WO2002059777A2

WO2002059777A2 - A system and method for managing information

Info

Publication number: WO2002059777A2
Application number: PCT/CA2002/000080
Authority: WO
Inventors: Paul Minshull; Daniel Hageman
Original assignee: Mindworks Consulting Inc.
Priority date: 2001-01-26
Filing date: 2002-01-25
Publication date: 2002-08-01
Also published as: WO2002059777A3; CA2332654A1

Abstract

In accordance with an aspect of the present invention there is provided an information retrieval system. The system comprises a plurality of local databases accessible by users on corresponding local networks and a parent database for managing information stored in the plurality of local databases, the parent database being coupled with the plurality of local databases by a global network. The system further comprises at least one server for receiving a query request from a user on one of the local networks for querying the corresponding local database and for querying the parent database to determine if the query can be fulfilled by others of the local databases.

Description

A SYSTEM AND METHOD FOR MANAGING INFORMATION The present invention relates to a system and method for supporting and automating workflows relating to the successful management of a multinational organization. In particular, the present invention relates to a system and method for storing, retrieving, manipulating, archiving, exporting and sorting data relating to workflows associated with brand management on a global basis within an enterprise class security architecture.

BACKGROUND OF THE INVENTION

Pharmaceutical and biotechnology companies have struggled to equip their brand management teams with the tools necessary to optimize their management of businesses in a global environment. Many companies find themselves tackling complex work processes such as competitive intelligence, strategic planning, quantitative modeling, skills enhancement and business development within a limited tool kit and with little vision on how to create global synergy through the companies' operations in different countries. ■ ^■

Product management teams are often reduced to utilizing integrated office suite software such as Microsoft^® Office to manage these tasks. This type of approach creates many problems for the companies.

Team members, or users, create the working objects (word processing files, spread sheeting analyses or relational databases) to manage their workflow from scratch. This places a great burden on the skill set of the users to develop the data planning elements and actually build them with their "office suite" tools. Most users lack the experience to adequately data model their requirements and lack the experience to utilize the higher level functions and integration contained within their "office suite". The result is that users spend most of their time on the methodology of creating their tools and not enough time and effort creating the content.

The reliance on individuals to manage their work processes creates an individualistic solution to a team problem. The lack of integrated vision means that members of one product management team lack the ability to communicate and synergize with other teams within either an inter or intra-affiliate nature. This disconnected inf astructure leads to significant inefficiencies at the product team level and the senior management level where the companies are trying to make resource allocation decisions.

The issue of connecting workflows at the inter-affiliate level poses many technological challenges as systems must create data equivalency across disparately named data objects that are operating in a dynamic world.

Significant advances in technology are occurring at a rapid pace, but it is difficult to implement these advances in an environment where the workflows are being managed at the individual level. Advanced forecasting tools have become available over the last few years which can revolutionize the quantitative modeling approach, however, their implementation within a common framework and methodology lias been limited due to the lack of enterprise vision on how quantitative modeling should be implemented.

The workflows described above often lead to an inability to source and adequately protect data that is produced within a company. An enterprise vision on workflows supported by a system solution begins to apply a common standard of care on processes that are mission critical to the organization.

In a world where hardware and global communication infrastructure provide opportunities for global data management, many companies find highly sensitive data stored in an ad hoc basis.

In cases where companies have attempted to integrate more workflow oriented tools or systems, they have often found themselves in the position of creating functional vertical silos. The tools manage a single workflow, but have an inability to access and feed data to other related workflows.

An example of this would be the company that creates a quantitative modeling tool to manage market and financial related data. The tool lacks the ability to dynamically access third party data in the company's data warehouse. The tool also lacks the integration to feed the corporate business planning workflow and has only minimal integration with the financial systems of the company. Users are often faced with filling the integration gaps and this can lead to significant inefficiencies. Information technology support functions have become increasingly involved in supporting the desktop environment for users. Many systems solutions have been developed and implemented in a manner that consumes significant information technology resources to maintain upgrades and manage platform (operating system) related compatibility.

SUMMARY OF THE INVENTION

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a block diagram of the top-level view of GBMS system architecture in accordance with the present invention;

FIG. 2 is a block diagram of the portal authentication and profile serving process in accordance with the present invention; FIG. 3 is a block diagram of the inter-user communication system in accordance with the present invention;

FIG. 4 is a block diagram of sub-system architecture in accordance with the present invention;

FIG. 5 is a block diagram of the GBMS server architecture in accordance with the present invention; FIG. 6 is a block diagram of the sub-system architecture and interconnectivity in accordance with the present invention;

FIG. 7 is a block diagram of the intelligence sub-system workflow in accordance with the present invention; FIG. 8 is a block diagram of an example interface design in accordance with the present invention;

FIG. 9 is a block diagram of the intelligence sub-system - unstructured intelligence item management in accordance with the present invention; FIG. 10 is a block diagram of the intelligence sub-system - imaging workflow in accordance with the present invention;

FIG. 11 is a block diagram of the inter-country system request process in accordance with the present invention;

FIG. 12 is a block diagram of the structured intelligence - desktop unification process in accordance with the present invention;

FIG. 13 is a block diagram of the custom data element process in accordance with the present invention;

FIG. 14 is a block diagram of the sub-system object integration - structured intelligence to planning sub-system process in accordance with the present invention; FIG. 15 is a block diagram of the business planning sub-system architecture in accordance with the present invention;

FIG. 16 is a block diagram of the business planning sub-system - planning and deployment hierarchy in accordance with the present invention;

FIG. 17 is a block diagram of the database to Microsoft^® Office object process in accordance with the present invention;

FIG. 18 is a block diagram of the hierarchy based planning administrator process in accordance with the present invention;

FIG. 19 is a block diagram of the quantitative modeling sub-system architecture in accordance with the present invention; FIG. 20 is a block diagram of the quantitative modeling analysis workflow in accordance with the present invention;

FIG. 21 is a block diagram of the quantitative modeling sub-system - hierarchical country summary structure in accordance with the present invention;

FIG. 22 is a block diagram of the quantitative modeling sub-system - matrix oriented international summary structure in accordance with the present invention;

FIG. 23 is a block diagram of the business development sub-system architecture in accordance with the present invention; FIG. 24 is a block diagram of the training sub-system architecture in accordance with the present invention;

FIG. 25 is a block diagram of the training sub-system - career training history in accordance with the present invention; FIG. 26 is a block diagram of the training sub-system - training resource addition in accordance with the present invention;

FIG. 27 is a block diagram of the CHE sub-system architecture in accordance with the present invention;

FIG. 28 is a block diagram of the global dynamic variable engine (GDNE) in accordance with the present invention;

FIG. 29 is a block diagram of the GBMS data distribution center in accordance with the present invention;

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention will now be described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout.

Referring to FIG. 1, a top-level view of a Global Brand Management System (GBMS) system architecture is illustrated. A user can navigate to any of a number of sub-systems after entering through a GBMS portal 1-1. A more detailed explanation of the GBMS portal authentication and profile serving is outlined with reference to FIG. 2. The GBMS initially provides six sub-systems ranging from an intelligence sub-system 1-2, business planning sub-system 1-4, quantitative modeling sub-system 1-5, business development sub-system 1-6, training sub-system 1-7, and a continuing health education (CHE) subsystem 1-9. The structural design and architecture of the system allows for other sub_r systems to be integrated, further adding to the system's functionality and scalability.

The GBMS also maintains integrated system administration 1-10 functionality throughout each sub-system as well as a robust internal communication system 1-11.

