Operational intelligence (OI) is a category of real-time dynamic, business analytics that delivers visibility and insight into data, streaming events and business operations. Operational Intelligence solutions run queries against streaming data feeds and event data to deliver real-time analytic results as operational instructions. Operational Intelligence provides organizations the ability to make decisions and immediately act on these analytic insights, through manual or automated actions

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Purpose

The purpose of OI is to monitor business activities and identify and detect situations relating to inefficiencies, opportunities, and threats and provide operational solutions. Some definitions define operational intelligence an event-centric approach to delivering information that empowers people to make better decisions.

In addition, these metrics act as the starting point for further analysis (drilling down into details, performing root cause analysis — tying anomalies to specific transactions and of the business activity).

Sophisticated OI systems also provide the ability to associate metadata with metrics, process steps, channels, etc. With this, it becomes easy to get related information, e.g., “retrieve the contact information of the person that manages the application that executed the step in the business transaction that took 60% more time than the norm,” or “view the acceptance/rejection trend for the customer who was denied approval in this transaction,” or “Launch the application that this process step interacted with

Different operational intelligence solutions may use many different technologies and be implemented in different ways. This section lists the common features of an operational intelligence solution:

  1. Real-time monitoring
  2. Real-time situation detection
  3. Real-time dashboards for different user roles
  4. Correlation of events
  5. Industry-specific dashboards
  6. Multidimensional analysis
    1. Root cause analysis
    2. Time Series and trend analysis
  7. Big Data Analytics: Operational Intelligence is well suited to address the inherent challenges of Big Data. Operational Intelligence continuously monitors and analyzes the variety of high velocity, high volume Big Data sources. Often performed in memory, OI platforms and solutions then present the incremental calculations and changes, in real-time, to the end-user.

Operational intelligence solutions share many features, and therefore many also share technology components. This is a list of some of the commonly found technology components, and the features they enable:

  1. Business activity monitoring (BAM) – Dashboard customization and personalization
  2. Complex event processing (CEP) – Advanced, continuous analysis of real-time information and historical data
  3. Business process management (BPM) – To perform model-driven execution of policies and processes defined as Business Process Model and Notation (BPMN) models
  4. Metadata framework to model and link events to resources
  5. Multi-channel publishing and notification
  6. Dimensional database
  7. Root cause analysis
  8. Multi-protocol event collection

Operational intelligence is a relatively new market segment (compared to the more mature business intelligence and business process management segments). In addition to companies that produce dedicated and focussed products in this area, there are numerous companies in adjacent areas that provide solutions with some OI components.

Operational intelligence places complete information at one’s fingertips, enabling one to make smarter decisions in time to maximize impact. By correlating a wide variety of events and data from both streaming feeds and historical data silos, operational intelligence helps organizations gain real-time visibility of information, in context, through advanced dashboards, real-time insight into business performance, health and status so that immediate action based on business policies and processes can be taken. Operational intelligence applies the benefits of real-time analytics, alerts, and actions to a broad spectrum of use cases across and beyond the enterprise.

One specific technology segment is AIDC (Automatic Identification and Data Capture) represented by barcodes, RFID and voice recognition.