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Attention to data creates growth
Krijn Poppe Wageningen Economic Research
Based on work with WUR team (Sjaak Wolfert, Cor Verdouw, Lan Ge, Marc
Jeroen Bogaardt, Jan Willem Kruize and others)
November 2017 Global Food Summit, Berlin
Content of the presentation
What is happening: disruptive ict trends leading to data capturing
New players challenge food chains
Why does that happen now: long wave theory
Institutional change is happening
Changes in the organisation of the food chain
How to organise data exchange
Next steps for business and governments
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.
Block Chain – Tracing & Tracking, Contracts.
Big Data - Web of Data, Linked Open Data, Big data algorithms
High Potential for unprecedented innovations!
everywhere
anything
anywhere
everybody
Big Data – the ‘official’ definition: 5 V’s
Volume – vast amounts of data
Velocity – different types, unstructured
Veracity – speed of generation / transfer
Veriaty – messiness / trustworthiness
Value – generated by artificial intelligence● Symbolic reasoning● Connections modeled on the basis of
the brain's neurons● Evolutionary algorithms that test
variation● Bayesian inference● Sytems that learn by analogy
DATA CAPTURING TOOLS FOR
BETTER CONTROL
Prescriptive AgriculturePredictive Maintenance
6
IoT in Smart Farming
cloud-based event and data
management
smart sensing& monitoring
smart analysis & planning
smart control
Virtual Box
Location A Location B
Location
& State
update
Location &
State
update Location
& State
update
IoT in Agri-Food Supply Chains (digital twins)
7Drones, Big Data and Agriculture
IoT and the consumer: food and health
Smart Farming
Smart Logistics
tracking & tracing
Domotics Health
Fitness/Well-being
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 by3 °C
Event
Management
I am too warm: I lowerthe cooling of my truck
X by 2 °C.
I don’t want tostand besidesthat banana!
I am thirsty!
I am warm!
Optimalisation
Autonomy
Trends in the food chain
10
Dynamic landscape of Big Data & Farming
11
Farm
Farm
Farm
Farm
Data
Start-ups
Farming
AgBusinessMonsanto
Cargill
Dupont...
ICT Companies
IBM
Oracle...
Ag TechJohn Deere
Trimble
Precision planting
...
ICTStart-ups
Farm
Ag software
Companies
AgTech
Start-upsVenture Capital
Founders Fund
Kleiner Perkins
Anterra
...
Farm
tijd
Mate van verspreiding
van technologische revolutie
Installatie periode
Volgende
golf
Uitrol periode
Draai-
punt
INDRINGER
EXTASE
SYNERGIE
RIJPHEID
Door-
braak
WerkeloosheidStilstand oude bedrijfstakken
Kapitaal zoekt nieuwe techniek
Financiele bubbleOnevenwichtighedenPolarisatie arm en rijk
Gouden eeuwCoherente groei
Toenemende externalities
Techniek bereikt grenzenMarktverzadiging
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 bubbleDecoupling in the system
Polarisation poor and rich
Golden age
Coherent growth
Increasing externalities
Last products & industries
Market saturation
Disappointment vscomplacency
Crash
2008
1929
1893
1847
1797
Institutional
innovation
Based on Perez, 2002
The opportunity for green growth
1971 chip ICT1908 car, oil, mass production1875 steel1829 steam, railways1771 water, textiles
The end of the expert >> citizen science?
Post-modernism: “science is just another opinion”
Distrust of experts; and of elites / the powerful
But also search for ‘gurus’ (e.g. in food consumption), strong dogma’s.
Commercial and competitive influences in research (funding, need to be in the media, publications and citations as yardstick)
Media looking for new business models (advertising goes
online)
Single issue NGO’s, with their own ‘business model’
Politicians exploit fear instead of reducing it; toofocussed on next vote? Quality issues in civil service?
One answer: citizen science, (digital) commons ????
Food chain: 2 weak spots – opportunity?
Input industriesFarmerFood processorConsumer Retail
• Public health issues –obesity, Diabetes-2 etc.
