Getting in the Driver’s Seat With Business Analytics


By Fernando Larez – @mando_vzl
Marketing Manager at @VUESoftware

No doubt we’ve got plenty of useful data today — but it can be like a shiny new sports car that requires a slow, deliberate chauffeur! Maybe you’ve had the experience of needing a report and waiting weeks or more for someone to generate it. The data is stale and almost useless by then. Fortunately, analytics gives you the keys to the car.

Using a solid business analytics platform, you can slice and dice data however you want and generate custom reports when needed — without technical knowledge. Analytics, a computerized statistical tool, identifies meaningful data patterns. It performs a high-speed data analysis, then presents the results in easily understood formats that help you make rapid, informed decisions.

Key Performance Indicators

Analytics measures Key Performance Indicators (KPIs), which are areas your company determines are critical to monitor for success. The possibilities are nearly limitless. Here are a few:

  • Ratios for converting prospects to customers
  • Profit/loss ratios
  • Speed of insurance policy conversions
  • Percentage of product defects
  • Sales of a targeted product
  • Sales within a certain geographic area or for a particular demographic
  • Customer satisfaction and retention
  • Individual and collective business performance
  • System up time


A bit like the dashboard on that sports car, analytics dashboards present data in visual formats such as graphs, pie charts and maps. You get a bird’s-eye view of trends, comparisons and data concentrations for fast decision-making. It’s easy to build reports for your own use or to share with upper management or others on your team.

Good analytics software lets you drill down into details, fine-tune queries and customize further analyses from there. For example, an insurance carrier might target all producers in a given geographical area, identify current top performers and then determine what incentive would best motivate them to sell a new product.

Data Mining

Before results appear in the analytics dashboard, the analytics engine uses data mining to detect and extract relevant data based on your criteria. Data quality inconsistencies and legacy systems — which are older, often homegrown applications that may have been pieced together over time — can be data-extraction challenges. That means a robust analytics platform is important.

Big-Data Use

Big data refers to data stores that exist in extremely large volumes, run at very high speeds and/or contain a wide variety of data sources and types. Traditional systems are inadequate for processing big data, which forces a company to adopt new data management methods. Analytics is a must for making sense of big data and leveraging its great value.

The insurance industry in particular needs high-performance analytics for extracting critical information from massive, complex data stores. Claims processing creates extremely heavy demands on a continuous basis. There’s also a huge data-handling burden from financial accounting, statutory reporting, producer management and other tasks.

Decisions and Actions

Improved decision-making with analytics helps you discover solutions to business problems and boosts your success. For example, the saying goes that hindsight is always 20/20. With predictive analytics, you get business insight to understand trends and forecast probable outcomes. You’ll be able to predict future performance, then make strategic decisions to modify existing tactics for better results. This helps with everything from cross-selling and customer retention to incentive compensation design and direct marketing.

Need hindsight? After you’ve made changes in products, services, features, pricing, programs and so on, analytics lets you evaluate results with before-and-after, cause-and-effect comparisons.

Real-time analytics makes you more nimble than competitors. You can conduct strategic reports on-the-fly and respond quickly to market changes with compelling product offers, marketing plans and sales incentives.

Insurance Industry Advantages

For insurance, analytics is a powerful, time-saving tool for putting data to work. You might choose to track KPIs like profit/loss ratios, conversion ratios for account and policy renewals, and policy conversion velocity. KPIs involving sales goals, producer performance, incentive results and underwriting risk levels guide decision-making and directly impact profitability. Insurance analytics also helps to align sales performance with company objectives through strategically designed incentive plans that motivate agents.

A top analytics platform provides performance indicators and customizable dashboards. It even generates automatic alerts when specified metrics go out of range. You can customize the platform to support insurance-specific tasks you perform regularly. For example, a good platform will let you create personalized views and custom reports according to insurance product lines, the most recently quoted plans, organizational hierarchy, geographic territories assigned to producers and many other dimensions.

The insurance industry handles vast amounts of data across multiple sources, making analytics a must. Insurance is so data-driven that those who can’t effectively leverage analytics across their entire dataset are likely to struggle with inefficiencies and lose ground to competitors. It’s important for insurance organizations to do the research to find the best analytics platform for their needs.

The next step is the sports car. By the way, have fun driving. There’s no speed limit! and share your thoughts with us in the comment box below.


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