target

Status

FK1 Month

Product Cost Reduction Performance

PK,FK1 Month

Unit Price

Target

Status

First Pass Yield Performance

PK Item Number

FPY

Target

Status

FK1 Month

Supplier Audit Corrective Action Closure Performance

PK,FK1 Month

Number of Findings

Target

Status


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5.10 Design Output

The dashboard can be viewed at:

http://68.38.10.229:8001/projects/SmartBiz/SmartBizPage1.jsp

6.0 Conclusion

Business Intelligence is one of the leading investment priorities for companies today. This

reflects greater recognition of the need to reduce complexity caused by multiple sources of

information and to improve decision-making processes in the enterprise. Yet companies face

implementation challenges, notably data integration, scalability, availability, and security issues.

Finally, providing innovative business practices that address cost of implementation issues, such as

fixed cost implementation, are creative ways to reduce customer risk and gain increased customer

mindshare as a true partner for BI implementations.


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The approach described in this project demonstrates a simple but effective methodology of

translating key company measures into an operational dashboard for decision-making by SmartBiz,

Inc. With variations to this approach, it is easy to establish design of similar dashboards to provide

business intelligence to the executives and operational managers in any organization.

7.0 References

1. Hoisington, Steven H. Vaneswaran, SA. Implementing Strategic Change: Tools for

Transforming an Organization, McGraw-Hill, 2005.

2. Eastwood, Matthew. Vesset, Dan. Morris, Henry D. HP: Delivering Value in Business

Intelligence, White Paper, February 2005.

3. Knightsbridge Solutions LLC. A Practical Approach to Data Quality: Proven Formulas for

Delivering Measurable Results, White Paper, 2005.

4. Chicago Business Intelligence Group (CBIG). Using Business Intelligence and Data

Warehousing Methods, Tools and Processes to Drive Business Results, White Paper, 2005.

5. Ariyachandra, Thilini. Watson, Hugh. Benchmarks for BI and Data Warehousing Success.

http://www.dmreview.com/article_sub.cfm?articleID=1044330. January 2006.

6. Hall, Owen P, Jr. Using Dashboard-based Business Intelligence Systems: An approach to

improving business performance. http://gbr.pepperdine.edu/034/bis.html. 2003.

7. TechRepublic. Information Management Trends in 2005. CNET Networks. 2005.

8.0 Acknowledgements

I wish to place on record my deep appreciation for all the guidance and advice given by my

professor, Bryan D. French, throughout the tenure of this project. His insightful comments now and

then helped me to be aware of certain aspects of this project that would not have been possible

otherwise. I also wish to thank some of my friends for their help and inputs.

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