| Oracle® Business Intelligence Applications Installation Guide for Informatica PowerCenter Users Version 7.9.5.1 Part Number E13765-01 |
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| Oracle® Business Intelligence Applications Installation Guide for Informatica PowerCenter Users Version 7.9.5.1 Part Number E13765-01 |
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View PDF |
Oracle's Siebel applications are shipped with certain Oracle Business Intelligence metadata. These metadata repositories are included with Oracle's Siebel operational applications and Oracle's Siebel Industry Applications. All the rules for security, data modeling, aggregate navigation, caching, and connectivity for the Oracle Business Analytics Warehouse are stored in metadata repositories on the Oracle Business Intelligence Server.
This appendix describes configuration necessary for the Oracle Business Intelligence metadata for Oracle's Siebel operational applications, specifically those areas that a Siebel administrator may need to adjust. These administrative tasks generally cover two subareas:
Dashboard content of Oracle's Siebel operational applications
Metadata requirements for Oracle's Siebel operational applications
This appendix contains the following topics:
Externalizing Financial Services Metadata Translation Strings
Analytics Metadata Requirements for Oracle's Siebel Industry Applications
Oracle's Siebel Operational Applications are built around a general business function, such as Oracle's Siebel Sales, Oracle's Siebel Service, and Oracle's Siebel Call Center.
Oracle's Siebel Industry Applications are built around specific industries' business practices:
Financial Services
Consumer Sector
Communications, Media, and Energy (CME)
Pharma Sales
Note:
You can license one or more Siebel Industry Applications for Oracle Business Intelligence. Licensing allows access to particular dashboards, subject areas, and reports.In the Oracle BI repository file, logical table sources are set by default to settings in Oracle's Financial Analytics family of products (Finance Sales Analytics, Finance Service Analytics, Finance Marketing Analytics, Finance Institutional Analytics, Finance Retail Analytics), the Healthcare Analytics family of products (Oracle Healthcare Sales Analytics, Oracle Healthcare Service Analytics, Oracle Healthcare Marketing Analytics, Oracle Healthcare Partner Manager Analytics), and the Oracle Insurance Analytics family of products (Oracle Insurance Partner Manager Analytics, Oracle Insurance Sales Analytics, Oracle Insurance Service Analytics, Oracle Insurance Marketing Analytics, Oracle Insurance Partner Manager Analytics). Before using these Financial Services Analytics applications, you must update the logical sources for two tables in the Oracle Business Intelligence repository file. These logical sources must be deactivated in order for Oracle's Financial Analytics family of products (Finance Sales Analytics, Finance Service Analytics, Finance Marketing Analytics, Finance Institutional Analytics, Finance Retail Analytics), the Healthcare Analytics family of products (Oracle Healthcare Sales Analytics, Oracle Healthcare Service Analytics, Oracle Healthcare Marketing Analytics, Oracle Healthcare Partner Manager Analytics), and one of the Oracle Insurance Analytics family of products (Oracle Insurance Partner Manager Analytics, Oracle Insurance Sales Analytics, Oracle Insurance Service Analytics, Oracle Insurance Marketing Analytics, Oracle Insurance Partner Manager Analytics) reports to point to the correct logical model and retrieve the correct data. Do this by deactivating the sources for the Fact-Asset logical table in the Core subject area and activating the FINS logical sources, as shown in the following procedure.
Using the Oracle BI Administration Tool, open the Analytics Repository (OracleBIAnalyticsApps.rpd).
Go to the Business Model and Mapping dialog (the logical layer dialog) and open the Core folder.
Scroll down to the Fact - CRM - Asset logical table and open its Sources folder.
In the list of logical table sources, right-click Fact_ASSET_F_FINS.
Select Properties.
Click the General tab in the Properties dialog and make sure that the Active check box is checked. If it is not, check it.
In the list of logical table sources, right-click W_ASSET_F.
Select Properties.
Click the General tab in the Properties dialog and make sure that the Active check box is deselected.
Click OK and save the repository.
Restart Oracle BI Server.
The Financial Services applications use a different set of translation strings from other Siebel operational applications.
You must externalize the metadata strings in the Analytics repository.
To externalize metadata strings in the Analytics repository
Using the Oracle BI Administration Tool, open the OracleBIAnalyticsApps.rpd.
Select the entire presentation layer and right-click the mouse to display the menu.
Choose Display Names.
With this configuration, all metadata strings are read from an external Siebel operational application database, specifically from the table W_LOCALIZED_STRING_G.
