Turning Information into Insights
Becoming a data-powered business is an essential strategy for insurance brokerages in the “Age of Data.”
organizations are 110% more valuable than
their less analytically driven peers.
Strategy Meets Action (SMA) Survey 2018
of agents are investing in diagnostic analytics tools.
of companies will be using data-driven business insights by 2020.
Benefits of Data Analytics
Leading brokerages understand that yesterday’s reporting is no longer sufficient in today’s highly competitive and changing insurance marketplace. Armed with superior data and analytics tools, you position your brokerage to compete with traditional competitors as well as emerging Insurtechs.
Drive greater business value with data analytics:
Visualize opportunities and risks at a glance
Optimize internal business operations
Make faster, more informed decisions
Unlock the Next Chapter
Data analytics is using specific technologies and business processes to gather, organize and analyze a company’s existing data to provide greater insights into operations for faster, more informed decision making. Like other technologies, data analytics solutions have rapidly advanced and are extremely accessible to any business regardless of size, revenue or IT resources. Data-powered businesses gain a competitive edge through enhanced decision making, insight discovery and process optimization.
What is data analytics?
of all data in existence has been created in the last two years.
of organizations will use analytics in key business functions across the enterprise by 2020.
of global enterprise data is still unexploited for better business insights.
Introduction to Data Analytics
Arthur C. Nielsen, Market Researcher & Founder of ACNielsen
“The price of light is less than the cost of darkness.”
“By the year 2020, 1.7 megabytes of new information will be created every second for every human being on the planet.”
What agencies have lacked is true insights from data analytics.
An explosion of data has accumulated since the 1990s when insurance businesses started to collect huge amounts of disparate data that could be used to support decision making. The norm for most insurance agencies has been to turn that raw system data into antiquated reports focused on financial metrics to inform operations and strategic planning.
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John Tukey, Mathematician
“The greatest value of a picture is when it forces us to notice what we never expected to see.”
Data analytics goes further by providing a root-cause analysis and answers more complex business questions such as “why did it happen.” Data analytics is designed to explain business results and what might happen in the future versus simply giving a description. Characterized by drill-down, data discovery, data mining and correlations techniques, data analytics is more advanced in how it analyzes data and delivers multiple levels of analysis via highly graphical, interactive dashboards. Because data analytics solutions are automated and utilize real-time information, users are empowered to make faster, more insightful decisions across many aspects of a business – without spending countless hours manually pulling reports.
How do reporting and data analytics differ?
What’s missing from reporting is the ability to understand why something happened.
Traditional reporting provides historical business insights at an aggregate level by summarizing raw data to answer the question “what happened” at a specific time in the past. It is usually performed manually, with the resulting output in the form of static data in Excel spreadsheets.
Andrew Chen, Rider Growth Head, Uber
“Don’t build metrics that aren’t going to be part of your day-to-day operations. Building reports that no one looks at is just activity without accomplishment, and is a waste of time.”
Move Beyond Simple Reporting
False. Traditional reporting summarizes raw data to answer “what happened” at a specific time in the past. Data analytics is capable of answering more complex business questions to explain business results.
Test Your Knowledge
Report measurement criteria can’t be easily changed. When pre-determined criteria are modified, the report produces a single, specific outcome.
Only analyzes past events.
Snapshot of a past point in time.
Assists in predicting future outcomes based on real-time analysis of business performance.
What happened and why.
Real-time business performance.
Users can easily change one or more measurement criteria to produce an entirely new view of the business.
True or False. “What happened” and “why it happened” are questions traditional reporting answers.
Budget constraints are not a key driver to embracing data anatytics.
Which is not a key driver to embracing data analytics:
"This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization."
Key Drivers to Embracing Data Analytics
Let’s examine the key drivers pushing forward-looking insurance brokerages to embrace data analytics:
The insurance landscape is no longer static. It’s dynamic and agile. In this new environment, reliance on outdated, manual reporting is no longer sufficient.
Data Analytics Drivers
A flood of new competition from InsurTechs who have a digital-first mindset.
of insurance customers use InsurTechs exclusively or in combination with incumbents.
Power has shifted from businesses to consumers.
The speed of business has increased and the bar for service raised.
Less time to do more.
