Businesses generate huge amount of information, structured, semi-structured and unstructured. Data could be in the form of emails, memos, presentations, user chats, documents from support groups, web pages, video files and so on. According to Merrill Lynch, more than 85% of data exists in one of these forms. Businesses typically use this data once and then it gets discarded.
With the changing dynamics of the market place, a paradigm shift was also required in how the data generated was used by the businesses. The advent of Big Data and Analytics gave the much needed push to businesses to leverage on the data and not only save revenues but also generate newer sources of income. The term Operational Intelligence (OI) was coined in 2008 and is described as set of methodologies which can be used to gain visibility into the business and discovering insights for IT and throughout the enterprise.
Operational intelligence is not an outgrowth of Business intelligence. It is a new approach based on sources of information not typically in the purview of BI solutions. Operational Intelligence delivers by using not only the streaming feeds of live data but also by accessing typical data warehouses and marts which store the past history of events that have already occurred. It provides real time statistics of both data in rest and data in motion for predicting patterns based on data as it being generated and even before it is fed into the databases.
Thus, Operational Intelligence caters to some of the fundamental needs of the current generation businesses derived from the need for immediacy such as
- Real time monitoring and detection of situations
- Time series and trending analysis
- Correlation of events
- Industry specific dashboards
- Multi-dimensional analysis
- Big Data analytics
The biggest driving force behind businesses to adopt Operational Intelligence is its reduced latency in arriving at insights into the data. Instead of waiting for weeks and months, it is possible to get split second decisions. This helps as new situations are encountered in this highly dynamic world. Operational Intelligence thus joins as another new tool in the data analyst’s toolbox alongside other popular tools such as Business Intelligence, Complex Event Processing and Business Activity Monitoring.
A very good example which illustrates the power of Operational Intelligence is advertising. A telecom communications company does a real time analysis of the types of calls that a subscriber engages in and looking at the patterns and usage of the talk time and the expenses incurred, advertises a tempting offer which actually caters to the needs of the subscriber thereby increasing the chances of user continuing with the telecom operator rather than switching over to a rival service provider.
OI can thus empower a business with the ability to make decisions and act on them immediately and hence gaining a competitive advantage in the market. The wide spread adoption of analytics, cloud computing and virtualization can thus provide the perfect launch pad for the adoption of Operational Intelligence.