Operational Intelligence refers to a new category of methods and technology for gaining visibility into business operations, discovering insights, and then rapidly taking effective action, frequently through automation. Operational Intelligence is not an outgrowth of business intelligence but a whole new field based on new sources of information analyzed by new types of technology.
Operational Intelligence is not about looking at what happened in the past. It is about understanding what is happening right now in a business.
If business intelligence is the sports page you read on Monday, operational intelligence is the communication that happens during the game.
To find out what is happening right now the following steps are taken in various permutations:
- New sources of streaming, real-time data are analyzed and visualized
- Technology such as complex event processing is employed to find correlations and recognize patterns
- Business rules and policies help decide what to do
- Business process management systems carry out actions to take advantage of opportunities or solve problems
Because operational intelligence systems usually orchestrate technology that is already in place, CITOs are in an ideal position to recognize when such systems may be profitably applied. This problem statement describes research that would define operational intelligence and then explore how CITOs can play a role in determining if such systems would help a business.
Context and Background
Dale Skeen, CTO of Vitria Technology, defines operational intelligence in three stages:
- Visibility, in which new sources data and events are examined
- Insight, in which an technology is applied to the data to understand operations at a deeper level
- Action, in which the correct action is decided upon and taken
Operational intelligence systems have been successfully implemented in a variety of different business scenarios because many of the processes in companies are occluded.
A process may start in one application, continue through several others, and have the results stored in still others. Operational intelligence systems frequently create the equivalent of tracking processes that describe a process in one unified view and monitor the important events as they occur in the various systems.
Operational intelligence systems also bring in sources of streaming data about the larger environment surrounding the process and use that to help understand what is happening or what is about to happen.
A simple example in the logistics space brings this to light.
A logistics provider found that packages would sometimes stack up in front of planes and exceed the capacity for a shipping route. A new plane perhaps one that would fly partially full would have to be added to complete the shipping.
The information needed to identify gaps in capacity was in the order management system but it was not being aggregated in time for it to inform the scheduling of planes. By monitoring the stream of orders as they arrived using an operational intelligence system, the logistics provider was able to see gaps in capacity in time for an orderly and less costly reallocation of capacity.
A complex example involves an service provisioning process in a telecommunication provider. Dozens of systems are involved in the provisioning process. At each step, various kinds of exceptions can occur.
An operational intelligence system was built to monitor these exceptions and then resolve the ones that were understood in an automated fashion. The system identified hundreds of exceptions and implemented more than 1,000 rules to help respond.
As a result, the demands on the customer service staff were reduced. In addition, when a problem occurred with a high-value customer, remediation could be prioritized.
Some times operational intelligence systems a constructed to handle new sources of data and to take action with newly created systems. Most of the time, operational intelligence systems sit on top vast collections of information and technology and become the brain, helping fill white space that exists between systems and speed the resolution of problems and the pursuit of opportunities.
Operational intelligence systems are most often built of modern technology. They employ ideas like mashups, business rules, and visual configuration.
As a result, these systems become repositories of tribal knowledge that evolve and grow over time. CITOs are perfectly positioned to help envision when an operational intelligence system may be needed. But there are many challenges from the beginning of a vision to the implementation of a successful system.
The goal of this research is to shed light on that journey.