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How Embedded Analytics Supports Digital Transformation

Blog: The Tibco Blog

Reading Time: 2 minutes

Today, most business users of business intelligence (BI) face challenges. Mainly, insights and recommendations are delivered in separate applications from the ones that business users spend most of their time in and actually use. 

A recent report from Constellation Research indicates that to succeed with digital transformation, you need to ensure analytics are available within the transactional applications where business users spend most of their time. This embedded analytics approach will, according to Constellation, help speed decision-making and power new business models. 

According to the report, embedded analytics has evolved significantly. Formerly used only by those enterprises that could manage the associated IT complexity, using embedded analytics is now more standard practice for innovative companies of all kinds. They use embedded analytics to meet the rising demand for easier and faster decision-making; the pursuit of innovation and new business models; and emerging opportunities to harness prediction, machine learning (ML), and automation. The need for intelligence everywhere means traditional BI tools that don’t enable embedded analytics are no longer enough.

Traditional BI tools can lead to “analysis paralysis,” where there are too many conflicting dashboards and reports, and users have to repeatedly decide which one to trust. Traditional BI tools that promise to enable “self-service” analytics are often too complex for true business user self-service. The weekly/daily reports that have been a mainstay of traditional BI aren’t current enough for modern decision support, leading many companies to turn to dashboards for up-to-the-minute data. However, even dashboards are often housed in a different location from the application where the business user is spending her time, slowing time to insight and action for users. 

For instance, a user may spend most of her day in Quickbooks, tracking invoices. She also needs critical insights on a minute-by-minute business that affect her daily tasks like late payments, checks that didn’t cash, and similar. In order to connect those insights to invoices, she has to manually jump from application to dashboard to an application, slowing her productivity and introducing the chance for error.

To meet the demands of digital transformation, users need to see actionable insights in context. You need to put the data where the business user needs it – in the transactional applications that they use every day. 

Download a complimentary copy of this report from Constellation Research for a complete discussion of the different levels of embedded analytics available, some terrific case studies of embedded analytics from real estate to manufacturing, and the top five questions you need to assess the right approach for building an embedded analytics solution for your organization. 

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