Before companies can optimize BI spend and increase ROI, it is necessary to first understand what causes low BI ROI. There are several areas to consider:
- Data Silos: Fragmented information lies in various EHRs, which limits data that is extracted for analysis.
- High setup and maintenance costs: Choosing an expensive BI solution for your company, especially for small to medium-sized businesses, is problematic.
- Missing, undefined or changing BI vision: Uncharted BI vision increases the IT overhead for operations and ongoing change management. It is also impacts the prolonged development cycle, which puts BI projects at risk.
- Too many BI tools/infrastructures: BI tools are expensive and require additional hardware infrastructure. Each tool needs a set of administrative efforts that are typically not considered while procuring the BI tools.
- Mortality rates of analytical algorithms: It takes a long time to develop clinical algorithms, and mortality associated is very high.
- Lack of automated data: Lack of automation on data quality checks leads to manual data corrections, and bad data leads to bad analytics and faulty conclusions.
- Substandard ETL and BI coding: Code developed using substandard data increases maintenance efforts and has a high operational cost. Many organizations spend 40–50 percent of their available capacity on either maintaining or keeping BI live.
- Underestimating existing capabilities: Failing to understand how current IT infrastructure and resources could be leveraged to reduce cost estimates causes a missed opportunity to make a project more attractive to business executives.
- Forgetting that change is constant: Regardless of the accuracy of the initial project estimates, the numbers should be updated and communicated to reflect reality.