presentation on business aspects of ICT given at EU FRESH INFO congress in Rotterdam

1. Is there a business(case) in fresh
without ICT?
Krijn Poppe
LEI Wageningen UR
Based on work with Sjaak Wolfert, Cor Verdouw and others December 2015

2. Supervisory Board
Executive Board
Environmental
Sciences
Group
Alterra
Agrotechnology
& Food Sciences
Group
Food & Biobased
Research
Livestock Research
Central Veterinary
Institute
Animal
Sciences
Group
Plant
Sciences
Group
Plant
Research
International
Applied Plant
Research
Social
Sciences
Group
Wageningen University
Contract Research Organisation
Concern Staff Facilities & Services
Wageningen
Academy
IMARES
Wageningen
International
LEI
Centre for
Development
Innovation
RIKILT
(food safety)
Environmental
Sciences
Animal Sciences Plant Sciences Social SciencesAgrotechnology
& Food Sciences
Wageningen UR
and LEI

3. 265
employees
65% male
35% female
LEI
Wageningen
UR
Facts
40%
Accepted EU
R&D proposals
in societal
challenge 2
Turnover
€ 31 mln
...
Yearly
around 100
references
in parlement

4. working
on
global
challenges
worldwide
Food Security
Biobased Economy
Water, Energy and Climate
Sustainable Food Clusters

5. CONTENT
1. ICT: What is happening
2. Why now?
3. Business collaboration
4. Food and health
5. How to organise this all?

6. ICT brings info for farmer and consumer
Royal Gala apple
Origin: Girona
Pesticides: No
Organic farming: Yes
Carbon footprint:1,2 kg CO2e

7. Drones, Big Data and Agriculture 7
IoT in Smart Farming
cloud-based event
and data
management
smart sensing
& monitoring
smart analysis
& planning
smart control

8. Connected Nursery
8
Order info
Cultivation
info
Stock info
Quality info
Financial
info
Systems in Supply
Chain Network
Trader
Retail
Service
provider
Accountant
Service
provider
Trader
Etail
Detail
Rules issuing authorities
Systems Authorities
Compliance info
Supplier info
Supplier
Systems
Seed supplier
Packaging supplier
Pesticides supplier
Info exchange
Supply Chain
Network
Enterprise
System Grower
Systems and machines in the primary production / cultivation
Internal info
exchange
cultivation
related
machines Work definition Work planningWork capacity Work performance

9. Adoption of Connected
Nursery solutions
Economic reality
High ICT
complexity
High path
dependency
Relative small scale
of farms
Low rate of
investments of
growers
Decrease high-
end market
Low willingness to
cooperate
Limited
development of
integration solutions
Negative
perception relative
advantage

10. Towards smart autonomous objects
Source: Deloitte (2014), IT Trends en Innovatie Survey
Tracking &
Tracing
Monitoring
I am thirsty: water
me within 1 hour!
I am product X at
locatie L of Z
My vaselife is
optimal at a
temperature of
4,3 °C.
I am too warm:
lower the
temperature by
3 °C
Event
Management
I am too warm: I lower
the cooling of my truck
X by 2 °C.
I don’t want to
stand besides
that banana!
I am thirsty!
I am warm!
Optimalisation
Autonomy

11. Virtual Box
Location A Location B
Location
& State
update
Location &
State
update Location
& State
update
IoT in Agri-Food Supply Chains
11Drones, Big Data and Agriculture

12. Quality-controlled Supply Chain
12

13. Disruptive ICT Trends:
 Mobile/Cloud Computing – smart phones, wearables,
incl. sensors
 Internet of Things – everything gets connected in the
internet (virtualisation, M2M, autonomous devices)
 Location-based monitoring - satellite and remote sensing
technology, geo information, drones, etc.
 Social media - Facebook, Twitter, Wiki, etc.
Big Data - Web of Data, Linked Open Data
High Potential for unprecedented innovations!
everywhere
anything
anywhere
everybody

