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How IoT is changing the agribusiness
landscape
Sjaak Wolfert – Sr. Scientist Infomanagement & ICT in Agri-Food
IoT Event, High Tech Campus, Eindhoven, 8 June 2016
Your image of farming?
Is this the actual image?
smart sensing
& monitoring
smart analysis
& planning
smart control
Closing the cyber-physical management cycle
BIG
DATA
IoT involves the whole supply chain
network and beyond
5
Source: Hisense.com
Smart Farming
Smart Logistics
tracking/& tracing
Domotics Health Fitness/Well-being
Which innovations and new business models are possible ?
Precision Farming/Advice Segment Cons. supportService ++
• Prescriptive farming
• Predictive maintenance
• Eco-systems of apps
• Big Data analysis for science,
advise, risk mgt, etc.
• Personalized
advise by apps
• Online shops
• Integrated supply chains
• Feedback consumer-producer
• Measure, pay
sustainability
• Better T&T
• Paperless chain
• Store
replenishment
• Category
management
Sustainability HealthFood SafetyFood Security
LoyaltySMEs Cost priceGRIN Cope with retail
Transport
Input industries
Farmer Food processor Retail / consumerSoftware
Provider
Logistic
solution
providers
Transport+
Collaboration and Data Exchange is needed!
Current key
competition issues
Public challenges
How more data
can help
New Business Models based on Big Data
See: Arent van 't Spijker: "The New Oil - using innovative business models to turn data into profit“, 2014
 Basic data sales
● commercial equivalent of open data (e.g. FarmMobile)
 Product innovation
● use data to improve your product (machinery industry, e.g. John
Deere, Lely’s milking robots)
 Commodity swap
● data for data (e.g. between farmers and (food) processors to
increase service component)
 Value chain integration
● use data to control the whole chain (e.g. Monsanto’s Fieldscript)
 Value net creation
● pool data from the same consumer (e.g. AgriPlace)
Redefining Industry Boundaries (1/2)
(according to Porter and Heppelmann, Harvard Business Review, 2014)
8
3. Smart, connected product
+
+
+
2. Smart Product
1. Product
Redefining Industry Boundaries (2/2)
(according to Porter and Heppelmann, Harvard Business Review, 2014)
9
5. System of systems
farm
management
system
farm
equipment
system
weather
data
system
irrigation
system
seed
optimizing
system
field
sensors
irrigation
nodes
irrigation
application
seed
optimization
application
farm
performance
database
seed
database
weather data
application
weather
forecasts
weather
maps
rain, humidity,
temperature sensors
farm
equipment
system
planters
tillers
combine
harvesters
4. Product system
Your company
How many platforms should
users and developers enter?
How many interfaces to
maintain?
Battlefield of IoT, Big Data and Farming
Farm
Farm
Farm
Farm
Data
Start-ups
Farming
Cooperatives
Open Ag Data
Alliance
...
AgBusiness
Monsanto
Cargill
Dupont
...
Tech
Companies
Google
IBM
Oracle
...
Ag Tech
John Deere
Trimble
Precision planting
...
Tech
Start-upsFarm
Tech
Start-ups
Data
Start-upsVenture
Capital
Anterra
Founders Fund
Kleiner Perkins
...
Farm
Example: Monsanto Fieldscripts
11
PRESCRIPTIVE
FARMING
based on
VARIABLE RATE
APPLICATION
Dairy Software Ecosystem
Data-driven dairy application development
Genotypic
cow data
Roughage
intake
Medicines
Milk
production
Animal
monitoring
Logistics
Dairy
products/
process
Consumer
use
Open Data Infrastructure
(privacy, security, trust)
Application
Services &
Components
Platform
Actors
Open
Software
Organization
Domain
Knowledge/
Models
Concentra
tes intake
...? ...?
SmartAgriFood2,
FInish, Fractals
FIspace collaboration platform architecture
150+ start-ups
Conclusions
 Agri-Food chains become more technology/data-driven
● Can cause major shifts in roles and power relations among
different players in agri-food chain networks
● Infrastructure and software development are key issues
 Significant socio-economic impacts; two scenarios:
1. Strong integrated supply chain
• farmer becomes franchiser/contractor
• limited freedom in doing business
2. Open collaboration network
• Farmer empowered through easier switch
between suppliers
• Options for direct sales to consumers
Reality somewhere in between?
F
F
Thank you for
your attention
Questions?
More information
sjaak.wolfert@wur.nl
nl.linkedin.com/in/sjaakwolfert/
Twitter: @sjaakwolfert
http://www.slideshare.net/SjaakWolfert

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How IoT is changing the agribusiness landscape

