Business Intelligence (BI) is one of the most critical enablers for business transformation and business performance
management in today's corporate environment. Recent advancements in BI software and hardware technology have led to capabilities that seemed like science fiction just a few years ago.
For example, with in-memory technology the billions of records that enterprise applications contain can be processed and analyzed in seconds, and users can access them simply and seamlessly on numerous types of devices. In addition, informational BI insights can help companies manage business costs and risk, while strategic BI insights can increase the value of their investments and build a competitive advantage.
EIM for business transformation
To realize the benefits from such BI insights and to use their investments in leading-edge BI capabilities effectively, organizations must think about the big picture in terms of enterprise information management (EIM) rather than just in terms of on-spot BI solutions. They also should steer clear of such specific feature sets as fancy dashboards and state-of-the-art hardware and software. Focusing on the EIM big picture means making sure the organization has a strong foundation in place in terms of people, processes and data management.
The segment of an organization that owns its business processes should lead the BI initiative, and IT should be the key partner in enabling the technology. The business side first must understand how its leadership operates and measures performance. This means identifying key performance indicators across functions and mapping them to BI business requirements. Each requirement should be analyzed from the perspective of the underlying data -- specifically the master data (about customers, suppliers, employees and chart of accounts, for example) that forms the foundation for most business transactions.
Organizations should have strong data and information governance capabilities to ensure that the data in their BI source systems is clean, reliable and accessible. If an organization doesn't have such capabilities, the business must lead a formal initiative in partnership with IT to establish a data governance capability before the organization deploys BI technology.
BI initiatives should have executive-level sponsorship and ownership that drive a dedicated BI Center of Excellence (CoE) for developing and maintaining BI capabilities. Although the operating model for a CoE will vary depending on such things as the type of business and its organizational culture and structure, it is important that a CoE be established before significant investments are made in BI software.
Data governance economics
By following these guidelines, a Fortune 1000 manufacturing company was able to save $5 million to $10 million a year by focusing on supply chain and customer service performance indicators. The company's success was facilitated by its establishing a business-led data governance organization and aligning its objectives and ongoing activities with enterprise-wide BI initiatives.
This company moved from a reactive data and information-cleansing approach to a proactive approach that significantly reduced the amount of bad data and information getting into its systems, and allowed it to deliver timely, value-added services.
Many companies today are struggling to realize value from their BI implementations. The three most common reasons for their failure are these: significant problems with data quality and integrity, a lack of executive sponsorship, and the absence of a dedicated, well-defined BI organization that is driven to use BI as a strategic advantage. Focusing on the foundations of BI (people, process, data management), not just BI technology, is therefore a critical success factor for all BI initiatives.
Rajiv K. Arora, a senior manager at Ernst & Young LLP, provides IT advisory services to senior executives of the consultancy's global clients.