Surfing on the Innovation hype curve: Time to explore business models for agtech on the innovation trigger

Transcription

1 Surfing on the Innovation hype curve: Time to explore business models for agtech on the innovation trigger Grigoris Chatzikostas Head of Business Development Department BioSense Institute Brussels,

2 Trends/Investments in AgriTech Innovation hype curve 03 Technologies in focus - Blockchain 04 Technologies in focus Big Data 05 Technologies in focus - IoT BioSense Institute at glance Next steps 01 Agenda 07 2

3 BioSense Institute at glance 3

4 We cannot feed today s world with yesterday s agriculture! In 1900 one farmer produced enough food for 10 people. Today one farmer feeds over 120 people. 4

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6 BioSense Vision Agriculture of the Future 6

7 Business development department Challenge indentification Call identification New project proposal preparation Accelerator Selection of start-ups Funding Proposal writting process Consortium establishment Mentoring Investment readiness program Business Development Technology watch Initiatives, calls Ecosystem building Contacts and partnerships Strategic Planning BDD Project Management Capacity Building Internal and external trainings PA4ALL Start-up mentoring Project reporting Project implementation Implementation schedule Consortia meetings Performance monitoring External / interal communication Project administration Deliverables preparation 7

8 34 projects with 40 + M 8

9 H2020 KATANA

10 H2020 KATANA Selection and funding scheme Supporting services Technology Peer-2-peer evaluation Reward crowdfunding Equity crowdfunding Matchmaking facility Training program Lean start-up approach Marketplace for PA Services IoT Platform for reaching consumers Toolbox for the design of functional foods 10

11 Total nr. of teams H2020 KATANA 1 ST PHASE RESULTS Applications from KATANA Consortium countries NUMBER OF TEAM MEMBERS Non KATANA Consortium countries 31% KATANA Consortium countries 69% Nr of team mebers GENDER BALANCE Male; 62% Female; 38% 11

12 H2020 KATANA 1 ST PHASE RESULTS Fields of application of the selected projects Smart farming technologies 17 Shelf-life 3 Waste/bio-cascading and stream valorization 8 Personalised Nutrition and Health Novel food products New ways of purchasing food Increasing farming efficiency 6 Food quality analyses/food processing monitoring 2 Primary Production 45 Food processing 18 Distribution & retail 15 12

13 H2020 KATANA - NEXT PHASE Pitch Evaluation Bootcamp Evaluation 2 minute pitch as a qualificati on for next round Peer-2-Peer evaluation, without external evaluators Mentoring; Webinars; Customer-focused business modelling training; Matchmaking facility; Consortium building Reward crowdfunding Funding and Services KATANA additional services: Investment readiness program; 5 webinars; Export promotion e-learning training courses; Equity 13 crowdfunding.

14 H2020 Smart-AKIS

15 Smart-AKIS Smart Farming Technologies An inventory of direct applicable solutions from the large stock of research results and commercial applications. Online Smart Community Platform Inventory Networking area Innovation hubs 7 hubs Transnational workshops Reports on needs of farmers from France, Germany, Greece, Netherlands, Serbia, Spain and UK. Farmers community Report on factors hindering the adoption of Smart Farming in Europe. 15

16 Smart-AKIS 1 st year findings Platform indicators: search box Ranking of TRL searched TRL9 16

17 Trends/Investments in AgriTech 17

18 What do newspapers say about agriculture? 18

19 Investments in Agriculture (2016) Agtech investment dropped 30% in 2016 year-over-year after exponential growth for three consecutive years, but remains above 2014 levels. The pullback in funding reflected declines in bioenergy, drone technology and food delivery investment. It follows a 10% decline across the global venture capital markets after record-breaking highs in 2015 for both the global VC markets ($141bn) and the agtech sector. Source: AgTech Investing Report Year in review 2016, January 31,

20 Where are investors placing their bets? Top priorities 1. Big Data and analytics 2. Food security and tracebility 3. Biologics 4. Optimization hardware 5. Sensors and connectivity 6. New-crop technology 7. Autonomous equipment Source: BCG-AgFunder survey, October

21 Innovation hype curve Ryan Rakestraw, Venture Principal at Monsanto Growth Ventures, PrecisionAg Vision event, October

22 Innovation hype curve IoT Blockchain Big Data Ryan Rakestraw, Venture Principal at Monsanto Growth Ventures, PrecisionAg Vision event, October

23 Blockchain in Agriculture

24 Blockchain opportunities&challenges Outcomes from the Blockchain summit, 23rd of February Opportunities in the field of: Securing and simplifying commodity management Simplify and de-risk trade finance Provenance Challenges while addressing these opportunities Ability to identify and verify not just people but also other actors in the supply chain such as machinery, trucks, and IoT devices. New standards and governance models must be developed Adaptation of existing organizations, systems and processes to the fundamentally different market structures Transparency overall will have an unknown impact on market structures and behaviors 24

