Centralize data and insights to avoid decision-making delays
To help boost patient-centricity, centralization of internal and external data allows for faster insight generation among pharmaceutical company teams.
Siloed data creates a time lag between data collection and insight generation. For a customer-centric business strategy, it is important for teams to have access to real-time information, which allows them to make evidence-based decisions that can improve customer experience. Centralization of information will require an internal shift in mindset, which can be met with internal resistance.
Actionable Insights:
- Centralizing internal and external data and insights allows full understanding of customer journeys: Using one portal or app can ease integration difficulties and reduce the time taken for internal staff to search for information
- Expanding the use of existing metrics and incorporating sentiment analysis: To provide alternative perspectives to improving customer journeys
- Data privacy concerns and permissions may hinder full data centralization: Representative samples should be enough to reveal customer needs
- For pharma companies to transition from being product-driven to customer-driven, changing company culture is crucial: Such a shift will require changing mindsets and adopting more integrated internal processes through collaboration
To improve a pharma company’s market strategy, data across internal teams needs to be collated. This includes data based on sales and engagement with patients and healthcare providers. When mapped, contextualized, and centralized, the data and analysis enable a company-wide view on how and when to engage with external stakeholders, specifically patients. Efficacy of engagement strategies need to be continuously reviewed, so approaches can be tweaked to meet evolving patient needs.
There is no homogenous approach to marketing, so pharma companies need to continuously understand different customer segments to establish distinct journeys. Internal analytics teams can gauge customer sentiment across patient journeys and aggregate data to generate insights and further improve protocols. Sentiment analysis is particularly useful for aligning external-facing teams – salespeople, customer service, and marketing teams – to ensure they promptly resolve issues and patients receive appropriate and consistent communications. As an example of sentiment analysis, Roche employed a process wherein its call center can predict adverse events and optimize resourcing across service teams to promptly prevent or resolve issues.
Data insights need to be communicated to relevant internal stakeholders on time. For example, there can be a time lag before salespeople are informed of marketing campaign outcomes. Updates delivered via portals or an app allow timely information for salespeople of all marketing activities within a particular health system or territory. Nonetheless, centralizing previously siloed information can create uncertainty around dataset quality. Thus, teams should be trained on the shift with an emphasis on trust ahead of data centralization.
Pharma companies can use external healthcare data to find patients who are at high risk of disease. But in using these data sources, companies should be cognizant of data privacy procedures and secure permissions to access data. To enhance efficiency, a representative sample can be used to minimize the need for full coverage of a particular patient segment. Where data gaps are prevalent, internal teams should be transparent instead of making unsound inferences.
To pursue a more patient-centric business strategy, pharma companies need to go through an overall cultural shift. Establishing a data governance model can anchor a data-driven culture within the organization. To adopt strategic and cultural change, organizations should start off small when incorporating data into their decision-making process to establish a minimum viable product.
Industry Experts Who Contributed:
- Thomas Lampron, US AVP, Woman's Cancers and Eisai Collaboration Leader, Merck
- Mayank Misra, Head of Business Insights and Analytics, Takeda Oncology
- Ketan Paranjape, VP, Commercial Business Operations, Business Intelligence and Analytics, Roche
- Dr Kenneth Park, SVP and General Manager, Life Sciences Solutions, Clarify Health
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