The six sub-systems designed within the GBMS offer an integrated workflow environment to improve efficiencies relating to the functional tasks related to managing brands / product on a global basis. The intelligence sub-system provides a robust environment that manages both structured information and unstructured information. The intelligence sub-system allows users to store any type of unstructured intelligence and their related electronic attachments. An intelligent meta tagging process ensures that the intelligence item can be retrieved through more advanced searches. Because the intelligence sub-system meta tagging process is connected to a unifying data variable library (that is, a Global Dynamic Variable Engine GDVE), users can execute their searches across other affiliates within their global organization. Current search and retrieval systems in this area rely primarily on the full- text searching of intelligence times and the electronic attachments and do not employ dynamic international variable functionality. As an example a product manager in the pharmaceutical industry wants to find out what intelligence is available in five other affiliates. The challenge is that the product in question has different names in three of the five countries. The GBMS functionality is able to create equivalency with the product names through the connection to the dynamic variable library (GDVE). The structured intelligence area of the intelligence sub-system provides a unification environment for a variety of data sources. In the current environment, product team members must connect to a variety, of intranet systems, networked CD-ROMs, paper reports and peer knowledge in order to consolidate an intelligence profile against an information area of reference. These areas of reference might deal with competitive products, customers, market segments, or competitive companies. The GBMS unifies these disparate data sources and provides additional information conversion utilities where necessary. This means that a user can enter the GBMS, select a competitive product and view a complete range of data and information through a single interface. This unification significantly improves the efficiency of the user to gain access to this critical planning information. This efficiency redirects much of the user effort towards interpretation of data to achieve business objectives instead of "collating" available data. The GBMS structured intelligence sub-system recognizes that the unification of the information is also meant to facilitate the subsequent workflows relating to the management of brands or products on a global basis. A significant portion of the information managed within the intelligence system is meant to shape the situational analysis of a variety of planning exercises. The GBMS contains strong integration with the business planning sub-system. This allows a user to select a piece of intelligence, interpret its meaning to the business and stage it directly into a dynamic table of contents structure within a strategic or business plan. Automating this process of information unification, interpretation and business plan integration dramatically improves the efficiency of business planning efforts within global brand management teams.

The business planning sub-system acts as dynamic environment to accept staged information from any of the other sub-systems. The management of the planning process in a collaborative database managed environment supports the efficient delivery of planning output to daily requirements through the flexible Microsoft^® Office automation. A variety of users can make changes in various areas of the planning workflow and maintain the flexibility to recompile the output files for the most recent version. It is important to recognize that the underlying content of the plan is database treated and therefore provides a much greater range of reporting capabilities. Current processes, which manage large parts of this process within collaborative environments as a word processing object lack the ability to execute detailed queries and create advanced reports. Within the GBMS, a user could generate a detailed report on strategies or tactics against a particular customer type across multiple countries because these objects reside in database managed tables. In the current systems this information would likely reside in an embedded table with a word processing document and would not therefore lend itself to this level of reporting. This increase in functionality supports the informational needs of product teams' critical decision-making process. The planning system also maintains real time integration with information in the quantitative modeling system. This ensures that the financial information within the planning system always reflects the most up to date statistics.

The quantitative modeling system provides an environment that offers flexibility to meet the unique parameters of each market, yet maintains some common data architecture:. This means that users can manage the unique aspects of a particular market, but still maintain horizontal analysis capabilities within a country or vertical analysis across countries. There is a great deal of interactivity and integration with the structured intelligence system. Historical data is passed from the intelligence sub-system, forecasted future data is generated in the modeling system and in turn the values from the default scenario are transferred back to the intelligence system. This allows users in the intelligence system to see historical and future data in the same view and stage both to the planning system. The quantitative modeling system also maintains the ability to communicate with other critical client systems to ensure real time connectivity of critical data, such as financial information contained in the user's enterprise financial system. The sub-system connectivity and strong pre-built analytical data models produce an efficient modeling environment that focuses users on appropriate input management and output evaluation and not on building the analytical methodology and architecture. The business development sub-system supports the sub-system structures between intelligence, planning and modeling with additional functionality specific to the business development process. As an example, the business development sub-system facilitates additional functionality within the modeling sub-system to deal with differing forms of deal structure. The training sub-system provides a comprehensive on-line training environment to deliver education or knowledge components, comprehension testing and feedback. The sub-system maintains a training desktop for each user which is managed through a variety of algorithm, management and personal mechanisms. One of the most beneficial aspects of this sub-systems is its ability to provide workflow relational support to the other sub- systems. This means that a user who is working within a particular interface location within another sub-system can get instant access to training programs that relate to the subject matter in the interface. Bringing the training content to the user in the context of their active workflow provides a more productive environment than forcing the user to find available resources through a separate search and retrieval system. The final sub-system involves the management of information relating to specific workflows in a particular customer segment. The continuing health education sub-system illustrates the functionality gained by integrating information about educational initiatives and opinion leading customers within a pharmaceutical market example.

The functionality and implementation of the sub-systems above are described in detail as follows.

Referring to FIG. 2, a flow diagram illustrating the functionality of the portal authentication and profile serving, available to the user is shown. The user connects to an intranet login page using a web browser and enters their user credentials 2-1. The request is sent to the web server. The web server reads the user's information and uses authentication objects to pass that information through to the user database 2-3. The user credentials are checked against the user database 2-3 and the designated application and security privileges are enabled 2-3 upon a match. The user profile is then compiled 2-4 and applied to the information presented in the user interface in the form of a custom user portal 2-5. The user then selects one of the sub-systems from the menu 2-6 and the subsystem is presented, in the context of their profile, in a new application window 2-7. Within the sub-system application the user requests information through a navigation system 2-8. Requests are sent to an application server and processed by a database query engine 2-9 which communicates with a GBMS database 2-10. Database request results are returned 2-11 to the database query engine where presentation is created based on the user profile 2-12 and the results are displayed in the application window of the user interface 2-13.

Referring to Fig. 3, a flow diagram of the inter-user communication system, illustrates how messaging items are issued and retrieved in the system. The user creates a messaging item from within the interface of the sub-system application 3-1. Recipients of the message are selected 3-2 based on an available list for the sender's user profile from the user database 3-3. The message is then created 3-4 and sent to the recipients messaging folder in the GBMS database 3-8. A notification is activated within the recipients' user profiles 3-5. When the recipient user logs into the application they are presented with the notification and can then open the message. A request for the message 3-6 is sent to the database query engine 3-7 which in turn requests the message from the database 3-8. The results 3-9 are returned to the query engine where they are formatted based on the user profile 3-10 and the results are displayed in the application window of the user interface 3- 11.

Referring to Fig. 4, a multi-tiered architecture of the sub-system applications is illustrated. A GBMS database server tier houses 4-1 database tables and stored procedures. A business logic is located in COM+ objects 4-2 on an application server tier. Sub-system code is compiled into applications, which access the COM+ objects, which in turn communicate the requests to the database and return the results to the applications 4-3. The sub-system applications are then presented in a dynamic Active Server Page (ASP) format using embedded objects (e.g. Active X, Java), as well as DHTML and Javascript for the client 4-4. When the client connects their web browser to the GBMS web interface, their system is checked for the appropriate browser version, settings and embedded objects. Required objects are downloaded on first connection if they are missing 4-5. The client is then able to display the interface and sub-system applications within the web browser 4-6 and not have to install client software locally. Updates to the interface and application sub-systems are automatically pushed out to the client through this mechanism.

