235958021 bi-apps-financial-analytics-on-jde

© Peak Indicators Limited

BI Apps - Financial Analytics on – JD Edwards

Overview, Implementation and Next Steps

Tony Cassidy & Shaun Mullen

June 2012

© Peak Indicators Limited 2

Agenda

Introduction

BI Apps - Overview

BI Apps – Financial Analytics

BI Apps – Financial Analytics – JD Edwards Specifics

BISC Implementation

Customisation

Security

ETL Statistics

Training

Key Success Factors - General

Key Success Factors - BISC

Next Steps


Introduction


Customer: In Ireland

Business Needs: Ability to report on Non Pay and Open Commitments

Ability to report More Frequently than before

Open to Overall Improvements on Operational Financial Reporting

Deploy in relatively short time frame

Budget

Solution Considerations: OBIEE Existing

JD Edwards Existing

Immediate Operational Financial Reporting Requirement (Non Pay)

TCO on BI Apps - Financial Analytics V OBIEE Custom Product Layers = Schemas, ETL, Adapters & Dashboards

ROI on BI Apps – Financial Analytics – Wider Usage

Decision: BI Apps – Financial Analytics on JD Edwards

Introduction Business Need & Solution Consideration


Introduction Decision = BI Continuum for JD Edwards

Oracle

EPM

Futu

re O

riente

d

Strategic Dynamic

Static Operational Past

Ori

ente

d

JDE E1

JDE E1 Standardized Reporting

• JDE E1 UBE, QBE (Query By Example)

• Oracle BI Publisher

1 1

JDE E1 Operational Consoles

• Financial Mgmt & Compliance Console

• Plant Manager Dashboard

2 2

Oracle Predictive Modeling Tools

• Hyperion Essbase

• Real Time Decisions

5

5 Oracle EPM • Hyperion Planning and Budgeting

• Hyperion Financial Management

• more

4

4 Oracle BI Applications • Financial Analytics

• Supply Chain & Order Mgmt Analytics

• Procurement & Spend Analytics

• more

3

3


BI Apps - Overview


BI Apps - Overview

Oracle BI Applications (BI Apps) is a complete data-warehouse solution based on the Oracle BI Enterprise Edition product suite

BI Apps enables organisations to rapidly deploy an end-to-end analytics solution providing a comprehensive and rich set of Business Intelligence dashboards

BI Apps comes with pre-built meta-data to source from various source transactional applications including: Oracle eBusiness Suite Siebel CRM Peoplesoft JD Edwards

BI Apps is designed so that it can be tailored to suit an organisation’s own

individual reporting needs


BI Apps - Overview

Faster Delivery, Lower TCO

Build from Scratch with Traditional BI Tools

Oracle Analytic Applications

Prebuilt Business Adapters for Oracle, PeopleSoft, Siebel, SAP, others

Prebuilt DW design, adapts to your EDW

Role-based dashboards and thousands of pre-defined metrics

Easy to use, easy to adapt

Weeks or Months

Back-end ETL and Mapping

DW Design

Define Metrics & Dashboards

Back-end ETL and Mapping

DW Design

Define Metrics & Dashboards

Training / Roll-out

Training / Rollout

Months or Years

Oracle Analytic Applications solutions approach:

• Faster time to value • Lower TCO • Assured business value

Source: Patricia Seybold Research, Gartner, Merrill Lynch, Oracle Analysis


Oracle Business Intelligence Enterprise Edition Plus (OBIEE)

Oracle Business Intelligence Applications (BI Apps) –Prebuilt Metadata

BI Apps - Overview OBIEE V BI Apps – Why?


Extension of DW Schema for extension columns, additional tables, external sources, aggregates, indices, etc.

Extension of ETL for extension columns, descriptive flex fields, additional tables, external sources, etc.

Additional derived metrics, custom drill paths, exposing extensions in physical, logical and presentation layer, etc.

Additional dashboards and reports, guided and conditional navigations, iBot’s, etc.

