Analytics: Pharma Analytics (Siebel 7.8) Student Guide

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1 Analytics: Pharma Analytics (Siebel 7.8) Student Guide D44606GC11 Edition 1.1 March 2008 D54241

2 Copyright 2008, Oracle. All rights reserved. Disclaimer This document contains proprietary information and is protected by copyright and other intellectual property laws. You may copy and print this document solely for your own use in an Oracle training course. The document may not be modified or altered in any way. Except where your use constitutes "fair use" under copyright law, you may not use, share, download, upload, copy, print, display, perform, reproduce, publish, license, post, transmit, or distribute this document in whole or in part without the express authorization of Oracle. The information contained in this document is subject to change without notice. If you find any problems in the document, please report them in writing to: Oracle University, 500 Oracle Parkway, Redwood Shores, California USA. This document is not warranted to be error-free. Restricted Rights Notice If this documentation is delivered to the United States Government or anyone using the documentation on behalf of the United States Government, the following notice is applicable: U.S. GOVERNMENT RIGHTS The U.S. Government s rights to use, modify, reproduce, release, perform, display, or disclose these training materials are restricted by the terms of the applicable Oracle license agreement and/or the applicable U.S. Government contract. Trademark Notice Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners.

3 Contents Module i: Course Introduction Module Agenda i.3 Instructor and Class Participants i.4 Training Site Information i.5 Course Audience i.6 Course Prerequisites i.7 Course Goal i.8 Course Objectives i.9 Course Methodology i.10 Course Materials i.11 Course Agenda i.12 Summary i.14 Module 1: Siebel Pharma Analytics Introduction Module Objectives 1.2 Pharmaceutical Customer Management Process 1.3 Develop Customer Strategy 1.4 Develop Customer Tactics 1.5 Gain Customer Access 1.6 Influence Rx Behavior 1.7 Track Results 1.8 Business Intelligence Challenges 1.9 Physician Targeting 1.10 Data Integration 1.11 Sales Analytics for Distributed Teams 1.12 Creating Value over the Product Life Cycle 1.13 Areas Where Siebel Pharma Analytics Creates Value 1.14 Components of Siebel Pharma Analytics 1.16 Siebel ETL Plans 1.17 Prebuilt Pharma Star Schemas 1.18 Best Practices Library of Reports 1.19 Pre-Mapped Metadata for Star Schemas 1.20 Summary 1.21 Lab 1.22 iii

4 Module 2: Siebel Pharma Analytics Application Overview Module Objectives 2.2 Siebel Pharma Analytics Applications 2.3 Sales Rx Analytics 2.4 Call Activity Analytics 2.5 Sales Objectives Analytics 2.6 Medical Education Analytics 2.7 Physician/Account Profiling Analytics 2.8 Role-Based Bundled Applications 2.9 Sales Executive Analytics 2.10 Sales Representative Analytics 2.11 District Manager Analytics 2.12 Terminology 2.13 Summary 2.14 Lab 2.15 Module 3: Exploring Pharma Analytics Business Model and Physical Structures Module Objectives 3.2 Siebel Pharma Analytics Applications 3.3 Pharma Analytics Application Content 3.4 Siebel Relationship Management Warehouse 3.5 Data Warehouse Application Console: Tasks 3.7 Data Warehouse Application Console: Table Group 3.8 Data Warehouse Application Console: Subject Area 3.9 Data Warehouse Application Console: Execution Plan 3.10 Informatica: Source Dependent Extract (SDE) Mapping 3.11 Informatica: Source Independent Load (SIL) Mapping 3.12 Repository 3.13 Repository: Physical 3.14 Repository: Business Model and Mapping 3.15 Repository: Presentation 3.18 Dashboard 3.19 Medical Education Analytics Application Content 3.20 Slowly Changing Dimension (SCD) Tables 3.21 Siebel Pharma Application SCD Tables 3.22 Account: Type and Name 3.23 Account: Parent and Beds 3.24 Alignment 3.25 Alignment Data Model 3.26 Operational and Power User Tables 3.27 Operational Tables: Aligned 3.28 iv

