5 min read

Operational Intelligence Enters the Spotlight

Understanding the technology components of OI.

Ventana Research has defined a new category of software called operational intelligence (OI). For front-line workers who need to improve their execution of the daily tasks that contribute to achieving strategic goals, OI reduces latency in awareness, evaluation and management of changes in the state of business performance. Unlike business intelligence (BI), OI uses an event-driven architecture to detect the current state of activities and processes and analyze them against expected states. Unlike business activity monitoring (BAM), OI embeds intelligence into process workflows that helps users determine the most appropriate response to threats and opportunities.

Operational intelligence incorporates technology components from other software categories, among them business intelligence, business rules, complex event processing and business process management. These components address different aspects of events, the data they contain and the processes they are part of to improve front-line decision-making.

The first requirement of OI is to integrate events from multiple sources that flow across the enterprise service bus. To do this requires a broad spectrum of input adapters for things such as system logs, network protocols, relational databases, API calls, messaging queues and Web services. The input adapters must be able to detect events at different points in the business process workflow to enable throughput and temporal analysis. (From an OI perspective an "event" is an object that contains information about a change in the state of an operational activity or process. For example a new customer order would be an event that contains information such as products, quantity and price, which is used in the process of filling the order.)

Further, OI must be able to detect events across multiple processes and nonlinear workflows in a single process, which enables correlation of activities to changes in business performance. This last aspect requires workflow modeling capabilities or the ability to integrate with modeling tools using workflow specification languages such as Business Process Execution Language (BPEL).

OI also requires the capability to model the attributes, constraints and dependencies of events. As an information object, an event is an entity that has attributes, such as data values, time of occurrence, process ID and workflow sequence, that can be used to define queries and constraints for simple pattern-matching. Event entities also have dependencies between each other that can be modeled into hierarchies and used to match against more complex business patterns. Predictive analytics can assist in the creation of an event model when the structures and relationships are not well-understood. Users can employ statistical modeling to estimate the attributes and dependencies when the general event structure can be hypothesized on the basis of domain knowledge and analysis. If the structure is completely unknown, data mining can be employed to infer both the attributes and dependencies of an event model.

The event-processing engine matches sets of events from different workflow streams against patterns in the event model. Filtering reduces the total event set to just the relevant subsets, which are aggregated based on dependencies at different levels within the model hierarchy. Then the event engine uses constraints to detect patterns that should never occur, those that should always occur and changes in state conditions at different hierarchical levels. When constraints are violated, the event processing engine executes response rules, such as delivering information to front-line workers or changing the routing of process workflow.

At a human interface level, OI uses dashboards to deliver personalized views of process activities and events. Semantic layers take the burden off the user to sort out inconsistencies between the meanings of event information displayed from different applications. Dashboards enable users to drill down through the event hierarchies to understand the underlying causes of complex event patterns. Federated query and search capabilities enable front-line workers to access information in databases, documents, and e-mail messages and on the Web to add context to event information.

For organizations that need to improve operational performance, Ventana Research recommends using event-driven architectures to align front-line workers' daily tasks with strategic goals. Companies should start by defining a use case that requires reducing the latency in awareness, evaluation and management of changes in the state of operational performance. Then take an inventory of what technology components you already have for filtering specific events out of the streams flowing across the enterprise service bus, aggregating them into higher-level patterns, evaluating pattern instances against constraints, and executing rules and controls in response to changing business conditions. Next, perform a situation assessment to identify gaps and analyze what level of interoperability is required between the technology components. Once that is done, you can compare the time and cost of building the OI application versus buying it from a vendor that has already integrated the technology components.

About Ventana Research
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