Level of Effort

Degree of Customization

Easy

Moderate

Intermediate

Involved

Dashboards & Reports

OBIEE Metadata

DW Schema

ETL

BI Apps - Overview Effort & Customization Balance


Ad

min

istr

atio

n

Met

adat

a

Oracle BI Presentation

Services

Dashboards by Role

Reports, Analysis / Analytic Workflows

Metrics / KPIs

Logical Model / Subject Areas

Physical Map

Oracle BI Server

Direct Access to Source Data

Data Warehouse / Data Model

ETL

Load Process

Staging Area

Extraction Process

DA

C

Federated Data Sources

Siebel Oracle PSFT EDW Other

Role Based Dashboards

Analytic Workflow

Guided Navigation

Security / Visibility

Alerts & Proactive Delivery

Logical to Physical Abstraction Layer

Calculations and Metrics Definition

Visibility & Personalization

Dynamic SQL Generation

Highly Parallel

Multistage and Customizable

Deployment Modularity

Abstracted Data Model

Conformed Dimensions

Heterogeneous Database support

Database specific indexing

BI Apps - Overview Architecture


BI Apps - Financial Analytics


Travel & Trans

Auto Comms & Media

Complex Mfg

Consumer Sector

Energy Financial Services

High Tech

Insurance & Health

Life Sciences

Public Sector

Oracle BI Suite Enterprise Edition

Prebuilt adapters:

Sales Service & Contact Center

Marketing Order Management & Fulfillment

Supply Chain Financials Human Resources

Pipeline Analysis

Triangulated Forecasting

Sales Team Effectiveness

Up-sell / Cross-sell

Cycle Time Analysis

Lead Conversion

Absence Management

Compensation Analysis

HR Performance

Workforce Profile

Learning Management

Recruitment Management

A/R & A/P Analysis

GL / Balance Sheet Analysis Customer & Product Profitability

P&L Analysis

Expense Management

Cash Flow Analysis

Supplier Performance

Spend Analysis

Procurement Cycle Times

Inventory Availability

Employee Expenses

BOM Analysis

Order Linearity

Orders vs. Available Inventory

Cycle Time Analysis

Backlog Analysis

Fulfillment Status

Customer Receivables

Campaign Scorecard

Response Rates

Product Propensity

Loyalty and Attrition

Market Basket Analysis

Campaign ROI

Churn Propensity

Customer Satisfaction

Resolution Rates

Service Rep Effectiveness

Service Cost Analysis

Service Trends

BI Apps – Financial Analytics Financial Subject Areas

http://www.siebel.com/

http://www.sap.com/index.asp

http://www.peoplesoft.com/corp/en/public_index.jsp


Payables Analytics Provides visibility into payments due to suppliers and expense line detail so managers can manage cash outflows and control expenses. When combined with Supply Chain Analytics, it allows full procurement analysis from Requisition to Check.

Receivables Analytics Monitors collections processes to show what customers buy and how they pay, enabling managers to identify overdue balances and other receivables bottlenecks. When combined with Oracle Sales Analytics and Oracle Order Management & Fulfillment Analytics, it enables more efficient management of the entire Lead to Cash process.

General Ledger & Profitability Analytics Incorporates detail-level general ledger transactions and cash flow analysis across locations, customers, products, sales territories, distribution channels, and business units. Identifies the customers and transactions that are providing maximum profits by product, location, department, and geographic detail. When combined with Marketing Analytics, it enables analysis of Campaign ROI and assists in customer segmentation.

BI Apps – Financial Analytics Comprehensive View of Financial Performance


Pre-mapped metadata, including embedded best

practice calculations and metrics for Financial,

Executives and other Business Users.

Presentation Layer

Logical Business

Model

Physical Sources

3

Pre-built ETL to extract data from over 3,000

operational tables and load it into the DW,

sourced from JDE, PSFT, and other sources.