5 Power User Tables: Non-Aligned 3.29 Position 3.30 Sales Force (Position Hierarchy Data Model) 3.31 Product 3.32 Account Rank 3.33 Summary 3.34 Lab 3.35 Module 4: Transactional Data Population Rules Module Objectives 4.2 Transactional Data Requirements Overview 4.3 ETL Requirements and Siebel Pharma Configuration 4.4 Siebel Pharma Analytics Hierarchies 4.5 Hierarchy Tables 4.6 Product Hierarchies 4.9 Data Population Rules for Siebel Pharma CRM 4.12 Standard Product Hierarchy 4.13 Product Catalog and Category Hierarchies 4.16 Sales Objectives 4.18 Medical Education Events 4.21 Call Activity: View, Applets, and Business Components 4.23 Call Activity: Source Population Rules 4.24 Summary 4.26 Lab 4.27 Module 5: Creating Sales Hierarchies Module Objectives 5.2 Sales Hierarchies Overview 5.3 Building Sales Position and Territory Hierarchies 5.4 Populating the Sales Position Hierarchy Build Raw Hierarchy Push Down Lowest Populated Level 5.7 Sales Force Hierarchies: Presentation Layer 5.8 Populating the Sales Territory Hierarchy 5.10 Alignment Dimension Hierarchy ETL Process 5.11 Populating Sales Territories in Siebel Pharma 5.12 Entering Transactional Data Create Primary Sales Force Hierarchies Create Assignment Rules 5.15 v

6 3. Control Sales Territory Alignment Versions 5.20 Summary 5.22 Lab 5.23 Module 6: Exploring Syndicated Data Module Objectives 6.2 Business Challenge 6.3 Solution 6.4 Siebel Pharma Analytics: Syndicated Data 6.5 Syndicated Data Definitions 6.7 Syndicated Data: High-Level ETL Process 6.8 Syndicated Data Components 6.9 Cross-Reference Data 6.10 Cross-Reference Data: File Types 6.11 Cross-Reference Data: Example 6.12 Cross-Reference Data: Loading 6.13 Cross-Reference Data: Mappings 6.16 Cross-Reference Data: Source-to-Target Mapping 6.17 Syndicated Data 6.18 Syndicated Data: File Types 6.19 Syndicated Data: Example 6.21 Syndicated Data: Mappings 6.22 Syndicated Data: Source to Target Mapping 6.23 Summary 6.24 Lab 6.25 Module 7: Loading Syndicated Data Module Objectives 7.2 Syndicated Data Loading Options 7.3 Use Syndicated Data Staging Tables 7.4 Use Syndicated Data Staging Tables: ETL Process 7.5 Use Siebel Transactional Database 7.7 Use Syndicated Market Staging Tables 7.9 Use Syndicated Market Staging Tables: ETL Process 7.10 Use Syndicated Market Staging Tables: Enabling 7.12 Alignment Assignment Type 7.13 Alignment Dimension Hierarchy 7.15 Alignment Dimension Hierarchy: ETL Process 7.16 Product Dimension Hierarchy 7.17 Product Dimension Hierarchy: ETL Process 7.18 Syndicated Data Loading Features 7.19 vi

7 Calculated Syndicated Market Fact 7.20 Calculated Syndicated Market Fact: Tables 7.21 Syndicated Data Fact Replication 7.22 Syndicated Data Fact Replication: Tables 7.23 Syndicated Data Fact De-Duplication 7.24 Syndicated Data Fact De-Duplication: Tables 7.25 Syndicated Data Fact Aggregation 7.26 Syndicated Data Fact Aggregation: Tables 7.27 Syndicated Data Loading: Source Files 7.29 Syndicated Data Loading: Execution Plan 7.30 Syndicated Data Loading: Subject Area 7.31 Summary 7.32 Lab 7.33 Module 8: Mobile Analytics Overview Module Objectives 8.2 Business Challenge 8.3 Solution: Siebel Mobile Analytics 8.4 Siebel Mobile Analytics Options 8.5 Mobile Analytics Application 8.6 Synchronization Operation 8.7 Disconnected Analytics Application Manager (DAAM) 8.8 Mobile Analytics Components 8.9 Mobile Analytics Repository 8.10 Mobile Analytics Web Catalog 8.11 SQL Script Files 8.12 Sourcing Query 8.13 Data Set 8.14 Mobile Application Configuration File 8.15 Mobile Directory Structure 8.16 Mobile Analytics Architecture 8.17 Installing Siebel Mobile Analytics 8.18 Summary 8.19 Lab 8.20 Module 9: Exploring the Prebuilt Pharma Mobile Analytics Application Module Objectives 9.2 Pharma Mobile Analytics 9.3 Pharma Mobile Analytics Components 9.4 Prebuilt Role-Based Dashboards 9.5 Pharma Sales Representative Dashboard 9.6 vii

