Customer Engagement – One Chapter Ahead Series
Home / Intelligence / Blog / Foundational Differentiation: CE Requires Efficient Operationalization of Data
Published November 5, 2024
What is data operationalization, and why is it important in life sciences?
The ability to integrate insights from your data into your business workflows is commonly referred to as data operationalization.
Throughout life sciences organizations, functional needs and behaviors have evolved, making data operationalization at scale a vital source of competitive advantage for life sciences.
It is no longer enough to derive business strategy from data to ensure a competitive advantage. Executives now expect real-time updates from the market—and patients and prescribers expect seamless omnichannel experiences. The differentiator is in connecting petabytes of data from multiple sources quickly to optimize tactics.
Today’s customer engagement activities are more targeted and personalized, requiring precision and frequent refinement
The Data Foundation
Historical
Today
Field & Sales Execution
Field & Sales Execution
Static target lists based on market deciles
Dynamic targeting and segmentation
Marketing
Marketing
One-time campaign planning and few messages
Continuous refinement and flexible journeys
Executive Leadership
Executive Leadership
Weekly and monthly reports
Daily tracking and forward-looking insights
Patient Services & Market Access
Patient Services &
Market Access
Siloed and reactionary
Collaborative and prospective
Finance
Finance
Scorekeeper and gatekeeper
Partner to business optimizing channel and payer contracts
Where should life sciences organizations focus as they operationalize data?
To support the increased need for nuanced, targeted insights that are continually refining, data operationalization should be developed with these things in mind:
- Data contextualization—When integrating third-party and first-party datasets, incorporating nuanced business rules improves relevance of the data and drives better understanding.
- Alignment on performance metrics and definitions—Cohesive goals and reporting encourage collaboration and clarity.
- Automated data ingestion and quality checks—Speed and accuracy are lost if the organization relies on manual processes or human intervention.
Setting up an efficient, scalable data foundation is integral to success in customer engagement. A robust and operational data foundation will enable both strategic and operational impact. Savvy companies will also be vigilant for new ways to augment their existing data to bring more actionable customer, channel and content intelligence.
Authors: Nancy Phelan, Paramita Kar & Vishnu Prashanth Veerasamy
This blog is part of the One Chapter Ahead blog series, a Customer Engagement-focused thought leadership initiative to bring an informed, inspired point of view. Our intent is to bring a fresh perspective, driven by data, benchmarks, insights and expertise.
Other blog posts in this series:
Have a question? Reach out to our experts.
Ask Us A Question | Schedule A Meeting | info@trinitylifesciences.com
Explore Trinity Customer Engagement | www.trinitylifesciences.com
Technologies and approaches that leverage advanced analytics and AI for driving commercialization strategies will have a significant impact on LSOs. We expect digital life science platforms to be mainstream in the next five to 10 years, enabling them to nimbly adapt their business and operating models in response to external disruption and change in business strategy.
—Gartner®*
In the August 2024 Gartner® Hype Cycle™ for Life Sciences Commercial Operations report, Trinity Life Sciences is recognized as a Sample Vendor in the following sectors:
- AI in Commercial Operations
- Advanced Decision Support for Sales
- Personalization Engines in LS (Life Science)
- D&A (Data & Analytics) Platforms in Commercial LS
*Gartner, Hype Cycle for Life Sciences Commercial Operations, Animesh Gandhi, published 13 August 2024.
GARTNER is a registered trademark and service mark of Gartner and Hype Cycle is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Related Intelligence
Webinars
Who “Owns” the Customer in Customer Engagement?
Available On Demand
In your company, is it Sales, Marketing, Analytics, Operations, Medical…? If you are struggling to answer this question, you are not alone. With the rising adoption of digital and virtual approaches to customer engagement, companies are facing more complexity in commercialization. Organizations that lack clarity find that achieving the desired impact from customer engagement strategies […]
Watch Now
Blog
Integrated Data + Hyper-local + Cross‑channel = Customer Engagement
The customer is changing The landscape around life sciences is more competitive than ever, with a shorter runway to success and market dynamics (payer, competition, etc.) that are indisputably changing the role and level of influence at a customer level. These changes are happening at a hyper-local level, not just at a homogenous national level. […]
Read More
Blog
Get Ready to Orchestrate a Better Customer Experience
What does orchestration mean for a brand? True orchestration considers a customer’s preferences before communicating with them. Learnings from past interactions and outcomes are used to identify the most relevant action to lead to a rewarding experience for both the customer and the brand. Orchestration can be defined as all channels learning from each other […]
Read More