“The rapid acceleration of big data adoption has created new business opportunities, further amplified by the COVID-19 landscape. Initially defined by three key attributes—volume, velocity, and variety—big data has since expanded to include nine additional characteristics: variability, veracity, visualization, value, vinculation, validity, vulnerability, volatility, and viscosity. While data quality and governance have long been a challenge, the sheer scale and complexity of big data have made managing and controlling data even more daunting. As the volume of data continues to grow, both challenges and opportunities are expanding alongside it.
The assumption that more data is inherently better is common, yet the true power lies in identifying the right data. Small, well-curated data sets can often be more impactful than large, unstructured ones when integrated into a company’s broader strategy. The combined potential of both big and small data holds immense promise, offering significant benefits to business performance. However, achieving a strong return on investment while addressing all twelve dimensions of big data remains an ongoing challenge. Understanding how data science contributes to unlocking this value is essential.
The emergence of big data coincided with advances in data science and machine learning, which have transformed how businesses extract actionable insights. Data science serves as the missing link, bridging the gap between raw data and tangible ROI. Forward-thinking executives increasingly recognize that data must be viewed as an asset rather than an abstract repository of information. To drive innovation and differentiation, companies must estimate the inherent value of their data and align it with strategic objectives. Data monetization depends on reframing perspectives, ensuring that data serves a purpose, and applying scientific rigor to extract value. Skilled data scientists play a crucial role in this process by leveraging analytical frameworks to generate intelligence, drive business decisions, and enable highly personalized customer engagement.
A compelling example of big data’s impact can be seen in Lincoln Financial’s approach to distribution. With a vast B2B network encompassing broker-dealers and over 300,000 financial professionals, Lincoln Financial Distributors (LFD) recognized the need to enhance its sales effectiveness. By establishing a dedicated Data & Analytics team eight years ago, the company prioritized clean, consistent, and accurate data to support analytics-driven decision-making. Partnering with IT, the organization strengthened its data governance practices, with a particular focus on optimizing sales pipeline data. Investments in analytics empowered the company to create sophisticated assets for data scientists, refining targeting strategies and optimizing engagement.
These efforts proved invaluable as the business environment rapidly evolved in response to COVID-19. As in-person interactions became impossible, the distribution team leveraged data and analytics to prioritize financial professionals most likely to sell Lincoln solutions. Advanced predictive and prescriptive models helped personalize engagement strategies, optimizing outreach efforts in a fully virtual setting. By incorporating new analytical approaches, Lincoln explored deeper insights into financial professionals’ behavior, utilizing techniques such as affective computing to understand sentiment and engagement preferences.
The salesforce benefited significantly from these data-driven advancements, utilizing a single key metric that encapsulated intelligence, predictive capabilities, and engagement prioritization. The results included improved efficiency, better segmentation, enhanced advisor satisfaction, optimized resource allocation, and increased wholesaler capacity—all contributing to a rise in sales. The recalibration of predictive models during the pandemic further underscored the power of data, with small data analysis playing a critical role in adapting to sudden market changes. By incorporating fresh insights, Lincoln refined its models to provide more prescriptive recommendations for virtual engagement, tailoring strategies based on advisors’ preferences for digital versus in-person interactions.
As businesses navigate the evolving landscape, the ability to extract meaningful insights from data remains crucial. The pandemic highlighted the necessity of understanding emerging trends and responding with agility. Lincoln continues to explore new opportunities, deepening its understanding of financial professionals’ engagement through advanced data science methodologies. The organization remains focused on leveraging insights to shape the future of virtual and in-person interactions.
Recognizing data as a valuable asset is imperative in today’s landscape. Lincoln’s data science team continues to uncover new ways to harness this value, integrating insights into products and services that enhance customer experiences. By staying at the forefront of data-driven innovation, the company ensures that its strategic approach remains relevant and impactful in the long term.