Make sure that the connection pool Externalized Metadata Strings points to the Siebel operational application database and is working correctly.
Go to the Manage Variables menu and locate the initialization block External Metadata Strings.
Double-click on the initialization block to open the Edit dialog.
In the Initialization SQL area, change the SQL:
from
select MSG_NUM, MSG_TEXT
from VALUEOF(OLAP_TBO).W_LOCALIZED_STRING_G
where MSG_TYPE = 'Metadata' and
LANG_ID = decode('VALUEOF(NQ_SESSION.WEBLANGUAGE)'... [more]
to
select MSG_NUM, MSG_TEXT
from VALUEOF(OLAP_TBO).W_LOCALIZED_STRING_G
where MSG_TYPE = 'FINS_Metadata' and
LANG_ID = decode('VALUEOF(NQ_SESSION.WEBLANGUAGE)'... [more]
Click OK to commit the changes and save the repository.
Restart the Oracle BI Server.
In the Analytics Repository file, logical table sources are set by default to settings in Oracle's Siebel Financial Analytics, the Healthcare Analytics family of products (Oracle Healthcare Sales Analytics, Oracle Healthcare Service Analytics, Oracle Healthcare Marketing Analytics, Oracle Healthcare Partner Manager Analytics), and the Oracle Insurance Analytics family of products (Oracle Insurance Partner Manager Analytics, Oracle Insurance Sales Analytics, Oracle Insurance Service Analytics, Oracle Insurance Marketing Analytics, Oracle Insurance Partner Manager Analytics). If you are using any Siebel Industry application that is not Oracle's Siebel Financial Services Analytics, you must first update the logical table sources in the Analytics Repository file.
These logical table sources must be deactivated in order for your Siebel Industry application Analytics reports to point to the correct logical model and retrieve the correct data. Do this by deactivating the FINS sources for the logical tables in the Core subject area and activating the other logical sources, as shown in the following procedure.
Note:
Before performing the following procedure, shut down the Oracle BI Server.To update Logical Table sources for Oracle's Siebel Industry Applications Analytics
Using the Oracle BI Administration Tool, open the Analytics Repository (OracleBIAnalyticsApps.rpd).
Go to Business Model and Mapping dialog (the logical layer dialog) and open the Core folder.
Scroll down to the Fact - CMR - Asset logical table and open its Sources folder.
In the list of logical table sources, right-click Fact_W_ASSET_F_FINS.
Select Properties.
Click the General tab in the Properties dialog and deselect the Active check box.
In the list of logical table sources, right-click W_ASSET_F.
Select Properties.
Click the General tab in the Properties dialog.
Make sure that the Active check box is checked. If it is not, check it.
Click OK and save the repository.
Restart Oracle BI Server.
The Loyalty Management Dashboard and several Oracle Business Intelligence subject areas use customer scores generated from Oracle Real-Time Decisions. Oracle Real-Time Decisions uses mathematical models to predict customer behavior. For customer scoring to be made available for analysis in Oracle Business Intelligence, CME metadata is provided which maps these customer scores to dashboards and subject areas.
The following procedure describes the process of developing and deploying these predictive scores.
To develop and deploy predictive scores
Generate predictive scores using Oracle Real-Time Decisions.
Note:
This is performed outside of the Siebel operational application.Integrate the scores into the Oracle Business Analytics Warehouse.
Once this is completed, scores may be viewed in the Siebel operational application by accessing the Accounts, then Profiles, then Loyalty Profile view.
Load the integrated scores into the Oracle Business Analytics Warehouse during the extraction, transformation, and loading (ETL) process.
After the scores are loaded into the Oracle Business Analytics Warehouse, map them to the following Oracle Business Intelligence metadata fields:
Churn Score
Customer Lifetime Value Score
Upsell Score
Cross-Sell Score
Financial Risk Score
In conjunction with other associated metadata, these fields are primarily used to populate the Loyalty Management dashboard.
Some metadata needs to be set up properly in the Oracle Business Analytics Warehouse for it to be displayed accurately in Oracle Business Intelligence. The following topics describe the metadata structure for each of the following Oracle's Siebel Industry Applications:
Oracle's Siebel Consumer Sector Sales Analytics extends the base Sales Analytics application to include Trade Funds Management Analytics, Trade Promotion Evaluation Analytics, Sales Performance Analytics, and Retail Audit Analytics.