  • 1. How IoT is changing the agribusiness landscape Sjaak Wolfert – Sr. Scientist Infomanagement & ICT in Agri-Food IoT Event, High Tech Campus, Eindhoven, 8 June 2016
  • 2. Your image of farming?
  • 3. Is this the actual image?
  • 4. smart sensing & monitoring smart analysis & planning smart control Closing the cyber-physical management cycle BIG DATA
  • 5. IoT involves the whole supply chain network and beyond 5 Source: Hisense.com Smart Farming Smart Logistics tracking/& tracing Domotics Health Fitness/Well-being
  • 6. Which innovations and new business models are possible ? Precision Farming/Advice Segment Cons. supportService ++ • Prescriptive farming • Predictive maintenance • Eco-systems of apps • Big Data analysis for science, advise, risk mgt, etc. • Personalized advise by apps • Online shops • Integrated supply chains • Feedback consumer-producer • Measure, pay sustainability • Better T&T • Paperless chain • Store replenishment • Category management Sustainability HealthFood SafetyFood Security LoyaltySMEs Cost priceGRIN Cope with retail Transport Input industries Farmer Food processor Retail / consumerSoftware Provider Logistic solution providers Transport+ Collaboration and Data Exchange is needed! Current key competition issues Public challenges How more data can help
  • 7. New Business Models based on Big Data See: Arent van 't Spijker: "The New Oil - using innovative business models to turn data into profit“, 2014  Basic data sales ● commercial equivalent of open data (e.g. FarmMobile)  Product innovation ● use data to improve your product (machinery industry, e.g. John Deere, Lely’s milking robots)  Commodity swap ● data for data (e.g. between farmers and (food) processors to increase service component)  Value chain integration ● use data to control the whole chain (e.g. Monsanto’s Fieldscript)  Value net creation ● pool data from the same consumer (e.g. AgriPlace)
  • 8. Redefining Industry Boundaries (1/2) (according to Porter and Heppelmann, Harvard Business Review, 2014) 8 3. Smart, connected product + + + 2. Smart Product 1. Product
  • 9. Redefining Industry Boundaries (2/2) (according to Porter and Heppelmann, Harvard Business Review, 2014) 9 5. System of systems farm management system farm equipment system weather data system irrigation system seed optimizing system field sensors irrigation nodes irrigation application seed optimization application farm performance database seed database weather data application weather forecasts weather maps rain, humidity, temperature sensors farm equipment system planters tillers combine harvesters 4. Product system Your company How many platforms should users and developers enter? How many interfaces to maintain?
  • 10. Battlefield of IoT, Big Data and Farming Farm Farm Farm Farm Data Start-ups Farming Cooperatives Open Ag Data Alliance ... AgBusiness Monsanto Cargill Dupont ... Tech Companies Google IBM Oracle ... Ag Tech John Deere Trimble Precision planting ... Tech Start-upsFarm Tech Start-ups Data Start-upsVenture Capital Anterra Founders Fund Kleiner Perkins ... Farm
  • 12. Dairy Software Ecosystem Data-driven dairy application development Genotypic cow data Roughage intake Medicines Milk production Animal monitoring Logistics Dairy products/ process Consumer use Open Data Infrastructure (privacy, security, trust) Application Services & Components Platform Actors Open Software Organization Domain Knowledge/ Models Concentra tes intake ...? ...?
  • 13. SmartAgriFood2, FInish, Fractals FIspace collaboration platform architecture 150+ start-ups
  • 14. Conclusions  Agri-Food chains become more technology/data-driven ● Can cause major shifts in roles and power relations among different players in agri-food chain networks ● Infrastructure and software development are key issues  Significant socio-economic impacts; two scenarios: 1. Strong integrated supply chain • farmer becomes franchiser/contractor • limited freedom in doing business 2. Open collaboration network • Farmer empowered through easier switch between suppliers • Options for direct sales to consumers Reality somewhere in between? F F
  • 15. Thank you for your attention Questions? More information sjaak.wolfert@wur.nl nl.linkedin.com/in/sjaakwolfert/ Twitter: @sjaakwolfert http://www.slideshare.net/SjaakWolfert

Editor's Notes

  1. SW: through smart production (farming) and logistics food ends at the consumers plate Smart tracking and tracing is necessary to provide the right information about the product (contents, freshness, etc.) This information can be related to other (IoT) domains such as: Domotics (recipes, shopping, etc.) Health (allergies, obesitas, etc.) Fitness/Well-being (calorie-metering, healthy ingredients, etc.)
  2. Note that for most of these
  3. Current Farm management systems are not capable to do what is suggested in the picture. Therefore we have developed FIspace!
  4. Battlefield! Farming cooperatives, alliances - covenants