BI Apps - Financial Analytics on JD Edwards

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1 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 Peak Indicators Limited 2

3 Introduction Peak Indicators Limited 3

4 Introduction Business Need & Solution Consideration 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 Peak Indicators Limited 4

5 Past Oriented Introduction Decision = BI Continuum for JD Edwards Oracle Predictive Modeling Tools Hyperion Essbase Real Time Decisions Oracle EPM Hyperion Planning and Budgeting Hyperion Financial Management more Oracle BI Applications Financial Analytics Supply Chain & Order Mgmt Analytics Procurement & Spend Analytics more JDE E1 Operational Consoles Financial Mgmt & Compliance Console Plant Manager Dashboard JDE E1 Standardized Reporting JDE E1 UBE, QBE (Query By Example) Oracle BI Publisher Strategic Operational 1 JDE E1 2 3 Oracle EPM 4 Dynamic Static 5 Future Oriented Peak Indicators Limited 5

6 BI Apps - Overview Peak Indicators Limited 6

7 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 Peak Indicators Limited 7

8 BI Apps - Overview Faster Delivery, Lower TCO Build from Scratch with Traditional BI Tools Oracle Analytic Applications Training / Roll-out Define Metrics & Dashboards DW Design Oracle Analytic Applications solutions approach: Faster time to value Lower TCO Assured business value Back-end ETL and Mapping Months or Years Training / Rollout Define Metrics & Dashboards DW Design Back-end ETL and Mapping Weeks or Months Easy to use, easy to adapt Role-based dashboards and thousands of pre-defined metrics Prebuilt DW design, adapts to your EDW Prebuilt Business Adapters for Oracle, PeopleSoft, Siebel, SAP, others Source: Patricia Seybold Research, Gartner, Merrill Lynch, Oracle Analysis Peak Indicators Limited 8

9 BI Apps - Overview OBIEE V BI Apps Why? Oracle Business Intelligence Enterprise Edition Plus (OBIEE) Oracle Business Intelligence Applications (BI Apps) Prebuilt Metadata Peak Indicators Limited 9

10 BI Apps - Overview Effort & Customization Balance Dashboards & Reports Easy Additional dashboards and reports, guided and conditional navigations, ibot s, etc. OBIEE Metadata Moderate Additional derived metrics, custom drill paths, exposing extensions in physical, logical and presentation layer, etc. DW Schema ETL Degree of Customization Intermediate Involved Level of Effort 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. Peak Indicators Limited 10

11 Administration BI Apps - Overview Architecture DAC Metadata Dashboards by Role Reports, Analysis / Analytic Workflows Oracle BI Presentation Services Role Based Dashboards Analytic Workflow Guided Navigation Security / Visibility Alerts & Proactive Delivery Metrics / KPIs Logical Model / Subject Areas Direct Access to Source Data Physical Map Data Warehouse / Data Model Load Process Staging Area Extraction Process Oracle BI Server ETL Logical to Physical Abstraction Layer Calculations and Metrics Definition Visibility & Personalization Dynamic SQL Generation Abstracted Data Model Conformed Dimensions Heterogeneous Database support Database specific indexing Highly Parallel Multistage and Customizable Deployment Modularity Oracle Siebel PSFT EDW Other Federated Data Sources Peak Indicators Limited 11

12 BI Apps - Financial Analytics Peak Indicators Limited 12

13 BI Apps Financial Analytics Financial Subject Areas Auto Comms & Media Complex Mfg Consumer Sector Energy Financial Services High Tech Insurance & Health Life Sciences Public Sector Travel & Trans Sales Pipeline Analysis Service & Contact Center Churn Propensity Marketing Campaign Scorecard Order Management & Fulfillment Order Linearity Supply Chain Supplier Performance Financials A/R & A/P Analysis Human Resources Absence Management Triangulated Forecasting Sales Team Effectiveness Customer Satisfaction Resolution Rates Response Rates Product Propensity Orders vs. Available Inventory Cycle Time Analysis Spend Analysis Procurement Cycle Times GL / Balance Sheet Analysis Customer & Product Profitability Compensation Analysis HR Performance Up-sell / Cross-sell Service Rep Effectiveness Loyalty and Attrition Backlog Analysis Inventory Availability P&L Analysis Workforce Profile Cycle Time Analysis Service Cost Analysis Market Basket Analysis Fulfillment Status Employee Expenses Expense Management Learning Management Lead Conversion Service Trends Campaign ROI Customer Receivables BOM Analysis Cash Flow Analysis Recruitment Management Prebuilt adapters: Oracle BI Suite Enterprise Edition Peak Indicators Limited 13

