Business Intelligence Framework For Pharmaceutical

Business Intelligence For Pharmaceutical Industry More than ever, the pharmaceutical industry is challenged with an increasingly dynamic environment. Growing competition, government regulation, product segmentation, and corporate consolidation have driven the need for organizations to effectively analyze both internal and external information. This document studies the challenge of Business Intelligence in the pharmaceutical industry and presents conceptual solutions to deliver information to the enterprise.

The Pharmaceutical Business Similar to other industries, Figure 1 displays the business flow for a typical pharmaceutical company.

Figure 1: This figure displays the business flow of a pharmaceutical organization. The Business Defined From a business perspective, each component drives every other component in a synergistic cycle. The effectiveness of each organization has traditionally been assessed individually through department-specific Business Intelligence systems. However, true power is harnessed when information is integrated across components. The Information Challenge The challenge with integrating data across business components is that most information systems are built around the day-to-day operational needs of the business unit. In order to satisfy the corporate-wide information integration requirements, enterprise business intelligence (BI) systems must be developed and deployed. Such systems help companies with: Business Intelligence - Understand the needs of the business Business Management - Manage internal operations based on those needs Business Operations - Run the business based on management directives These capacities enable companies to realize the opportunity of a business landscape characterized by customer relationships, product delivery, and opportunity-driven profit. One of the key enabling technologies to this evolution is the Enterprise Data Warehouse (EDW).

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Business Intelligence For Pharmaceutical Industry The Enterprise Data Warehouse Conceptually, an Enterprise Data Warehouse (EDW) is a platform upon which an organization can integrate information from a variety of sources into a common and consistent format and deliver it to analysts through a business-oriented semantic layer. The EDW approach is widely recognized as a necessity for companies around the world. Figure 2 illustrates how the data warehouse delivers business intelligence capabilities to support business functions in the pharmaceutical industry. Though not covered in the scope of this document, the figure also illustrates how the operational data store, a key component of any EDW deployment, delivers business management capabilities to complete the information solution.

Figure 2: This figure displays the processes and resulting functions of an EDW approach. More than ever, an EDW approach is critical in the pharmaceutical industry. With a variety of data sources (both internal and external to the company) and a trend of consolidation, it has become increasingly challenging to analyze information across systems, particularly when the number of systems multiply after a merger.

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Business Intelligence For Pharmaceutical Industry Pharmaceutical Analysis Like other industries, the pharmaceutical data warehouse provides insight that drives new customers, helps retain current ones, streamlines operations, reduces costs, and helps management to achieve their targets. One of the unique characteristics of a pharmaceutical EDW, however is the fact that there are a broad range of candidate data sources to integrate. Figure 3 displays just a few of these data sources. It is challenging just to prioritize these sources and find methodologies to merge them into the EDW.

Figure 3: This figure displays some of the candidate data sources for a pharmaceutical EDW.

Several additional key challenges are unique to the pharmaceutical industry: o

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The pharmaceutical industry has a great dependency on third-party data. Companies such as IMS, NDC, and Scott Levin gather information directly from data sources about patient care and prescriptions. Since most pharmaceutical inventory is sold to wholesalers and not directly to customers, it would be very difficult to analyze sales data without third-party information. Many of the data sources are available at different intervals. External data sources frequently become available months after the transactions occur, while internal data may be available real-time. Internal reporting needs may require an EDW to house different data sources with different load intervals. External and internal data often are not readily nor easily mapped together. They are often aligned by different keys and have differing levels of granularity and cleanliness. This may require a substantial scrubbing process to cross-match the data. · Different parts of the business often view or align the same data in different ways. For instance, marketing analysts may view product and market roll-ups differently than sales analysts. This results in a more challenging development process than typical for other industries. Many pharmaceutical data warehouse users are often remotely located which may drive the need for a more sophisticated delivery process. There are many regulatory security and reporting requirements that are imposed on the pharmaceutical industry. Since Federal law protects customer privacy, it is more critical to carefully design the warehouse for security and the appropriate level of anonymity. The pharmaceutical industry is highly dynamic. With legislation and business changes to the health care industry, the sales process (and consequently the data) is in a constant state of change. Therefore, an EDW must be constructed with adequate flexibility so that such changes do not require major modifications to the system.