Referring to Fig. 5, a physical embodiment of the data architecture in server topology is illustrated. Starting at a back end, a fourth tier comprises clustered enterprise class database servers 5-1. Database replication between the servers ensures data consistency and high availability. In the event of a database server failure, the cluster server automatically redirects requests to another cluster member. The business logic layer is abstracted to COM+ objects on application servers in the third tier 5-2. Component load balancing is employed to balance the application server load across application cluster members transparently to the client. In the event of an application server failure, the component load-balancing server automatically moves the affected COM+ objects to another cluster member. Compiled 32-bit sub-system applications are deployed to the client web interface via a load balanced "thin-client"/server farm in a second tier 5-3. In the case of a "thin-client"/server failure, users reauthenticate to another server and relaunch the sub-system application. If a client disconnects from their "thin-client'Vserver session, their session remains open awaiting their reconnection. Web servers in the first tier employ windows load balancing to maintain high availability to the client 5-4. Each web server handles a pre-set percentage of the load. If a web server fails, the load is dynamically redistributed among the remaining servers.

Referring to Fig. 6, (sub-system architecture and interconnectivity) a flow diagram, illustrates a high level view of sub-system components. FIG. 6 describes the si currently existing sub-systems: intelligence sub-system (IS) 6-1 [described more fully in FIG. 7- 14,28], business planning sub-system (BPS) 6-2 [described more fully in FIG. 15-18], quantitative modeling sub-system (QMS) 6-3 [described more fully in FIG. 19-22], business development sub-system (BDS) 6-4 [described more fully in FIG. 23], training sub-system (TS) 6-5 [described more fully in FIG. 24-26] and continuing health education sub-system (CHES) 6-6 [described more fully in FIG. 27]. The GBMS is built on a security architecture with a common portal with a robust data model which enables new sub-systems to be added and integrated with the existing sub-systems. The lines connecting elements of different sub-systems in FIG. 6 depict a sub-set of active integration relating to workflows and/or data transfer. This extensive integration between workflows in the individual sub-systems provides a more functional environment than in the existing workflow environments. Each of these integration synergies is described in the context of their sub-systems in other figures throughout the document. It is however worth exploring a specific example to illustrate the increase in functionality. When a user is editing the strategies / tactics / budgets portion of a planning exercise within the business planning sub-system 6-2 they are establishing a dynamic link to the investment manager of the quantitative modeling sub-system 6-3. This real-time connectivity ensures that the financial performance reports from the quantitative modeling sub-system 6-3 always represent the most relevant measures of performance. The GBMS contains strong internal integration, but is also enabled to communicate with other important client systems 6-7.

Referring to FIG. 7, the flow of information through the intelligence sub-system is illustrated. The intelligence sub-system is segmented into two different types of intelligence storage. A first area of information storage deals with unstructured intelligence storage and retrieval 7-1. Unstructured intelligence is primarily made up of ad hoc information produced through user generated entries 7-6. An intelligence item management area 7-2 allows users to enter intelligence items into the GBMS using an algorithm generator and intelligent meta-tags described with reference to FIG. 9. The unstructured intelligence item management area creates an "item" in the GBMS with a set of linked properties, which will maximize the efficiency of retrieval and data management. The sub-system is also equipped to manage electronic file attachments of any format and mobilize them to distributed users provided the necessary security authentications occur. The intelligence item management area is built with an open standard, which allows an information technology system administrator, user system administrator and disease class system administrator the ability to modify elements of the data structure and interface display based on user security [described more fully with reference to FIG. 9]. The unstructured intelligence sub-system area also supports robust searching 7-3 at either the inter-affiliate or intra-affiliate level. Searching 7-3 on an inter-affiliate or intra- affiliate level is supported by functionality delivered through a global dynamic variable engine 7-20 (GDVE) [described more fully with reference to FIG. 28]. The searches

n - created in the intelligence sub-system are also enabled for conversion to search "filters". These filters run the supporting database queries at a user-selected frequency against either the country (affiliate) or parent-level (global organization) server as outlined in FIG. 11. The unstructured intelligence system manages a wide range of content. The system is able to capture paper-based intelligence within intelligence items. An item storage process involving paper based information will generate an imaging work order 7-12 which will be fulfilled at an imaging workstation 7-13 that resides either at the customer or a third party service company and in turn stored within the system 7-2 via a GBMS imaging import utility 7-14 which matches the scanned document to the appropriate intelligence item [described more fully in FIG. 10].

The second area of the intelligence sub-system deals with structured intelligence. This structured intelligence 7-4 represents predictable information that is managed on a regular basis. The structured information can be segmented into areas of common interest and unified in order to improve the efficiencies at the user level. FIG. 7 depicts a possible segmentation of structured information based on a pharmaceutical example. Users would be able to view organized information relating to disease information 7-5, product and market information 7-16, customer information 7-17 and company information 7-18.

The country level structured intelligence storage is "segmented" based on therapeutic and disease classes with associated security access identified for all GBMS system users [described more fully in FIG. 8 in association with 8-5].

The disease profiling area 7-5 of the intelligence sub-system stores information relating to the disease selected by the user. An example disease information management configuration might include the following: incidence, prevalence, symptoms, drug treatments, non-drug treatments, onset, course, outcome, disease cost and web site URLs. The product profiling area 7-16 of the intelligence sub-system stores information relating to products. This information includes but is not limited to the following: product supply, indications, unit pricing, therapeutic pricing, utilization pricing, patents, positioning, SWOT (strengths, weaknesses, opportunities, threats), FABs (features, advantages, and benefits). The customer profiling area 7-17 of the intelligence sub-system stores information relating to customers. A sample customer information management configuration includes the following: summaries from market research, segmentation, salesforce activity, demographics, cross-referenced strategies from the Business Planning Sub-System described with reference to FIG. 15-18. A company profiling area 7-17 of the intelligence sub-system stores information relating to companies. The companies served up in a therapeutic or disease class are created through the data linkage between therapeutic or disease class technologies and their selling companies. This information includes but is not limited to the following: sales history, infrastructure, key management, product cross references, portfolio analysis, business development deals.

All areas of structured information storage within the pharmaceutical example in FIG. 7 (disease 7-4, product / market 7-16, customer 7-17 and company 7-18) are built with an open standard in mind which allows the information technology system administrator, user system administrator and disease class administrator the ability to modify elements of the data structure and interface display based on user security utilizing the custom data element functionality 7-22 [described more fully with reference to FIG. 13]. It is also important to recognize the role of the global dynamic variable engine 7-20 in unifying the large amount of disparate information against these reference segments. A more complete description of the unification process is described with reference to FIG. 12. Each of the content oriented elements of the intelligence sub-system is supported by search and reporting functionality 7-19.

The intelligence sub-system component areas gain content through three main processes. The first process involves user-generated entries 7-6. The second and third processes involve more automated support from the GBMS. The second content creation process involves scheduled data extraction 7-9 from databases and data warehouses outside of the GBMS. The GBMS data extraction utility 7-9 can extract data and format it for interface display via access to internal customer data warehouses 7-7 or to third party databases 7-8. The extraction utility imports the identified data and creates linkage to the internal global dynamic variable engine (GDVE described more fully with reference to FIG. 28). The third method involves more dynamic data that is served up within the intelligence sub-system interface. An example of dynamic data managed within the intelligence system relates to web content. An information profile generated from a publicly available web site could be dynamically linked within the product section of the intelligence sub-system. The dynamic data linking utility 7-11 manages the URL connection and data display or extraction from the resident web-site search engine. Dynamic database content 7-10 is dynamically loaded within the GBMS structured intelligence sub-system upon user request through the GBMS dynamic data linking utility 7-11. The data linking utility 7-11 imports the identified data and creates a link to the internal global dynamic variable engine (GDVE described more fully with reference to FIG. 28) on a dynamic basis that is set via either the information technology system administrator, user system administrator or disease class administrator. Certain types of data managed through the three types of data input may require additional processing in order to deliver the unified information the user requires. Supporting this need are specially designed data to information utilities 7-21. An example of a data to information utility within the product segment of the pharmaceutical industry involves "utilization pricing". Users are interested in different levels of competitive pricing. These include product unit pricing, therapeutic pricing and utilization pricing. Utilization pricing involves the average cost of a particular drug when it is actually used by patients. In order to calculate utilization pricing, the system combines information relating to unit availability, unit pricing and strength utilization by customer segment to calculate the weighted average cost of utilization. The existing data model presents the utilization pricing information unified against each available product. (This GBMS- process replaces the inefficient user driven process that is currently in use.)

