Business Intelligence: Distilling Raw Data into Useful Information

Data is everywhere. You probably have silos filled with it in every department of your organization. Enterprise resource planning (ERP) and customer relationship management (CRM) applications accumulate data at a furious pace. So much innovative technology has been focused on capturing, storing, replicating and archiving data, however, the intrinsic value of data as the raw material from which information is made has been obscured. Just coping with all of it has gotten all the attention. But we are starting to see that change.

Thoughtful executives on both sides of the business and technology aisle are peering into the stockpiles of data scattered around their organizations and finding gems of information: insights on how to become more efficient, how to market products and services more effectively and how to satisfy customers and win their undying loyalty. Using a variety of business intelligence (BI) techniques to distill information from data today has become the key to gaining competitive advantage in virtually every marketplace, including manufacturing.

Distilling raw data into useful information is the genius of business intelligence. There are a variety of software tools involved including data marts and a data warehouses, but business intelligence is not a project. You don't install BI the way you do VoIP, nor is it something that CEOs or CIOs can cause to happen on their own. It's more of an approach, an attitude even, and it can only be accomplished with the effective collaboration of both business and technology professionals.

The most fundamental way business intelligence impacts the balance sheet is by helping companies make better decisions at all levels, from executive decisions all the way to daily operational decisions. One of the questions often asked to determine the level of business intelligence in an organization is: Are your business users able to obtain accurate, timely and reliable reporting information about how the business is doing? You often hear "Yes" from an IT manager, but you almost never hear "Yes" from a business manager. This disconnect between business managers and IT needs to be resolved before information can be distilled from data. They are different sides of the same equation. Without the other's direct collaboration, the best intentions of either group amounts to the sound of one hand clapping.

The Makeup of Business Intelligence

Business intelligence has three closely interrelated components:

• Enterprise reporting
• Executive information systems
• Predictive analytics

The three components form a hierarchy of increasing sophistication and escalating value and are often combined with enterprise portal solutions to make the gathered intelligence available throughout an organization.

• Enterprise reporting includes basic ad hoc and templated reports generated from available data that create snapshots of specific aspects of an organization's operations. Often they draw on data from multiple sources and merge them together.
• Executive Information Systems (EIS) apply intelligence to the data that is reported and produce score cards and Key Performance Indicators (KPIs) that show whether standards are being met or not. Often presented in enterprise portal dashboards, EIS systems present an analysis of the current health of an organization.
• Predictive analytics uses techniques such as pricing optimization, market basket analytics, and clustering to identify and project trends. They look into the future and help you see where you are going instead of where you've been.

Most corporations never get to predictive analytics, which creates a significant opportunity to gain competitive advantage for those that do.

Opportunities to Leverage Business Intelligence

A good time to ramp up a Business Intelligence initiative is...

• When new systems are coming online.
• When you are enhancing and/or expanding an existing data warehouse.
• When you are expanding a departmental BI solution into an enterprise-wide solution.
• When you are moving beyond simple reporting to predictive analytics and performance management.
• When you want to provide dashboards with KPIs.
• When you are narrowcasting sets of information to a specific audience.
• When you are externalizing specific business procedures to a third party.

The Business Information Management Self-Help Test

Quality business intelligence depends on a solid business information management foundation. Your answer to these questions will help you evaluate your intelligence potential.

• Is your data quality at an acceptable level?
• Do you have a plan to manage your data to ensure quality?
• Can you rely on your data to make business decisions?
• Does your organization have access to all the reports needed?
• Can you easily see a 360-degree view of your customers?
• Can you afford to answer "no" to any of the above?

These days, there is an increase in small and mid-market companies using BI to stay agile, position for growth in a tough economy and compete with larger companies. Real-time BI is being used to drive lower-level and tactical decisions. And we are seeing more predictive analytics, which are decision models that help companies predict what will happen in the future by interpreting past events and looking for patterns. Whatever your data situation is, it is likely your company can extract more meaning and valuable business insights from it.

Chris Rafter is Vice President Consulting Services of Logicalis, which is a provider of high-performance technology solutions. The 1500-person company has more than 6,500 clients worldwide. To find out more about and how Logicalis has helped companies such as Cummins, Allergan, Intel, Toyota, IDEXX and WR Grace, please go to www.us.logicalis.com