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Business Intelligence For Pharmaceutical Industry Building a pharmaceutical data warehouse is a complex and iterative process. Understanding the uniqueness of the industry is absolutely essential for success. A carefully constructed data warehouse is not only beneficial to the business, but has become a necessity to the strategic direction of any pharmaceutical company facing increased competition and external pressures. The following sections identify the information needs of each business organization, and explore solutions in addressing them. Each section includes a brief description of the business organization and the information challenges it faces. Each section breaks out the types of analysis for each business organization and discusses the specific challenges and possible approaches for each.

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Business Intelligence For Pharmaceutical Industry Finance Pharmaceutical finance departments are responsible for a complex business model. In addition to unexacting stock market metrics, many pharmaceutical companies are challenged with managing a very wide breadth of suppliers and customers. In addition, finance organizations must manage agreements with a variety of buyers ranging from direct customers (for over-the-counter products), distributors, hospitals/managed care organizations, prescribers (for sample products), and pharmacies. Some of the key finance analysis challenges are broken out below. Budgeting/Forecasting/SEC Reporting Challenge: It is difficult to consolidate information about allocated funds and predicted funds to meet the market demands. Furthermore, it is difficult to update and reevaluate these values throughout the year when the information is maintained in different systems. In addition, companies must build financial performance estimates based on sketchy information on sales and pipeline. This is not easy without a consolidated big-picture information store. What costs should be cut? What would the impact be? What is our budget versus actual? What is the historical market trend? Will we hit our target? Approach: By extracting information from forecasting and finance systems and integrating it with manufacturing, market research, and sales data, accurate values can be derived for budget, manufacturing, and outlook. This delivers a single version of truth for all information consumers. With insight into sales and marketing initiatives, it is much easier to build SEC estimates from the bottom up not top-down. Business cost, R&D, manufacturing, and sales information can be combined to generate such an assessment. Merger & Acquisition Analysis Challenge: Pharmaceutical companies often merge even where a wide overlap in product lines and operation functions exists. Heavy analysis is needed before committing to a merger or acquisition, heavy analysis is needed to determine financial viability given various scenarios. What products serve the same customer base? What products have synergies? What new cross-sell opportunities exist? Should some of the products be sold off? What is the fiscal impact? How can we integrate business intelligence information from both companies? How in line is their financial infrastructure with ours? What is the overlap from a manpower perspective for operations, R&D, and manufacturing? Approach: With analytic insight into product performance, doctor segmentation, competitor information, and product synergies, many more informed decisions could be made with respect to possible mergers and acquisitions. Market research, R&D, and pipeline data can be integrated to support this analysis. Pricing Challenge:

Price sensitivity is not only a sensitive political issue but also difficult to measure.

Approach: An integrated EDW allows analysts to measure the impact that pricing has on consumption and prescriber/user acceptance. Key sales and prescriber information may be consolidated with price information to measure elasticity.

Chargebacks/Rebates Challenge: Some customers require greater rebates while others have more chargebacks. It can be challenging to target the most lucrative customers while addressing those who are more problematic. Approach: Integrating sales and financial information into an EDW and providing access via a set of analytical tools facilitates effective targeting and management of different customers. By www.baconsultinggroup.com

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Business Intelligence For Pharmaceutical Industry integrating Enterprise Resource Planning (ERP) information with sales and marketing information, companies can determine the value of its customers and how best to manage those who are not high value. KPI Reporting Challenge: Consistency and accuracy is paramount when reporting key performance indicators to the business. What is the overall state of the company? Are we on target versus our plan? What is the state of our financial ratios? Who are slow payers? What debts are due soon? What does my cash flow look like? What are my inventory levels? Approach: Everyone in the organization should receive the same numbers for the same KPIs. An integrated EDW provides a single consistent source of information that can then be disseminated through various means. Financial KPI reporting may integrate information from a wide breadth of systems but are often primarily driven from the ERP system.

