Big Data, Analytics, and IoT in Cross-Border Ecommerce

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1 Big Data, Analytics, and IoT in Cross-Border Ecommerce James A Fairweather, PhD Vice President, PB Technology, Experience and Ecommerce 11 February 2015

2 How we enable transactions in commerce. Our solutions help businesses manage customer information and turn it into datadriven insights We help companies convert geographic data into better customer experiences and smarter strategic decisions We help transform the way our clients engage with their customers driving consistent interactions and targeted, orchestrated connections We help clients increase the speed of the mail process while cutting costs We remove barriers to cross-border shipping Pitney Bowes January 14,

3 We remove barriers to cross-border shipping. By uniquely guaranteeing the cost of international shipping, our Global Ecommerce solutions make it easier for online retailers to ship parcels and packages to anyone in the world without surprises. We do this by: Guaranteeing shipping costs for every single transaction Removing the guesswork when calculating foreign taxes and fees Studying every aspect of customs processes to simplify cross-border complexity Product Classification Catalog harmonization Machine learning Hub Operations International shipping lables Commercial invoice preparation SOFTWARE SERVICES Product Goods Management Import / export compliance Hazmat & dangerous goods TRANSPORTATION SERVICES Carrier Management Organic, optimized carrier network International line haul API / WEB INTEGRATION Fully landed costs Duties & taxes Shipping Parcel Tracking Consistent & reliable tracking visibility API integration & tracking portal Empowering customers worldwide to easily and efficiently track their parcels and packages no matter where they are Pitney Bowes January 14,

4 OUR SITUATION Executives received static, canned reports with limited information. Some analysis was done by populating manually in Excel spreadsheets. Operations teams and product team heavily relied on reports for day to day operations. Lot of manual efforts spent in analyzing the reports to drive actionable insights. COMPLICATIONS Multiple data sources No centralized storage High volumes KEY QUESTIONS How can we integrate disparate data into a single view? How do we make available to multiple stakeholders? DESIRED STATE Centralized data store KPI dashboard via Web, mobile & notifications Interactive, self serving drill down Looking for insight into parcel status, SLA achievement, hub performance and more Pitney Bowes January 14,

5 Parcel Process Flow Inbound to PB hub: Retailer/shipper prepares parcels ASN transmitted to PB PB generates a Universal Parcel Identifier (UPID) Retailer/shipper sends parcels PB coordinates and consolidates parcels for international line-haul Parcels are transported to the PB Hub (single parcel or freight) Parcel is received at the PB Hub PB coordinates with a contracted agent or a commercial carrier, depending upon the destination country Goods are cleared through foreign customs via a PB Broker PB prepares the parcels for International line-haul -- HS Classification Export Compliance (ECCN) review Import Restrictions Screening review Content Inspection Commercial Invoices TSA Screening Parcel reaches the customer

6 Tracking Event Aggregation & Architecture Carrier 1 Carrier 2 Carrier 3 Carrier 4 Carrier 5 Carrier 6 Tracking Data Carrier 7 Carrier 8 Carrier 9 Ring scanners Belt scan, weigh and dimension Hub Operations Software Hub application, Hub application database FTP, HTTP/XML, Web Services Carrier Tracking Services Parcel API, Adapters Central Parcel DB Reporting (operational, analytics, etc.) Pitney Bowes January 14,

7 Strategic foundational technologies Mobile Solution/ Business Outcome Information How Technology is Consumed SaaS APIm Big Data M2M / IoT Machine Learning &AI Analytics SW/HW Products Evolution of Industry Technologies Physical Digital (Web) Digital (Mobile) Convergence: Broader Digitization (People, Machines, Things, Logistics) Pitney Bowes January 14,

8 Drive Fact Dimensions to KPI Dashboards APPLICATION DATA SOURCES DATA WAREHOUSE KPI DASHBOARDS Carrier data INSIGHTS Pitney Bowes January 14,

9 Data System Architecture Pitney Bowes January 14,

10 Insights from Dashboards Dashboard of In-transit, shipped forward from hub Current status within four SLA categories o Delivered In SLA o Delivered Out of SLA o Undelivered o Undelivered, but still within SLA Trends for the same over prior months Can be filtered in real time on partner, which outbound hub, destination country, and vendors/shippers Pitney Bowes January 14,

11 Learnings Janitor Work 1 in data cleanup and aggregation Data de-normalization and duplicate data resolution across application data systems Incremental data feeds from existing systems (RDBMS) were challenging Understanding of Hadoop cluster capacity planning and resource management within a shared infrastructure 1. We quickly adopted patterns to abstract the data ingestion layer, to accommodate ongoing changes in source data schemas 11

12 Conclusions We have deployed a Hadoop based production big data solution based on a data lake architecture to integrate data from multiple data sources, and built a data warehouse. Data is made available at centralized store for responsive Dashboard queries and batch/real-time analytics. We have built a series of web accessible Dashboards for Business and Operations teams to monitor key KPI s (parcel status, SLA achievement, hub efficiency) and make informed operating decisions. Dashboard users can interact and have self-service drill down capability. Data warehouse definitions are published so additional advanced analytics can be developed by our analysts as required. Integrated Pitney Bowes Location Intelligence capabilities to cleanse and geocode global addresses, perform demographic segmentation and derive location based insights. Pitney Bowes January 14,

13 Thank you James A Fairweather, PhD Pitney Bowes January 14,

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