14. Disruptive scenario: Toshiba’s lettuce growing

15. tijd
Mate van verspreiding
van technologische revolutie
Installatie periode
Volgende
golf
Uitrol periode
Draai-
punt
INDRINGER
EXTASE
SYNERGIE
RIJPHEID
Door-
braak
Werkeloosheid
Stilstand oude bedrijfstakken
Kapitaal zoekt nieuwe techniek
Financiele bubble
Onevenwichtigheden
Polarisatie arm en rijk
Gouden eeuw
Coherente groei
Toenemende externalities
Techniek bereikt grenzen
Marktverzadiging
Teleurstelling en gemakzucht
Institutionele
innovatie
Naar Perez, 2002
Crash
2008
1929
1893
1847
1797
time
Degree of diffusion of the
technological revoluton
Installation period
Next
wave
Deployment
period
Turning
point
IRRUPTION
FRENZY
SYNERGY
MATURITY
Big Bang
Unemployment
Decline of old industries
Capital searches new techniques
Financial bubble
Decoupling in the system
Polarisation poor and rich
Golden age
Coherent growth
Increasing externalities
Last products & industries
Market saturation
Disappointment vs
complacency
Crash
2008
1929
1893
1847
1797
Institutional
innovation
Based on Perez, 2002
The opportunity for green growth
1971 chip ICT
1908 car, oil, mass production
1875 steel
1829 steam, railways
1771 water, textiles

16. Europe towards
2050
3 scenarios to
explore the
future of EU
agriculture
source: SCAR-AKIS

17.  HighTech: strong influence new technology owned by
multinationals. Driverless tractors, contract farming and a
rural exodus. US of Europe. Rich society with inequality.
Sustainability issues solved. Bio-boom scenario.
 Self-organisation: Europe of regions where new ICT
technologies with disruptive business models lead to self-
organisation, bottom-up democracy, short-supply chains,
multi-functional agriculture. European institutions are weak,
regions and cities rule. Inequalities between regions,
depending on endowments.
 Collapse: Big climate change effects, mass-migration and
political turbulence leads to a collapse of institutions and
European integration. Regional and local communities look
for self-sufficiency. Bio-scarcity and labour intensive
agriculture. Technology development becomes dependent on
science in China, India, Brazil.

18. Chain organisation changes (©Gereffi et al., 2005)
inputsEndproduct
PRICE
Shops Complete
IntegrationLead
company
Lead
company
Turnkey
supplier
Relational
supplier
Market Modular Relational Captive Hierarchy
Low Degree of explicit coordination and power asymmetry High
Lead
company
Farmers

19. Which innovations and new business models are possible ?
Precision Farming/Advice Segment Cons. supportService ++
• Prescriptive farming
• Predictive maintenance
• Eco-systems of apps
• Regionally pooled big data
analysis for science and
advise (and risk mgt.)
• 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!

20. Data exchange by ABCDEFs
 Large organisations mostly have gone digital, with ERP
and other systems
 But between organisations (especially with SMEs) data
exchange and interoperability is still very poor
 While more data exchange for collaboration and business
process control in the chain is needed
● As data need to be combined to create value
● The better we exchange data, the less disruptive it is
for current business models and organisations
There is a need for ABCDEFs:
Agri-Business Collaboration & Data Exchange Facility
Proprietary/closed or open ABCDEFs?

21. Redefining Industry Boundaries (1/2)
(according to Porter and Heppelmann, Harvard Business Review, 2014)
21
3. Smart, connected product
+
+
+
2. Smart Product
1. Product

22. Redefining Industry Boundaries (2/2)
(according to Porter and Heppelmann, Harvard Business Review, 2014)
22
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
Is this
‘mono-equipment
system’ reality?
How to cope with
changes in industry
boundries?
How many
platforms should
users and
developers enter?

