Organizations have some major incentives for using embedded analytics, as doing so can significantly boost operating efficiency. Moreover, embedding analytics can enable users to access data insights from anywhere, even without business intelligence tools at hand. If your app or service creates data, letting your users explore that data makes it more valuable and that’s what embedded analytics lets you achieve with ease.
5 Key Features and Benefits of Embedding Analytics
1. Better Business Decisions at All Levels
The underlying reason for data analytics is to improve business operations. When you have the information to make good choices, that power can make an entire enterprise more efficient. Unlike many business intelligence tools that require training or deep knowledge of data, embedded analytics can be used and understood by most workers. Due to the universality of embedded analytics, it’s much easier to spread the power of data throughout an organization. This leads to better business decisions at all levels of the company.
2. More Streamlined Workflows
Workflows are an essential consideration when reviewing the overall operating efficiency of a business. If workers are spending time on unnecessary or redundant tasks, that’s money coming out of the bottom line. Furthermore, employees don’t want to feel bogged down at work, which can often be the case when they’re forced to function within a poorly designed workflow.
Embedded analytics is the perfect BI tool for improving the workflows of regular employees. This is because embedded analytics can take useful BI visualizations and put them right next to what you’re working on in other applications. With this flexibility, workers are freed of switching between different programs to do their jobs and can focus more intently on the task at hand.
3. Greater Data Democratization
People who have been in the business world for a few decades have seen data’s progression from being kept under wraps to being used by many people within an organization. This change can largely be attributed to data democratization. The idea here is data is actually far more useful to enterprises when it’s taken out of the dark and brought out to be used by everyone who has a need for it.
In the past, executives were worried about security and the accuracy of analysis when letting too many people interact with data. While these are still valid concerns, technological advancements — including embedded analytics — have made data democratization a far more appealing idea.
For starters, democratizing data through embedded analytics means more people within an organization are going to work with, and find value in, data. One of the great benefits of using embedded analytics is people don’t need specialized skills to extract value from information. When a wider variety of people can use data productively, organizations can grow faster and more effectively. The fact is, data is often more valuable than a service itself, hence the need to apportion more resources into analyzing data for timely business decisions. With embedded analytics, extracted and processed data can be monetized.
Further Reading: Understanding Sentiment Analysis and Semantic Analysis
4. Develop a Data Culture
When you get enough people within an enterprise working with data all the time, it’s going to start making a difference beyond individual decisions. This is often referred to as establishing a data culture. An organization that has a culture of data inherently looks to measurement-based approaches to problem-solving. In other words, people will more often use evidence over emotion when making business decisions, which is exactly what an enterprise should be striving for in this era.
5. Accelerate ROI
Because the return on investment (ROI) of business tools is directly related to the utilization, embedded analytics gives enterprises an opportunity to achieve positive ROI on data infrastructure investments much sooner.
Think of a company that uses embedded analytics versus one that decides against it. The business incorporating embedded analytics is setting up its employees to have infinitely more opportunities to use data for decisions. By simply putting embedded analytics into an employee’s toolbox, you’re fostering a situation where all team members provide frictionless ROI.
Conclusion
The benefits of embedding analytics outweigh any amount of investment in setting it up and it will be a colossal error for business executives to overlook the trends of embedded analytics in this digital era. Think of Fitbit’s business model of data capturing and interfacing with the audience. Capturing the data is excellent, but exposing it to users to be able to explore it makes it much more fun and valuable as part of the overall product experience – thereby having a positive impact on the company’s overall acceptance and income. This is a perfect example of creating an embedded user experience along with a business model.
Going forward, embedding analytics should be part of your 2021 business investment and execution goals.
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