Advanced Analytics & Operational Intelligence: A Perfect Marriage?

In today’s fast-paced, data-driven economy, traditional Business Intelligence moves too slowly since it uses historical data to inform future decisions. With the growing volume, variety, and velocity of data and the demand for an enhanced customer experience, enterprises need to rapidly sense and respond to changing business conditions in real-time.

Operational Intelligence – the ability to sense and respond quickly to changing business conditions – complements Business Intelligence by taking into account the real-time status of business processes as they occur.

Business Intelligence uses traditional approaches, such as data warehouses or relational database management systems, to build static data models on historical data for future decisions, wherein the data and reports are disconnected from the activity streams. However, Operational Intelligence uses all types of data and information, including unstructured data types, to provide real-time information tied to the business processes.

Operaional Intelligence Use Cases

Figure 1. Operational Intelligence Use Cases

The benefits of Operational Intelligence are far-reaching and applicable to a wide range of industries. A few examples across such verticals are:

Process Manufacturing

Manufacturers strive to minimize downtime, reduce scrap rate, and optimize performance, but it can be difficult to achieve when faced with complex processes and scores of systems and applications.

Operational Intelligence helps manufacturers excel in the following areas:

  • Creating a highly responsive supply chain to meet the needs of customers
  • Monitoring performance and uptime of systems and applications
  • Providing visibility into complex processes and ensuring continuous and efficient operations

Telecommunications

Communications service providers (CSPs) operate large networks on a global scale. With converged services, device proliferation, and new competition, CSPs are seeking ways to move from a connectivity-based business model to a value-based business model to have a prominent role in the value chain.

Here are some examples of how Operational Intelligence helps CSPs achieve this goal:

  • Network Service Assurance
  • Customer Experience Management
  • Real-Time 1-to-1 Marketing
  • Fraud Detection & Prevention
  • Real-Time Billing

Financial Services

Retail banks, investment banks, and insurance companies generate terabytes of data daily for high-volume activities, such as trading, payment or claims processing, and multichannel banking.

With Operational Intelligence, financial service firms benefit from the following:

  • Fraud Detection & Prevention
  • Regulatory Compliance
  • Customer Experience Management

Operational Intelligence provides enterprises real-time visibility and continuous insights into data, events, and business operations. Operational Intelligence provides a continuous view of business processes to support greater business agility. The ability to make timely decisions based on real-time insights hinges heavily on the ability to execute across the analytics value chain – streaming analytics, historical analytics, and predictive analytics. Recent advancements in analytics have paved the way for Operational Intelligence.

Enterprises can complement Business Intelligence with Operational Intelligence to optimize business processes in real-time to avert interruptions, avoid bottlenecks, or drive new services.

Advanced Analytics For Operational Intelligence White Paper

To learn more about how advanced analytics enhances Operational Intelligence, download the white paper now.

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