business intelligence - methodology dror har bi/dw practice lead ibm bcs, israel

Business Intelligence - Methodology

Dror HarBI/DW Practice LeadIBM BCS, Israel

Things I thought to talk about:

• IM versus DW versus BI versus KM

• IBM BI Methodology

• Business Cases:– Business Case (FS)– Data Modeling (Telco)

• Q&A

Changes In IBM!!!

PwC Consulting IBM Global Service

IBM Business Consulting Services

Business Innovation Services

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How We’ll Operate

Strategic Strategic ChangeChange

CRMCRM

Supply Chain Supply Chain and Operationsand Operations

Financial Financial ManagementManagement

Human CapitalHuman Capital

e-BIe-BI

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Sectors/IndustriesSectors/Industries

BCS Israel BI/DW Group

• BI/DW group of ~40 people• Offerings:

– Full implementation (…, BI Programs & BI outsourcing)

– Phase Zero (Analysis and High Level Design)

– Roadmap / Vision (Business, Applications & Technical)

– Business Applications – “Unlocking the Value”

– Improvement Package– Ongoing Development and Support

BCS Israel BI/DW Group (Cont.)

• Skills– Business Analysts

– Information Analysts

– Technical Architects

– Data Modelers

– ETL architects and programmers

– Front-End programmers

– DBA’s

– Program and Project managers

BCS Israel BI/DW Group (Cont.)

The Israeli BI/DW gained world wide recognition

• IM versus DW versus BI versus KM

Unstructured data:-Documents- Intranet pages- Library- Notes / Email

Structured Data:- Internal DB- Files- External Information

IM / DW / BI / KM

KMBI / DW

Information Management

• BI Methodology

Our Information Management Methodology

Project Initiation

Project Initiation

Analysis Design Construction Implementation

Technology and Tools Definition


InformationAnalysis

InformationAnalysis

Businessand Process

Analysis

Businessand Process

Analysis

ETL DesignETL Design

TechnologyArchitecture Design


Process Change IntegrationProcess Change Integration

Front-End Application

Design


Design

Data DesignData Design

TrainingTraining

DocumentationDocumentation

Database Construction


Front-End SystemConstruction


Systemand

IntegrationTesting

Systemand

IntegrationTesting

RolloutRollout

ETLConstruction

ETLConstruction

Post Implementation

Review

Post Implementation

Review

Project Management & Quality Assurance

Analysis and Design Phase

Project Management and Quality AssuranceProject Management and Quality Assurance

Bus. & Systems Analysis

Planning and DefinitionBusiness Use and Vision

Inventory & Systems

Assessment

Inventory & Systems

Assessment

Information &

Organisation Analysis

Information &

Organisation Analysis

Business AnalysisBusiness Analysis

Determine Key

Performance Measures

Determine Key


Identify Business

Opportunities

Identify Business

Opportunities

Systems Vision for Business

Needs


Needs

Finalize Priority &

Vision

High-Level Data Model High-Level Data Model

High-Level Application

Functionality

High-Level Application

Functionality

High-Level Extract and

Mapping

High-Level Extract and

Mapping

Architecture &

Management Strategy

Architecture &

Management Strategy

Action Plans, Budget, and Architecture

& Information Based

Application Suite

Action Plans, Budget, and Architecture

& Information Based

Application Suite

Business TrackBusiness Track

Info. TrackInfo. Track

Technology TrackTechnology Track

The Business Track


Business and Systems Analysis

Planning and Definition

Business Use and Vision

Perform Business Analysis

Perform Business Analysis

Identify Business

Opportunities

Identify Business

Opportunities

Finalize Business Priority

and Vision

Determine High-Level Functionalit

y

Determine High-Level Functionalit

y

Submit Plan,

Budget, and Architecture

Submit Plan,


Key business objectives / problems / opportunities

Information usage and objectives linkage

Business requirements Best practices

comparison Value chain analysis

High-level business case for application suite

Application definition tied to business requirements

High-level front-end and analytical functionality

Process impact analysis

Initial source-to-target mapping of existing reports to planned data warehouse toolset

Sample analysis of major reports using desired report template

The Information Track






and Vision

Submit Plan,


Submit Plan,


Conduct Information

Analysis

Conduct Information

Analysis

Determine Key


(KPM)

Determine Key


(KPM)

Build High-Level Data

Model

Build High-Level Data

Model

Build High-Level

Extract and Mapping

Build High-Level

Extract and Mapping

Source systems definition and mapping

High-level data entity description

Data access and technology requirements matrix

Source system data to target information map

Source-to-target gap analysis

List of existing key performance measures

Listing of suggested performance measures by subject / application area

Tie between performance measures and business objectives / problems / opportunities

Metadata management strategy

High-level target data model with key facts, dimensions, and attributes.

