The basic premise of decision making is having the right information delivered to the right people at the right time. But the pace of change in business today means that the window of opportunity to make an informed decision is short-lived. The reason: data lies fragmented across numerous sources and it is often difficult to bring it together in a holistic way.

So it’s not surprising that organisations have spent billions over the last decade investing in business intelligence solutions to improve their decision making processes. According to Forrester Research, most businesses have between five and 15 separate business intelligence (BI) solutions, with many applications having been deployed at a departmental, rather than enterprise level, creating a host of redundant reporting tools and data inconsistencies.

This pattern of spending is not set to change, not least because the wave of regulatory requirements has forced BI to move out of the department level and into the boardroom. Today, BI is one of the highest priorities for CIOs, with new licence revenue expected to grow to $3.2 billion by 2010, say Forrester analysts.

What is set to change, however, is what organisations are demanding from their BI systems as they begin to consolidate their business intelligence tools onto a single platform.

Many business intelligence systems do not analyse current business performance. Instead, they drill down on historical data that has been loaded into data warehouses or business ‘cubes’ from live, operational systems such as enterprise resource planning (ERP) applications. And depending on the frequency of this process, data can already be hours, days or even weeks old.

Despite this model being an exercise in finding out what has already happened, it has worked well. Until recently, it has been impossible to analyse or draw data into reports from live databases as the systems have been unable to cope with the cost in overhead processing involved.

But the disconnect between the ‘dual-data model’ has its drawbacks: the analysis is not showing what is happening now and therefore cannot offer much insight into what is likely to happen next. And because of the extract and load nature of the model, latency is inherent: information in the operational systems will always be out of synch with that of the business intelligence system.

Within certain business functions, this latency has become unacceptable. Corporate accounting is one such example where this method of working is calling into question the validity of financial statements.

Information needed for month- or year-end reports needs to be both accurate and timely, but these competing demands place strains on the supporting infrastructure. The delay in posting end-of-period journal entries into the transactional system and those entries appearing in the business intelligence system has given birth to the ‘Excel culture’ – the use of spreadsheets to bring the two sets of numbers together. This has created a third, unofficial reporting system, but it is one that is difficult to regulate and is now increasingly falling foul of numerous regulatory requirements.

To address these shortcomings, business intelligence vendors are starting to offer real-time business intelligence systems. But marrying real-time analysis into the operational infrastructure of an organisation is difficult: a failure to do so invariably runs the risk of breaking regulatory requirements, while implementing real-time functionality is likely to slow down or even halt operational systems when large queries are run against them.

Extending business intelligence to employees at the operational level of the organisation is becoming increasingly vital, but finding the balance between real-time reporting and operational requirements is a complex task that few organisations have got right – business intelligence tools have, until recently, only been available to very few decision makers within the organisation.

According to consultancy Intelligence Business Strategies (IBS), operations managers and business analysts account for 80% of the tools usage, while only 10% of operations staff or users at the ‘coalface’ of the organisation have access to any form of analytics.

So while top management sets the strategic goals for the business, employees on the lower tiers could potentially act contrary to these goals because they are not able to view and act upon the same information that is available to those in the upper echelons.

Part of the solution in bringing information to all employees – the so-called democratisation of information – as well as standardising the plethora of tools that exist is the task of the Business Intelligence Competency Centre (BICC).

Gartner defines the BICC as a cross-functional team whose main goal is supporting and promoting the effective use of business intelligence across the organisation. Ultimately, the goal of a BICC is to help give the organisation a competitive advantage through the use of BI, irrespective of the diverse set of applications such as workplace tools, analytic applications, business activity monitoring, reporting and data-mining solutions.

The BICC concept is not new: Gartner first introduced it in 2002. But the centre is becoming increasingly important as BI is extended not only across the organisation, but to customers and suppliers as well. Their warning is clear: businesses that do not invest in a BICC risk losing control of their business intelligence strategy and jeopardising the organisation’s strategic objectives.