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Business Intelligence For Pharmaceutical Industry Contracting / Legal Pharmaceuticals have one of the most stringent regulatory bodies of any industry. This is due to the nature of the business and the fact that it is highly patent driven. In addition, the rules governing product disbursements, inventory, pricing, clinical trials, FDA approval, and manufacturing are also highly regulated. The recent enactment of the Health Insurance Portability and Accountability Act of 1996 ("HIPAA") has expanded protection of patient data. Some of the key contracting and legal analysis challenges are broken out below. Regulatory Compliance Challenge: Development, manufacturing and inventory information is often fragmented across a wide range of operational systems. This creates a challenge not only for regulatory compliance but also for internal reporting and tracking. Am I within CGMP regulations? Are my clinical trials successful? Should I Fast-Track clinical trials? Is sample distribution within compliance? Approach: An integrated EDW allows analysts to track market research, manufacturing, inventory and distribution data and report on it internally and externally with the same rules and assumptions. This allows analysts to assess whether manufacturing, distribution are in compliance. Furthermore, it will help market researchers with clinical trials analysis. Data sources would likely include market research, ERP systems, external vendors (e.g., for samples), manufacturing, and distribution. Bids & Contracts Challenge: A big-picture view of how the industry behaves is often difficult to generate. This makes it challenging to structure contracts that account for a dynamic industry. Which companies default most frequently? What is my fiscal exposure if a contract goes to litigation? What are the commonly accepted price thresholds? Approach: By integrating data across sources, the EDW can provide invaluable insight into what should be considered standard practice and what is an outlier. For example, a pharmaceutical company may be able to contest a payer's refusal to cover charges for services deemed unnecessary if the data shows that such tests or treatments are standard among patients with the same condition. Furthermore, such observations may result in contracting policies that protect the company in the future. Market research data must be integrated into internal contracting data to drive such analysis. Privacy Challenge: It is difficult to ensure consistency between systems with respect to customer privacy. Since the advent of HIPAA, it has become more important than ever to ensure privacy. Approach: With an integrated EDW and corresponding data dictionary it becomes much easier to consistently manage privacy across both operational and analytical systems. From an analysis standpoint Extract Transform and Load (ETL) rules can drive consistency across data sources. It becomes possible to ensure consistency and make certain that individually identifiable information such as a patient's name, social security number or address are not stored or accessed across the organization. On the other hand, aggregate data, which is data that has been stripped of individual identifiers, may be made available for analysis in a consistent and legal manner.

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Business Intelligence For Pharmaceutical Industry R&D R&D is the lifeblood of modern pharmaceuticals. Companies are measured, not only on how they perform, but also on what their R&D pipeline looks like. Some of the key R&D analysis challenges are broken out below. Market Research Challenge: Ideally, decisions that drive a product’s commercial potential are made long before that drug enters the market. As companies realize this, they begin market research activities in the prelaunch drug development process. This can greatly impact a drug’s selling power at launch and improve acceptance by the marketplace. What markets should we be getting into? What is the upside potential of a drug? What drugs should be further segmented by form or strength? Who are my primary competitors? Why do customers change drugs? What are the insurance and managed care organizations saying about my and other drugs? Approach: By establishing an integrated repository of analog drugs, insurance and managed care purchase trends, and competitive intelligence market analysts can better work with upper management and R&D to drive the company’s overall product strategy and focus. Testing & Clinical Trial Analysis Challenge: Pharmaceutical companies are challenged with keeping abreast of progress in various clinical trials and the FDA approval process. The impact of such results can transform a company but often the information resides in a variety of locations. What is the progress for all clinical trials for a particular product? What side effects have been identified during a study? What other medical uses might exist for a product? Approach: By consolidating clinical trial information into a single information store, an organization is empowered to investigate and report on a variety of metrics. Outcomes of groups of similarly afflicted patients treated with different drug regimens can be compared to determine which treatments statistically work better. In addition, studies can be made to better predict the effects of diverse drug combinations and interactions. Up-to-date progress reports may be generated and new discoveries identified. Furthermore, existing document management systems can be raised to a new level of capability by both sourcing and feeding the integrated EDW. Risk Analysis Challenge: The pipeline drives not only strategic and acquisition strategies but also drives the overall corporate picture on Wall Street. The pipeline is surrounded with technical and business risk, however. Will a drug be developed on time? Will it pass clinical trials and be approved? How big could a product be? What might the manufacturing challenges be to deliver the product? Approach: In addition to qualitative risk assessments in R&D, a more quantitative approach may be possible provided the underlying information is available for electronic access. Molecule Database Challenge: Keeping track of thousands of molecules that have been developed and all of their characteristics is a daunting task, especially when you have development facilities scattered across the globe. Which ones look promising for developing treatments for a target indication? How can we effectively share this information to all users? Approach: Maintaining a database of these molecules can allow R&D executives and scientists the ability to search for certain characteristics and adverse interactions among them. This can streamline development and eliminate unproductive development paths. It also makes the information available for disparate users. Data mining applications can also be used to explore possible permutations of this information.