• Climate change asks for changes in diet
• Strong structural change
• Environmental costs need to be internalised
• Climate change (GHG) strengthens this
Is it coincidence that these 2 are the weakest groups?Are these issues business opportunities and does ICT help?Which institutional innovations are needed?
Issues at several institutional levels
Data ethics, privacy thinking, on-line and wiki culture. Libertarian ‘californisation’
Data “ownership”, right to be forgotten, right to repair, open data, cyber security laws etc.
Platforms (nested markets), contract design (liability !), open source bus. models
Value of data and information
• Products change: the tractor withICT – from product to service
• New products: smart phones, apps, drones: should markets becreated or regulated ?
New entrants:• Designers on Etsy• Landlords on AirBnb• Drivers on Uber
New entrants:• Direct international
sales by website• Long tail: buyers for
rare products
• Due to ICT new options to fine tune regulation / monitor behaviour
• Regulation can be out of date
• New types of pricing and contracts: on-lineauctions, dynamic pricing, risk profiling etc.
• Shorter supply chains (intermediaries as travel agencies and book shops disappear)
• Strong network effects in on-line platforms (rents and monopolies)
Chain organisation changes (©Gereffi et al., 2005)
inputs
End p
roduct
PRICE
Shops
Complete Integration
Lead company
Leadcompany
Turnkeysupplier
Relationalsupplier
Market Modular Relational Captive Hierarchy
Low Degree of explicit coordination and power asymmetry High
Leadcompany
Farmers
There is a need for
software ecosystems
for ABCDEFs:
Agri-Business
Collaboration & Data
Exchange Facilities
• Large organisations have gone digital, with ERP systems
• But between organisations (especially with SMEs) data exchange and interoperability is still poor
• ABCDEF platforms help
law & regulation
innovation
geographic
cluster
horizontal
fulfillment
Vertical
Agri-Food chains become more technology/data-driven
Probably causes major shifts in roles and power relations among different players in agri-food chain networks
Governance and Business Models are key issues
There is a need for a facilitating open infrastructure (scenario 2)
Two extreme scenarios:
1. Strong integrated supply chain
2. Open collaboration network
Reality somewhere in between!
2 Scenarios, with significant impacts ?
2 Scenario’s to explore the future:
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.
(Based on EU SCAR AKIS-3 report that also included a Collapse scenario:
Big climate change effects, mass-migration and political turbulence leads to a
collapse of institutions and European integration).
Data gets value by combining them
Property rights on data needs to be designed
Privacy disappears, de-anonimisation with big data techniques (profiling) becomes too easy.
Where do my data travel ?
Need to exercise data property rights withauthorisations
Best situation for the farmer is that (s)he has oneportal for all authorizations (like a password manager)
Governance of this portal: public, non-profit, profit?21
DataFAIR: AgriTrust authorization registerto build trust in data exchange
Sustainability: Incentivise farmers
0
20
40
60
80
100
Cost priceper 100 kg milk
Income perFamily
Labour unit
solvability (%)
Energy use per euro output
Water use per euro output
Pesticide useper hectare
Grazing days
Education
Surplus of
Phosphate per hectare
Surplus ofNitrogen per
hectare
PEOPLE
PROFIT
<< PLANET >>
Agriplace –compliance in food safety etc. made easy
Two platform examples from our work
Donate to (citizen) research
RICHFIELDS: manage yourfood, lifestyle, health data and donate data toresearch infrastructure
audit
FMIS
Next steps for the agri-food sector
Climate change - a new narrative for change
● Food Policy to connect farming and consumers
● Digitalisation to support change
● Sustainability monitoring with data exchange in the whole food chain (see the FLINT project)
● Including food, lifestyle and health data at consumer level to support healthy lifestyles
Governments should care for ict infrastructure including utilities like essential platforms
Replace privacy thinking by data “ownership” (consent) thinking. Farmers and consumers should show more ownership, companies should share.
Thanks for your
attention
and we welcome
collaboration in
your projects !!
www.wur.nl
