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Creating a Data Strategy and Enablement Framework for Life Sciences
Five data strategy success metrics to consider for success
Inderpreet Kambo, Principal, Information Management and Analytics, IQVIA
Ankur Chopra, Senior Principal, Information Management & Analytics Solutions, IQVIA
Sep 01, 2023

Traditional IT systems and processes can no longer meet the expectations of life science organizations given the growth of information sources, nuanced engagement models, and myriad of stakeholders to manage.

The need for a well-crafted digital strategy is greater than ever

There is also a clear consensus on the need to engage seamlessly across an evolving ecosystem of digital, personal, and 3rd-party channels to connect various artifacts of data. This is not a mere tactical business operation, but an actual value-driven activity to realize uncapped business value and drive actionable insights for the business. From supporting scientific innovation to designing new commercial model designs, life science businesses are using a use-case-driven approach to define the right data strategy. Having supported 20+ customers with different maturity indexes of data strategy, the IQVIA team has grouped data strategy success metrics into the following categories:

  1. Comprehensive view of the customers: All relevant customers should be evaluated before making a data strategy framework including providers, patients, payers, and pharmacies. The data acquired must optimally support needed insights for each stakeholder group.
  2. Identify relevant key performance indicators (KPIs): Gain a clear understanding of the KPIs that each of the stakeholders require to manage their business and meet their goals.
  3. Data governance: Manage quality control and validation for the newly acquired data as well as ensure ongoing checks and balances using master data management and stewardship for a successful and correct data product.
  4. Privacy and compliance: While acquisition of data is critical, it is equally important to ensure that proper guidelines are met for data collection and reporting with concerned regulatory bodies.
  5. Accurate and timely insights: Get access to highest quality insights and reports via aggregated, integrated, and enriched data through intuitive smart self-service applications.

Going forward, life science organizations will need to follow a rational and logical business plan to create a strong enterprise grade data strategy that helps unlock the true value of data and supports an optimized data to insights journey. IQVIA supports life science companies by defining and execute their data-strategy and can partner across all aspects of the information management framework.

Framework for enterprise information management

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