BI:Looking beyond boundaries

Any business for survival and success will have an action plan. It is often the catalyst for business analysis across departments of an enterprise. An action plan actually helps the enterprise carry out a reality check on their actual performance. Surprisingly, the data warehouse does not produce this comparison. The simple reason is that plain data is seldom included in the data warehouse design.

According to Rajesh Naik, a freelance business consultant, " The so called state-of- the-art business intelligence applications backed by the best data warehouses lack important capabilities required to support the process of decision making and implementation."

A more significant shortcoming of the data warehouse and business intelligence applications which analysts point out is the support provided for decision implementation. Decision implementation is a collaborative process involving many people throughout the enterprise and often external to the enterprise. Decisions must be approved and communicated to everyone who must take action. In order to support decision implementation, information must flow back into the operational and financial systems that serve as the sources for the data warehouse.

The Road Ahead

The goal of business intelligence is to answer business managers' endless streams of questions. The answer to one question almost always generates a new question. Each new question requires more comprehensive analysis. Many business intelligence tools focus on query generation and reporting data with very little analysis capabilities.

As organisations become successful in answering management’s' easy questions, they must anticipate more difficult questions. The hardest questions to answer are "Why" and "What if? " Answering these questions is essential and requires sophisticated data modeling and projection tools.

This is not to suggest that all business managers require statistical analysis and data mining tools. A few might, but most simply want the application of the technology delivered as a solution to their business issues. In other words, as business intelligence matures, it will take on the form of solutions to business issues.

The application of the technology of business intelligence is already addressing issues associated with customer relationship management (CRM). Advanced business intelligence technology is required for analysis of customer behavior and market segmentation.

A second application direction for business intelligence is demand forecasting. Improving operational efficiencies within the enterprise and across the extended supply chain is one of the most important business issues confronting organisations today. Demand forecasting addresses the "what-if" questions, which are essential to business planning. To do this, business intelligence must encourage greater user collaboration associated with business management processes.

The data warehouse and business intelligence must operate outside the boundaries of a single enterprise. Business intelligence must be web optimized for ease of delivery. Issues such as security and scalability are extremely important.

However it is certain that data warehousing and business intelligence has the potential to change the rules for how a company operates and competes in a competitive world. The non-trivial challenge is positioning the data warehouse and business intelligence in the centre of what a business requires to compete here.

All this looks a certain possibility in the long run. Having said that, the biggest stumbling block to this would be the integration of the data warehouse and business intelligence with business management processes.