INTERVIEW SERIES ON PREDICTIVE ANALYSIS – PART 4

Q: In your work with predictive analytics, what behavior or outcome do your models predict? A: In order to plan drivers’ day, we predict where deliveries are going to occur as well as how long it will take a driver to complete his / her route.  This opens the door to planning, execution, and analysis tools which we created.  However…  This is NOT the end game.  There is more than prediction. Q: How does predictive analytics deliver value at your organization – what is one specific way in which it actively drives decisions or operations? A: Based on what was described above, UPS reduced 85 million miles driven per year. Q: Can you describe a quantitative result, such as the predictive lift of your model or the ROI of an analytics initiative? A: As mentioned, looking forward with predictive data and planning tools, we reduced 85 million miles driven per year while also offering new services to customers. Q: What surprising discovery or insight have you unearthed in your data? A: Prediction is NOT an end game.  Optimization is… By adding optimizations (prescriptive analytics) to our predictive models, UPS reduced an ADDITIONAL 100 million miles driven per year.  This totaled to a 185 million mile reduction annually.  The prescriptive analytics alone is reducing cost of between $300M to $400M annually. Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World. A: I will discuss the different types of analytics and how UPS has used each.  I will point out how prescriptive analytics will find solutions that are not readily apparent and often counter intuitive.  I will also go through some best practices.