As was outlined in FIG. 6, a significant level of data connectivity exists between the intelligence sub-system and the business planning sub-system 7-15. Elements of the disease information 7-5, product information 7-16, customer information 7-17, and company information 7-18 are integrated within the business planning interface control as illustrated in FIG. 14 - 15.

The intelligence sub-system also maintains a cross referencing feature within the intelligence algorithm generator 9-1 described with reference to FIG. 9. This cross- referencing allows intelligence items and their attachments to be embedded 7-23 in the disease information 7-5, product information 7-16, customer information 7-17, and company information 7-18 areas of the structured intelligence area 7-4.

Referring to Fig. 8, a sample interface design used within the system is illustrated. The interface is displayed within a web browser and represents the interface a user is presented with while accessing information on product availability within the product / market information (7-16 from FIG. 7) section of the structured intelligence system (6-1 in FIG. 6). The upper part of the interface 8-12 manages aspects relating to the user portal and sub-system navigation. Each icon 8-1 represents the available GBMS sub-systems (intelligence sub-system 6-1, business planning sub-system 6-2, quantitative modeling sub-system 6-3, business development sub-system 6-4, training sub-system 6-5 and continuing health education sub-system 6-6). Also, the user's home page may be activated by selecting their name field 8-2. These features are available at all times. Selecting a sub-system launches a new web session and loads the appropriate sub-system interface. Each sub-system is designed with both menu drop-down functionality 8-3 and short cut icons 8-4 to enhance functionality. The left hand side of the interface houses the workflow navigation controls (8-5,8-6,8-7, 8-8). The combination control boxes on 8-5 represent a two tiered navigation system example from the pharmaceutical industry. The upper combination control box allows the user to select a therapeutic area and the lower combination box selects a disease relating to the therapeutic area (for example, therapeutic area - central nervous system, disease - depression). The selection of the disease area loads all the structured information relating to disease, product, customer and company within the interface. The workflow navigation consists of workflow tiles 8-5 that navigate the user to specific workflow related objects 8-7. FIG. 8 displays the user located at the product availability "workflow node" 8-8 within the product navigation. It is important to note that many workflow tiles require custom controls to display and unify the underlying information to support the "workflow nodes". The product control 8-6 allows the therapeutic administrator to build market segments and position the available products within the hierarchy. This control also displays integration status with the business planning system when the intelligence system is running in "plan mode". When a workflow node is selected 8-8, the associated interface functionality is displayed in the core interface pane 8-10. These panes incorporate a variety of objects: free text, list views, combo selections, images, graph objects. In the particular example shown here the structured intelligence system is running in "plan mode", which enables a user interpretation pane 8-11 at the bottom of the interface. The interpretations made here are connected to the active planning object that the user has connected to which is displayed in the navigation status bar 8-9.

Referring to Fig. 9, intelligence item management algorithm, illustrates the ability of the GBMS to apply a predefined algorithm for intelligence entry based on input to the intelligence algorithm generator 9-1. The user will be prompted through the intelligence algorithm generator 9-1 to provide answers to a set of defined questions. These questions will determine which elements of the intelligence item "tagging" process are required and which order will maximize user efficiency. The GBMS will provide the ability to create newly defined algorithms through system administrator functionality.

The intelligence item "tagging" process 9-2 gives the intelligence item the properties to enable the distributed searching and report generation capabilities associated with 7-3 in FIG. 7. An example of a potential "tagging" process for intelligence items within the pharmaceutical industry is segmented into four workflows. The intelligence item is first enabled with content "tags" 9-3 which includes (but is not limited to the following): title, description, entry date and attachments 9-7. The attachments may represent any form of electronic file content.

The second stage in the "tagging" workflow involves giving the intelligence item a frame of reference 9-4, which includes (but is not limited to the following): technology name, technology class, company and disease. The technology name can be further subdivided into scientific and brand names which are managed in a linked manner. This frame of reference is differentiated from the third stage of properties 9-5, since it embodies the main "tag" to which most pharmaceutical intelligence items would be stored.

The third stage in the "tagging" workflow involves giving the intelligence item properties 9-5, which includes (but is not limited to the following): source, topic, keywords and geography. The intelligence item properties 9-5 support the ability to create more advanced search queries and reporting strings to be executed against either the country GBMS database 11-3 in FIG. 11 or 11-7 in FIG. 11. An example would be a search string that involved: Technology Name: pemantine

Topic: safety and adverse events Source: promotional material Geography: US, UK, Canada, Australia The final stage in the "tagging" workflow involves giving the intelligence item security and distribution 9-6, which includes (but is not limited to the following): item security, user security level, visibility, security groups, geographical security and distribution list. These properties enable the intelligence sub-system to set the security parameters for the GBMS database and ensure that the items are treated with a common security framework across the entire distributed system.

Once the four-stage process is completed, the intelligence item is stored in the local country GBMS database 9-8. It is however important to remember that the user is not required to complete all available meta-tags. The intelligence item information in the local country GBMS database is also communicated to the parent GBMS 9-9 which manages inter-country requests described in with reference to FIG. 11. This communication may take many forms such as, replication, synchronization or indexing to name a few, depending on the specific requirements of the customer. This communication process will then be implemented based on the choice and functionality of the chosen enterprise-class database platform. The electronic attachment that may accompany some intelligence entries may be excluded from the parent communication process based on the attachment properties. The GBMS system settings may, as an example, recognize that any portable document format (PDF) objects over 1.0 Mb will reside solely on the local country GBMS database. This process is meant to minimize the impact of data transfer on company wide bandwidth. FIG. 11 describes how attachments stored in this manner may be mobilized under a search or report request. The parent GBMS database 9-9 houses the intelligence item communication from all of the distributed country GBMS databases.

Referring to Fig. 10, the stepwise process employed to scan paper-based materials and integrate them within the GBMS database is illustrated. An imaging work order 10-1 is generated through the intelligence item management. The interface prompts the user on the characteristics of the output. The GBMS selects a preloaded imaging workflow 10-2 based on the user input contained in the imaging work order 10-1. The GBMS imaging work order also determines the type of imaging workstation that will execute the capture. These include options such as a small or large format flatbed, or a slow versus fast throughput automatic document fed scanning workstation. The workstation captures 10-3 the document and the resulting image file is indexed 10-4. The GBMS image import utility 10-5 locates indexed image files ready for integration on a scheduled basis and links them within the GBMS customer database to the original intelligence entry within the unstructured intelligence sub-system 10-6. Referring to Fig. 11, inter-country system request process, illustrates the method in which information requests are processed from one country affiliate database to another. A connected user in country "A" 11-1 creates a request for information 11-2 that searches against their country database 11-3. If the search is for information from the country "A" database then the results are returned to the user 11-4. If the request is for information from another country database then the request is passed to the foreign request cache 11-5. If the requested information is located in the cache it is passed back to the user. If not then the request is passed on to the global equivalency manager 11-6, which utilizes the variable library managed by the global dynamic variable engine (GDNE described more fully in FIG. 28), where it acquires the additional properties required for international searching (e.g. foreign product names). With equivalency established, the search runs against the index database information within the parent GBMS database 11-7 which maintains critical information relevant to the foreign country databases 11-8. If the user has appropriate international security privileges in the Parent database then the result 11-9 is returned to the foreign request cache 11-5 and back to the user. If a foreign request result contains attachments then the user is able to schedule the delivery of the attachments 11-10 to best accommodate the customers intranet traffic patterns. Attachments are cached in the foreign request cache for quick retrieval on subsequent searches.

