Can New Technology Fix Old Business Intelligence Failures?

Can New Technology Fix Old Business Intelligence Failures?

Business intelligence is creating new opportunities for information technology and computer science degree seeking students.

According to research firm Forrester, business intelligence continues to be one of the top enterprise software and applications market segments. Ever-increasing data volumes, complex enterprise operations, and regulatory reporting requirements continue to drive demand for BI in the middle (risk management) and back (finance, HR, operations) offices, Forrester says.

In fact, as the overall software market dropped by eight percent in 2009, the BI software market increased 15 percent. The major solutions manufacturers include Actuate, IBM Cognos, Information Builders, Microsoft, MicroStrategy, Oracle, Panorama Software, QlikTech, SAP BusinessObjects, SAS and TIBCO Spotfire.

This type of growth shows healthy employment opportunities for anybody seeking IT work.

But, this same growth has yielded BI technology providing solutions for data storage and decision reporting—two very different areas that require different processes. There has also been a growing concern amongst BI professionals about failed systems for reasons that range from inadequate integration to poor data quality processes. (See 50 TOP FAILURES for Business Intelligence Industry).

When considering a BI solution, one must consider data integration, cleansing, modeling, warehousing, metrics creation and management, reports, dashboards, queries, alerts, and many more. All of these approaches must come together in one application. According to analyst Boris Evelson, “this multitude of components and complexities makes rapid prototyping challenging at best, impossible at worst.”

The Dilemma

Many believe there’s such a large interest in business intelligence because of the many failed data warehousing and BI projects the past ten years. According to the Gartner Business Intelligence & Information Management Summit, anywhere from 70 percent and 80 percent of BI projects fail.

Meanwhile, major companies are creating new solutions to better service the industry. Some technical analysts believe Agile BI Methodology is the future. In theory, this method decreases time spent creating reports and reacts to business requirements more quickly.

“Mostly, Agile BI is no different than any Agile development methodology that calls for incrementally delivering products versus a big-bang approach; for rapid prototypes versus specifications; for reacting versus planning; and for personal interactions with business users versus documentation,” Evelson writes. “The Agile BI methodology differs from other Agile approaches in that it requires new and different technologies and architectures for support. Metadata-generated BI applications are one such example of a new technology supporting Agile BI.”

Evelson believes Alternative database management system engines will emerge as one of the compelling BI technologies.

But Steve Williams, president of DecisionPath Consulting, writes the agile BI approach does little to address some of key problem areas associated with BI failures. While the high degree of business engagement associated with agile BI certainly is a positive step, he writes, it could amount to doing the wrong things – and still failing – more rapidly.

In his blog, Williams recommends:

1. Developing a pragmatic, comprehensive BI Strategy and Roadmap aligned with both short-term and long-term business goals and strategies to ensure both a balanced business focus and a more holistic perspective on where BI opportunities exist  to achieve a rapid return on investment

2. Defining a data architecture, leveraging a proven architecture approach that can be used during agile development to facilitate sound data management practices

3. Investigating the limitations of current data sources in relation to BI information requirements, understanding where the quick-win agile projects do and do not exist

4. Using a proven BI business requirements approach to ensure that there is explicit traceability between agile projects and business information requirements that align with and explicitly support key business goals and strategies

5. Determining roles and responsibilities for making the necessary business process changes needed to ensure that  that new BI capabilities are incorporated into the business and the potential business value of new BI capabilities is captured

While Williams’ points are clear and effective, it’s also apparent there’s a lot of room for technology improvements in this growing sector. Who knows? Maybe you’ll fix the problems of BI technology.