What is the difference between Operational Intelligence (OI) and Business Intelligence (BI)?


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March 09, 2021

What is the difference between Operational Intelligence (OI) and Business Intelligence (BI)?

Understanding the differences between operational intelligence (OI) and business intelligence (BI) is crucial to contextualizing and taking action on the information and insights provided by your analytics toolset. While both operational and business intelligence are used to drive action and inform decision making, there are key differences that distinguish these two areas of analysis.

Business intelligence maintains a relatively narrow focus with an emphasis on finding efficiencies that optimize revenue or profitability. BI typically means taking a snapshot of data over a defined period of time in the past and reviewing it to understand how the organization might achieve better success in the future.

In contrast, operational intelligence focuses on systems, rather than profits. OI uses real-time data collection and analysis to reveal trends or problems that could affect the operation of IT systems and to help front-line workers make the best decisions about how to address those problems.

The differences between operational intelligence and business intelligence can be summarized as follows:

Business intelligence focuses on finding efficiencies that increase or protect profits, while operational intelligence focuses on maintaining the health of IT systems.

Business intelligence leverages more historical data, while operational intelligence relies on real-time data collection and analysis. Operational intelligence has been described as immediate business intelligence gained from ongoing operational functions, a definition that speaks to the real-time nature of data collection and focuses on the operational functions that characterize operational intelligence in an enterprise environment. While business intelligence typically runs within a specific data silo, operational intelligence helps organizations break down data silos to uncover trends and patterns of activity within complex and disparate systems.

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