Embedded Analytics in Your Business Applications

Introduction

“Embedded analytics is a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application.”  The definition from Gartner continues by describing that most implementations are narrowly deployed around certain business functions.

An application with embedded analytics enables users to simplify work by providing a way to analyze data important to tasks and employ that data where it’s most useful.  The data is also shareable, so insights can be used by colleagues.

Product and Services managers should think beyond the notion that embedded analytics are simply to meet their users’ expectations and needs and imagine how embedded analytics can support the evolution of those needs. A well-planned embedded analytics solution will be positioned to grow as the user’s business changes and with evolving technologies.

1. Superior Customer Service

Introducing embedded analytics into your products and services is a great way to help your customers optimize their use of your software. If you have a good product, then helping your clients optimize the value it provides is your responsibility, and embedded analytics is great way to extend the scope and value you provide.

2. Keep Users Inside Your Application

Users tend to spend time in a small number of applications.  Embedded analytics, done correctly, helps users complete their tasks and offers a greater number of reasons to remain in your application.

It’s never good when a user has to leave your application to find information that the application should be able to provide. If the user must leave to find what they need:

• They mentally draw boundaries on the types of value your product provides.
• You open the door for other applications to spread into your value stream.
• You fail to service your customer in the best possible way–by valuing their time and productivity.

3. Empower Users with a Customizable Platform

More often than not, users are more familiar with their needs than product managers and software developers. The information users need to perform a task will change often and may not be predictable in advance. Consequently, an important part of our job, beyond providing answers, is providing tools to find more answers.

Limiting information will impede innovation on the front lines, and blocks users from creating their own solutions, limiting value and pride of ownership.

4. A Means of Efficiency

Analytics and business insights are not the end-state.  Imagine the new possibilities that come with those insights. In solution ideation, it is helpful to ask yourself, “What will my customer wish to achieve now that they have timely, meaningful, and personal analysis?”  Once equipped with some thoughts, seek to deliver tools that allow users to achieve that next level of usability, efficiency, and productivity.

Analytics are great and easy to deliver when they provide timely answers to known questions, such as, “how big is the job queue” or “how long is it taking to create and display a contract to a user?”  They aren’t great if the information provided isn’t relevant to the most important and timely questions.

5. To Build or Buy

The answer to this question depends on the type of product and service you provide and how data-intensive it is.

Building analytics could be the right approach if your product or service supports a singular or specific use case. 

Buying or subscribing to an embedded analytics engine is a better choice when your product or service is data driven, workflow intensive, or operates in a heterogeneous architecture.  Building yourself is too risky unless you can:

• Be more cost-effective than commercial options
• Invest in creating and maintaining a solution that embraces the evolution of your business
• Build with the commercial flexibility to seamlessly integrate new technologies and ideas

Key Takeaways

• The Embedded analytics market is not as mature as you might expect. There are many tools with different approaches and fluid functional boundaries. Expect to encounter a wide variety of solutions as you consider your path.
• Embedded Analytics for data rich, deep and wide systems need to be forward thinking. Short-sighted decision making today will become tomorrow’s limitation.
• Give your clients the power to take ownership of their experience – they’ll be loyal.

Citations

EY “Claims in a Digital Era, Data, analytics and AI transform the customer experience”
LexisNexis “2019 Future of Claims Study, Balancing Claims Automation and Empathy, February 2019”