The rise of smartphones, sensors, and connected devices in recent years has caused a data explosion. With massive amounts of data on tap, how organizations handle that avalanche of information is key.
But how do you turn your data into goldmine-worthy insights so you can truly benefit from it?
The Answer: Data Analytics
While traditional reporting provides a snapshot of what happened in the past, data analytics goes further by giving 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.
It’s more advanced in analyzing data and delivering multiple levels of analysis via highly graphical, interactive dashboards. Because data analytics solutions are automated and use real-time information, users can make faster, more insightful decisions across many aspects of a business – without spending countless hours manually pulling reports.
What Is Data Analytics?
Test Your Knowledge
True or False?
"What happened" and "Why did it happen" are questions traditonal reporting answers.
True
False
False
Traditional reporting summarizes raw data to answer “What happened” at a specific time in the past. Data analytics answers more complex business questions to explain business results.
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Why Invest in Data Analytics and Why Now?
The insurance landscape is no longer static. It’s dynamic and agile. Reliance on outdated, manual reporting is no longer sufficient in this new environment. If you want to remain competitive, it’s time to invest in data analytics to maximize the value of your data. Riches await those who do.
Make faster, more informed decisions
Optimize internal business operations
Improve financial performance
How can you harness the power of data and experience these benefits at your company?
While implementing data analytics into your agency 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.
How to Make Data Analytics Work at Your Agency
Roadmap to Data Analytics Success
7-Point Framework for Data Analytics Success
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Define business goals and objectives.
Start your data analytics project by determining the business problem you want to solve and setting well-defined goals.
2. Collect and organize relevant data.
Once you know what problem you’re trying to solve, it’s time to gather all data you need to find those answers. Because there are multiple data sources, you need to build a central data repository to serve as a single place where internal and external data can be organized, integrated, engineered, and modeled.
3. Cleanse and standardize data.
You’ve collected and combined data from multiple sources. Now it’s time for you to “clean” and filter it. Think of this process as organizing and tidying up the data, removing what is no longer needed, replacing what is missing, and standardizing the format across all the data collected.
4. Analyze and interpret data to inform decision-making.
After the data is collected and cleansed, it is ready for analysis. Data analysis is the process of using statistical techniques to examine the data and extract useful information.
5. Use visualization tools to communicate insights.
You’ve distilled your data into insights, but it may be hard for key stakeholders to digest it in its raw form. Creating visuals can help tell the story of your data in a way that everyone can understand.
6. Improve processes.
Data analytics is an ongoing endeavor; it doesn’t end once the initial pain point is resolved. You should develop ways to measure accountability, effectiveness and efficacy, and constantly compare the operation with desired outcomes, making adjustments as needed.
7. Build a data-driven culture.
To be truly data-driven, you must build a culture where everyone uses data to make decisions. This includes training employees on how to use data analytics and giving them access to the tools they need. It also involves creating a culture of accountability in which everyone is responsible for using data to make better decisions.
Ready to get started?
Read our Unearth the Power of Data Analytics eBook for tech recommendations to become more data-driven.
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463
exabytes
of data will be produced
daily by 2025
Accenture
5
exabytes
of data is produced daily
Accenture