Data Strategy Behaviors

According to recent research, while companies are investing in data technology, many are still falling short with their data initiatives. The research from Vantage Partners Data and AI Executive Survey 2022, indicates that 92.2 percent of companies continue to identify culture (people, process, organization, and change management) as the most significant impediment to becoming data-driven organizations.

People & Culture

Refers to how we bring together business knowledge, technical skills, data skills and culture across the organizations. For example, historical Pricing and Actuarial ways of working hid ineffective data processes. These ways of working were largely driven by legacy tool sets which created entrenched behavior. Those insurers that moved away from legacy tools, embracing advanced data processes, meant they were able to leverage advanced data techniques and new data sets to drive change at pace. The outcome for early movers was the improved accuracy of risk models, more granular analytics which supported better customer conversion and retention, as well as reduced cost of claims. Unfortunately, for those insurers that remained with the legacy mentality, the cost of change increased affecting profits, competitiveness, and increasing customer churn.

Change Management

There is no “one-size-fits-all” solution for change management. Many businesses believe that they must compile a list of stakeholders and work with champions to implement the necessary change. In reality, change is more profound than collaborating with key stakeholders. It requires a fundamental mindset shift, as well as building coalitions with teams at all levels of the organization to ensure an understanding of the need for change, and motivation for success. Incentivized stakeholders will more likely support a data-driven organization and drive new behaviors, change policies, and implement measures to track people-based success factors.

Operating Model

How do insurers organize data and analytics teams around the business need for speed and responsiveness, quality of service, customer experience, and the changing landscape of regulations?

An operating model defines how the delivery of services and capabilities will be distributed across an organization and acts as the basis for defining interactions between the key groups. There are a number of different operating models that insurers can organize their teams around:

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There isn’t one straightforward and efficient operating model for organizations. Insurers need to evaluate the organization’s maturity, skills and capability gaps, data, and analytics requirements before selecting the right fit.

As well as this, we know that an organization culture already exists, and we work with key practitioners, to ensure data is weaved into the culture, complementing data literacy and fluency efforts.

Key business and data professionals are encouraged to collaborate effectively and build momentum, that leads to innovation and making brave decisions. Insurers should consider using data maturity assessments to pinpoint cultural issues and create a of data initiatives to ensure successful adoption and implementation.