Referring to Fig. 12, the integration of diverse data sources to a unified desktop is illustrated. As outlined in FIG. 7, structured intelligence can enter the intelligence system through user-generated object 12-1, internal data warehouse objects 12-2 and third party database objects 12-3. In this particular example each one of these sources has organized their objects referenced against products. Unfortunately this approach causes users to have to access many systems to consolidate information about a reference product for a naturally occurring workflow (business review, competitive review, strategic plan...). By utilizing a global dynamic variable engine 12-4 (more fully described in with reference to FIG. 28), the GBMS is able to reorganize the incoming information and display the different sources of information subordinate to a product selection hierarchy that is actively managed by a market administrator 12-5 through the dynamic heirearchy control 12-6. The dashed lines in FIG. 12 demonstrate the ability to unify disparate information sources relating to "Product 1" within the structured intelligence sub-system. Referring to Fig. 13, illustrates a process for adding new data elements to the GBMS sub-systems. A specific example within the structured intelligence 7-4 is described to illustrate the custom data element (CDE) process.

The GBMS provides a library of available objects for initial configuration within the specific customer deployment. It is however inevitable that the customer will require the addition of new data elements to support their required workflows. The eight step process outlined in FIG. 13 allows administrator within a GBMS deployment to add new data elements with all the end functionality and integration of "out of the box" data elements.

The administrator is taken through the eight-step process in a "wizard"- like control. The first step involves the selection of the object type (free form text, flexgrid, OLAP graphing object...) and establishing its specifications, which in turn creates the necessary database tables 13-1 to enable the object. The administrator locates the workflow node 13-2 associated with the new data element within the workflow navigation (8-7 in FIG. 8). The administrator creates the core pane interface 13-3 associated with the new data element. If this were a list view item than the administrator would instruct the interface creation process associated with a list view object. These attributes includes column/row style, format, sorting features, preview mode. The administrator creates the sub-system integration 13-4. A new item relating to products pointed for inclusion within the existing and future products section of competitive profiling within the long-range and one year business planning templates. Any selection of the new data element while in planning mode would enable the integration within the appropriate table of contents (TOC) location (more fully described with reference to FIG. 14, 15). The administrator selects the appropriate Microsoft^® Office automation 13-5 template to ensure that compiling functionality within the sub-systems delivers an appropriate embedded full function object. This means that a graph that is created in the intelligence system will be automated as a Microsoft^® Graph object embedded within Microsoft^® Word or Microsoft^® PowerPoint and retains full functionality when in edit mode. The administrator has the ability to alter the properties of template objects if they do not meet the specific requirements of the new data element. The administrator instructs the reporting engine 13-6 on the relevant selections to create a report associated with the object. This will also include parameters for the report display. The administrator creates relationships to key variables that manage the relationship of training resources 13-7 within a training subsystem to the GBMS interface location. The final step in the administrator process involves setting the portal security parameters 13-8 around users and user groups. These settings include read, write, edit and save privileges.

It is important to recognize that the eight step custom data element process is used for modifying elements of the GBMS database 13-9 and the GBMS interface 13-10 in order to achieve full functionality.

Referring to Fig. 14, one of the strongest sub-system integration processes is illustrated. Structured information 14-3 managed within the intelligence system is largely meant to unify the management of important information in order to enable critical workflows within the customer. One of the most critical workflows managed at the customer level involves business planning. When a user wishes to integrate structured intelligence within a business planning object, they select the desired planning template 14-1 from a list derived by their security profile. Once the plan is activated the intelligence system adjusts to "planning mode" 14-2. This modifies the interface through additional functionality built into the workflow controls. This additional functionality supports object tracking and integration within the active plan.

The user has the opportunity to add an intelligence object to the active plan through a three-step process. The first step is to configure the selected object 14-4. This feature is particularly relevant if it involves information with configuration functionality in the pane interface. If the selected object was therapeutic pricing for a particular product, then the user would have the option to select pricing relevant to a particular payer, a specific disease and specific time frame. With a specific object created, the user could then integrate the intelligence object 14-5 to the active plan. The final stage of the process involves the user interpreting the meaning of the intelligence object 14-6 to provide context to the active plan.

Carrying forward on the above example, items that were selected relating to Product 1 (a product in the market) for integration within the product information area 14-10 of structured information 14-3 within the intelligence sub-system would be integrated under the table of contents heading related to existing competitors 14-7. Selecting Product 1 within the active TOC within the business planning sub-system would provide a detailed object integration status 14-8 and would support the dynamic ability to compile supported Microsoft^® office objects 14-9. Referring to Fig. 15, architecture and workflow involved in the creation of business plans are illustrated. In a pharmaceutical example they are created within a disease class The business planning sub-system involves a five-step process. The first process involves data integration 15-18 from a variety of sources. User generated entries 15-1 comprise a portion of the information integrated within the business planning interface control which manages the active plan table of contents 15-19. Quantitative market data supporting the market assessment within the plan can be accessed directly from the intelligence subsystem 15-5 or through the GBMS data extraction utility 15-2 which accesses either an internal customer data warehouse 15-4 or third party databases 15-3. A large part of the situational analysis needs (both external and internal) within the plan is imported from the intelligence sub-system 15-5. An overview of this process was described with reference to FIG. 14. Data relating to the financial analysis of the disease class will be integrated with , the quantitative modeling system 15-6.

The second step in the business planning process involves the management of the active plan table of contents 15-19. The Business Planning Sub-system interface table of contents is engineered to provide maximum flexibility while maintaining the required underlying data model integrity to enable advanced reporting. FIG. 15 depicts a TOC structure that includes, disease assessment, market assessment, customer assessment, competitive assessment, internal assessment, opportunities/threats, goals/objectives, strategies/tactics/budgets and financial summaries. This represents an example table of contents for either a long-range of one-year business plan within the pharmaceutical market. The template driving the initial TOC loaded can be modified through a hierarchy administrator structure that is described with reference to FIG. 18. The TOC allows qualified users to modify the TOC structure by adding new content, headings and integrated objects (through the custom data element process as described with reference to FIG. 13).

The third process involves the business integration process 15-20. Each corresponding TOC element has its unique integration process. The disease assessment integration process 15-7 allows the user to select from a set of predefined disease related write-ups produced either internally or on a syndicated basis. These editable word processing objects include topics such as epidemiology, local prevalence, diagnosis, onset/course/outcome, treatment, research efforts. The market assessment process 15-8 involves the import of quantitative market data from other sources. The user selects from a predefined list of market assessments and authors interpretations of the data that is presented. The customer 15-9, competitive 15-10 and internal 15-11 assessments provide a list view to users identifying the data integration from the structured intelligence subsystem 15-5. It is, however, possible to add summary table functionality directly within the business planning sub-system TOC which drills into the available data model from the structured intelligence system 15-5.

A proactive portion of the business planning exercise, which involves the identification of opportunities/ threats and their conversion to goals/objectives 15-12 as well as the articulation of strategies/tactics and budgets 15-13, is managed directly in the planning system. In order to support the facilitation that is required within the planning team, brainstorming controls are integrated with "drag and drop" functionality to the goals strategies and tactics. The tactical elements of the GBMS business planning exercise also provide valuable data links into other systems within the customer. As an example, integrating the accounting expense codes within the tactical budgeting exercise allows for the creation of custom reporting within the GBMS that is synchronized with the existing expense breakdowns. A more detailed description of processes 15-12 and 15-13 is contained with reference to FIG. 16. The financial summaries integration process 15-14 provides a menu type list to users to specify the level of data integration and formatting for information derived from the quantitative modeling sub-system 15-6. The fourth step in the process involves the management of the business planning subsystem flexible Microsoft^® Office automation 15-21. The GBMS operates on a database to Microsoft^® Office object environment (described more fully with reference to FIG. 17), which maintains all editing processes within the GBMS interface. This step in the process allows the business planning sub-system users with appropriate privileges to generate Microsoft^® office objects (primarily Word and PowerPoint). These objects can be generated at any level of the TOC and all output files are stored within the system and referenced within the active business plan.