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Business Intelligence For Pharmaceutical Industry Manufacturing Manufacturing is a logistically challenging and cost-intensive component of the business. Three key areas of manufacturing are imperative; regulatory compliance, cost control, and satisfying market demand. By adequately analyzing manufacturing information an organization becomes much more capable of addressing these issues. Some of the key manufacturing analysis challenges are broken out below. Production Analysis Challenge: Producing the correct amount of product to satisfy market demand can be a daunting task, particularly when considering seasonal products. What will my demand be? Will my product inventory adequately supply the demand? Will delivery devices and packaging be delivered on time? What are my manufacturing costs and how can I control them? Approach: Through an integrated EDW, analysts can analyze historical information and detect seasonal trends, enabling them to predict future demand and ensure that the proper inventory is available. Furthermore manufacturing information can help to include production estimates to begin ramping production prior to seasonal requirements. Resulting metrics might include predicted orders and units for an extended timeframe. Other metrics may include planned orders versus produced orders, manufacturing life cycle, and pipeline predictions. Inventory Tracking Challenge: The more money a company has tied up in inventory, the less they have available for other investment. How can a company minimize its inventory while keeping up with demand? Inventory tracking may also include information about samples on hand and distributed by sales representatives. Approach: The EDW can integrate data to determine optimal inventory levels across all product lines. This may use historical values for similar products and prediction factors from market research data. Furthermore, sales representative sample inventory may be optimized to reduce spoilage. Supply Chain Analysis Challenge: In today’s world of Just In Time (JIT) manufacturing, knowing when you need to order raw materials for production can mean the difference between manufacturing delays and excess material buildup – all factors in controlling costs and cash flow efficiency. Approach: Data from ERP, supply chain software, etc. can be used in business intelligence applications to efficiently manage both raw materials and packaging material purchasing to eliminate inventory buildup, waste, and ensure on-time delivery of supplies. Data can then be integrated with logistics to combine manufacturing and shipping time frame analysis. Vendor Performance Challenge: Which vendors are more efficient than others? Who gets me their shipments on time and who is always late? What are we paying for raw materials among various vendors? Can cost efficiencies be achieved? Approach: Using data from supply chain, ERP, vendor source systems, and Business-to-Business applications, analysts can rate vendor performance and price and use the information to negotiate new contracts, prices, and delivery mechanisms. Regulatory Compliance Challenge: The government closely governs manufacturing of pharmaceutical products. Am I within CGMP regulations? Approach: By integrating manufacturing information into a consolidated system, it is much easier to meet regulatory compliance reporting and audits. www.baconsultinggroup.com

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Business Intelligence For Pharmaceutical Industry Marketing Pharmaceutical marketing varies from other industries in that it spans a wide breadth of customers. Pharmaceutical companies must target product end-users, prescribers, hospitals, and distribution channels. Furthermore, Federal law restricts the amount of information that they can track and use for specific customers. This makes pharmaceutical marketing a challenging proposition, particularly when considering the increasingly competitive climate in the industry. Some of the key marketing analysis challenges are broken out below. Demographic Analysis and Segmentation Challenge: How can a pharmaceutical company best target its customers? This not only includes product consumers but also prescribers and institutions. The message delivered to each should be tailored and should promote high-valued customers. This ultimately results in improving satisfaction for current customers and acquiring new customers with the same profile as highly satisfied customers. In concept, this is an incredibly powerful paradigm. In practicality, however, it is challenging. Not only can the data integration be difficult, but also deploying such a system without compromising customer anonymity requires a well-thought-out approach. Approach: By using an EDW to consolidate strategic knowledge about customer value, a pharmaceutical company can develop profiles of loyal customers and determine customer lifetime value. With information such as demographics, behavioral or lifestyle data, product utilization, refill information, and survey data, the marketing message can be tailored to deliver the right message to the right people. Integrating data sources including purchased sales data, samples and details data, marketing campaign information, purchased demographic and census information, web site and survey data, and ERP information provides a great deal of information capability. With respect to privacy, there are several mechanisms to provide valuable analysis without compromising legally mandated anonymity. By using a customer key that eliminates personally identifiable information, or by aggregating demographic information, an EDW can protect confidential information while enabling highly valuable analysis. Product Analysis Challenge: It is challenging to determine the most effective product segmentation and acquisition/development strategies within the pharmaceutical industry. Thought must go into factors such as multi-product treatments, product overlap, synergies, future product releases (both internally and within the market as a whole), manufacturability, suppliers and so forth. It is critical to ensure that new and/or segmented drugs provide the greatest value and open new markets to a company while not overly cannibalizing existing product sales. Approach: Marketing data within an EDW provides information about the products that customers’ use most often, which they most value, and their consistency in renewing prescriptions or purchasing additional product. Furthermore, information about multi-drug regimens, product synergies, and cross-sell information may be obtained. By integrating clinical trials information with product segmentation, sales information, and survey data, it is possible to generate an analysis system within the EDW to support strategic analysis such as this. This can help marketing analysts to determine factors such as market share, retail vs. non-retail performance, packaging, and product form performance. Data Mining Challenge: The breadth of pharmaceutical data makes it a prime candidate for data mining. Analysts oftentimes don’t look for a specific piece of information, but rather want to identify potential trends or patterns of events. Although the value of data mining has been identified across the industry, few companies have successfully deployed it. Often this is due to the fact that an EDW is not available from which to source consistent and cleansed information. How do various factors about a product impact the products performance within a market? How do these factors affect other products in other markets? How does prescriber specialty impact the way they prescribe our www.baconsultinggroup.com

