Part 2: Embedded Analytics – The Value of Context

Embedded Analytics Image

In the first part of this blog, we focused on the differences in capabilities and requirements between real-time, embedded analytics-based business systems and historical enterprise systems. We’ll now go into more detail about the game-changing importance of real-time analytics that enable real-time decisions based on critical context.

The question ‘What is Happening Now?” is answered by real-time analytics—enabling business people to proactively deal with exceptions in the moment—as the why clues shift to real time so that we can direct business action in the present. Embedded analytics are expansive in scope and can answer complex questions and provide corrective action regarding topics like cash or cost management.

Just think of the automobile analogy—providing simple dashboards supporting what is happening now—we know our current speed, fuel level and tire pressure. Navigation systems predict my arrival and, if there is an exception, it gives me corrective action in real time. The embedded analytics of real-time business platforms provide the same insights to your enterprise—in the moment dashboards on liquidity, profit, corrective planning actions and alternatives that take into account multiple cross- functional implications.

Yet, the real value of embedded analytics to real-time business is being able to predict what might happen—the ability to simulate unforeseen events. This capability requires all the components of analytics working in concert with real-time capability to take action. These solutions require the speed of in-memory data management, the ability to access structured and unstructured data sources stored and accessed at their most granular level.

Real-time business platforms should support these analytics with a unified data model across all applications that is free from redundancy and can be seamlessly accessed by pre-packaged predictive algorithms providing best fit recommendations. The above provides a foundation for business scenario simulations and the ability to seamlessly adopt acceptable models into the current business operations.

Real-time business requires real-time platforms and embedded analytics to provide the necessary context to enable daily operational decisions in the moment—while simulating the impact of changes in business to capture market share. Enterprise systems based upon historical models will not get you there—today’s digital and generational transformations demand higher performance and capabilities.

The question is: Who will be first—your enterprise or your competitors—including the ones you do not know about yet? Is the value gained from the insight of real-time embedded analytics to change the direction of your business process and reveal flaws in your historical tribal understanding of the business part of your story? As always, we look forward to your thoughts and questions.

 

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