AdvantageMS works with many life sciences companies and regardless of company size, products, or organizational structure, we see common themes and concerns with business application architectures and approaches to customer data quality.
Common Issues and Concerns
- Application and data architectures are developed organically to address immediate and specific needs with no overarching plan or vision.
- Lack of governance both in terms of system architecture and data.
- Business dissatisfaction with the inability to meet both basic and strategic requirements and flexibility to meet changing needs.
- A high level of apprehension relative to regulatory compliance and no clear strategy to meet the changing requirements.
- Lack of a master data management strategy and limited understanding of the end-to-end stewardship processes across the entire commercial landscape.
- No clear understanding on how to maximize the business value of the third party data spend.
Our Solution: Clean, Accurate, Integrated Customer Data
AdvantageMS integrates disparate data sources to create a clean customer master that can be used by the entire business. It's a flexible solution that allows for more accurate sales, marketing and operational analytics. The process, that we often refer to as Customer Data Quality, includes: cleansing, matching, de-duping, and appending of HCP and Account data.
For the last 10 years, we’ve been collecting and validating important data elements like demographics, state license numbers, NPI IDs, degrees, and specialties. Our collection process has given us a significant advantage in matching client data to our validated database, which reduces manual workload and manages overall project costs.
Clean Data Benefits:
- A clear view of your customer
- Precise targeting data for marketing and sales teams
- Improved data for territory management
- Accurate account information for fair incentive compensation
- Straightforward data for operational analytics
- Lower costs for ad-hoc processes
- Reduced manual resolution workload