Once the business plan editing process is complete and a final approved plan 15-15 is ready it can be stored within the unstructured intelligence sub-system 15-16 for efficient retrieval (storage procedure is described more fully with reference to FIG. 7).

Referring to Fig. 16, a flow of information from the user input 16-1 into the proactive planning phase of the business plan. The user, through either group interaction or direct feedback, determines the resulting strategies 16-3 and tactics 16-4 to achieve the brand objectives 16-2 within the planning horizon. The user is guided through a process to input these elements. The tactical information includes tactics 16-4, measures, responsibilities, customer 16-5, investment (budget), accounting code, currency, and supplier 16-6. These pieces of information are all linked so that the tactical elements of the plan can be run through advanced sorting features 16-7 and custom reporting 16-8. This allows the user to assess the effectiveness of their planning from a number of perspectives. The user can produce custom reports that evaluate the effectiveness of the tactics and strategies from the standpoint of customer coverage, objectives coverage and promotional mix. It is also possible to enable the identified tactic to trigger a workflow management process 16-9, a project collaboration 16-10 or a customer execution or campaign 16-11. Enabling this level of post-planning functionality allows the deployment aspects of the plan to be managed within the business planning sub-system.

Referring to Fig. 17, the process which supports the office automation of each element within the system is illustrated. GBMS operates on a philosophy of database treating all objects managed within the system 17-1 and storing them within the GBMS database 17- 2. Each of these objects is assigned a set of office automation parameters 17-3 that ensures the office compile process executes in an efficient manner. The office objects can take many formats 17-4 and as a result require a wide range of parameters 17-3 to be managed. The automation parameters relating to each data element are stored within the database to maintain flexibility. These automation parameters not only control functions within core applications 17-5 such as word processing, but must also manage embedded controls 17-6 used to create more complex objects. An example of the embedded control 17-6 automation would involve structured intelligence that contains quantitative table data for presentation in a graph format. Graphs are created and embedded within most word processing and presentation software. As such, the GBMS must automate the parameterβ within the embedded graphing control in order to create a fully functional object that can be edited by the user after the compile process is complete. In addition to the automation parameters associated with each GBMS data element, there are automation templates 17-7 to deliver compound workflow functionality. An example of this is the "group export" feature within the structured intelligence sub-system. A user can create a word processing object involving structured intelligence elements according to templates constructed by the administrators. A "default existing competitor" template manages not only the individual elements to be included, but also advanced word processing features (automated table of contents, captioning, indexing).

Requests to create complex Microsoft^® Office automation objects (word processing, presentation, spread sheet objects) are routed to office automation application server components 17-8. The middle tier components operate on load balanced server clusters able to deliver the necessary processing power to create word processing files greater than 200 pages with more than 100 embedded objects. The application server components complete their task in the background freeing the user to move about the interface to complete other tasks or workflows. The completed Microsoft^® Office file is stored within the GBMS system 17-9 in reference to the requested operation. The GBMS system also provides the ability to export the completed office file 17-10 to the user's desktop provided they have the appropriate security clearance.

Referring to Fig. 18, the ability to apply multi-level administrator control to business planning templates and active plans in a flow diagram illustrated. The business planning sub-system is designed to allow for administration control at the global planning process administrator 18-1, country planning process administrator 18-2, and the active plan "owner" administrator 18-3. A global planning administrator can design a core template 18-4 of the long range planning process based on the structure and process the company would like to implement on a global basis. The country planning process administrator can modify the country planning template 18-6 based on country specific content and processes 18-5. The changes may be driven by a fundamental difference in the market, such as a distinct reimbursement system or differences in information that is available in each country. The resulting country planning table of contents (TOC) template 18-6 can be further modified by the plan "owner" administrator. This ability to incorporate disease or product specific content / process 18-7 into the active plan TOC18-8 ensures that enough flexibility is maintained at the front-line to successfully complete complex planning exercises.

Referring to Fig. 19, a flow diagram illustrates the workflow supporting the financial analysis of a product within its defined market. The quantitative modeling sub-system includes market set-up wizard 19-7, input assumptions manager 19-8, investment manager 19-9, scenario / forecasting / simulation manager 19-10, deal parameter manager 19-11, consolidated analyzer 19-12 and output reporting 19-13.

The market set-up wizard 13-7 plays an important role by moving the user through a set of sequential questions which guide the GBMS toward the appropriate table and functionality structure to support the users needs. A more complete description of the modeling structural flow is contained with reference to FIG.20.

The input assumption manager 19-8 draws historical data necessary to populate the model table structure. This table structure may be integrated directly with the quantitative data housed in the intelligence sub-system 19-17 or may be drawn from an internal customer data warehouse 19-2 or a third party database 19-3 using the GBMS data extraction utility 19-4.

The investment manager tracks expenses that the product or marketing team intends on investing in the product's growth. The information to support the "baseline" case is imported from the tactical budget (16-6 in FIG. 16) information in the business planning sub-system 19-5.

With a market structure set in place 19-7, historical input assumptions populated 19-8 and baseline investment data 19-9, the user is ready to begin the process of evaluation and optimization. The scenario/forecasting/simulation manager 19-10 integrates advanced capabilities from a third party analysis engine 19-14. In cases where the financial analysis is related to a business development opportunity under consideration or is a business development product in the implementation phase, the deal parameter manager 19-11 layers on a set of deal assumptions. Much of the information driving the deal parameter structure is imported from the business development sub-system. The consolidated analyzer 19-12 now allows the user to create new ingredient mixes and run a consolidated analysis. The resulting data is stored within the GBMS and can be called up into more hierarchical financial analysis involving divisions and affiliates as referenced in FIG. 21.

The output reporting 19-13 for the quantitative modeling system provides important functionality within the entire GBMS. These output reports depict the sales, expenses and profitability of the customers most valuable assets, their products. The output reports corresponding to the default forecasts are uploaded into the business planning sub-system into the financial summaries (shown in FIG. 15). The output reports corresponding to the default forecasts are also exported through a GBMS financial utility 19-15 for integration within the companies financial system 19-16. This GBMS financial utility contains data connectors that facilitate the communication of the financial data to a variety of commercially available enterprise class financial systems.

Referring to Fig. 20, a flow diagram illustrates the workflow that occurs between market creation and financial outputs. The entire process flows through either one or two passes depending on whether there is a need to measure business develop related impact. .

In a case without deal related impact, the user defines the modeling infrastructure through a market set-up manager 20-1. The market set-up manager 20-1 walks the user through a series of questions which determines the core data to be managed and the data model structure required to model the market. The market set-up manager 20-1 contains a robust decision tree that allows the GBMS to create a variety of advanced data structures. Within a pharmaceutical market example, the market set-up manager process includes baseline units for market definition (prescriptions, days of therapy, patient epidemiology), time periods for historical analysis, data source, levels of market definition hierarchy (that is n- tiered factoring for baseline measures), and reimbursement access.

The GBMS then sets up a market structure and underlying tables 20-2 within the data model to support the brand analysis in the corresponding disease class. Input "ingredients" 20-3 for a profit and loss analysis are presented to the user with the corresponding forecast functionality of the third party forecasting engine. The user has the ability to create a number of scenarios of each input ingredient. The user then creates a modeling "run" or save by granting it a name and by combining all the required input ingredients in a forecasting mix 20-4. A profit and loss analyzer 20-5 creates the supporting profitability tables and displays the resulting summary. The profit and loss structure 20-5 and presentation follows templates that are controlled within the administrator console for the quantitative modeling sub-system. An output reporting 20-6 unit provides for a number of segmented views of the existing profit and loss (P&L) analyses. Comparisons of multiple P&L analyses are also supported to allow the user to evaluate relative profitability under different ingredient mixes.

If the analysis requires a deal related component to the model, a similar algorithm is layered on top of the baseline analysis. A deal set-up wizard 20-7 sets up the deal structure and tables 20-8. The deal ingredients 20-9 include clinical, sales or regulatory milestone payments, royalties, minimum purchase quantities, development expenses, and clinical sharing expenses. The user creates a deal mix 20-10, creates consolidated P&Ls 20-11 and can generate a variety of deal related output reports 20-12.

Referring to Fig. 21, a block diagram illustrates how the various models within a single country GBMS flow together. The elemental level is a brand / product model 21-1. Multiple brand models within a therapeutic division aggregate to form a therapeutic or divisional model 21-2. That is the structure is dynamically linked and changes to the default forecasts at the brand level will cascade changes to the upper hierarchies. The therapeutic or divisional models 21-2 also feed the affiliate level model 21-3. The achievement of this modeling integration comes from a disciplined management of the core data elements within the modeling process. Three different brands may be operating on three different market definition structures. One product may involve a days of therapy (DOTs) approach given the different DOTs per prescription within the leading competitors. The second product may utilize a traditional prescription approach with a disease treatment factor applied to isolate use of competitor product usage outside of the reference disease(s). The third product relies on a patient epidemiology approach with three levels of factors to move the market definition from general patient incidence to a specific segment of the patient population that is appropriate the user's product. Despite the differences in market management strategies, the underlying data model manages certain critical variables in a common architecture facilitating the linkage process described above.

Referring to Fig. 22, a block diagram illustrates the relationships between the various models within the distributed server aspects of the quantitative modeling system. The GBMS maintains the ability to consolidate data horizontally at the country level 22-1, the region level 22-2, or vertically at the affiliate level 22-3, the global business unit 22-4 or the global product team 22-5. The dynamic links present in the system ensure that any changes made by users with security privileges are cascaded through the financial "matrix".

Referring to Fig. 23, a flow diagram illustrates the workflow and related data transfer ' that occurs within the business development sub-system. The business development sub- system contains five function elements. The first element is a business development (BD) status manager 22-1, which manages summaries of the BD deals that have work activity or status. This functional element provides data summaries to the business planning subsystem 23-2. The second element is a BD contact manager 23-3, which collects and manages person related contact data specific in content to the BD process. The data collected in this element may either be managed independently or may be integrated with a user's existing customer relationship management system (CRM) 23-4. The third element involves the management of an active BD deal desktop. Quantitative market data may be drawn into the BD desktop 23-5 from either an internal customer data warehouse 23-6 or a third party database 23-7 using the GBMS data extraction utility 23-8. The BD desktop also offers data integration with the intelligence sub-system 23-13. The next element involves performance reporting 23-9. The final element of the sub-system involves the financial analysis 23-11 and offers data integration with the customer's financial system 23-10. This is imported from the quantitative modeling system 23-12, which utilizes the deal related functionality described in FIG. 20.

Referring to Fig. 24, a flow diagram illustrates the major elements of the training subsystem including a detailed breakdown of a training publisher 24-15.

The training sub-system includes seven main elements. The first element for review is the training publisher 24-15. The training publisher 24-15 is made up of five stages, which create the training or educational resource in a Standard that will seamlessly integrate into a publisher administration control 24-10. The first stage of the educational publishing process involves creating the properties for indexing the resource within the system through the program property utility 24-1. These properties include program objectives, program author overview, program workflow, knowledge element table of contents, difficulty rating. The second stage, knowledge element management 24-2 supports the author in creating the core knowledge resources to one of a number of defined standards. The knowledge element management 24-2 is designed to manage the creation of the core object, whether it is a rich function portable document format (PDF), html object, flash object or other web based object. The knowledge element management 24-2 also plays a critical role in managing the supporting multimedia attachments (that is - streaming audio or video) so that they integrate properly with the server structure within the client server architecture. The next stage provides the author with a robust test generator 24-3. This not only supports the author in creating the testing questions, but also sets the standards and criteria for the training sub-system to administer the testing. The training publisher 24-15 also supports a robust feedback and evaluation process 24-4 linked to each training resource or object. The entire process of building and "publishing" a training resource is facilitated through a publishing status manager 24-5. The publishing status manager 24-5 moves the training resource through the publishing process as the author submits the finished "unapproved" resource to the publisher administration control 24-10. The training sub-system administrator can stage the addition of the resource to the GBMS once it has been validated and tested. The client / administrator components of the training sub-system are made up of a training resource utility 24-6, relational workflow support 24-7, non-GBMS system communication 24-8, training algorithm manager 24-9, publisher administration control 24-10 and a searching and reporting 24-11 function.

The training resource utility 24-7 manages and organizes the available training resources. This includes the ability to drill within the program library within the local GBMS and any distributed GBMS server clusters that have enabled the training program sharing feature. The training resource utility 24-7 also manages the active desktop for the user which includes training resources or programs that have been added under a variety of conditions (more fully described with reference to FIG.26). There is a fundamental need within the educational process to bring available education as close to the user's natural workflows as possible. The relational workflow support manager 24-6 creates relational links between interface location within any of the connected GBMS sub-systems (intelligence sub-system 24-12, business planning subsystem 24-13, quantitative modeling sub-system 24-14, business development sub-system 24-15 and continuing health education sub-system 24-16) and the training resources that supports the subject matter on the interface location. If, for example, the user were viewing information about a competitive product's patents within the structured information in the intelligence sub-system 24-12 (product / market information 7-16 in Fig. 7) they might realize that they do not understand the difference between a product, process and method of use patent. By dragging the patent icon on the workflow navigation (8-7 in FIG. 8) to the training sub-system icon (8-1 in FIG. 8), the user is displayed a dialog box containing a list of the available training programs on patents^'. Creating this relationship between interface content and available training programs is facilitated through the custom data element process FIG. 13, which defines training resource relate 13-7 as an integral part of the process.

The non-GBMS system communication 24-8 provides the necessary data connectors to establish a two-way communication with other client systems _λ (that is sales reporting system 24-17 or human resources system 24-18). The training resource utility 24-6 has the ability to present access to the user as well as their direct reports. Information about reporting structure is dynamically connected with the reporting structure stored within the human resources system 24-18. The fransactional training history of each user (described more fully in with reference to FIG. 25) is in turn communicated to the human resources system 24-18, demonstrating the two-way flow of information.

The training algorithm manager 24-9 is designed to support the deployment of training algorithms relating to the user's role within the organization. These algorithms are user group membership oriented and are created by the training administrators. This system involves a complex decision rules process to manage the impact of joint group access. A user as an example might belong to a group relating to their specific job function (marketing manager), but also belong to a group relating to their management level (senior management team) in the company. The system will be capable of prioritizing and reorganizing the user training schedule based on their available time allocation for training related activities. The publisher administrator control 24-10 manages the addition and modification of training resources to the system. In addition to staging related activities, the administrator control also offers campaign related features. The administrator can create system or e- mail driven campaigns that can be triggered by a number of defined events (ie - 30 days post program completion). Output reporting 24-11 from the training sub-system can also be exported to the human resources database 24-18. A number of specific features (such as feedback logs and evaluation reports) have been added to the training sub-system in order to provide consolidated reporting to the authors / publishers 24-15 of the training resources themselves. The reporting functionality delivers three levels of rich reporting: user , management and administrator.