14 BI Apps Financial Analytics Comprehensive View of Financial Performance 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. 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. Peak Indicators Limited 14

15 1 BI Apps Financial Analytics Product Layers Pre-built warehouse with more than 15 starschemas designed for analysis and reporting on Financial Analytics 3 Pre-mapped metadata, including embedded best practice calculations and metrics for Financial, Executives and other Business Users. Presentation Layer Logical Business Model Physical Sources 2 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. 4 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 Peak Indicators Limited 15

16 BI Apps Financial Analytics JD Edwards Specifics Peak Indicators Limited 16

17 JDE Approach Created new Data Source Num IDs Data Source Name Data Source Number JDE_8.11 SP1 15 JDE_ JDE_ 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 Peak Indicators Limited 17

18 Financial Analytics Dimensions Dimension W_MCAL_PERIOD_D W_MCAL_CAL_D W_MCAL_CONTEXT_G W_INT_ORG_D W_LEDGER_D W_PROFIT_CENTER_D W_COST_CENTER_D W_INT_ORG_DH W_GL_ACCOUNT_D W_HIERARCHY_D W_GL_SEGMENT_D Primary JDE E1 Source Table F0008 Fiscal Date Patterns F0008 Fiscal Date Patterns F0010 Company Master F0010 Company Master F0006 Business Unit Master F0010 Company Master F0010 Company Master F0006 Business Unit Master F0050 Organizational Structure Master F0901 Account Master F0901 Account Master F0901 Account Master Peak Indicators Limited 18

19 Financial Analytics Dimensions Dimension W_PARTY_ORG_D W_CUSTOMER_LOC_D W_USER_D W_CUSTOMER_FIN_PROFL_D W_CUSTOMER_ACCOUNT_D W_SUPPLIER_ACCOUNT_D W_PRODUCT_D W_EMPLOYEE_D Primary JDE E1 Source Table F0101 Address Book Master F03012 Customer Master by Line of Business F0401 Supplier Master F0101 Address Book Master F0101 Address Book Master F03012 Customer Master by Line of Business F03012 Customer Master by Line of Business F0401 Supplier Master F4101 Item Master F Employee Master Peak Indicators Limited 19

20 Financial Analytics Dimensions Dimension W_AP_TERMS_D W_PAYMENT_TERMS_D W_CODE_D W_STATUS_D W_XACT_TYPE_D W_PAYMENT_METHOD_D W_EXCH_RATE_GS W_JDEE1_DECIMALSHIFT_G Primary JDE E1 Source Table F0014 Payment Terms F0014 Payment Terms F0005 User Defined Code Values F0005 User Defined Code Values F0005 User Defined Code Values F0005 User Defined Code Values F0015 Currency Exchange Rates F9210 Data Dictionary Peak Indicators Limited 20

21 Financial Analytics Facts Dimension W_AP_XACT_F W_AR_XACT_F W_GL_REVN_F W_GL_COGS_F W_GL_OTHER_F W_GL_BALANCE_F W_ACCT_BUDGET_F Primary JDE E1 Source Table F0411 Accounts Payable Ledger F0413 Accounts Payable Matching Document Header F0414 Accounts Payable Matching Document Detail F03B11 Customer Ledger F03B13 Receipts Header F03B14 Receipts Detail F0911 Account Ledger F0911 Account Ledger F0911 Account Ledger F0902 Account Balances F0902 Account Balances Peak Indicators Limited 21

22 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 Peak Indicators Limited 22

23 Data Model AP AR GL Custom Tables Peak Indicators Limited 23

24 Many JDE E1 Modules Feed Accounts Payable Peak Indicators Limited 24

25 JDE E1 Accounts Payable - Process Flow Peak Indicators Limited 25

26 Financial Analytics Data Model Base Fact W_AP_XACT_F Primary JDE E1 Source Tables F0411 Accounts Payable Ledger F0413 Accounts Payable Matching Document Header F0414 Accounts Payable Matching Document Detail Only mapping transactions that have been posted Peak Indicators Limited 26

27 Many JDE E1 Modules Feed Accounts Receivable Contact and Service Billing Sales Order Management Address Book Service & Warranty Management Accounts Receivable Real Estate Management General Accounting Peak Indicators Limited 27