All Consumer Sector specific metadata has been added to a single subject area. In the Oracle BI Administration Tool, this metadata is tagged with a red apple icon. The following topic covers each fundamental area of Consumer Sector Analytics and provides tips for data entry for effective analytics.
The Consumer Sector dashboards and pages available to the end user are described in Table E-1.
Table E-1 Consumer Sector Dashboards and Page Tabs
| Dashboard | Page | Function |
|---|---|---|
|
Retail Audit |
Last Audit |
Shows the aggregated results of the last audit, defined the last time a product was audited at a specific account and merchandising location. The aggregated metrics can be drilled into to get a list of accounts or products to target future efforts. |
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Trends |
Displays key metrics captured in a retail audit over time across accounts or product categories. |
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|
Position |
Combines account and product performance with the individual representative responsible. |
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Promotion |
Plan Year To Date |
Displays both individual promotional performance with cumulative trends to provide overall perspective on meeting promotional targets. |
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Key Accounts |
Shows post promotion evaluation from a key account perspective across several levels of detail including plan, promotion, or promoted product detail. |
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Corporate |
Shows post promotion evaluation from a brand managers perspective, by evaluating corporate promotions. |
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Funds |
Summary |
Displays the key analyses for a fund manager, including Remaining Amounts which provides a status of all funds relative to all other funds. |
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Accounts |
Highlights status of funds and funds spent at a specific account and is targeted to assist key account managers in determining how to fund future promotions. |
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Sales Performance |
Sales Volume Planning |
Details the key metrics used in sales volume planning, including incremental, target, shipment and consumption volumes, over time and in comparison to one another. Baseline and estimated incremental volumes are stacked and compared to targets to assist in identifying future progress against targets. This analysis uses a global filter to assist end users in getting to the level of details they want in one selection. |
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Hierarchy |
Similar in content to Sales Volume Planning, however, this analysis is organized to promote exploration of data, allowing end users to freely drill up or down the account, time, or category product hierarchies. This page should be used to help sales managers identify where sales exceeded expectations. |
|
|
Trends |
Depicts sales trends across accounts, channels, and categories as well as compares account performance in order to rank them. |
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Growth |
Displays key sales metrics versus the year ago and charts the rate of growth. |
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VP Sales |
Business Overview |
This page focuses on answering key business questions of a sales executive including where are my sales? How effective are my promotions by channel? Which account plans are top and bottom performers? How is my promoted volumes and funds spend trending as compared to last year? What are my top five accounts in each category? |
|
Product Overview |
This page focuses on answering key product questions of a sales executive. For example, What percentage of total sales is in each category? What products are selling where by whom? |
|
|
Key Account Manager |
Account |
This page focuses on answering key business questions of a key account manager. For example, How I am performing versus my account plan? What is my promotional forecast accuracy? What funds are available to plan additional retail activity? |
|
Category |
This page focuses on answering key product questions of a key account manager. For example, Which category is best promoted at my accounts? How are my store conditions trending? Are out of stocks preventing me from reaching my targets? |
The data requirements for the Consumer Sector–specific portion of the data model are detailed in Table E-2. This includes the fund, promotion, performance and retail audit schema.
Table E-2 Data Requirements for Consumer Sector Schema
| Page | Function |
|---|---|
|
Funds |
Trade Fund Management Analytics incorporates the latest Trade fund functionality including aggregation of approved adjustments, transfers, deal allocations, and payments at all statuses. |
|
Promotion |
In the transactional database, fund allocations and product movement (incremental volumes) can be assigned to a promotion at the promotion or the promoted product level. The ETL transfers this information at the promoted product level only. If you allocate funds at the promotion level and assign product detail such as shipment quantities at the promoted product level, the fund allocation data needs to be pushed to the promoted product level to be accurately stored in the Oracle Business Analytics Warehouse. |
|
Performance |
Sales Performance Analytics is used primarily in conjunction with the category product hierarchy as defined by Oracle's Siebel Sales Volume Planning. To create the category-product hierarchy, the SVP adopt flag must be selected in order to aggregate product data up the category product hierarchy. This flag can be found by navigating to Catalog Administration, then SVP Category Details View, then Products list. The data warehouse and all prebuilt analyses are built from the end date of a period. To make sure data is accurate, the periods in the Oracle Business Analytics Warehouse tables must be of a single duration. If they are different, inaccurate data could be stored in the data warehouse. For example, if a week and a month end on the same date, the actual shipped quantities are combined during the building of the data warehouse. |
|
Retail Audit |
The Last Audit Flag is set during the ETL process. The flag is set to Yes for the most recent record for a product at an account and merchandising location. All other audit records for that combination of product, account, and merchandising location are set to No. The observation date is used to sort the retail audit records to determine which is the last audit. The observation date is populated when the status of a retail audit activity is changed to Done. The field observation date does not show up in the Oracle Business Analytics Warehouse user interface and does not have to be the same as the activity date. |
Oracle's CME family of products (Oracle Communications, Media and Energy Sales Analytics,
Oracle Communications, Media and Energy Service Analytics, Oracle Communications, Media and Energy Marketing Analytics) makes use of order management functionality configured for CME. For Oracle's CME applications to fully reflect the information collected by CME order management functionality, some extensions to the Oracle CME Analytics application may be required. This topic explains these potential extensions.