23. Agri-Food Supply
Chain Networks
are multi-
dimensional
• Markets allocate
products to different
destinations
• Chains are
supported by many
service providers
• Intensive data-
exchange with
governments
law & regulation
innovation
geographic
cluster
horizontal
fulfillment
Vertical

24. Farm Digital project
Sharing Data with AgriPlace:
Compliance Made Easy
http://www.farmdigital.nl/

25. LESS ADMINISTRATIVE BURDEN
AND CREATING VALUE
Auditors
• More effective audit on farm
• More new clients
• Savings of >€100 per audit visit
Farmers and Growers
• Less time and irritation to collect data
• More digital management
• Savings of >€500 euro per grower
Retailers
• Quicker and more complete data
• Better risk management
• > €30 savings per farm request
Importers and Food processors
• Cost savings on data collection
• Increase data quality
• Savings > €10,000 per importer
Consumers
• Relation with growers
• Better understanding of labels
• More transparency
PROTOTYPE
AGRI-PLACE
FMS-manage-
ment software
GOV. open data
LEI Wageningen UR
Benchmark-data

26. The USA battleground: Monsanto (et al.)
26
PRESCRIPTIVE
FARMING
based on
VARIABLE RATE
APPLICATION

27. USA: Farmers Business Network
27
Farmers’ owned,
investment by Google
Ventures
Summer 2015:
FBN has aggregated data from 7
million acres of farm land across
17 states, and they’re growing
30% month over month. The
platform is currently
able to assess the performance
of 500 seeds and 16 different
crops.
Costs farmer $ 500 / year.

28. USA: Farm Mobile
28
“Farmers believe their trust has been violated”:
their data go to multinationals, that announce
big future income from big data, while they have
pay for everything.
Farmers collect
‘crop stories’
and decide where
they travel (and get a
few cents per item?)

29. Discusions among US farmers:
29
Code of Conduct
• Do I own my own data?
• Who has access to my data?
• Does the government have access?
• Do companies gain market power on future markets ?
• Is there a lock inn ?
• Do I become a franchiser with the risks but not the
returns?

30. Towards the future:
30
• Horticulture and farming become data based
• Data have mainly a value if they are combined
and aggregated
• Huge network effects can lead to monopolies
• That means that collaboration / cooperation is
needed and good governance is key.
• Is there a solution?

31. Is an eco-system of apps an alternative?
FARMER SCANS PESTICIDES PACKAGE IN THE FIELD
APP CONNECTS BASF FOR E-INSTRUCTION,
CROP AND SOIL SPECIFIC
APP ASK METEO FOR 24 hour WEATHER FORECAST
BASF SENDS INSTRUCTION TO SPRAYING MACHINE
ON WATER / PESTICIDE RATIO >> Machine adjusts
APP CHECKS ADVISE WITH GOV.AGENCY
FARMER CAN SHARE DATA WITH GOVERNMENT,
SGS-AUDITOR GLOBAL GAP AND PUBLIC
CAN I USE
MY CURRENT
SERVICE ?
CAN I USE
MY FMS ?
DOES IT
WORK WITH
BAYER /
DEERE
DOES IT
WORK WITH
BRC /
ISAcert
Can we link apps / services in a clever way ?
Leading to a market for services (apps and
data)?
Can this market be European (not MS), so
that development costs of services (apps and
data) are shared ?

32. Towards highly integrated solutions
Platforms in the cloud of input suppliers and food processors:
• What is the scope (connect only machinery or also with chemical
companies and accountants ?)
• Reduce costs of linking individually with many other platforms and
software packages (especially in chains that are not integrated)
• Is it possible to use apps with their own business model, so that the
platform does not have to pay all their costs? >> can (non-strategic)
apps be available on several platforms?
• How to prevent that farmers complain to have to pay for basis apps
(e.g. weather service) more than once?
MyJohnDeere.com Farmers
Biz architect
bundles apps
in a platform
...
80 Accelerator
companies
Apps

33. Towards highly integrated solutions
Highly Integrated Service Solutions
• Event-driven
• Configurable
• Customizable
• Service model
Data (Standardisation) Services
AdaptEPCIS
MyJohnDeere.com
Data Standards
to connect
Business
Collaboration
Services -
Based on Open
Source Software
Farmers
Biz architect
bundles apps
in a platform
...
80 Accelerator
companies
Apps
Modules:
Single SignOn
Biz Collab.
Event Proces.
System-Data
integration
App repository

