Predictive Analytics [UTC]
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Predictive analytics uses past data and statistical algorithms to predict future outcomes and trends. It allows organizations to be more proactive by predicting events before they occur to improve revenue, reduce costs, and increase competitiveness. Studies show companies using predictive analytics are 36% more likely to experience above average revenue growth and twice as likely to outperform peers. For example, predictive analytics helped the Memphis Police Department reduce serious and violent crimes by positioning resources before crimes were committed. It also helped First Tennessee Bank increase its marketing response rate by 3.1% and return over 600% on its marketing investment.
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1) The document discusses opportunities to apply artificial intelligence (AI) to real-world problems in both the physical world of "things" like vehicles and equipment as well as human activities.
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Predictive Analytics [UTC]
- 1. Matous Havlena matous@havlena.net Maricela Gomez Herrera yjl858@mocs.utc.edu Maria Isabel Hernandez Eguibar cyt536@mocs.utc.edu Predictive Analytics UTC University Production and Operations Management
- 2. Why does it What is it? Case Studies matter?
- 3. What is Predictive Analytics? Data Information Decision
- 4. Intelligence vs. Analytics What happened? Why did it happen? Who? When? Will it happen again? How many? What will happen if we change x? ...historical predictive...
- 5. Why does it matter? Revenue Costs Competitiveness IBM's CFO study 36% growth in revenue or more 2X more likely to outperform peers IBM/MIT study
- 6. Crime Prediction Memphis Police Department positions resources more likely to encounter problems before crimes are committed reduction in 27% serious crimes drop in 15% violent crimes
- 7. Predictive Customer Analytics First Tennessee Bank optimizes its marketing resources increase in 3.1% marketing response overall return 600% on investment
- 8. Matous Havlena matous@havlena.net Maricela Gomez Herrera yjl858@mocs.utc.edu Maria Isabel Hernandez Eguibar cyt536@mocs.utc.edu Thank you!