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Business Intelligence For Pharmaceutical Industry products? Other products? What prescription profile over time indicates a prescriber that will jump to another product? What prescription profile over time indicates a prescriber that will begin prescribing more? What marketing and sales activities impact the behavior of a prescriber? How? Approach: Data mining can be used for a variety of purposes from R&D to marketing. Starting with clean and consistent information, however, is crucial. Data Mining is only as good as the input information. By sourcing an EDW, data mining analysts may begin to generate value through analysis such as doctor segmentation and targeting, customer segmentation, and product molecule discovery. Knowledge of the business and the data generated by that business comes first in the process. The business rules and data sources are documented and reviewed. The second step is integrating the data into one system or file structure. Typically this is called data preparation, or the ETL process. The third step is to select the modeling techniques. Different tools use different modeling methods, and familiarity with those tools is essential to getting the desired results. In the Fourth step, the results of the model must then be evaluated, and a decision to change algorithms or continue with the chosen ones must be made. This feedback loop is critical. The sensitivity of the data and results always drives the degree to which the model is tuned. Finally, the fifth step is the delivery of the model results to the business users. How this information is displayed can vary widely. Infowise has used delivery mechanisms ranging from simple spreadsheets to seamless integration into existing business intelligence systems Geography, Payer & Prescriber Analysis Challenge: A marketing organization must target buyers and geographies that provide the greatest value to the company. Many organizations have difficulty viewing prescription volume trends at a national level, let alone at the region or district level. It is crucial to assess where the greatest lift is derived between channels such as retail, non-retail, mail order, or institutional. It is also important to assess what payment medium provides the most benefit between cash, Medicaid, or third-party. Finally, geographically based marketing depends on state or even zip-code level information. This helps complete the big-picture for a marketing organization and helps them to tailor their focus towards a high-value customer focus. What payers are generating the most revenue? What payers are underutilized? What is my geographical market share? What prescribers should I target? Approach: All of these factors vary over time with changing policies and administrations so there is an added importance on live information and continual monitoring and reassessment. A marketing data mart or data warehouse can integrate purchased data from a variety of resources and internal sales information to determine aggregate and atomic level performance of total prescriptions (TRx) as well as new prescriptions (NRx) activity at a prescriber and zip code level. This information may then be aggregated to provide national level totals. It allows a pharmaceutical organization to analyze prescription information broken out by payer and prescriber over time, market, geography, and sales organization. Campaign Analysis Challenge: Because it is difficult to directly track customer behavior in an environment where customer privacy is protected, campaign performance often goes unmeasured. Approach: Through an EDW approach, it is possible to assimilate demographic, campaign and sales performance information to obtain high-level campaign analysis. Obviously, privacy restrictions will limit the detail level of analysis, however, aggregate or anonymous customer data may be used so that customers are no longer individually identifiable. EBusiness Challenge: Ebusiness in the pharmaceutical industry may be broken into two main categories. Business-to-business (B2B) typically applies to reorder systems and business transaction type information. Business-to-Customer (B2C), applies to product marketing web sites. Many pharmaceutical organizations have yet to adequately analyze either of these. It is often difficult to www.baconsultinggroup.com

