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Intelligent Enterprise: How to Create the Customer Experience of the Future? - Roosi Magi
- 1. 1 @roosimgi Intelligent Enterprise: How to Create a Customer Experience of the Future? @roosimgi
- 3. What is common in these examples? EXPERIENCE ECONOMY
- 4. Customer Experience: an emotional reaction consumers have at any point of the customer journey
- 5. We live in a new world 80% 59% Say tailored engagement based on past interactions is very important Source: SalesForce Of customers have chosen to switch brands due to poor customer experience Source: Qualitrics of business leaders say that delivering a relevant and reliable customer experience is critical to their company’s overall business performance Source: Harvard Business Review 73%
- 6. 80% 8% Of CEOs believe they are delivering a superior experience of their customers agree The Experience Gap Source: Bain & Company
- 9. SAP Strategy: Deliver the Intelligent Enterprise The Core
- 10. Intelligent enterprise & Automation Machine Learning Key enabler
- 11. Our Promise: Intelligent Enterprise Customer Churn Product Recommendation Call Center Optimization Production Planning Predictive Maintenance Intelligent Service New Business Services
- 12. Business Process Example – Need for Machine Learning Search Select Order Pay Receive facilitate suggest products assess risk define terms ship reconcile • Customer data • Product data • Click stream • Buying history • Pricing data • Payment history • External scores • Fraud scores • Invoice data • Payment terms • Account statements customer data retailer
- 13. Search Select Order Pay Receive facilitate suggest products assess risk define terms ship reconcile • Customer data • Product data • Click stream • Buying history • Pricing data • Payment history • External scores • Fraud scores • Invoice data • Payment terms • Account statements customer data retailer Use Case 1 Search Use Case 3 Product Recommendation Use Case 2 Customer Analysis Use Case 5 Fraud Detection Use Case 4 Payment Risk Use Case 6 Accruals prediction Use Case 7 Reconciliation Business Process Example – Multiple Machine Learning Use Cases
- 15. 15 @roosimgi Experience Matters! Thank you! @roosimgi Roosi Magi SAP Global
Editor's Notes
- The Intelligent Enterprise leverages emerging technologies such as AI/ML, IoT, and Analytics to enable the workforce to focus on higher value outcomes. SAP will deliver the Intelligent Enterprise through the framework pictured on the right. The framework features 3 key components: Intelligent Suite – to enable our customers to automate their day-to-day business processes and better interact with their customers, suppliers, employees, etc., through applications that have intelligence embedded in them Digital Platform - to facilitate the collection, connection, and orchestration of data as well as the integration and extension of processes in our Integrated Applications Intelligent Technologies - to enable our customers to leverage their data to detect patterns, predict outcomes, and suggest actions
- Key Capabilities: Intelligent enterprises differentiate through three key capabilities. They operate with: Visibility: the ability to collect and connect data that was previously siloed, and recognize unseen patterns Focus: the ability to simulate the impact of potential options, and direct scarce resources to the areas of maximum impact Agility: the ability to respond faster to changes in the marketplace or the business, and pivot business processes towards the right customer outcomes Business Outcomes By adopting the capabilities of an intelligent enterprise, our customers can achieve game-changing outcomes faster, more effectively, and with less risk. They can: Redefine the end-to-end customer experience Deliver a step change in productivity Transform workforce engagement
- Data drives business process: customer searches, selects, orders and pays for product.
- ML use cases along customer journey. SAP HANA Predictive Analysis Library (PAL) provides algorithmic capability for each step per use case in combination with SAP HANA database. PAL: Addresses all key scenarios like Classification, Regression or Time Series Forecasting (and more); 90+ algorithms cover 99% ML use cases.
- Increase a port’s capacity by 50% without building a dock* At SAP, we’ve cultured, implemented, and helped customers fine-tune dozens of predictive use cases that solve real business problems. Whether you want to begin answering advanced business questions in sales and marketing OR fraud and risk analysis, you can be sure that our approach to predictive analytics is derived from a business use case and not a technical tool. Lines of business are looking at technologies, like predictive analytics, to mine the masses of data they are collecting and use the data to help them make decisions, understand customers, recommend products, improve business performance, predict asset maintenance, in a nutshell use data to get a forward looking perspective. Copyright SAP