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En platform-drevet fremtid med vær som brensel @ First Tuesday Bergen

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En platform-drevet fremtid med vær som brensel
Torleif M. Lunde - Chief Product Officer @ StormGeo

Den digitale revolusjonen har ført alle industrier nærmere hverandre, noe som åpner opp for helt nye muligheter. Fra å være et selskap med fokus på best mulig værvarsler, har StormGeo utviklet seg til å jobbe med AI og platformbygging. Sammen med verdens største forsikringsselskaper, teleselskaper, sosiale medier, og shipping-konsern, bruker vi AI som en naturlig del for å effiktivisere deres og egne produksjonslinjer. I foredraget fortelles historien om hvordan StormGeo har tatt været ut i verden, til nå å bygge en platform bestående av hyperlokalt vær, kundedata, AI-dreven beslutningsstøtte, med leveranse gjennom visualisering, APIer, event-drevne prosesser og personlig service.

Torleif Markussen Lunde. Chief Product Officer I StormGeo fra oktober 2018. Ansatt i 2014. Holder en PhD i malaria og klima, og har lang erfaring i big data og data science med erfaring fra olje og gass, transport, forsikring og helse. De siste årene har fokus dreid i retning organisjonsutvikling, strategi og M&A.

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En platform-drevet fremtid med vær som brensel @ First Tuesday Bergen