2 A “best practice” library of over 360 pre-built

metrics, Intelligent Dashboards, 200+ Reports and

alerts for CFO, Finance Controller, Financial

Analyst, AR/AP Managers and

Executive

4

Pre-built warehouse with more than 15 star-

schemas designed for analysis and reporting on

Financial Analytics

1

BI Apps – Financial Analytics Product Layers


BI Apps – Financial Analytics – JD Edwards Specifics


JDE Approach

Created new Data Source Num IDs

ETL (Informatica)

Map from JDE E1 tables to the existing staging tables (SDE)

Configuration (.csv) files, domain values

DAC parms (new and existing), DAC execution plan

No OBIA data model changes except:

Added 20 additional attributes to 4 dimensions to support JDE E1 Category Codes

Data Source Name Data Source Number

JDE_8.11 SP1 15

JDE_8.12 15

JDE_9.0 25


Financial Analytics – Dimensions

Dimension Primary JDE E1 Source Table

W_MCAL_PERIOD_D F0008 – Fiscal Date Patterns

W_MCAL_CAL_D F0008 – Fiscal Date Patterns

W_MCAL_CONTEXT_G F0010 – Company Master

W_INT_ORG_D F0010 – Company Master

F0006 – Business Unit Master

W_LEDGER_D F0010 – Company Master

W_PROFIT_CENTER_D F0010 – Company Master

W_COST_CENTER_D F0006 – Business Unit Master

W_INT_ORG_DH F0050 – Organizational Structure Master

W_GL_ACCOUNT_D F0901 – Account Master

W_HIERARCHY_D F0901 – Account Master

W_GL_SEGMENT_D F0901 – Account Master




W_PARTY_ORG_D

F0101 – Address Book Master

F03012 – Customer Master by Line of Business

F0401 – Supplier Master

W_CUSTOMER_LOC_D F0101 – Address Book Master

W_USER_D F0101 – Address Book Master

W_CUSTOMER_FIN_PROFL_D F03012 – Customer Master by Line of Business

W_CUSTOMER_ACCOUNT_D F03012 – Customer Master by Line of Business

W_SUPPLIER_ACCOUNT_D F0401 – Supplier Master

W_PRODUCT_D F4101 – Item Master

W_EMPLOYEE_D F060116 – Employee Master




W_AP_TERMS_D F0014 – Payment Terms

W_PAYMENT_TERMS_D F0014 – Payment Terms

W_CODE_D F0005 – User Defined Code Values

W_STATUS_D F0005 – User Defined Code Values

W_XACT_TYPE_D F0005 – User Defined Code Values

W_PAYMENT_METHOD_D F0005 – User Defined Code Values

W_EXCH_RATE_GS F0015 – Currency Exchange Rates

W_JDEE1_DECIMALSHIFT_G F9210 – Data Dictionary


Financial Analytics – Facts


W_AP_XACT_F

F0411 – Accounts Payable Ledger

F0413 – Accounts Payable Matching Document Header

F0414 – Accounts Payable Matching Document Detail

W_AR_XACT_F

F03B11 – Customer Ledger

F03B13 – Receipts Header

F03B14 – Receipts Detail

W_GL_REVN_F F0911 – Account Ledger

W_GL_COGS_F F0911 – Account Ledger

W_GL_OTHER_F F0911 – Account Ledger

W_GL_BALANCE_F F0902 – Account Balances

W_ACCT_BUDGET_F F0902 – Account Balances


Other JDE E1 Adapter Notes

Rely on Universal Adapter for:

W_BUDGET_D

W_CUSTOMER_COST_LINE_F

W_PRODUCT_COST_LINE_F

JDE E1 Adapter does not support the following:

W_BANK_D

W_TAX_TYPE_D

W_PARTY_PER_D

W_TAX_XACT_F


Data Model

AP

AR

GL

Custom Tables


Many JDE E1 Modules Feed Accounts Payable


JDE E1 Accounts Payable - Process Flow


Financial Analytics Data Model

Base Fact “Primary” JDE E1 Source Tables

W_AP_XACT_F

F0411 – Accounts Payable Ledger

F0413 – Accounts Payable Matching Document Header

F0414 – Accounts Payable Matching Document Detail

Only mapping transactions that have been posted


Many JDE E1 Modules Feed Accounts Receivable

Contact and Service Billing

Accounts Receivable

General Accounting

Address Book

Sales Order Management

Service & Warranty Management

Real Estate Management


JDE E1 Accounts Receivable - Process Flow




W_AR_XACT_F

F03B11 – Customer Ledger

F03B13 – Receipts Header

F03B14 – Receipts Detail





W_GL_REVN_F F0911 – Account Ledger

W_GL_COGS_F F0911 – Account Ledger

W_GL_OTHER_F F0911 – Account Ledger

W_GL_BALANCE_F F0902 – Account Balances


Only mapping “actual” ledger types

The Financial Statement Item Code associated with the Account on the GL transaction (F0911) determines if a GL Transaction is mapped to W_GL_REVN_F, W_GL_COGS_F, or W_GL_OTHER_F

Other JDE E1 Adapter Notes:

Don’t support Reconciliation process that exists with EBS Adapter

Don’t support drill back from GL to AP or AR




W_ACCT_BUDGET_F F0902 – Account Balances


Only mapping “budget” ledger type


Category Codes

20 new attribute columns were added to the following dimension tables and their associated _DS tables:

W_INT_ORG_D – Attribute columns were added to support Business Unit (F0006) category codes.

W_CUSTOMER_ACCOUNT_D – Attribute columns were added to support Customer Master by Line of Business (F03012) category codes.

W_PARTY_ORG_D – Attribute columns were added to support Address Book Master (F0101) and Customer Master by Line of Business (F03012) category codes.

W_PRODUCT_D – Attribute columns were added to support Item Master (F4101) category codes.


Additional Tables for Category Codes

Table Column W_INT_ORG_DS STATE_REGION

W_INT_ORG_DS COUNTRY_REGION

W_INT_ORG_DS CONFIG_CAT_CODE

W_PRODUCT_DS INDUSTRY_CODE

W_PRODUCT_DS BRAND

W_PRODUCT_DS COLOR

W_PRODUCT_DS UNIV_PROD_CODE

W_CUSTOMER_ACCOUNT_DS ACCOUNT_TYPE_CODE

W_CUSTOMER_ACCOUNT_DS ACCOUNT_CLASS_CODE

W_PARTY_ORG_DS LINE_OF_BUSINESS

W_PARTY_ORG_DS REGION

W_PARTY_ORG_DS ACCNT_AHA_NUM

W_PARTY_ORG_DS ACCNT_CLASS

W_PARTY_ORG_DS ACCNT_HIN_NUM

W_PARTY_ORG_DS ACCNT_REGION

W_PARTY_ORG_DS ACCNT_VALUE

W_PARTY_ORG_DS CUST_CAT_CODE


User Defined Codes

The file_udc_category_mapping_jde.csv file loads JDE E1 user defined codes (UDCs) into the Code (W_CODE_D) dimension. Use the flat file to specify a particular set of UDCs that you want to load.

There are three columns in the CSV file. The first two columns are used to identify the system codes and user defined codes. Together, these columns are used to identify the UDCs that will be loaded into W_CODE_D. The third column is the category into which you want to load the codes in W_CODE_D.

Categories in W_CODE_D are used to group together codes intended for a similar purpose. For example, UDC 00||CN stores the country code and description. To store this under the COUNTRY category in W_CODE_D, enter the following row in the CSV file: 00 CN COUNTRY


User Defined Codes

In the CSV file, you specify the system code and user defined code and associate it with the category to which you want the UDCs loaded. This data is loaded into UDC_CATEGORY_MAP_TMP table, which leverages the data and loads the relevant codes into the Code dimension.

Example…..

System Code User Defined Code Category

00 PY SUPPLIER_PAYMENT_METHOD

00 CN COUNTRY

01 GD GENDER

01 LP LANGUAGE


Group Account Numbers

Group Account numbers are configured in the same way as EBS through the file file_group_account_codes_jde.csv The file has an additional column of company required for JDE.

COMPANY FROM ACCT TO ACCT GROUP_ACCT_NUM

00000 4100 4190 AP

00000 1200 1299 AR

00000 2120 2195 ACC DEPCN

00000 4200 4211 ACC LIAB

00000 1100 1121 CASH

00000 4900 4910 CMMN STOCK


GL Hierarchy

The JDE E1 account dimension mapping generates hierarchies for each AID (Account ID) based on the LDA (Level of Detail). This is a relative hierarchy dependant on the order of incoming records.

Check the results with JDE functional consultant & Config guide to confirm. The ETL generates a hierarchy as below:


Rate Type

The concept of Rate Type in JDE is different than how it is defined in the Warehouse. In JDE, the rate type is an optional key; it is not used during exchange rate calculations.

DAC uses the $$JDE_RATE_TYPE source system parameter to populate the Rate_Type field in the W_EXCH_RATE_GS table. By default, the $$JDE_RATE_TYPE source system parameter in DAC has a value of "Actual."

The query and lookup on W_EXCH_RATE_G will fail if the RATE_TYPE field in the W_EXCH_RATE_G table does not contain the same value as the GLOBAL1_RATE_TYPE, GLOBAL2_RATE_TYPE 2 and GLOBAL3_RATE_TYPE fields in the W_GLOBAL_CURR_G table.


Integrated Security

Elements of

Security

JDE E1 OBIEE/OBIA Integrated Security

Option

User Security - Validate username/pw - Validate username/pw - Maintain JDE E1 credentials

in LDAP so OBIEE can

leverage it

Object

Security

- Based on User ID and Role

Note: Roles are not based on

“job function” or

“responsibility”

- Based on Security Groups

- Security Groups based on

user’s job function. User’s

job function can be derived

from the roles/resp. in the

OLTP system if the OLTP

roles/resp. are “job-function”

based.

- LDAP schema supported by

JDE E1 could contain Security

Group, so both JDE E1 and

OBIEE object security can be

set up in LDAP

Data Security - Based on User ID and

Role, defined at the

table/row/column level

Note: User ID (Profile) is not

associated with an

“organization”

- Based on Organization/Job

function , applies to all

tables

- Can be derived from the

OLTP system if the OLTP’s

user profile contains the

user’s “organization”

Dual Maintenance Required

- JDE E1 User ID (Profile) is

not associated with an

“organization” yet an

“organization” is required for

Integrated data security


BISC Implementation


BISC Implementation

Week 15

Weeks 5-12

Weeks 2-4

Weeks 13-14

Week 1

Install & Populate BI Application

Unit Testing

System Testing

Development

Review Contents

Prioritise Requirements

User Training

UAT Migration

UAT

Deploy to PROD

Post-Live Support (BISC)

Project Plan

Workshops

Questionnaire

Expert Services

(BISC)


BISC Implementation

BISC Project Team

Business Business Sponsor

Business Analysts

Users

BISC Team

0.5 - BISC Project Manager

0.5 - BI Architect

1 - BI Specialist

1 - BISC Consultant


BISC Implementation

Installation

Financial Analytics 7.9.6.3 configured for the following build: Microsoft Windows Server 2003 Standard Edition OBIEE 10g OBIA 7.9.6.2 DAC 10.1.3.4.1 Informatica 8.6.1

3.5 days for complete installation and a full ETL run.

Produced an install guide running over 70 pages for installation and

configuration of all software components.

Peak installed on DEV and then the Internal BISC team were able to follow the install guide and install both UAT and PROD with minimum fuss.


BISC Implementation

Requirements Capture

Every customer is different when it comes to their requirements – leading into an entirely different extension to BI Apps.

A series of demos and workshops and questionnaire driven requirements capture.