28 JDE E1 Accounts Receivable - Process Flow Peak Indicators Limited 28

29 Financial Analytics Data Model Base Fact W_AR_XACT_F Primary JDE E1 Source Tables F03B11 Customer Ledger F03B13 Receipts Header F03B14 Receipts Detail Only mapping transactions that have been posted Peak Indicators Limited 29

30 Financial Analytics Data Model Base Fact W_GL_REVN_F W_GL_COGS_F W_GL_OTHER_F W_GL_BALANCE_F Primary JDE E1 Source Tables F0911 Account Ledger F0911 Account Ledger F0911 Account Ledger F0902 Account Balances Only mapping transactions that have been posted 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 Peak Indicators Limited 30

31 Financial Analytics Data Model Base Fact W_ACCT_BUDGET_F Primary JDE E1 Source Tables F0902 Account Balances Only mapping transactions that have been posted Only mapping budget ledger type Peak Indicators Limited 31

32 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. Peak Indicators Limited 32

33 Additional Tables for Category Codes Table W_INT_ORG_DS W_INT_ORG_DS W_INT_ORG_DS W_PRODUCT_DS W_PRODUCT_DS W_PRODUCT_DS W_PRODUCT_DS W_CUSTOMER_ACCOUNT_DS W_CUSTOMER_ACCOUNT_DS W_PARTY_ORG_DS W_PARTY_ORG_DS W_PARTY_ORG_DS W_PARTY_ORG_DS W_PARTY_ORG_DS W_PARTY_ORG_DS W_PARTY_ORG_DS W_PARTY_ORG_DS Column STATE_REGION COUNTRY_REGION CONFIG_CAT_CODE INDUSTRY_CODE BRAND COLOR UNIV_PROD_CODE ACCOUNT_TYPE_CODE ACCOUNT_CLASS_CODE LINE_OF_BUSINESS REGION ACCNT_AHA_NUM ACCNT_CLASS ACCNT_HIN_NUM ACCNT_REGION ACCNT_VALUE CUST_CAT_CODE Peak Indicators Limited 33

34 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 Peak Indicators Limited 34

35 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 Peak Indicators Limited 35

36 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 AP AR ACC DEPCN ACC LIAB CASH CMMN STOCK Peak Indicators Limited 36

37 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: Peak Indicators Limited 37

38 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. Peak Indicators Limited 38

39 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 Peak Indicators Limited 39

40 BISC Implementation Peak Indicators Limited 40

41 BISC Implementation Project Plan Week 1 Weeks 2-4 Weeks 5-12 Weeks Week 15 Install & Populate BI Application Review Contents Questionnaire Workshops Prioritise Requirements Development Unit Testing System Testing User Training UAT Migration UAT Deploy to PROD Post-Live Support (BISC) Expert Services (BISC) Peak Indicators Limited 41

42 BISC Implementation BISC Project Team Business Business Sponsor Business Analysts Users BISC Team BISC Project Manager BI Architect 1 - BI Specialist 1 - BISC Consultant Peak Indicators Limited 42

43 BISC Implementation Installation Financial Analytics configured for the following build: Microsoft Windows Server 2003 Standard Edition OBIEE 10g OBIA DAC Informatica 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. Peak Indicators Limited 43

44 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 Peak Indicators Limited 44

45 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 Peak Indicators Limited 45

46 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 Peak Indicators Limited 46

47 Customisation Peak Indicators Limited 47

48 Customisation Requirements Ability to report on Non-Pay data in OBI since last three years. Extensions to Out-of-Box with additional 120+ fields related to... Non-Pay Subject Area 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. Peak Indicators Limited 48

49 Security Peak Indicators Limited 49

50 Security Application Roles Core finance team have high visibility Cost Centre managers have restricted visibility based on application role Oracle Business Intelligence BI Presentation Services BI Server BI Scheduler Oracle BI Application Roles Data Warehouse JD Edwards ETL Informatica Star Schemas Staging Peak Indicators Limited 50

51 ETL Statistics Full Load 10 Hours (DEV) 6 Hours (UAT & PROD) Incremental 5.5 Hours (DEV) 3.5 Hours (UAT & PROD) Peak Indicators Limited 51

52 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 Peak Indicators Limited 52

53 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 Peak Indicators Limited 53

54 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: 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 Peak Indicators Limited 54

55 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 - Peak Indicators Limited 55

56 Peak Indicators Limited Questions?

57 Helping Your Business Intelligence Journey Peak Indicators Limited

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