34. Value proposition
Platforms solve the issue of connecting individually with a lot of business
partners to exchange data : connect easily to apps (and data
services in apps) based on EDI-standards or let farmers / end-users
make the connection
App-developers Develop one app for different platforms
Reach a European / Global market
Governments
(and industry
organisations)
See above for your government platform (paying agency, public
advisory service etc.)
Promote innovation by a competitive market for apps with new
services
Prevent lock-inn situations for farmers and unbalanced power
relations in the information exchange in food chains
Farmers Not a direct FIspace client. Platforms using FIspace inside provide
you more choice
Software writers
in platforms and
app-companies
Helps you to be part of an open source community that cares for
sustainable food production with up to date ICT – be recognized by
your peers

35. FIspace
App Store
80 Accelerator
companies
Configure &
Use Systems
First Commercial MVP by ... ?
App developer Business Configurator End User
Advertiser
Access fee
Use Fee Use Fee
Access fee (e.g.
CargoSwApp)
Pay for app use (e.g.
Spraying Advice)
Sponsored app
FIspace Foundation
MVP – open source
My JohnDeere
365 Farmnet
Akkerweb
Dacom/CROP-R
Datalab Pantheon
ICT company Service model ?

36. Towards highly integrated solutions
Highly Integrated Service Solutions
• Event-driven
• Configurable
• Customizable
• Service model
Data (Standardisation) Services
AdaptEPCIS
MyJohnDeere.com
Data Standards
to connect
Business
Collaboration
Services -
Based on Open
Source Software
Farmers
Biz architect
bundles apps
in a platform
...
80 Accelerator
companies
Apps
Modules:
Single SignOn
Biz Collab.
Event Proces.
System-Data
integration
App repository
Is this commercially feasible?
Or is it too much a common pool
investment in a market where
everybody wants to grab a stake, over-
estimates the value of its own data and
finds it easier to builds its own website
?

37. IoT and the consumer
37Drones, Big Data and Agriculture
Source: Hisense.com
Smart Farming
Smart Logistics
tracking/& tracing
Domotics Health Fitness/Well-being

38. Food consumption compared to official
advise, NL 2007 – 2010 (source: PBL)
38

39. Consumer Interaction
A. Quick Scan Food Apps
1. Generic product information
2. Specific product information
3. Cooking information
4. Purchase support / retailer
5. Food safety
B. Qualitative Reserach
C. Quantitative Research

40. A SMARTer Greenport
Consumer Interaction
1. Veggipedia-app
2. User Generated Content
→ Interviews learn us that there is not much interest in
providing USG (even with digital natives).
→ Recipes score best

41. www.eurodish.eu02/12/201p. 41
Big data for smart food and health
services
41
Lifestyle
Health
Food

42. Big Data Horticulture
42
BIG
DATA
OPEN
DATA
Social media - Unstructured - Event-driven Information systems – Structured - Transaction-driven
HORTI-
CONNECTOR
HORTI-
RADAR
HORTI-CUBE
MAP
ANONY
MISE
AGGRE
GATE
COM
BINE
COL
LECT
INTER
PRET
TOPICS
TRENDS
ALERTS
NORMS
TRANSACTIONS
REGISTRATIONS
BUSINESS GOVERNMENT RESEARCH
CULTIVATION IMPORT PRODUCT MARKET LOCATION FLOW
apps services

43. Need for (institutional) innovation
 Adoption bottlenecks in small companies (Connected
Nursery)
 Organisation of the chain under discussion (Gereffi)
 Discussions on ownership, privacy etc. (US examples)
 Scope of systems and platforms (Porter et al. HBR)
 Common pool investments needed in standards and data
exchange facility (Fispace example)
 Business model and governance (Farm Digital)
 Consumer interaction: not easy
 Big data and open data: still a struggle ?
 INCREASES CHANCE OF DISRUPTIVE INNOVATION ?

44. Can we speed up these trends?
 Can we learn from the organisation of the FI-PPP ?
 Pay more attention to business models, data ownership,
sustainability after project ??
 Create free experimentation zones with Hackatons, Plug-
fests, Data-paloozas etc.

45. Thanks for your
attention
krijn.poppe@wur.nl
www.lei.wur.nl