Requirements specification document created and signed-off


BISC Implementation

Configuration

Financial Ledgers – Actual & Commitment ledgers

Mapping Account Segment codes to columns in F0901 account master table

Accounting Aggregates – which account segments to produce aggregates for

Date patterns to support fiscal quarters


BISC Implementation

Configuration

Set DAC parameters determining volume of historical data in Data Warehouse: Initial Extract Date - date from which to extract data Analysis Start- date from which to extract data Analysis End - date to which data should be extracted

Other DAC parameters

Currencies • $$GLOBAL1_CURR_CODE

Rate Types • $$GLOBAL1_RATE_TYPE

Calendar • $$GBL_CALENDAR_ID • $$GBL_DATASOURCE_NUM_ID


Customisation


Customisation

Requirements

Extensions

to Out-of-Box with additional 120+ fields related to...

Non-Pay Subject Area

Ability to report on Non-Pay data in OBI since last three years.

Ability to report on Non-Pay data for different time periods – weekly, monthly, annually.

Ability to replicate current reporting on JDE.

Ability to report more accurately on Non-Pay Transactions.

Ability to report more accurately on changes between any two dates.

Ability to report on Transactions between any two dates.

Ad-hoc reporting of Orders and Suppliers with specific filters.


Security


Security

Application Roles

ETL Informatica

JD Edwards Data Warehouse

Staging Star Schemas

Oracle Business Intelligence • BI Presentation Services • BI Server • BI Scheduler

Oracle BI “Application Roles”

Core finance team have high visibility

Cost Centre managers have restricted visibility based on

application role


ETL Statistics

Full Load • 10 Hours (DEV) • 6 Hours (UAT & PROD)

Incremental • 5.5 Hours (DEV) • 3.5 Hours (UAT & PROD)


Training

Client specific Training Manual Delivered training on Reports and Dashboard A further BI Apps Bootcamp training is planned Parallel Support period ensures additional detailed Knowledge Transfer


Key Success Factors - General

Proven BI Apps implementation experience Peak Indicators has a combined total of over 20 years in-depth experience

implementing various modules of BI Apps Utilising Peak’s “Quick-Start” approach

Extended OOTB subject areas utilising 90% of OOTB contents rather than

building new subject areas from scratch. Controlled Project scope within the “Quick Start” approach System and UAT testing Strong BI Project Management Executive level sponsorship


Key Success Factors - BISC

Use of the Peak Indicators BISC Approach.

What is BISC? BISC is the “New Improved Generation” of BICC or BICoE! Forrester and the BISC:

“Forrester firmly believes that tried and true best practices for enterprise software development and support just don’t work for business intelligence (BI). Earlier-generation BI support centers — organized along the same lines as support centers for all other enterprise software — fall short when it comes to taking BI’s peculiarities into account. These unique BI requirements include less reliance on the traditional software development life cycle (SDLC) and project planning and more emphasis on reacting to the constant change of business requirements. Forrester recommends structuring your BISC along somewhat different lines than traditional technical support organizations. “ ... “A permanent, cross-functional, virtual or physical organizational structure, loosely coupled for flexibility and agility, responsible for the governance and processes necessary to deliver or facilitate the delivery of successful BI solutions, as well as being an institutional steward of, protector of, and forum for BI best practices.” REF: http://blogs.forrester.com/category/bisc

Parallel Support and Knowledge Integration to internal BISC Detailed Requirements Definition completed by internal BISC Conformity to Internal Governance and development standards by internal BISC

http://blogs.forrester.com/category/bisc

http://blogs.forrester.com/category/bisc


Next Steps

Current implementation – Non-Pay Transactions (20 Named Users)

On Site Support in Internal BISC Remote Advanced Support in BISC

Future Phases – Wider Rollout (20+ Users) Roll out additional dashboards and reports (20+ Named Users)

Training – BI Apps Bootcamp - http://www.peakindicators.com/index.php/obiee-training

http://www.peakindicators.com/index.php/obiee-training




Questions?


Helping Your Business Intelligence Journey