Business Intelligence vs. Operational Intelligence

By David Kelly and Heather Ashton

Insight is everything in business. Having the right tools to optimize business processes is the wish of every business analyst. While business intelligence as a discipline has existed for many years in enterprise computing, operational intelligence has emerged in recent years as the hot-button area for driving business optimization.

The goal of operational intelligence (or business process intelligence) is to provide business analysts with real-time data related to business processes and activities as they are executed. This real-time information can then be used to optimize business processes by enabling them to make changes midstream to avert an interruption or avoid a bottleneck.

There are many different types of solutions on the market that attempt to provide business analysts with this operational intelligence. One that is worth taking a closer look at provides a very different approach than more traditional business intelligence. It is semantic technology, and Upside Research believes it may be the sweet spot to really drive success in operational intelligence throughout the enterprise.

BI vs. OI
With business intelligence solutions from vendors such as Cognos, Hyperion, and Clickview, data is reported on a periodic basis, such as daily, weekly or monthly. The users are given tools to create the parameters for the reports, and then can take the generated reports to analyze and make the appropriate business changes. Traditional approaches to business intelligence sit on top of data warehouses or relational data stores, and require a static data model to be defined in order to build the reports for analysis.

In contrast, operational intelligence solutions look at the real-time status of the business process. They are often interactive and enable drill-down capabilities to enable the analyst to get to the most accurate information at that moment and make appropriate business decisions based on that timely information. In order to get real-time reporting on today’s business conditions, you need to embrace loosely coupled data, such that the data is not organized in an orderly model with defined parameters. The data provides a more incremental view of the ever-changing nuances of a business process, and supports greater agility and change.

At the heart of the matter, with business intelligence, analysts are looking at past data, using their conclusions to inform future decisions, but the data and reports are disconnected from the activity stream. With operational intelligence, the data and information are on-going, tied directly to the events and activities that surround a business process, and analysts are proactively tying the decisions with the business processes as they occur.

That’s where a solution like semantic technology can come in. Semantic technology is an approach (or more correctly, as set of approaches) that tries to provide a framework for managing and interacting not just with business data, but with the context of the data. And that can have a big impact when we’re talking about operational intelligence. In our next column, we’ll dive into the specific impact semantic technology can have when it comes to up-to-the-minute operational intelligence applications.