Parcel Delivery - Intel Segmentation and Last Mile Opt.pptx

Editor's Notes

1. SAS is the largest private software company Solely works on data analytics, machine learning and AI Invests a big portion of the revenues to R&D and has roughly 3000 PhD’s on board.
2. We talked about the need to take a holistic approach to AI. ​This is one of the reasons why SAS has been so successful, we don’t just offer visualization, we don’t just offer machine learning, but we help organizations achieve their business goals through practical applications of AI and analytics in concert.​ Starting the journey with the right data management and visualization capabilities. ​ No matter what your data type from images, to text, to more structured data, a successful implementation will require data capabilities for the next phase.​ The Discovery phase of AI is where you can apply a broad range of advanced AI techniques to gain insight, for example:​ Machine Learning and deep learning enables us to find complex patterns in data that are not evident to us. One of SAS customers; Rogers Communication used machine learning and reduced customer complaints by 53%​ Computer Vision is the ability to recognize objects, and SAS is helping customers in manufacturing, in security with Computer Vision. WildTrack is a SAS partner who is using Computer Vision to identify animals in the wild using nothing but the tracks they make, so just by analyzing the image of the paw, we are able to determine what the species is, and a whole host of other information using computer vision.​ Natural Language is really the future of how we will communicate with AI. In fact, already today you can speak to Visual Analytics app on your smartphone, and you can ask for reports in a way that is natural and does not require specialized skill.​ And even in very well understood analytics techniques such as forecasting and optimization, we are using machine learning to get better results and save our clients money and resources.​ Finally, to gain the real business value, you would deploy the models to production in a way that accounts for your business processes and constraints​ SAS offers the Analytics and AI lifecycle with the right tools that help you from data to discovery to deployment all on the unifying SAS Platform.
3. LTL Carriers are mostly at the Segmentation stage. Customers blindly trust PROs for Demand Modeling and Optimization but it is a black box model that is forced. Based on the force-fit they create a vision to senior management that past decisions have left a lot of money on the table. This is based on a price elasticity model with few data points and a huge margin of error. (reference: Bob Obee)
4. Per Bob Obee – this is unique to UPS – not typical in LTL, who are not this advanced with how they manage rates. However, related to pricing, LTL can be more complex than parcel package or truckload. SAS has a FLEXIBLE approach that can adapt to the customer’s style and culture. Revenue and Pricing Manager are incented by Profitability vs. Account Manager incented by sales volume.
5. Account Manager
6. Revenue Operator user
7. Rich to add Value Impact. Increase pricing by ½ % has a huge impact on the bottom line – Top Line impact vs. Cost Cutting.
8. Rich to add Value Impact. Increase pricing by ½ % has a huge impact on the bottom line – Top Line impact vs. Cost Cutting.
9. Rich to add Value Impact. Increase pricing by ½ % has a huge impact on the bottom line – Top Line impact vs. Cost Cutting.
10. Rich to add Value Impact. Increase pricing by ½ % has a huge impact on the bottom line – Top Line impact vs. Cost Cutting.
11. Revenue Operator user