I read a white paper authored by Ventana Research in which they surveyed over 2,600 companies on their use, application and satisfaction with predictive analytics deployments. While the paper is now over 2 years old, the insights are informative. You can get the white paper here.
Here are some of the study results:
- Revenue generating business areas are most apt to use predictive analytics: sales and marketing functional areas. These groups are analyzing customer data, marketing data, product data and financials.
- Resource availability is still a barrier to making progress with predictive analytics, particularly in smaller organizations.
- Adopted maturity shows big clusters at the bottom (entry point) and top (experienced users) with the rest scattered through the lifecycle.
- Predictive analysis implementations include revenue forecasting (for the purpose of maximizing profitability), market analysis (for the purpose of increasing market share), customer service and product mix predictions (for the purpose of cross-selling). Social network analysis is gaining momentum.
- The organizations with the highest level of satisfaction are revising their models real-time, or at a minimum, daily. The organizations with the least satisfaction update their models far less often.
- The skill-set distinction between developing analytics tools and using analytics tools is not well understood by management. The staff who perform analysis generally reside in their business units, not in the IT department.
- Most organizations that have implemented analytics do not provide adequate training or consulting support to truly maximize the value of their investment.