Source-to-target mapping between existing fields and high-level data model

Business rules listing High-level extract,

transform and load (E.T.L) algorithm

The Technology Track






and Vision

Submit Plan,


Submit Plan,


Inventory & Systems

Assessment

Inventory & Systems

Assessment


Needs


Needs

Architecture &

Management Strategy

Architecture &

Management Strategy

Technical documentation of current environment / initiatives

Identification of potential problems and opportunities vis-a-vis DW program

Technical architecture drawing with listing of all required components

Tool requirements matrix (Platforms, Front-End, E.T.L engine, DataBase Etc.)

Finalized technical architecture overview

Capacity and sizing estimates

Hardware & communications requirements

Confirmed toolset: Platform(s); Front End; Engines; E/T

Training, integration and support requirements

The Project Management Track






and Vision

Submit Plan,


Submit Plan,


ProjectInitiationProject

Initiation

Kick off documentation

Confirmed project objectives

Team members listing

Framework for workshop and meeting schedule

Project plan & timetables

Finalized project charter

Priority / value analysis of deployment options

Plan for information-based application(s)

Executive Summary Final overall architecture:

business; information; technical

Integrated action plan: Budget; Timetable

Project implementation structure: roles & responsibilities; team organization; management structure

Our Information Management Methodology

Project Initiation

Project Initiation

Analysis Design Construction Implementation



InformationAnalysis

InformationAnalysis

Businessand Process

Analysis

Businessand Process

Analysis

ETL DesignETL Design



Process Change IntegrationProcess Change Integration


Design


Design

Data DesignData Design

TrainingTraining

DocumentationDocumentation





Systemand

IntegrationTesting

Systemand

IntegrationTesting

RolloutRollout

ETLConstruction

ETLConstruction

Post Implementation

Review

Post Implementation

Review

Project Management & Quality Assurance

Purpose/Benefits Validate and articulate the business needs on two fronts: (1)

Problems facing the business, and (2) Opportunities for the business

Align the information-based sales and marketing initiative with the overall organization strategy and plan

Key Activities Understand business strategy Interviews/workshops with all levels of decision support users:

senior management; middle management; front-line users.

Build value chain of target business processes to be impacted by system

Determine key impact points of information on business decisions

Codify business needs along functional lines for example: reporting capabilities, decision-support capabilities, analytical applications, simulations, on-line operational feedback loop

Deliverables M.O.S.T. model

describing strategy Linkage between

information usage and business problems/opportunities

IBM “best practices” comparison in problem/opportunity areas

Client’s target area value chain analysis

Detailed WorkplanDetailed Workplan

Conduct Business Analysis

Epoch PartnersInvestment Bank

Value Chain - Main Activities

EquityOffering

ManagementResearch

Issuer Relationship Management

Marketing - New Business

• Analyze Online Partners investors

• Present Epoch capabilities

• Demonstrate attractiveness of retail market

• Identify and analyze merger & acquisition opportunities

• Bring equity offering information to potential retail investors

• Provide issuers effective demand curve data

• Help issuers set appropriate price

• Help Online Partners allocate shares

• Manage directed shares program

• Track post transaction share activity

• Conduct fundamental research on all clients

• Conduct fundamental research on selected industries and covered stocks (comparables)

• Publish research on Web

• Nurture existing relationships

• Identification of business opportunities

• References

InitialPublic

Offering

Secondary

Offering

Mergers&

Acquisitions

Value Chain - Critical Success Factors

• Knowledge of Online Partners’ investors

• Increased availability of offerings for retail investors

• Credible profile of potential buyers

• Presentation of equity offering information to retail investors

• Management of conditional offers to purchase across large retail investor base

• Creation and analysis of demand curve

• Credible pricing recommendations

• Credible recommendations for allocation to potential buyers

• Management of directed shares program

• Timely tracking of post transaction share activity

• Recognized for best available knowledge of clients

• In-depth knowledge of industry and selected industry comparables

• Insightful research analysis and reports delivered via Web

• Ability to track research impact on retail investor base

• Client awareness of stability of retail base

• Client awareness of investor activity

• Advice that positions clients for long term success

• Willingness of existing clients to provide meaningful references

InitialPublic

Offering

SecondaryOffering

Mergers&

Acquisitions

EquityOffering

ManagementResearch



Value Chain - Key Information Req.

