Life sciences organizations are presented with a unique conundrum due to their access to vast data reserves. This situation is paradoxical; on one hand, it poses significant logistical challenges in data management and analysis. On the other, it offers a treasure trove of information, unlocking potential for groundbreaking insights, ultimately leading to better customer engagement. The pivotal challenge lies in navigating these complexities to harness the full spectrum of opportunities available. The question is, how do life sciences companies overcome the challenges in order to take advantage of the opportunities?

More data means more challenges

The burgeoning data landscape in life sciences represents a contemporary evolution, yet the timeless adage of “maximizing output with minimal input” remains relevant. This principle holds true – leveraging data more effectively need not entail substantial cost surges. The essence of data centralization lies in its ability to streamline processes, eliminate duplicative efforts, and facilitate seamless data accessibility for users.

Inefficiencies arise when the same data is purchased multiple times by different parts of the organization, or when multiple groups purchase different data sets to tackle a similar task. Both problems are made worse when data is siloed across different parts of the network and the various groups within a single organization don’t know what information their peers are using. This fragmentation not only results in duplicated expenses and wasted resources but also creates an air of uncertainty and mistrust around the valuable findings that could otherwise be gleaned.

Redundant data also comes with cost and resource redundancies related to formatting, storage and access. For many companies, the cost and effort of making data ready to use is actually higher than the cost of generating insights from that data.

EMEA strategy development

Life sciences companies with operations in EMEA, as elsewhere, face complex and ever-changing regulations around data usage. These regulations vary among the many regions of Europe, the Middle East and Africa, making it even more difficult to ensure that only sanctioned data is used, and only for qualified purposes.

The push to increase efficiency starts with a fresh look at your overall data management strategy. In order to achieve fast turnaround of use cases and determine data priorities that serve both global needs and local needs, it is pivotal to clearly define data ownership, governance and domain expertise within organizations. Where the role does not already exist, companies should consider appointing a Chief Data Officer to oversee the organization and its regions or countries.

Data centralization/standardization brings major benefits

While data centralization requires some initial investment, it offers significant benefits in faster insights and potential long-term savings. For example, getting rid of redundant data management processes reduces annual costs. Additionally, there is no need to allocate a budget for constructing ingestion pipelines in every country for each data offering. Streamlining data ingestion through standardized data assets enables other data management processes that deal with single rather than multiple connections. Thus, organizations can develop uniform solutions (where country or brand are not relevant) and run automated processes that speed delivery of insights to all stakeholders.

In addition to accelerating time-to-insights, data centralization and delivery can help generate better insights by quickly and easily integrating market sales data with interaction data, customer insights, and other secondary or primary data. For example:

• Streamlined Data Access for Data Scientists: A data scientist tasked to run an ad hoc project to answer a specific question would have a single point of access for data from which they can generate a range of content and insights. After completing an analysis for one country, it’s markedly easier to duplicate that analysis across another ten countries. This increased agility enables teams to quickly deliver accurate answers to questions or insights to their stakeholders.
• Market Potential Assessment: Standardized data could support a multi-country product launch strategy by showing which markets have the best potential. You might discover, for example, that a particular market is already oversaturated with similar products, possibly even at a lower price. Or if multiple doses or delivery options are available, you can look at which variation of a product is most successful in which region. Data helps mitigate risk by enabling quick and accurate decisions.
• Multi-Source Insights: Combining data from various sources enhances insights. For instance, merging engagement data with prescription data allows for better measurement of success in specific areas. Similarly, tracking volume changes after deploying additional sales reps in a region provides actionable intelligence that is crucial for tracking sales and rep progress, enabling informed decisions and better business outcomes.
• Swift Recommendations: An analyst is better able to deliver smart recommendations, like Next Best Action, and do so almost immediately after data is ingested and standardized (as compared to taking months in the past). This data enables sales to access real-time territorial analytics, allowing sales messages to be tailored in real time for specific healthcare professionals (HCPs) to maintain a competitive edge.

Data-as-a-Service (DaaS) for end-to-end coverage

For some life sciences companies, the most direct and cost-effective way to achieve data centralization and delivery is to partner with a comprehensive Data-as-a-Service (DaaS) provider. A DaaS solution dismantles the different data formats and standards from all the various countries or regions and brings that data into one consistent format to:

• Accelerate implementation: Creating a multi-country solution with multiple stakeholders has traditionally been time-consuming and complex, and once achieved, implementation could get bogged down and take even longer. DaaS removes complexity and accelerates execution.
• Quickly generate actionable insights: DaaS enables you to ingest and process data promptly and in a standardized manner, so you don’t spend a lot of time managing and transforming that data, and users receive it ready-to-use.
• Improve scalability: With DaaS in place and integrated across multiple countries, you can easily expand into other regions or data domains and cost-effectively deploy new offerings much faster, with greater flexibility.
• Improve quality and consistency: A DaaS solution helps identify and classify data, including removing redundancies and standardizing discrepancies.
• Build a foundation for GenAI: DaaS brings a level of security and compliance to generative AI (GenAI) tools by helping ensure use cases are utilizing safe (clean, standardized and centralized) “healthcare-grade” data.

How IQVIA can help

It can be complex and costly to centralize different data sets from different countries and standardize its delivery across multiple stakeholders. IQVIA has the expertise and experience specifically in the complex realm of life sciences to accelerate the process. IQVIA DaaS delivers an innovative, modern and centralized hosting and data management solution that provides a cost-effective way to host, curate, integrate, organize, govern and access all your healthcare data assets in one place.

IQVIA DaaS enhances your data management experience by leveraging cutting-edge technology and automation. This not only streamlines your workflows but also offers significant cost and time savings. This solution, chosen by a majority of the top 20 life sciences companies, can empower you to effortlessly manage data across multiple countries, freeing you from the manual processes that slow down your progress.