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Q&A: Operational Intelligence Delivers True Real-Time Insights

By continuously analyzing events and business processes as they are happening, operational intelligence enables fully informed decisions that maximize business impact.

Most BI implementations, even so-called "real-time" applications, query data that is at least a few minutes old, thus representing completed business processes. Operational intelligence, however, offers true real-time insight into high-volume streaming data sources, current events, and ongoing business processes.

In this interview, Dale Skeen of Vitria explains how operational intelligence (OI) enables organizations to take action in real time, rather than after the fact. With operational intelligence, he says, corrective action can be taken while a transaction is still in process. "If your company wants to analyze current performance, perform predictive analysis on future performance, or correlate current performance and future performance against historical performance," Skeen says, "then you need OI." Real-world implementations of OI include energy utilities, mobile telecommunications, cyber security, e-commerce, and social media.

Skeen is the co-founder and chief technology officer of Vitria, whose software combines complex event processing, business process management, and real-time business analytics into a single product. Skeen, who holds a Ph.D. in computer science from the University of California, Berkeley, is credited with inventing distributed publish-subscribe communication, and holds over a dozen patents in this and related technologies. Skeen has contributed to 10 books and written numerous journal articles on distributed computing and integration technologies. Prior to Vitria, Skeen co-founded TIBCO Software, where he served as chief scientist.

BI This Week: Vitria uses the term "operational intelligence" to refer to its software. What is the difference between operational intelligence and business intelligence?

Dale Skeen: Operational intelligence provides real-time, continuous analytics on both historical as well as live, streaming data. Business intelligence, by contrast, looks only at historical data. OI is designed to provide real-time, event-driven analytics as well as complement existing BI data stores.

This real-time operational intelligence can be acted upon in a variety of ways: alerts can be sent or executive decisions can be made using real-time dashboards. OI solutions use real-time information to enable automated as well as human actions based on predefined business rules. In this way, security measures or exception management processes, or both, can be initiated.

Then what is meant by "operational BI?"

Operational BI is another term used to explain BI on-demand. By "on-demand," what is really meant is that the historical snapshot of operational data can be queried and returned upon request. The term "operational BI" is sometimes misapplied to the continuous, real-time intelligence provided by operational intelligence. The primary difference between OI and OBI is that OI provides continuous insight in real time, whereas OBI still provides only a historical snapshot.

Thus, operational intelligence enables an individual or an organization to take action in real time, rather than after the fact. With operational intelligence, corrective action can be taken while a transaction is still in process, whereas OBI allows corrective action to be taken only after the transaction has been completed. OI is used for next-action planning, whereas OBI is used for long-term planning.

How can companies evaluate if a problem is better suited for OI or BI?

If all that is needed is a glimpse at historical performance over a very specific period of time, existing BI solutions should meet your needs. The problem is that too many companies are looking at the rear-view mirror as an indicator of future performance. If your company wants to analyze current performance, perform predictive analysis on future performance, or correlate current performance and future performance against historical performance, then you need OI. Even more so, if your organization is looking to reduce the time between when intelligence is received and when action is taken, then operational intelligence is the correct solution.

Assuming an enterprise already has BI systems in place but sees the need for operational intelligence, how should OI be introduced?

Operational Intelligence platforms and solutions can be unobtrusively added to existing systems. OI can quickly tap into any data from anywhere: internal applications and systems, partner and social media, structured, semi-structured, and unstructured data. Thus, historical information from data warehouses and business intelligence reports can be correlated with streaming data, events, and feeds, all in real time, yielding more accurate forecasts and results.

OI also allows users to manage and balance large volumes of real-time events across multiple analytics engines. As a result, OI provides the durability, scalability, and availability of feeds, facilitating real-time analysis and elevating high-volume feeds to the status of first-class information.

Furthermore, OI uniformly incorporates next-generation, real-time BI and BPM capabilities into a complete intelligence platform. OI helps organizations makes smarter decisions with complete and up-to-the-second information in time to maximize impact. It can help organizations through comprehensive dashboards that offer real-time insight into business performance and health, so that immediate policy-based action can be taken.

Is a data warehouse needed to implement OI or can it be run on the production database?

At its core, operational intelligence is a real-time technology, continuously returning sub-second results from queries. Most of the real-time data and event processing for OI solutions will take place in memory. Alternative approaches, which leverage the data warehouse or the production database, are not capable of performing at the sub-second speed of OI. Thus, neither the data warehouse nor the production database is required. OI is used to query the data and return analysis when seconds matter and before the data hits the disk.

OI can also be used to get more out of the data warehouse by offloading the workload. OI can return query results and reports to the data warehouse in addition to the raw data. That can vastly reduce batch processing and data warehouse workloads.

