Big Data, Analytics, and IoT in
Cross-Border Ecommerce
James A Fairweather, PhD
Vice President, PB Technology, Experience and Ecommerce
How we enable transactions in commerce.
Our solutions help businesses manage customer information and turn it into data-driven 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
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
• Empowering customers worldwide to easily and efficiently
track their parcels and packages no matter where they are
3 SOFTWARE SERVICES TRANSPORTATION SERVICES API / WEB INTEGRATION Product Classification • Catalog harmonization • Machine learning Product Goods Management • Import / export compliance • Hazmat & dangerous goods Fully landed costs • Duties & taxes • Shipping Hub Operations • International shipping lables • Commercial invoice preparation Carrier Management • Organic, optimized carrier network • International line‐haul Parcel Tracking • Consistent & reliable tracking visibility • API integration & tracking portal
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…
Parcel Process Flow
Parcels are transported to the PB Hub (single parcel or freight)
Inbound to PB hub:
• Retailer/shipper prepares parcels • ASN transmitted to PB
• PB generates a Universal Parcel Identifier (UPID)
• Retailer/shipper sends parcels
Parcel is received at the PB Hub
Goods are cleared through foreign customs via a PB Broker
PB coordinates with a contracted agent or a
commercial carrier, depending upon the destination country
PB coordinates and consolidates parcels for international line-haul
PB prepares the parcels for International line-haul
--• HS Classification
• Export Compliance (ECCN) review • Import Restrictions Screening review • Content Inspection
• Commercial Invoices • TSA Screening
Tracking Event Aggregation & Architecture
Belt scan, weigh and dimension Ring scanners Central Parcel DB Hub Operations Software Hub application, Hub application database Carrier 1 Carrier 2 Carrier 3 Carrier 4 Carrier 5 Carrier 6 Carrier 7 Carrier 8 Carrier 9 Tracking Data FTP, HTTP/XML, Web Services Carrier Tracking Services Parcel API, Adapters Reporting (operational, analytics, etc.)Strategic foundational technologies
Solution/ Business Outcome Physical SW/HW Products Digital (Web)Convergence: Broader Digitization (People, Machines, Things, Logistics) Digital (Mobile) Evolution of Industry Technologies How Technology is Consumed Information SaaS SaaS Mobile Mobile APIm APIm Big Data Big Data Machine Learning & AI Machine Learning & AI Analytics Analytics M2M / IoT M2M / IoT 7 Pitney Bowes | January 14, 2015
Drive Fact Dimensions to KPI Dashboards
APPLICATION
DATA SOURCES DATA WAREHOUSE KPI DASHBOARDS
INSIGHTS
Carrier data
Data System Architecture
9 Pitney Bowes | January 14, 2015
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
Learnings
1. http://www.nytimes.com/2014/08/18/technology/for-big-data-scientists-hurdle-to-insights-is-janitor-work.html
11
“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
We quickly adopted patterns to abstract the data ingestion layer, to accommodate ongoing changes in source data schemas
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.