Oracle's Siebel Sales Orders include complex products and simple products.
Complex Products. A series of products related by a product hierarchy. The highest product in the hierarchy is the root product, and the lower level products are the child products. In complex products, revenue figures are summed and roll up to the root product using the ROLLUP_NET_PRI field. For a complex product, Oracle Business Intelligence examines only the root product when computing revenue. Child products are disregarded because their revenue is already reflected in the root.
Simple Products. A root product. Oracle Business Intelligence examines this root product when computing revenue, and nothing more.
Oracle's Siebel Communications, Media and Energy order management functionality supports products which have recurring charges over time (for example, $20 per month for 12 months), one-time charges (for example, one-time purchase price of equipment), and usage charges (for example, 15 cents per minute).
The revenue attributed to a product with recurring charges is valued by taking the product's net price and multiplying it by the number of months that product is anticipated to be active, as represented by the Number of Revenue Occurrences field. This field, contained in Quote Item and Order Item records, is contained in the Oracle Business Analytics Warehouse by the following fields:
W_QUOTEITEM_F.NUM_OCCURRENCE
W_ORDERITEM_F.NUM_OCCURRENCE
In Oracle's CME family of products (Oracle Communications, Media and Energy Sales Analytics, Oracle Communications, Media and Energy Service Analytics, Oracle Communications, Media and Energy Marketing Analytics), revenue metrics do not automatically account for all recurring charges, and do not consider the NUM_OCCURRENCE fields. Instead, Oracle's CME family of products revenue metrics incorporate one-time charges, one-month's worth of recurring charges, and no usage charges. To incorporate the anticipated value of all recurring charges, the W_QUOTEITEM_F.NUM_OCCURRENCE and W_ORDERITEM_F.NUM_OCCURRENCE fields may need to be incorporated into revenue calculations made during the Extraction, Transformation and Load (ETL) process for order item and line item records.
Alternatively, these fields in the Oracle Business Analytics Warehouse, representing the aggregated recurring and one-time product charges, may be used and incorporated into the ETL processes:
S_ORDERITEM.PER_MTH_CHG_SUBTOT
S_ORDERITEM.ONETIME_CHG_SUBTOT
S_QUOTEITEM.PER_MTH_CHG_SUBTOT
S_QUOTEITEM.ONETIME_CHG_SUBTOT
Each CME Order line item and Quote line item contains an Action Type of Add, Update, or Delete. Because Oracle Business Intelligence only looks at root product line items, only the Action Types associated with the root product are considered during analysis. Therefore, while all line items for a complex product may collectively include a combination of various Action Types, only the Action Type for the root product are considered during analysis. This is of special importance if a filter or query criteria in analysis is based on the Action Type field, which it is for most Account Management and Revenue Management dashboard reports.
Similarly, each CME Order line item and Quote line item is associated with a product of a particular Price Type. Because Oracle Business Intelligence considers root products only, only the Price Type associated with the root product is considered during analysis. Again, this is important if a filter or query criteria is based on Price Type. Such filter criteria apply to most Account Management and Revenue Management dashboard reports.
Oracle's Siebel Communications, Media and Energy (CME) Analytics contains corresponding industry-specific metadata. In the Oracle BI Administration Tool, industry-specific metadata is flagged with an icon picturing a telephone. Although this icon is visible in the Oracle BI Administration Tool, it is neither visible nor included within Oracle BI Answers. End users use Oracle BI Answers to access metadata for building queries and reports. For users of Oracle BI Answers to view and access CME metadata columns, they must log in using one of the CME responsibilities listed in Table E-3. These responsibilities also determine what subject areas the user may access.