25 Blockchain opportunities in agriculture (1/2) When everything claims to be handmade and eco, what can we trust? Supply chain intelligence needed! Improved product tracking Product tracking Retailers Consumers 25

26 Blockchain opportunities in agriculture (2/2) Fair pricing and decreased transaction fees Efficient financing Minimizing Human Error Better finance for the developing countries Efficient farm management Smart farm contracts Data monitoring Land registry The village Kolionovo, Russia, has become the first in the world to integrate Blockchain technology into its farming business and agriculture management 26

27 Blockchain in agriculture real world examples Core business: sensors development for monitoring of crop health and recording results in a blockchain Focused on: long-range wireless network Slogan: Build the business, not the network! Business Model: Filament s platform connect physical objects and existing networks into wider networks and applications making smart farm technology into reliable infrastructure. 27

28 Blockchain in agriculture real world examples Core business: Improvement of the traceability of food and providing concrete proof of its origin Focused on: Public, secure and all-inclusive information from the food supply chain Slogan: Look beyond the label! Know more, buy better! Business Model: Provenance provides buyers in the format of a real-time data platform with a fully transparent record allowing the end user to see each step of the journey the product has taken: where it is, who has it, and for how long Provenance is now experimenting with proving the supply chain of the tuna industry in Indonesia being delivered to Japanese restaurants 28

29 Blockchain in agriculture real world examples Core business: decentralized community-supported agriculture platform, using the blockchain to tokenize shares and encourage engagement in local food economies Focused on: creating new forms of community property ownership, collaborative labour relationships, and locally oriented alternative economies Business Model: 29

30 Big-data in agriculture

31 Business Model Investigation: Big-Data 31

32 Big Data opportunities in agriculture Four main areas where big data can be used in the food chain Development of new seed traits Precision Farming Food Tracking Effect on Supply Chains 32

33 Big Data in agriculture real world examples Core business: Digitalization of fields with automatic EFRs Focused on: Smart decision making Slogan: Your data. Real-time. Anytime. Business Model: 33

34 Big Data in agriculture real world examples Core business: independent and unbiased, farmer-to-farmer agronomic information network. The Network's mission is to improve the livelihood of farmers by making data useful and accessible Focused on: Smart decision making Slogan: Conceived by Farmers, Built by Innovators, and Improved Together. Business Model: FBN utilizes data science and machine learning to provide members with unbiased and unprecedented insights about each of their fields, powered by billions of data points from the network. Standard plan for 1 year - $600 34

35 IoT in Agriculture Source: Schmid Ag Technology

36 Market potential Source: Venture Scanner IoT Report Q1 2017, April

37 IoT in agriculture real world examples Core business: building devices and creating algorithms in the cloud that provide detection and prediction of real-world events that will enable the industrial internet of things Focused on: health tracking platform for dairy cows Slogan: Intelligent Dairy Farming Business Model: Pricing couldn t be simpler, 7.5 /sensor / month (ex vat), no extra fees Included in pricing: Ida Sensor Ida base station Upgrades always included Maintainance and support Damaged sensor replacement 37

38 IoT in agriculture real world examples Core business: Maps generation for crop stress identification and digital elevation models of the field. Focused on: complete aerial analytics package Slogan: Drone. Data. Decisions. Business Model: Pricing: $ for complete package (3DR Drone, Sony R10C camera, gimbal, hard case, 3 batteries; 1 year Site Scan license; 1 year Success Services) 38

39 Coming next

40 H2020 IoF2020

41 IoF2020 Open Call When? Winter 2018 Who? All legal persons eligible for Horizon 2020 funding How much? ; for beneficiaries Selection? platform-based evaluation system (FRACTALS) by a panel of independent experts Requirements? Clear description of the business challenge Contributing to at least one AgriFood challenge Clear IoT challenge Technology applied at least at TRL 5 Target for TRL 7 or 8 End users as partner in the proposal 41

42 H2020 DIATOMIC

43 DIATOMIC Open Call When? Open call 1 spring 2018 Open call 2 winter 2018 How much? ; for beneficiaries Who? Technology users/adopters and technology providers in microelectronics Selection? platform-based evaluation system by a panel of independent experts Requirements? Clear description of the business challenge Business model needed Field: Microelectronics End users as partner in the proposal 43

44 BioSense Accelerator

45 BioSense Accelerator Speed up time to market Expand talent and idea pool Grow competiti ve advantage Hosting Corporate Accelerator s 45

46 Thank you for your kind attention! Grigoris Chatzikostas BioSense Institute 46