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Harnessing Data: The Key to Smarter & Informed Decision-Making

November 15, 2023

Data forms the backbone of every industry, acting as the compass that guides our choices and plans. Without well-structured, reliable data, navigating the path to impactful decisions becomes convoluted and fraught with inaccuracies. Relying on flawed or disjointed data can bring severe consequences, leading companies down a road of significant setbacks. 

The importance of high-quality data becomes even more evident when we consider the insurance industry. According to McKinsey & Company, top insurance providers are leveraging data and sophisticated analytics to revolutionize risk assessment, augment customer experiences, and boost decision-making and efficiency within the underwriting process.  

Navigating the Data Landscape: A Guide for Insurers 

Data, with its vast potential, can often present complexity and challenges, particularly for insurers who are in the early stages of integrating smarter data insights into their operations. Understanding these challenges is the first step towards effective data management:  

  1. The Rapid Pace of Data Generation

    In the digital age, data grows exponentially at an unparalleled rate. For insurers, this can create a wealth of potential insights but can also bring challenges in capturing, processing, and analyzing data in a timely and efficient manner. Falling behind could lead to missed opportunities or erroneous decisions based on outdated information.
  2. The Hurdle of Data Diversification

    Data often originates from multiple sources and in multiple formats. For insurers, data comes from policyholders, third-party vendors, internal operations, reinsurers, and more. Having many sources of data can lead to a lack of uniformity and present a significant challenge when it comes to consolidating and interpreting data accurately, which could lead to misinformed decisions and missed insights.
  3. The Challenge of Data Visualization Complexity

    Data visualization tools are intended to simplify the representation of complex data, making it easier to uncover important insights. However, for insurers who are new to the world of modern data analysis, understanding and using these tools effectively can be a daunting task. If not navigated correctly, important insights about an insurer’s business may remain untapped or misunderstood.

3 Examples:  Detrimental Consequences of Inadequate Data-Driven Decisions 

According to Gartner, poor data quality can cost organizations an average of $15 million in losses annually. The repercussions of decisions based on poor data transcend industry boundaries, impacting various sectors in significant ways.  

  • In 2022, a credit bureau miscalculated credit scores for millions of consumers due to a coding issue, affecting 300,000 individuals and causing erroneous loan rejections. This mishap led to a 5% drop in their stock prices and a class-action lawsuit. The company had previously lost public trust due to negligent security practices resulting in a massive data breach. Their response involved moving their systems to a cloud environment for better control and monitoring.  
  • In the same year, a tech firm known for its 3-D content platform faced a significant data issue with their tool designed to aid game developers with marketing and advertising. This tool ingested bad data, leading to inaccuracies in the training sets for its machine learning (ML) algorithms and performance drop. The firm’s revenue-sharing model was directly affected, resulting in a loss of around $110 million. This incident caused a 37% drop in the tech firm’s shares and a loss of investor faith. 
  • In 2021, an insurance company experienced substantial financial losses and a severe hit to their stock prices because of their reliance on inconsistent and faulty data for underwriting and policy pricing. This led the company to adopt better predictive algorithms for improved pricing and faster claims. 

These instances underscore the substantial risks and repercussions of relying on poor quality data, highlighting the critical need for accurate, timely, and reliable data in decision-making processes across all industries. 

5 Strategies to Enhance Data Effectiveness 

The road to superior data management requires a precise and structured roadmap. Here are some key tactics that organizations can adopt to ensure they’re leveraging their data optimally: 

  1. Unify Your Data

    Centralizing all of your data in one place can alleviate the risk of missing crucial information that’s scattered across various locations. A unified data warehouse or a cloud-based platform can be instrumental in data consolidation.
  2. Swift Data Processing

    In today’s fast-paced world, data is generated at a breakneck speed. Organizations must ensure prompt and efficient data processing. Tools that enable real-time data processing and analytics can help manage large volumes of data and facilitate timely decision-making.
  3. Standardize Data Formats

    Inconsistent or incompatible data formats can lead to misinterpretation and error. Organizations should establish standardized data formats and guidelines for data entry and processing. Data transformation tools and automated data cleaning processes can play a crucial role here.
  4. Guarantee Data Accuracy and Security

    Data integrity and security are paramount. Implement stringent data validation checks and data audits and maintain robust security protocols to ensure data accuracy and protect sensitive information.
  5. Simplify Data Visualization

    The efficiency of decision-making can be substantially improved by presenting data in a simplified, comprehensible format. Data visualization tools that provide interactive dashboards and graphical representations of complex data sets can ensure that insights are easily understood and accessible to decision-makers. 

When implemented correctly, these strategies can help organizations navigate the data management maze and unlock the full potential of their data. 

Duck Creek Technologies: Guiding You Towards Effective Data Management 

At Duck Creek Technologies, we recognize the importance of quality data and its role in effective decision-making. We are committed to helping organizations streamline their data management processes. With our tools, insurers can identify opportunities for upselling, segment risks for profitable underwriting, and detect fraud to reduce claim costs. By partnering with a reliable provider like Duck Creek Technologies, your organization can be primed to make the most of your data and the insights data brings to your business.

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Elaine Rogalla
Director, Product Manager
Elaine is the Product and Strategic Leader of Duck Creek’s Claims and Insights products. She is responsible for understanding the voice of the customer and defining the R&D initiatives for the success of these products. Elaine has spent her 15+ year career in the insurance industry, beginning as a claims professional at Liberty Mutual with direct experience handling personal auto and homeowners claims as well as managing large teams of claim handlers. Elaine joined Duck Creek in 2019 as a Claims Product Manager. She holds an MBA from DePaul University with concentrations in Leadership and Change Management and Entrepreneurship.