As integration and information management applications take center stage in managing the critical business processes, there has been a growing need to have a robust enterprise scale data management and information delivery framework that can serve as the foundation for information needs of the organization. Due to the changing and dynamic nature of businesses, IT infrastructure is increasingly moving toward service-oriented architecture (SOA). This article discusses typical business challenges in the pharmaceutical industry and why data as a service is a viable option for information delivery, especially in the commercial operations of sales and marketing within this industry.
Pharmaceutical industries face some unique challenges to stay afloat and be profitable. Huge investment is required for new drug discoveries. The cycle time of drug discovery can take as long as 10 to 15 years, including clinical trials and regulatory approval, before a drug can be commercially sold. Subsequent to this long investment, the window of profitability lies within the period that the patent of the drug is valid. After the expiration of the patent, there can be serious competition from generic companies who can market cheaper version of the same drug.
Faced with such challenges, some of the most crucial business processes in a pharmaceutical organization include the efficient management of:
- Sales and Marketing functions - Segmentation and sales force productivity, portfolio optimization, brand management and product management.
- Research and development - Drug discovery, clinical trials and drug development.
- Manufacturing - Process control and optimization, production planning and quality control.
- Packaging and distribution - Supply chain optimization and management.
- General administration, including legal expenses.
Generally, for the prescription drugs, it has to be popular among the physicians to be sold to the patients. Hence, the selling must be targeted toward physicians and other major health care providers such as hospitals, clinics and so on. Key activities for the sales teams include:
- Targeting the right physicians and health care providers.
- Informed call planning of the sales force.
- Efficient and timely incentive and compensation calculations for the sales force.
- Contract management.
- Key opinion leaders (KOL) management.
- Product management.
Information Needs for Sales in a Pharma Company
The key information required for business analytics for commercial operations are sales (retail and outlet) and call activity data. Sales and marketing functions within the pharmaceutical companies, especially in the U.S. depend heavily on the external data providers for the projected sales data of their own drugs and those of their competitors. These data providers get the data from various pharmacies, clinics and hospitals, where the drugs are purchased by retail customers and outlets. Typical business analytics performed are:
- Market share analysis/regional analysis - To enable market competitiveness in the same therapeutic class and the market in general.
- Call planning and targeting - To prepare physician visit plan with the limited sales force organization to maximize visit coverage and effectiveness.
- Call activity monitoring - To analyze calls to physicians against plans and its impact on sales.
- Compensation calculation - To assess the performance of sales reps and corresponding compensation.
- Sample usage tracking - To analyze sample distribution and its effect on sales and cost.
- Contract effectiveness - To compare the effectiveness of contracts with outlets like hospitals, clinics and so on.
To support the above analytics, it is necessary to have a scalable, reliable and robust information management framework. Typically, this information management framework can be divided into two distinct areas: data acquisition and data exploitation.
To perform the various business analytics operation, it is necessary to acquire different business transaction data from both internal and external sources. Subsequent to that, the data needs to be processed and stored in an integrated data repository, which can be treated as the trusted, single version of truth for business analytics. The following diagram depicts a typical data acquisition scenario in a pharma business.
The data acquired from the above typical sources need to be delivered to various downstream consumers. In a typical pharma scenario, such consumers may be various business decision-makers or it may be downstream applications. Following is a list of typical business requirements of sales and marketing data.
Business Decision-Makers Downstream Applications
- Market share analysis.
- Effectiveness of call activity.
- Targeting of right physicians.
- Effectiveness of samples and its control.
- Contract effectiveness.
- Statutory and management reporting.
- Call planning activity through specialized external service providers.
- Compensation calculation through service providers.
- Data mining solutions for power users.
Issues and Challenges in Information Management
In the context of the above requirements, let us now try to understand the various issues and challenges of information management in a pharma company.
Data Acquisition and Management
- Because the companies are dependent on external agencies for critical sales data, it is always challenging to make sure that quality data is received from various data providers on time for processing.
- As sources of data are beyond the control and governance of the pharma companies, stringent data quality assurance processing needs to be done to ensure quality data is delivered for business analytics. This is in addition to the regular data integration processing required to create the integrated sales data repository.
Data Delivery and Exploitation
We now know the different needs of the sales and marketing data in a Pharma company. We see that the sales and marketing data is truly a reusable strategic asset of the enterprise. As the data is consumed and converted into actionable information by many diverse consumers (business users, transactional systems and external service providers), the same data from the data repository is extracted multiple times, partially or fully and possibly using different toolsets. This results in the following:
- Redundant components doing the same thing,
- Increased maintenance cost and total cost of ownership and
- Increased rework of the data extract components associated with the changes in the underlying data repository structure.
Addressing the above scenario through traditional data warehousing architecture will have the following issues:
- Full access to information-management.com including all searchable archived content
- Exclusive E-Newsletters delivering the latest headlines to your inbox
- Access to White Papers, Web Seminars, and Blog Discussions
- Discounts to upcoming conferences & events
- Uninterrupted access to all sponsored content, and MORE!
All Information Management articles are archived after 7 days. REGISTER NOW for unlimited access to all recently archived articles, as well as thousands of searchable stories. Registered Members also gain access to: