Understanding causes of low BI ROI in healthcare can help you make better BI decisions. Below is a list to get you started:
- 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.
Learn more about how to provide measurable ROI from your BI in our white paper.