• Analysis of investors:- holdings - trading patterns- demographics- money flows

• Analysis of comparables issues:

- trends- cross holdings- past IPO demand

and allocations

• Creation and analysis of demand curve (prior to IPO):

- real time- historical analysis

• Analysis of allocated shares distribution (during IPO)

• Trading activity for first 30 days (after IPO) and afterwards as required

• Impact of research publication:

- hits on Web page- trading effect

• Analysis of clients:- investor base- trading patterns

• Analysis of comparables:

- investor base- trading patterns

• Research impact:- trading effect

- business events (triggers)

InitialPublic

Offering

SecondaryOffering

Mergers&

Acquisitions

EquityOffering

ManagementResearch



Support for Detailed Information Req.

• Analyze Online Partners investors

Activity• The Data Warehouse will provide query and

analysis tools that allow the Investment Bankers to demonstrate an in-depth knowledge of the demographic characteristics of the retail client base of the Online Partners (“investors”). The information will be both general (e.g., number of investors, median age, median income level, median account size of all clients who invest more than 10% of their accounts in technology stocks) and detailed (e.g., same information for those investors who own or have owned, within the last six months, comparables a, b, and/or c).

• The Data Warehouse will provide tools that allow the Investment Banker to demonstrate in-depth knowledge of the holdings and trading patterns of investors in the client’s industry and in comparable stocks (e.g., the box positions of comparables a, b, and/or c as of month-end for the last 12 months, the aggregate current box position, the net purchases and sales for each month, the trading for each of the 5 days immediately following their latest earnings announcement, etc.).

• Provide information about gross money flows into and out of investor accounts

• Categorize investor information by IPO eligibility as determined by each Online Partner

• All of the information provided will be correlated with designated business events1

Data Warehouse Support• Investor demographics (monthly)

- geographic location- gender- income level- education level- age- investment sophistication- account type (cash, margin, retirement)- account tenure (how long opened)- IPO eligibility- channel preference (web, telephone, other)

• Account Summary (daily)- account size (total assets)- portfolio composition (cash, long / short position in

equities, mutual funds, bonds, options, selected industries w/i equities [e.g., technology])

• Holdings (daily)- ticker- shares owned (both long and short positions)- holding period (how long owned)- cost basis- how acquired (IPO, aftermarket)

• Trading pattern (daily)- frequency of trades (relative to business events)- shares acquired in IPO- shares acquired in aftermarket

• Money flows (weekly)- cash deposits / withdrawals- available cash and cash equivalents- available buying power

• Issues (as defined in “Demonstrate attractiveness of retail market” activity)

Information Requirement


EquityOffering

ManagementResearch


1 See “Epoch Value Chain - Business Events” (p. 7)

Support for Detailed Information Req.

• Help issuers set appropriate price

Activity• The final demand curve data (information

about the volume of interest in an IPO at various price levels) will be provided by the Epoch Demand Repository, which is outside the scope of the Data Warehouse project

• The Data Warehouse will provide query and analysis tools to correlate the final demand curve data with investor demographic characteristics and historical trading patterns. By analyzing key information (e.g., account size, cash availability for additional investments, trading

patterns in comparables, etc.), Epoch can present the issuer with probable behavior patterns for the investors at different price points on the demand curve

Data Warehouse Support• Investor demographics (as defined in

“Analyze Online Partners investors” activity)

• Account Summary (as defined in “Analyze Online Partners investors” activity)

• Holdings (as defined in “Analyze Online Partners investors” activity)

• Trading pattern (as defined in “Analyze Online Partners investors” activity)

• Final demand curve data- ticker- date- demand curve detail

price rangetotal offers to purchase / indications of

interest


EquityOffering

Management


ResearchIssuer

Relationship Management

Support for Detailed Information Req

• Nurture existing relationships

Activity• The Data Warehouse will provide query

and analysis tools that allow the Investment Bankers to continue to demonstrate an in-depth knowledge of the demographic characteristics and holdings and trading patterns of investors who own the client’s stock (e.g., median age, median income level, average account size, investment maturity, holdings of the client as of month-end for the last 12 months, aggregate current position, net purchases and sales for each month, trading activity for each of the 5 days immediately following significant business events, etc.).

Data Warehouse Support• Investor demographics (as defined in

“Analyze Online Partners investors” activity)

• Account Summary (as defined in “Analyze Online Partners investors” activity)

• Holdings (as defined in “Analyze Online Partners investors” activity)

• Trading pattern (as defined in “Analyze Online Partners investors” activity)

• Money flows (as defined in “Analyze Online Partners investors” activity)

• Issues (as defined in “Demonstrate attractiveness of retail market” activity)




EquityOffering

ManagementResearch

July 2001: Goldman Sachs buys Epoch Partners forapproximately $250M.

Goldman Sachs CEO’s news release:

“I am Pleased to acquire……..for 2 reasons. First it provides access to the valuable retail investment customer base andmost important Epoch’s customer and marketinginformation analytics capabilities are the most valuable

asset we could find in today’s market”.

MTNCellular Company

Data Modeling