Network data combines information from various systems like ERP, trading partners, and supply chain applications as well as outside data feeds. When analyzed using advanced tools, network data represents the next frontier of supply chain innovation by addressing over 70% of supply chain concerns. Elemica's evolving canonical data model aims to facilitate network data sharing and integration by defining a shared data model that can evolve over time while maintaining backward compatibility. The model supports key business processes and functions across finance, logistics, order management, quality, and supply chain.

1. Harnessing the Power
of Network Data

2. What is Network Data?
• Combination of data from:
– Your ERP
– Trading partner systems
– Network applications – Elemica Logistics or Supply Chain Applications
– Plus, outside data feeds

3. Network Data is a Disruptive: the
Next Frontier of SC Innovation
The combination of large, fast-moving, and varied
streams of big data and advanced tools and
techniques such as geoanalytics represents the next
frontier of supply chain innovation.
Making Big Data Work: Supply Chain Management.
Boston Consul*ng Group
January, 2015
The Supply Chain Officer’s Report
SCM World
September, 2014

4. Network Data Addresses >70%
Concerns
Weather. Raw material pricing.
Wars.
Strike.
Demand.
Weather.
Government
regula*ons
Track and trace.
First run quality stats.
Impact of ERP upgrade
Emerging markets – supply,
currency fluctua*ons
Emerging markets
– supply, currency
fluctua*ons
80/20 project – 80% of business by 20% of customers.
Transit availability / *mes.
Transport (import, export, domes*cs).
Rail
performance.
Truck performance.
Food and pharma need a high
degree of lot / batch management.
Business process requirements of customers
might go beyond what we can support.
Rail performance
Truck performance
Manufacturing scheduling – to forecasts and orders.
Warehousing network
performance.
Product stewardships (EHS, app support,
providing the right level of technical info).
M&A
Insight into research / experimental
products – schedule, setup.
Experimental
samples.
Impact of
new CRM.
Preproduc*on trials – not in SAP; manual.
Where are we headed?
How real is
demand.
What is the
future.
Strategic direc*on of the company.
Serializa*on requirements.
Forecasts.
Source 2015 Elemica Focus Group
Batch xyz has an issue.
Show me the serial
numbers and where
each is: in-transit, on-
shelf, or sold.
Will my carrier’s
performance for
lane xyz be worse
or beaer than
expected based on
all known data.

5. How do we get the data?
1) Companies
send their
standard.
2) Different
iden*fier
values.
3) Evolving
requirements.
4) Desire to
interpret non-
structured
data
5) Non-standard
use of
standards.
“The nice thing about standards is that there are so many to choose from.”
Tanenbaum, 2002
B2B integration still remains a big cost driver for
companies. Instead of forcing companies to adopt
huge standards, this article propagates an iteratively
improving schema… an Evolving Canonical Model.
Itera&ve Effort Reduc&on in B2B Schema Integra&on via a Canonical Data Model
Dietrich, Lemcke, and Stuhec. Dec 2013

6. Elemica’s Evolving Canonical
Model
Model real-world supply chains
• Serializa*on. Track. Trace.
• Complex packaging
Shared data model
• Across messages and applica*on.
Lifecycle management
• Backward compa*bility.
• Evolve by partner.
Mapping efficiency.
“…olen a company’s data
defini*ons are inconsistent… this
reduces value. ”
How to Avoid the Big Bad Data Trap
Boston Consul*ng Group
June, 19, 2015

7. Business Process Areas
Supported on 2.0
Finance
Invoice…
LogisHcs
Shipment Status…
Order
Management
Orders…
Quality
COA…
SerializaHon
Serial# Hierarchy…
Supply Chain
Forecast…

8. Example of New 2.0
Functions
“The farmer’s ability to locate a precise position in a
field allows for.... optimal application of seeds,
fertilizer, herbicides… A “pedigree” of each seed or
plant…that shows exactly what chemical (and even
batch) that was applied to each plant…
communicated through the supply chain operating
network across all steps in the food and beverage
value chain.”Internet-Based Technology Redefines F&B Supply Chain Opera=ons
Food Logistics Magazine
August 14, 2015
• Consumer specification of batch numbers and expirations
– For example, scarce supply of perishable materials
– Serial numbers, batch numbers, expiration dates, temperature
– Request specified characteristics in an order
• Stronger support for packaged goods
– For example, multi-customer pallet with multiple drop-offs
– Multiple pallets of packaged products supported
– Multiple serialized labels per packaging layer
• Geo-spatial coordinates
– Latitude, longitude, elevation, depth
• Strong, consistent data model to support analytics across all

9. Some Statistics
30 Message
Canonicals
• Invoice
• Shipment
Instruc*ons
• Order Crea*on
• Cer*ficate of
Analysis
• Serializa*on
Hierarchy
• Etc.
56 Major
Structures
• Date Time
• Partners
• Packaging
structure
• Test Specs
• etc.
52 Type Lists
• HazMat Type
• Partner ID Type
• PO Type
• Etc.
139 Unique Data
Fields
• La*tude
• Payment Ac*on
Code
• Product
Iden*fier
• Seal Number
• etc.

10. Contact
• gneights@Elemica.com
• 267-237-7294