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How IoT is changing the agribusiness landscape

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Smart Farming involves many sensing and monitoring devices, intelligent software for analysis & planning and mechatronics/robots closing the cyber-physical farm management cycle. Big Data on prices, markets, consumer behavior, etc. increasingly affect the whole agribusiness providing predictive insights in farming operations, drive real-time operational decisions and redesign business processes for game-changing business models. Major shifts in roles and power relations among different players in food supply chain networks can be expected. This presentation will briefly describe the IoT developments in agri-food business and present the changing business landscape with special attention to the role of software ecosystems in this development.

Published in: Technology
  • An good slide deck on IoT developments in the agribusiness, when NBIoT gets launched fully in the UK, the growth of applications/ solutions in this space will rapidly expand as people will be able to make use of greta coverage peneration of signal, faster data throughput, flexible power management of devices and simple more cost effective design of hardware.
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How IoT is changing the agribusiness landscape

  1. 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. 2. Your image of farming?
  3. 3. Is this the actual image?
  4. 4. smart sensing & monitoring smart analysis & planning smart control Closing the cyber-physical management cycle BIG DATA
  5. 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. 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. 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. 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. 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. 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
  11. 11. Example: Monsanto Fieldscripts 11 PRESCRIPTIVE FARMING based on VARIABLE RATE APPLICATION
  12. 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. 13. SmartAgriFood2, FInish, Fractals FIspace collaboration platform architecture 150+ start-ups
  14. 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. 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

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