The trend toward evidence-based decision-making is taking root in commercial, non-profit and public sector organizations. Driven by increased competition due to changing business models, deregulation or, in some cases, increased regulation in the form of new compliance requirements, organizations in all industries and of all sizes are turning to business intelligence (BI) and data warehousing (DW) technologies and services to either automate or support decision-making processes.
An increasing number of organizations are making BI functionality more pervasively available to all decision makers, be they executives or customer-facing employees, line-of-business managers or suppliers.
Like all organizations that took part in IDC’s research project, Cornell was influenced by both external and internal factors that triggered a need to re-evaluate its decision-making processes and the supporting BI and analytics technology architecture.
In the case of Cornell University, these business drivers were both strategic and operational:
- Identifying key performance indicators (KPIs)
- Creating consistency across reporting
- Establishing a clear understanding of what KPIs needed to be tracked and monitored
- Finding technology that is flexible enough to react to future BI platform expansion
To address its BI and analytics needs, Cornell embarked on a path toward pervasive BI that would
require changes to the organization’s culture, technologies, and business and IT processes.