  1. 1. Freedom to Perform Torleif Markussen Lunde – Chief Product Officer tlu@stormgeo.com En platform-drevet fremtid med vær som brensel
  2. 2. Først litt historie …
  3. 3. 1997
  4. 4. (startup)
  5. 5. oljepris 2019 EQT Nye markeder og M&A
  6. 6. Freedom to Perform ABOUT STORMGEO Owners  59% EQT  26% DNV GL  15% Other Company  6 global operations centers with 24/7/365 support  2 data centers  27 offices  15 countries  410 employees Business  66% Shipping  13% Oil & Gas  10% Renewables  8% Cross Industry  3% Media SHIPPING 12,000 vessels supported in total 29% penetration (SOLAS) with a StormGeo service OIL & GAS 90 000+ Unique customer specific forecasts issued every month 43% Market share in North Europe 18% market share world wide RENEWABLES 30% Market share in offshore wind worldwide 7% Market share in electric utility operations in the U.S. CROSS INDUSTRY 11 000+ U.S Onshore locations served on a daily basis Business Continuity solutions used by a variety of industries to enhance safety and minimize downtime MEDIA We boost your ratings Global weather data and professional visualization across any device or screen. Geography main portion of customers served in Europe, Middle East and Asia.
  7. 7. • Principal component regression, Software Linpack • Quantile regression, Software R • Logistic regression, Software R • Bayesian Statistics, Software R • +++ 2004-2011 ADVANCED STATISTICS • Neural networks, software pybrain • Support Vector Machine, software Scikit-Learn • Optical Flow, software OpenCV • Agglomerative Clustering, software Scikit-Learn • Random Forest Classification, software Scikit-Learn • Extreme gradient boosting, software xgboost 2011 - Present MACHINE LEARNING • Multiple linear regression, software S 2003 MODEL OUTPUT STATISTICS • Various neural network architectures, software Keras with Tensorflow backend • Running deep learning on four NVIDIA Titan X GPUs 2016-present DEEP LEARNING Siden 2003 har vi vært på søken etter den perfekte morgendagen Data Science
  8. 8. Hele forretningen til StormGeo er bygget rundt data, prediksjon og kommunikasjon Freedom to Perform
  9. 9. I praksis
  10. 10. Weather is the major cause of disruptions to society globally 2017: US $340 bn in overall losses due to natural disasters (*) Source: Munich Re Freedom to Perform (*)
  11. 11. Mobilitetsdata + smart meters + hyperlokalt vær + AI = strømforbruk Human mobility Weather Electricity Prescriptive model Forecasted house level electricity consumption
  12. 12. Weather Holidays Macro economy Light hours Market events/UMMs Input ∞Price Production Forecasting power consumption is key to plan power production, taking into account production from different sources in different areas. To improve our forecasting of power consumption, we combined weather intelligence with local, real time and historical power consumption data, to build a neural network going into our power price forecasts for the Nordic Power market. As new data becomes available, the model continue to improve. En modell for nordiske og europeiske stømpriser Observed Day ahead forecast (2% error) Real time power consumption forecast
  13. 13. 61 Categorical exposure features • Building material • Roof type • Line of Business • Company • Client age group 8 Numerical exposure features • Age of home/roof • Size of home • Client previous losses • Client insurance score • Client non-payments 2 Weather radar features • Max radar reflectivity • Average radar reflectivity 50 Wind features • Wind and gust • 5 different severity percentiles • 5 different geographical areas 121 Input features for model 1 Output feature Likelihood of claim Weather + Exposure = Claims Machine learning architecture
  14. 14. PAST What just happened? PRESENT What is about to happen? FUTURE What will happen soon? En av verdens største forsikringsselskaper bruker StormGeo for å varsle hvilke hus har høy risiko for skade
  15. 15. The StormGeo Infinity differentiator Normalization of data is the key to valuable performance analysis Comparing vessel performance and analyzing vessel trends using speed over ground can be highly misleading Speed over ground differences is first of all connected to differences in weather at the given time To analyze performance differences, the effect of the weather and currents on vessel speed needs to be subtracted The same goes for loading conditions and several other parameters The data needs to be normalized such that one is left with only analyzing based on the relevant performance speeds Speed Over Ground Raw Data Laden Ballast Consumption Speed Over Ground Performance Speed Normalized Data Laden Ballast Consumption Performance Analysis Sister vessel trade analysis Sister vessel Fuel consumption analysis Fleet Transport Fuel EfficiencyPerformance Speed / Calm Sea Speed
  16. 16. En platform-drevet fremtid med vær som brensel Vortex SaaS • Business optimization for weather exposed industries • Digital customer experience and intimacy on desktop and mobile • Delivery and interaction SaaS for data science driven Weather Insights BUSINESS ECOSYSTEM </Programmable APIs> • Data platform allowing integration in external enterprise-scale ecosystems • 99.98% uptime in 2018 • The connective tissue in StormGeo’s digital ecosystem Event driven • High-definition, IoT, micro- weather information as key enabler of autonomous data driven operations • Reactive, event driven, mobile notifications Data Science & Personal Service • 24/7 Weather Insights • Tailored solutions by customization and integration of third party data • Safe and SOX-compliant data platform • Personal users and role management allowing super users and self service
  17. 17. Working in close partnership with StormGeo; Data science in the core of your value creation Turbulence Workshop – when you know your workflow can be improved, but you don’t know how Pilot – when you know what to improve, but need expert help executing • Feasibility assessment • Roadmap development • Organization education • Data validation • Feasibility assessment • Business development and identification of stakeholders Discovery: 2-4 weeks Data Science Business Development Breeze Data collection & refining Company data is processed, cleaned, refined and restructured Method selection and exploration Based on the business objective and data, a customized solution to solve the specific problem is designed Prototype deployment Proof of concept, validation of methodology and estimated accuracy of the selected approach Data Science Proof of Concept: 1-4 months Gale Product testing and implementation Test with users to confirm benefits Site agnostic implementation Implementation of solution on or off premise Value creation through delivery method Deliver operational system with visualization and APIs. Data Science UX, IT and Front-End Developers Business Development Production: Project specific Storm Operational stability Support or take full responsibility of the operational product Validation and maintenance Follow up with validation and calibration if data input changes Data Science IT, Support Reinforcement and stability DeepStorm
  18. 18. Freedom to Perform Thank you
  19. 19. VorX 019

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