Insurers Behind on Data Mastery: SMA

The explosion of data coming from new devices and technologies has potential to transform insurers’ business strategies. Many have begun prioritizing BI and analytics capabilities to manage their information; however, the challenge of data mastery prevents most from uncovering intelligence.

Data mastery describes the ability to leverage and manage data as a strategic asset to derive transformative business insight. The Strategy Meets Action (SMA) Data Mastery Model depicts a framework that can help insurers evaluate their current levels of data mastery and develop a plan to move ahead.

“In today’s new digital world, data is increasingly critical to the future,” says Denise Garth, partner and chief digital officer at SMA. “We’ve always understood that data is the lifeblood for the industry, but we’ve never quite managed it as the strategic asset that it really is.”

The model represents five levels of data mastery maturity, each of which contains six defining components. Insurers can range from the ad hoc stage, which describes industry laggards lacking organization, to the transformative and innovative level reserved for market leaders with CEO-sponsored data strategies. Other stages include tactical (beginner mainstreamer), organized (advanced mainstreamer), and strategic (market movers).

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Data mastery must address six key areas, according to SMA. These include strategy and focus, organizational and sponsorship, data integration, governance and data quality, the business intelligence and analytics spectrum, and the data sources spectrum. While some organizations may place more focus on certain areas over others, each requires attention in order for a business to mature, Garth explains.

To best address the six key areas that boost maturity, insurers must focus on essential capabilities such as defined KPIs, enterprise architecture, C-level sponsorship, a mature enterprise data model, and the integration of BI and analytics into core business processes and workflow. Business-wide initiatives are necessary in order to comprehend the power of data mastery, according to the SMA report.

Regarding current progress in data mastery, the industry is in hot water. SMA research found that 55% of P&C and 34% of L&A companies are classified as laggards or beginner mainstreamers. Fewer have proven superior – nearly 40% of L&A and 24% of P&C insurers are at the organized or advanced mainstreamer levels.

The marked gap between L&A and P&C insurers took SMA by surprise and could be due to a difference in prioritization of core system replacement. Although legacy systems are a hindrance to data mastery, L&A insurers that have not yet started to replace them would have more time to implement enterprise data models, says Garth.

“There is probably higher focus in P&C for core legacy system replacement that offers an opportunity for these insurers to put in place an enterprise data model that will allow them to move to higher maturity levels,” she explains.

In addition to legacy systems, organizational silos can impede progress. Enterprise-wide support is critical, Garth says, and lack of collaboration is a hindrance. Data mastery is not a project for IT, but a business-driven initiative that should begin at the executive level and encompass each department.

“Achieving data mastery starts from strategy, C-level engagement, and having an enterprise architecture with a data model and data dictionary that brings together the entire organization, eliminating the silos,” says Garth.

Insurers in the early stages of developing their strategies should first determine where they stand across the six core elements then plan to align their strategy to their business goals. Not every organization wants to immediately achieve the top level of data mastery; some may start by aspiring to reach mainstreamer level.

With the ever-growing mountains of data insurers face each day, the time to act is now. “The longer that insurers wait to get a handle on their data mastery maturity, including their strategy and data model, the more difficult it will become to leverage the exploding amount of data coming from the new and emerging technologies that are redefining the new digital world,” Garth cautions.

Kelly Sheridan is the Staff Editor at Dark Reading, where she focuses on cybersecurity news and analysis. She is a business technology journalist who previously reported for InformationWeek, where she covered Microsoft, and Insurance & Technology, where she covered financial ... View Full Bio