Table E-3 Communications, Media and Energy Dashboards and Page Tabs
| Dashboard | Page | Function |
|---|---|---|
|
Loyalty Management |
Customer Lifetime Value |
Segments customers based upon defined ranges of scores predicting customer lifetime value. |
|
Churn Propensity |
Segments customers based on defined ranges of scores estimating churn propensity. |
|
|
Selling Propensity |
Segments customers based on defined ranges of scores valuing the potential of up-sell and cross-sell opportunities. |
|
|
Financial Risk |
Segments customers based on defined ranges of scores predicting financial risk. |
|
|
Actual Churn |
Shows trending of actual customer churn, and actual customer acquisition, over time. |
|
|
Revenue Management |
Revenue Trends |
Charts trends of order revenue and order volume over time, and identifies top products based on order revenue and volume. |
|
Service Activations |
Charts trends of service activations over time, and indicates top service activations based on order revenue and volume. |
|
|
Service Modifications |
Charts trends of service modifications over time, and indicates top service modifications based on order revenue and volume. |
|
|
Service Disconnections |
Charts trends of service disconnections over time, and identifies services with the highest disconnection volume. |
|
|
Account Management |
Sales Portal |
Identifies top accounts, and related top products, based upon order revenue and order volume. |
|
Service Activations |
Charts trends of account service activations, and indicates top accounts based on service activation performance metrics. |
|
|
Service Modifications |
Charts trends of account service modifications, and indicates top accounts based on service modification performance metrics. |
|
|
Service Disconnections |
Charts trends of account service disconnections, and identifies accounts with the highest volume of disconnections. |
|
|
Trouble Tickets |
Provides trouble ticket trending charts, and performance indicators, for particular accounts, and for accounts with selected common characteristics. |
|
|
Customer Satisfaction |
Provides customer satisfaction trending charts, and performance indicators, for particular accounts, and for accounts with selected common characteristics. |
The data requirements for each of the Communications, Media and Energy dashboards are detailed in Table E-4.
Table E-4 Data Requirements for Communications, Media and Energy Dashboards
| Dashboard | Function |
|---|---|
|
Loyalty Management |
This dashboard uses customer scores generated from any third-party predictive modeling application offering the following predictive models: Customer Lifetime Value, Churn Propensity, Up-Sell Propensity, Cross-Sell Propensity, and Financial Risk Propensity. Scores must be generated for each Siebel Account, integrated into the Siebel Transaction Database, and then written to the Oracle Business Analytics Warehouse. This dashboard uses the Oracle Business Intelligence Customers subject area. See Developing and Deploying Predictive Scores for more information. |
|
Revenue Management |
This dashboard uses data generated by Oracle's Siebel Communications, Media and Energy order management and interactive selling functionality. No specific data requirements are required beyond the data generated from these Siebel modules. This dashboard uses the Oracle Business Intelligence Orders and Products subject areas. |
|
Account Management |
This dashboard uses data generated by Oracle's Siebel Communications, Media and Energy order management, interactive selling, and service functionality. No specific data requirements are required beyond the data generated from these Siebel modules. This dashboard uses the Oracle Business Intelligence Orders, Products, Service Request and Customer Satisfaction subject areas. |
Although the following dimensions are used in all subject areas, this topic describes the configuration necessary for Pharma Analytics applications. For more information, please refer to Siebel Life Sciences Guide Version 8.0 Appendix B: Configuring Data for Siebel Pharma Analytics.
A sales territory is defined in Group Administration–Positions by a Siebel position. Creating parent positions creates the sales force hierarchy. Up to 10 levels of sales force hierarchy are supported by the application. Employees should be assigned to positions to populate employee hierarchy.
Position Types need to be set up according to compensation type (Rx or sales) only at the sales territory level. A district manager does not need to have a Position Type assigned to it. Sales Allocation needs to be exposed on the list to enter script compensation percentages (Rx or Sales) associated with each territory. For example, if all sales representatives receive 100% of the Rx on a ZIP Code, no action is needed or Position Type = Sales Representative can be assigned to the position.
Seed data on the Position Type list of values has been enhanced to include types for mirror, job share, and swat. Typically, both mirror and job share represent a position that receives less than 100% of the total scripts on a ZIP Code.
A sales territory alignment is the relationship of ZIP Code-to-territory or brick-to-territory. The alignment relationship is created in Oracle's Siebel Assignment Manager under Assignment Administration–Territories, as shown in Table E-5.