8 Pharma District Manager Dashboard 9.7 Prebuilt Subject Areas 9.8 Pharma Objective Achievement 9.9 Pharma Promotional Effectiveness 9.10 Pharma Sales Effectiveness 9.11 Prebuilt Star Schemas 9.12 Contact Call Activity Star 9.13 Contact Objective Star 9.14 Syndicated Data Direct Sales Star 9.15 Syndicated Data Indirect ales Star 9.16 Syndicated Data NRx/TRx Star 9.17 Prebuilt Dimensions 9.18 Prebuilt Dimensional Hierarchies 9.19 Prebuilt SQL Scripts 9.20 Prebuilt Sourcing Queries 9.21 Prebuilt Application Configuration File 9.22 Prebuilt Data Sets 9.23 Prebuilt Directory Structure 9.24 Additional Considerations and Recommendations 9.25 Key Differences Between Enterprise and Mobile Models 9.26 Data Visibility 9.27 Prebuilt Integration with Pharma CRM Application 9.28 Recommendations to Extend Mobile Pharma Data Model 9.29 Summary 9.30 Lab 9.31 Module 10: Customizing a Pharma Mobile Analytics Application Module Objectives 10.2 Overview 10.3 Building a Pharma Mobile Analytics Application 10.4 Identify Necessary Configuration Changes Build SQL Scripts Customize Mobile Repository: Overview Customize Mobile Repository: Local Database Customize Mobile Repository: Physical Schema Customize Mobile Repository: Physical Layer Customize Mobile Repository: Database Type Customize Mobile Repository: Connection Pool Customize Mobile Repository: BMM Layer Customize Mobile Repository: Presentation Layer Customize Mobile Repository: Security viii

9 4. Customize Mobile Web Catalog Set Up Sourcing Queries Set Up Sourcing Queries: Filters Modify Configuration File Modify Configuration File: Data Sets Populate Directory Structure Test and Validate: Application Test and Validate: Download Configuration Considerations and Recommendations Static Dimensions Common Dimensions Fact Tables and Private Dimensions Single Table Versus Multiple Table Data Sets Incremental Synchronization Incremental Data Sets Incremental Data Set Validity Checks Summary Lab Module 11: Synchronizing Siebel Mobile Analytics Module Objectives 11.2 Synchronization 11.3 Downloading an Application 11.4 DAD Files 11.5 Initial Synchronization 11.8 Steps Performed by Initial Synchronization Check Data Sets to Be Synchronized Run Sourcing Reports Download Metadata and Scripts Download Comma Separated Value Files Execute Scripts to Create Local Database Populate Local Database Generate Application-Specific Configuration Files Summary Lab Module 12: Configuring Additional Synchronizations Module Objectives 12.2 Synchronization Methods 12.3 Manual Synchronization 12.4 Silent Synchronization 12.5 ix

10 Steps to Perform Manual Synchronization Get Server Information Select Data Sets to Synchronize Synchronize Confirm Synchronization Silent Synchronization Silent Synchronization: Examples Synchronization Modes Standard Synchronization Preprocessed Synchronization Steps to Configure Preprocessed Synchronization Create ibots for Sourcing Reports Edit Configuration File Preprocessing Considerations Additional Considerations Summary Lab Module 13: Integrating Mobile Clients Module Objectives 13.2 Business Challenge and Solution 13.3 Siebel Pharma Mobile Web Client 13.4 Local Application Integration 13.6 Integrated Objects 13.7 Analytics Dashboards as Siebel Pharma Screens 13.8 Analytics Reports in the Siebel Pharma Home Page 13.9 Action Links Analytics Columns in Siebel Pharma Applets Target Lists in the Siebel Mobile Web Client Creating Target Lists Integrating Mobile Applications Steps to Integrate Mobile Applications Install the Siebel Pharma Mobile Web Client Configure the Siebel Pharma Mobile Web Client Modify the Local Repository to Use the Local OLTP Enable Siebel Mobile Analytics in Silent Mode Synchronize Both Applications Synchronization Considerations x

11 6. Test Prebuilt Screens and Action Links Summary Lab Module 14: Wrap-Up Module Objectives 14.2 Course Overview 14.3 Transactional Data Requirements 14.4 Creating Sales Hierarchies 14.5 Exploring and Loading Syndicated Data 14.6 Customizing a Pharma Mobile Analytics Application 14.9 Synchronizing Siebel Mobile Analytics Integrating Mobile Clients Future Resources Thank You Appendix: Application Content Sales Rx Analytics Application Content A.2 Call Activity Analytics Application Content A.5 Sales Objectives Analytics Application Content A.6 Physicians/Account Profile Analytics Application Content A.7 xi

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