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Business Intelligence For Pharmaceutical Industry do so due to the nature of the information being collected. o o o o o

The challenges often include:

Multiple web hosting companies Technology barriers (different web servers and log formats, availability of log files – FTP, different browser capabilities –session tracking & cookies) Different data sources and types of data Time sensitivity Privacy issues

What web sites provide the most traffic? What is my site performance and uptime? How many customers become qualified (e.g., fill out a survey, request information, etc) via web sites? How many vendors actually use my B2B systems to reorder or ask questions? How many prescribers use my websites? How do web site changes impact traffic? How effective is web-based marketing? How effective are banner and add campaigns? What is my ECommerce ROI? Approach: An EDW approach provides huge value to eBusiness analysts. It provides a set of conventions and processes that allow the integration of web-based information into the overall data warehouse. Not only does this facilitate web analysis such as customer analysis, campaign analysis, survey data, segmentation, and web-site performance, but it also opens the doors to integrating other enterprise information such as sales and marketing data. For example, an ebusiness data mart could enable an analyst to measure the product sales impact in a region for which a marketing campaign took place. It may even break this information out by customer demographic. It may allow that analyst to correlate web site design and performance to increases in prescriber and user acceptance. Web traffic data is readily integrated into an EDW. Although conventions and transformation processes are important, many of logistical factors are often they key to successfully deploying such a system. In addition to creating ETL scripts to import the identified eBusiness information, negotiations must take place with internal departments and external vendors to capture the required information from internal and external web sites, and to deliver it on the desired frequency and with the proper content to support technologies such as cookies and session variables.

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Business Intelligence For Pharmaceutical Industry Sales & Distribution A Pharmaceutical sales organization is unlike that in any other industry. Although some sales reps may sell product contracts to hospitals and managed care organizations, most act in more of a marketing capacity. Many pharmaceutical sales reps provide information to physicians and potential prescribers by discussing product characteristics and benefits. The goal of these sales representatives is to influence prescribing habits that may indirectly result in the sale of a product at the pharmacy. Some of the key sales analysis challenges are broken out below. Sales Force Analysis and Compensation Challenge: Tied closely with finance data, sales performance ultimately drives sales compensation. It is often difficult to integrate finance and sales information. Approach: By creating a cross-reference key between financial indicators and purchased sales performance information at the territory or sales representative level, it is possible to generate sales force metrics to analyze sales performance as a whole. Subsequently, it becomes possible to develop a compensation model that takes into account factors such as: o Prescribers that work out of multiple offices o Prescribers that move or go out of business o Constantly evolving sales force o Sales force organizational changes This is possible only if information such as profit, cash-flow, samples, calls and details, marketing program costs, NRX, and TRX are integrated and made available for access via an EDW. Sales Force Support Challenge: In the pharmaceutical industry, information is critical to the success of the sales presentation process. Pharmaceutical sales representatives and managers look for information that can provide insight into the management of the sales process. They need to know current business conditions (e.g., new drug launches), internal measurements (e.g., percent to quota), external measurements (e.g., percent of market), and why changes have occurred. They not only require a detailed knowledge of the product and marketplace, but also insight into what sales approaches and/or products are most readily accepted by a prescriber or organization. Approach: Certainly, a product database with product specifications, clinical trial and patient outcome results is an invaluable tool to the sales representative. When information such as this is integrated with prescriber segmentation, and quintile / decile / target information a pharmaceutical sales rep becomes empowered. An EDW provides a platform upon which to develop sales force reporting that pushes business intelligence to the field in support of sales initiatives, marketing campaigns, and targeted/focused selling methodologies. The data must be integrated across purchased sales information, market research and marketing data, pipeline news, technical product documentation, and internal financial and organization information. This integrated view is then pushed to the field. Logistics are often a hurdle when deploying a sales-force reporting application. Deployment may range from e-mail, file transfer, off-line reporting, or even on-line reporting Samples & Details Challenge: Samples and details accounts for a large component of cost in pursuit of new and continued business. Often, however, this information is difficult to obtain and/or integrate with the resulting sales data. This makes it difficult to “fine-tune” a sales operation by minimizing cost and maximizing sales. Approach: By creating a cross-reference key, it becomes possible to integrate sales cost information with sales performance data. By integrating internal and/or external sample and detail data with internal and/or purchased sales information at a common key level (e.g., ME#, SL#, DEA#) it becomes www.baconsultinggroup.com