Table E-5 Sales Territory Alignment
| Relationship | Criteria | Comments |
|---|---|---|
|
Contact ZIP to Territory |
Contact ZIP Code |
Use contact primary address ZIP Codes. Do not use ranges of ZIP Codes (that is, enter unique ZIP Codes as low and high values). Do not enter duplicate ZIP Codes. |
|
Account ZIP to Territory |
Account ZIP Code |
Do not use ranges of ZIP Codes (that is, enter unique ZIP Codes as low and high values). Do not enter duplicate ZIP Codes. |
|
Contact Brick to Territory |
Contact Brick |
Use contact primary address brick. Do not use ranges of bricks (that is, enter unique bricks as low and high values). Do not enter duplicate ZIP Codes. |
|
Account Brick to Territory |
Account Brick |
Do not use ranges of bricks (that is, enter unique bricks as low and high values). Do not enter duplicate ZIP Codes. |
|
Account to Territory |
Account |
Do not enter duplicate accounts. |
|
Contact to Territory |
Contact |
Do not enter duplicate contacts. |
The product hierarchy requires customer products (products of the company who licensed the software) to have predefined product types as shown in Table E-6.
Table E-6 Customer Products Predefined Product Types
| Product Level | Product Type | Example |
|---|---|---|
|
3 |
Sample |
Aracid 400 MG |
|
2 |
Detail |
Aracid |
|
No Level |
Sub Market |
COPD |
|
1 |
Market |
Asthma |
Note:
Competitive products should use the product type Competitor. Competitor product hierarchies are set up using parent product relationships exclusively and should not have product levels assigned to them.Product costs for customer products (that is, products of the company that licensed the software) require population in the Product Administration, Product Form, as shown in Table E-7.
This section discusses the subject areas used by Pharma Analytics. For more information, please refer to Siebel Life Sciences Guide Version 8.0 Appendix B: Configuring Data for Siebel Pharma Analytics.
This subject area is focused on syndicated data analytics.
The specific configuration required for the syndicated data depends on your data types, and the Analytics application and reports that you have licensed. The Data Loading Matrix table is the basis of prebuilt reports. The syndicated data loading matrix populates both base and derived metrics used in Pharmaceutical Sales Analytics.
Oracle Pharma Sales Analytics and Oracle Pharma Marketing Analytics supports custom and prebuilt product category trees to allow roll-up of syndicated data by alternative hierarchies. To populate a custom category, first create a Catalog in Catalogue Administration, and create categories and subcategories as part of the catalogue. Table E-8 lists the categories that need to have the Usage Type field populated in the Catalog Admin Category Detail list.
This subject area combines call activity data with syndicated data to analyze effectiveness of call activity.
Call Activity analysis records are derived from submitted call activity records stored in S_EVT_ACT in the Oracle Business Analytics Warehouse, where they are stamped with the ZIP Code or brick where the activity took place—that is, the Contact primary address's ZIP code/brick or the Account ZIP Code/brick. Allocation of these ZIP Code/brick records should be done by Assignment Manager rules to make sure that they are correctly allocated. Assignment Manager rules must match the Contact or Account primary address ZIP Codes or bricks. Otherwise, data integrity is not maintained.
Only calls that have status Submitted on the Pharma Professional Call Form are brought over from the Oracle Business Analytics Warehouse to the Oracle Business Analytics Warehouse.
This subject area combines measures from MedEd and Syndicated Data to measure effectiveness of medical education events used on Medical Education Analytics.
Only MedEd events with the status Completed on the Pharma ME Event List are extracted from Oracle Business Analytics Warehouse to populate the Oracle Business Analytics Warehouse.
MedEd Event costs are based on costs of activities in the Pharma ME Event Activity List. Costs are allocated based on MedEd Team cost allocation, and promoted products Cost Allocation on the MedEd event.
Costs are solely based on physician invitees with the status Attended in the Pharma ME Event Professional Invitee Session List.
Control groups are based on physicians who have the same contact ranking as attendee physicians within the same sales territory at the time of the event, but who did not attend the event.
This subject is used to measure achievement and results for pharma call activity and Rx/sales targets. It is based on Pharma Objectives.
Objectives need to have a Unit populated in Retail Objective Form. Actual target numbers per contact and account need to be populated in the Pharma Campaign Target Account List or the Pharma Campaign Target Professional List Toggle.
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