Referring to Fig. 25, a block diagram illustrates the ability of system to track a user's career training history 25-1 over time. Because the training sub-system maintains a link to human resource data, a history of the user's job positions 25-2 within various divisions is maintained as well as the training algorithms associated with those positions and their completed resources.

Referring to Fig. 26, a block diagram illustrates the ability to add training resources to the training profile of a user. Resources may be presented to the user as either required 26-4 and are associated with a scheduled completion date or recommended 26-5 in the current period. Resources can be added to a user's profile through one of three methodologies. The first involves the resource being loaded on the user's training desktop automatically based on their membership in a "group" (such as product managers with 0-6 months experience) and the application of a training algorithm 26-1. The second methodology involves managers 26-2 being able to place training resources within the training desktops of their direct reporting users. The final addition methodology involves the self-directed 26-3 addition of a training resource to the user's own training desktop.

Referring to Fig. 27, a flow diagram illustrates the workflow supported by the continuing health education (CHE) sub-system. The CHE sub-system is made up of four functional elements. The first element of the sub-system supports users in the process of program development 27-1. The second element manages the planning execution and follow-up of CHE programs 27-2 and maintains a dynamic link with the customers physician activity database 27-3 (PAD), electronic territory management system (ETM) or customer relationship management system (CRM) or pharmaceutical relationship management system (PRM). The third element manages extensive opinion leader profiling 27-4 information while maintaining dynamic links to the customer's PAD, ETM, CRM or PRM 27-3. The final element involves performance reporting 27-5 on programs, representatives and opinion leaders with dynamic links to the customer's PAD, ETM, CRM or PRM 27-3 as well as the business planning sub-system 27-6.

Referring to Fig. 28, a flow diagram illustrates an important a critical underlying feature of the GBMS data management strategy. Selected variables contained in the

GBMS must establish inter-country equivalency in order to support inter-country queries relating to searches and reports. The challenge lies in the significant amount of effort required to maintain this GDNE variable library in relation to the changing world around the customers. The GDVE library 28-1 is managed by a team of content experts outside of the customer GBMS 28-2 deployments. The GDVE library is replicated 28-3 to the customers' GBMS on a scheduled basis. This data strategy coordinates effort and allows for seamless integration across all GBMS customers. Within the GDVE library 28-1, data equivalences or links 28-4 are maintained by the GDVE administrators 28-6. It is important establish these variable equivalencies to support the global reporting environment and the local data unification described more fully with reference to FIG. 7. As an example the use of data equivalence enhances reporting of global competitive product information. Drugs around the world are identified through their brand name and generic name. These names do however differ between countries. An antidepressant having a brand name Promox in the United States may be called Promoxen in the United Kingdom. Without the GDVE equivalence functionality, no reporting equivalency could be derived between these two markets. The need for a dynamic structure is demonstrated when if two months later a company in the United Kingdom launches the same drug molecule under a co-promotion agreement under the brand name Paloft.

The customers will support the optimization of the GDVE library 28-1 by providing feedback 28-5 about changes in the market dynamics. This feedback will be received by GDVE administration, validated and integrated 28-6 within the GDVE library 28-1.

A sample table 28-7 illustrates the data management that occurs within the GDVE. Generic product name (GN), brand product name (BN) are managed globally through a MP-id (M-Mindworks, P-Product) system allowing each GBMS customer in the world to be synchronized against pharmaceutical products. The same strategy could be applied to companies with MC-id (M-Mindworks C-Company) as well as many other mission critical variables. , The GDVE library also delivers a secondary advantage to GBMS customers. Third party data 28-8 that references ("keyed") variables managed by GDVE can be served up to GBMS customers within their sub-system interfaces through a simple integration process. The required data is removed using the GBMS data extraction utility 28-9 and the data is restructured based on a GDVE library processing utility 28-10. The data has been extracted and restructured to be served up on the GBMS desktop 28-11 of any subscribing customer within the sub-system interface where the data creates value. A database on drugs in development could be synchronized or unified with the product / market information (7-16 in FIG. 7) in order to increase the efficiency of information serving to the user.

By maintaining the GDVE, the database entries contained within customer GBMS' can be optimized through a set of managed database "commands". If a change to the GDVE has been authenticated and it requires action, the GDVE administration writes /generates a GBMS database management script 28-12 which is routed to the customer system administrator for authentication 28-13 and execution. This command will now execute data management changes to the underlying enterprise-class database storing the GBMS data. An example to illustrate this principle could focus on the merger of two pharmaceutical companies. ABC Pharma and DEF Pharma have thousands of references within customer GBMS'. The companies undergo a merger and rename the new entity XYZ Pharma. There is a great risk to create data "orphaning" against the old company names. GDVE administrators would generate a GBMS database management script to add the XYZ Pharma "tag" to all entries previously having either ABC Pharma or DEF Pharma. The command would also eliminate ABC Pharma and DEF Pharma from all list views so that no more entries are made against the old company names. This consolidated approach will deliver a more optimized data management approach than the majority of enterprise class systems that rely on customer data management responsibility.

Referring to Fig. 29, a block diagram illustrates the process for distributing data to GBMS customers. Product data is received from third party industry data providers 29-1 via the data collection application servers 29-2. Data is processed into the database where each referenced variable for import is assigned a unique global standard in the GDVE library (see FIG. 28) 29-3. Product data updates can be accessed by the GBMS customers through the secure web portal 23-4 at the data distribution center. Customers incorporate the product data updates into their GBMS databases 29-5.

The descriptions of the preferred embodiments provided above have referenced application to the pharmaceutical industry to better illustrate sub-system functionality. The described invention can however be applied any number of other industries. >

If as an example the frame of reference were computer manufacturing, many of the underlying administration tools would support the conversion. In the intelligence system the therapeutic and disease class database segmentation hierarchy could be replaced with a hierarchy based on business vs personal or server vs desktop vs laptops. The underlying intelligence item algorithm with the exception of disease references would adequately support computer manufacturers. The GBMS would just need to be loaded with "tree- view" lists that support the industry in focus. The "topic" list would reflect topics associated with the global manufacture and sales of servers. The security, navigation and communication system could move from one industry to another without modification.

The terms and expressions that have been employed in this specification are used as terms of description and not of limitations, there is no intention in the use of such terms and expressions to exclude any equivalence of the features shown and described or portions thereof. For example, the use of Microsoft® Office tools is implemented for practical purposes and does not limit the invention to use of Microsoft® products.

Furthermore, while the invention has been described in connection with the specific embodiments thereof and in a specific use, specifically to the implementation of the invention in a pharmaceutical environment, various modifications will be apparent to those skilled in the art, without departing from the spirit of the invention as set forth in the claims appended hereto.

Claims

THE EMBODIMENTS OF THE INVENTION IN WHICH AN EXCLUSIVE PROPERTY OR PRIVILEGE IS CLAIMED ARE DEFINED AS FOLLOWS:

1) An information retrieval system comprising: a) a plurality of local databases accessible by users on corresponding local networks; b) a parent database for managing information stored in said plurality of local databases, said parent database being coupled with said plurality of local databases by a global network; c) at least one server for receiving a query request from a user on one of said local networks for querying said corresponding local database and- for querying said parent database to determine if said query can be fulfilled by others of said local databases.

2) A system as defined in claim 1, wherein said parent database includes an equivalency manager for adding additional information to said query request, said additional information comprising different nomenclature having an equivalent meaning to that of said query request.