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Business Intelligence For Pharmaceutical Industry possible to track pharmaceutical sales ROI. This enables sales analysts to not only regulate sample and detail counts but also to experiment with changes. With integrated information it becomes possible, for instance, to reduce the samples a prescriber receives and monitor the outcome. It also makes it possible to determine if some prescribers receive so many samples that they don’t have to prescribe the product at all. By evaluating sales rep to doctor associations, it is also possible to determine who is delivering the message that modifies the doctor’s behavior and who could use help. Business-to-Business Challenge: Pharmaceutical companies that use Business-to-Business systems for customers to place orders often experience difficulty both analyzing usage and acceptance of such systems as well as the resulting order information. Approach: By integrating business-to-business information with the EDW institutional sales information may be analyzed. Furthermore, system usage and change analysis can be investigated. Inventory Analysis & Control Challenge: As with manufacturing, inventory management is a crucial part of cost control. Samples often expire in sales representative garages. What regions, districts, and territories have the hardest time distributing inventory? How many samples are given out by geography and time? How much inventory is expiring and where? Approach: By integrating samples inventory information into the EDW along with expiration information, it becomes possible to more effectively distribute and manage sales activities. Additionally, analysis of such information may provide potential cost-management opportunities for upper management. Factory Sales Challenge: It is often difficult to view purchasing trends at a national level let alone at a more granular level. Approach: By sourcing and consolidating information out of internal financial and order systems, it is possible to analyze dollar and unit sales, credits dollars and units, and charge-backs for distributors and institutional buyers.

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Business Intelligence For Pharmaceutical Industry The Integration Advantage To this point, this paper has detailed each of the individual components of a pharmaceutical business and their respective information needs. Though important, this is only part of the overall solution. As important to the overall success of the organization is the capacity for cross-functional data integration. This enables two additional capabilities: 1)

It allows a consolidated and complete picture of the company for upper management

2)

It allows business components to interact more effectively with each other while reducing the information barriers between the components.

The implementation of an EDW allows the organization to achieve the ultimate integration goal. By integrating information from each business component and housing it in a manner that makes it accessible to all with a common shared vision, it is possible to supply all components of the business with a single version of “truth”. Strategic Planning An integrated EDW approach facilitates the ability to integrate disparate data sources for a complete picture of the business. In addition, it helps strategic planners to use this more complete picture to steer the company. Strategic planning evolves when upper management begins using the EDW to benchmark, track campaigns, analyze performance, and plan for the future. Based on their findings, marketers build a personalized, strategic approach that takes pharmaceutical marketing directly to the consumer. An EDW enables the organization to provide the customer information to other components of the organization. By sharing this information with finance, R&D, sales, and upper management, the pharmaceutical organization can improve tactical as well as strategic planning. Anyone accessing the database throughout the organization can see and understand a customer's value to the organization as well as the products and services that may be of interest to the customers. This allows them to make appropriate decisions on: o o o o o

Budgeting & Forecasting Cost Management Marketing & Sales Production Planning Research & Development

With everyone in the organization better equipped to understand and deliver customer value, true strategic planning emerges. Cross-Functional Integration An EDW approach enhances the information interface between business organizations within a pharmaceutical company. The benefits of this integration are broad reaching and may significantly impact the business as a whole. It will ensure that metrics and measures are consistently reported across organizations, while maintaining the specific “view” mandated by each business unit. For example alignments for sales, marketing, and managed care may vary while the underlying data and metrics are consistent. It will provide a centralized and common data dictionary or definition of information. Perhaps most importantly, it will allow analysts from each organization to access information about other organizations from a common information source. This enables business components to interact more seamlessly and have access to more accurate and timely information. The net result is an improvement in overall corporate efficiency and reduced corporate expenditures and costs.

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Business Intelligence For Pharmaceutical Industry Conclusion Rapid changes in the pharmaceutical landscape have demanded that companies re-evaluate their IT infrastructure and information delivery methods. Heavy competition for market share, as well as a variety of other industry-driven factors has necessitated the integration of disparate source systems to provide a single version of “truth”. Although each organization has company-specific nuances that impact information integration, this document provided and outlined an approach to satisfy these needs. The concepts addressed in this paper, in conjunction with a strategic company vision will drive effective strategic decisions; enabling pharmaceutical companies to continue to compete in an ever-evolving market.

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