The industry is overflowing with data amassed over the course of decades.
Explosion of data.
of consumers say technology makes it easier to take their business elsewhere.
of consumers expect companies to respond and interact in real time.
Stored data is growing at 4x the speed of the world economy.
Less time to do more
Explosion of data
“Information-centric organizations are 20% more profitable and 110% more valuable than their less analytically driven peers.”
Thrive in the Age of Data
To thrive in the age of data, brokerages need to have the ability to gather, process and get insights from data in real time across the entire business.
The industry is moving at a faster pace and today’s insurance consumer is more connected than ever before. At the center driving it all – is data.
• Determine how profitable their book of business is
• Adjust sales practices to improve profits
• Reduce time wasted on unresponsive policyholders
• Increase per agent and per customer profitability
• Maximize overall business profitability
Specifically, data analytics empowers brokerages to:
fear failing to use data analytics puts them at a competitive disadvantage.
already use analytics in key business functions.
consider data analytics a top strategic priority.
Although data analytics solutions have traditionally focused on areas of interest to brokerage principals and owners, these applications have evolved to provide more expansive insights of value to the entire business, including Sales and Accounting departments.
The Why Behind the What
With this in mind, consider data analytics to evaluate performance in the following core areas of your business:
• Which insurers are the most responsive?
• What ratio of business is placed with one or more insurers?
• Are we placing business with the
• Are we trending toward our projected fiscal performance?
• How are we trending year over year?
• Are we managing our accounting on time?
• Are we retaining clients?
• Which policy types are stickiest?
• Are we acquiring new clients?
• Can we expand into new regions? Which ones?
• How can we round out current accounts with new LOBs?
Book of Business
• Who drives the most revenue?
• Whose performance is lackluster?
• Are there workflow issues?
By 2020, the rate of those using data analytics is expected to double.
True or False. Information-centric organizations are 20% more profitable than their less analytically driven peers.
True. They are also 110% more valuable.
With data analytics successfully woven into the fabric of your brokerage, the better the decisions and the better business outcomes will be. By fully leveraging the volume, velocity, variety and value of data with analytics, you position your brokerage to retain current customers, acquire new customers, streamline operations, increase profitability and remain a viable competitor now and in the years ahead.
Start your data analytics project by determining what business criteria you want to evaluate with your data insights. Obtain the perspectives of everyone who will be using the tool – such as principals, producers, CSRs, marketing managers, accounting managers and claims managers – and have the group jointly define key business problems and the value of the analytics.
5 Point Framework for Data Analytics Success
While implementing data analytics into your brokerage has never been easier, the impetus to invest in data analytics never greater, and the time to adopt data analytics never better, a thoughtful approach and plan of action are key to success.
Peter Drucker, “The Founder of Modern Management”
“What gets measured gets improved.”
How To Achieve
Data Analytics Success
1. Define the business value.
Successful adoption requires employees to accept and trust the data analytics tools, understand how they work, and use them consistently. Managing this phase by ensuring people are on board, have the training they need, and know what is clearly expected of them with the data analytics tool is vital.
5. Manage adoption.
Incorporate data analytics review and analysis in your decision-making process. You can use it to design more effective work practices, efficient information flow, actionable reporting, improved transparency, and increased relevance of communications. This poses a significant behavioral challenge, so make sure that the data analytics solution you choose makes sense to those involved in using it and can be easily integrated into their workflows.
4. Integrate decision workflows.
It’s essential to have a clear vision of what the data insights are that you are looking to achieve. Define what key performance indicators your organization is trying to better understand, determine the level of frequency that you want your business reviewing the data, and consider if there are benchmarks that you would like to analyze your data against. Through this process, be open to identifying potential other data analytics possibilities, giving you opportunities to gain further knowledge and insights you didn’t even know you needed.
3. Outline your insights.
Because there are multiple sources for data, your brokerage needs to implement the technology and methodology to build a data architecture that is secure, fosters collaboration, and can easily scale as business demands grow. This is known as the data ecosystem. Your data ecosystem should serve as a single place where internal and external data can be organized, integrated, engineered, and modelled.
2. Create your data ecosystem.
Data Analytics Designed for Your Business
Applied Digital Brokerage Annual Report
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