Harnessing the Power of Network Data

Network Data is the Next Frontier of Supply Chain 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  

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

Network Data Addresses >70% Concerns

Weather.      Raw  material  pricing.    

Wars.    

Carrier  availability.    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.  

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.

IteraHve  Effort  ReducHon  in  B2B  Schema  IntegraHon  via  a  Canonical  Data  Model  Interna*onal  Journal  of  Strategic  Informa*on  Technology  and  Applica*ons  October-­‐December,  2013  

Elemica 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.    

“…omen  a  company’s  data  defini*ons  are  inconsistent…  this  reduces  value.  ”  

Addressing  this  was  a  priority  for  Elemica  when  developing  our  

canonicals.  

How  to  Avoid  the  Big  Bad  Data  Trap  Boston  Consul*ng  Group  June,  19,  2015  

Business Process Areas Supported on 2.0

Finance  Invoice…  

LogisHcs  Shipment  Status…  

Order  Management  

Orders…  

Quality  COA…  

SerializaHon  Serial#  Hierarchy…  

Supply  Chain  Forecast…  

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

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.