Can you cite some real-world examples of operational intelligence in use?

OI applies the benefits of real-time analytics, alerts, and actions to a broad spectrum of vertical and horizontal use cases across and beyond the enterprise. Within telecommunications, there are many examples where OI is used extensively.

Customer care/customer experience management: Most companies struggle to see a complete end-to-end view of critical customer service processes; they often span multiple systems, such as customer relationship management (CRM), service provisioning, and billing. With OI, customer care agents can see an end-to-end view of customer touch points across interdependent networks and distributed data sources. This includes overall visibility through exception and incident management. This approach enables customer care representatives to take corrective action before the customer experience is compromised, keeping both customer service costs and customer churn low.

Mobile Customer Monitoring/Mobile Device Management: Traditional network-centric service assurance solutions lack insight into customer behavior and the impact of network performance on their customers. As a result, call centers are overloaded and in the dark, as service providers attempt to resolve customer issues and meet SLA requirements using historical data and reactive processes. Operational intelligence is a new way to complement to service assurance solutions. It gives communications service providers and smart grid energy utilities visibility into real-time customer data and real-time network data.

OI for service assurance enables the predictive and proactive identification, prioritization, and resolution of service quality alerts and issues, often before they impact the customer. Added to your existing solution, OI works in concert with service assurance tools to help get the greatest return on investment. With OI, business analysts can quickly gain insight into a situation and modify traditional processes to assure that SLAs will be met.

By using real-time customer data and real-time network operating center data, OI provides real-time problem diagnosis and root-cause analysis to accurately locate the cause of service degradation issues. The result is a common operating picture that enables faster detection, analysis, and response to service quality and delivery issues.

Demand Response Management: Domestic energy consumption is rising. As a result, demand response management is a key part of the U.S. government's overall energy policy. Successful energy producers and utilities continue to deploy demand response programs to help ease peak time pressure on the electric utility infrastructure.

OI makes demand response programs more flexible, responsive, and manageable through real-time information sharing between the independent systems operator, the generator, and the consumer. As smart meter and smart grid technologies are deployed, energy producers and utilities can use OI to optimize demand response programs to receive real-time, dynamic updates in supply/demand characteristics and pricing inputs. OI enables these new capabilities by correlating and analyzing historical and real-time data from smart meter data monitoring and smart grid operations monitoring.

In addition, here are some application areas where OI can be applied to solve real-time, real world challenges:

Real-Time Process Visibility: Most business processes interact with a variety of enterprise software applications such as ERP and CRM systems that were not designed to provide visibility into operations. Even more so, broken processes are difficult to identify and often conceal new business opportunities and risks, resulting in costly SLA violations and customer enrollment errors. As a result of the lack of visibility into operational processes, strategic initiatives that drive revenue, such as increasing customer loyalty or maintaining regulatory compliance, are impacted.

Operational intelligence gives business and operations teams real-time visibility into these processes by identifying issues not otherwise detected by "silo" management reports and reporting systems. This includes the increasingly important and complex customer enrollment processes which often have workflows that span multiple systems and business partners.

Big Data Analytics: Operational intelligence provides real-time insight into both big data at rest and big data in motion. An OI platform analyzes big data from a wide variety of sources including Web feeds, legacy applications, and of course, Hadoop implementations.

With OI, organizations can leverage real-time insights into big data to reach performance and efficiency levels that were previously unattainable. Still, big data (at rest and in motion) is only a part of the picture. Fully informed decisions require insight into big data, events, and business processes. Vitria's OI Platform analyzes big data, complex events and business processes, in real time, to enable fully informed decisions and actions. With Vitria, both business and technical users can take fully informed and immediate action to optimize the customer experience, increase loyalty, reduce churn, and minimize risk.

Continuous Monitoring: With OI, organizations can improve governance, lower compliance costs, and optimize operational performance by continuously monitoring revenue, customer turnover, and other key performance indicators. The most effective organizations use continuous monitoring across a breadth of use cases, including governance, compliance, and situational awareness.

Information Security: Information security describes the collective role of policies combined with network and security devices from identity and access management applications to vulnerability management and policy compliance tools. OI can provide an organization complete situational awareness across all information assets, networks, and systems.

What are some of the tools and technologies used in OI?

OI unifies multiple advanced technologies into one platform. OI streams data from multiple sources of feeds and streams, such as Hadoop, Teradata, SAP, Twitter, or Facebook, analyzes data using a high-performance, complex-event processing (CEP) engine, and creates alerts or business rules using business process management capabilities. The continuous real-time results are viewed in live dashboards and easily shared across the organization using role-based access control (RBAC) to enable access to these lightweight Web applications.

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