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Unlocking the Power of Data: Data Driven Product Engineering, Evren Eryurek, CTO, GE Healthcare

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We live in a data-rich world - almost everything we do is being captured and stored somewhere. There are algorithms crunching the data every millisecond and conveying unknown and untapped information. At an enterprise level, data analytics provides us a 360-degree view of our customers, products and the business landscape to make effective, smart decisions. This presentation delves into how the traditional business philosophy of ‘proximity to customer’ will lose its significance and how data will drive product decisions.

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Unlocking the Power of Data: Data Driven Product Engineering, Evren Eryurek, CTO, GE Healthcare

  1. 1. Unlocking the power of Data: Data Driven Product Engineering Building Technology Organizations of Tomorrow Evren Eryurek, PhD GEHC Software CTO MARCH 2015
  2. 2. 2 Technology center of gravity is shifting Old IT Stack Analytics • Business Analytics Market to reach $50.7B by 2016 • 15.2% year-over-year • Market $7B devices • Mobile app development Mobile • Market $13 trillion over 15 yrs • Consumer Grade • NoSQL, Hadoop movement • Industrial-strength Industrial Internet ][ • Market $9B growing at CAGR 12% • Embedded in smart devices Intelligent Sensors New Platform • Lifecycles are measured in years - at an average of 18 years • Points of integration between IT & OT OT Security • Market $11B in size and growing at 33% • Volume, Velocity, Variety, Veracity Big Data • Market $24B in size and growing at 23% • Private and hybrid Cloud Computing © General Electric Company, 2014. All Rights Reserved.
  3. 3. 3 Industrial Internet What Happened When 1B People Became Connected? What Happens When 50B Machines Become Connected?  Operating Time is Virtualized  Analytics Become Predictive  Machines Self-Heal with Automation  Monitoring & Maintenance is Mobilized  Productivity/Decision-making Increase Enables dramatic improvements in outcomes by combining analytics with new forms of collaboration above isolated machines, workflows and data  Entertainment is Digitized  Social Marketing Emerged  Communications Mobilized  IT Architecture Virtualized  Retail & Ad Transformed
  4. 4. 4 A convergence of enabling technologies is setting the stage for industry transformation 1 $27B by 2017 for Mobile health services: The market for mHealth services has now entered the commercialization phase and will reach $26 billion globally by 2017 according to new “Global Mobile Health Market Report 2013-2017” by research2guidance. The report is one of the leading publications in the mHealth market. Companies that have purchased previous editions of the report includes: Agfa Healthcare, DTAG, Fresenius, Fujitso, GE Healthcare, LG, Nokia, Novartis, Pfizer, Qualcomm, Roche, Roland Berger, Sanofi Aventis and many more. Analytics 4 Internet of Things 1 Intelligent Machines 2 Big Data 3 “Hospital of Things” plethora of devices Accelerating Bio-sensor market/use Mobile healthcare explosion – $27B by 20171 Machines protecting and treating patients Devices for new care givers and settings Algorithms as updatable content High volume of data from physiology monitoring Care shift from population median to high-def individual Forecasting and predicting future health End of fee-for-service models drives data collect and analysis
  5. 5. 5 Software Modernization Required
  6. 6. 6 Ingredients of Modernization Optimizing SW portfolio to maximize customer success User Experience Data Science Advanced Research Commercial Strategy Cloud Services Architecture New business, operations and technology models Promoting rapid integration of new research into solutions Unifying service-based SW on protected automated environ Persona and context driven for increased adoption Automated DevOps environ with Scaled Agile processes Descriptive, predictive, and prescriptive analytics Development Security strategies to prevent, detect and address risks Cyber Security
  7. 7. 7 GE Approach to the Industrial Internet
  8. 8. 8 What is Big Data? And how to take advantage of it? Volume Data Quantity Variety Data Types Velocity Data Speed Value Data Impact
  9. 9. 9 Industrial big data – fast and vast *Source: IDC 50BMachines will be connected on the internet by 2020 2XIndustrial data growth within next 10 years *Source: IDC CRM, ERP, etc. Logs Social network data Geo-location data 9MM Data points per hour for each locomotive 500GB Data per blade by gas turbines Sensor data Content (images, videos, manuals, etc.) Historian data Machine data 35GB Data per day from each Smart Meter 50X Data growth in healthcare (2012 – 2020) 1TB Data per flight In practice only 3%of potentially useful data is tagged and even less is analyzed*
  10. 10. 10 Intelligent Hospital Customer challenges Diagnostic quality Patient-centric care System profitability Chronic Disease Management 29% Healthcare spend wasted each year $260B Annual value creation through healthcare IT 59% US lives covered in value- based care model by 2015 Clinical Quality Financial Performance Operational Efficiency Configurable Workflows
  11. 11. 11 Radiology Example: Reading protocols
  12. 12. 12 GE Machine Learning in Action Smart Reading Protocols Data Snapshot Info Fusion Text Mining Inference Engine The Challenge • Extremely complex & error prone to configure what images to display where for radiologist interpretation • Hospitals spending $$$ in lost productivity on non-value-add work • Entire industry struggling with this for 20 years The Outcome • 50% time savings for exam preparation • Robustness & accuracy • Ease of use • Ease of maintenance The Process
  13. 13. 13 O&G Example: The Intelligent pipeline Efficient dig & excavation activities Enhanced, digital assessment for pipelines More complete and near real-time MAOP Automated creation of dig sheets Data-driven prioritization of repairs / replacements More accurate validation of asset data Faster condition assessment & closure Delivering Safe & Efficient Outcomes in Oil & Gas
  14. 14. 14 GE’s SDMs are brilliant machines 1. More uptime, due to ‘hot’ software upgrades 5. Resiliency and efficiency, with standard way to develop and deploy machine apps 3. Unlimited compute, with standard distributed architecture from edge to cloud 2. Automated software updates, without change in hardware 4. Interoperable machines, with standard interfaces that apply across machines Aviation Example: Software defined everything A standard way to develop & deploy machine software
  15. 15. 15 Transportation Example… CSX – Productivity Velocity NS – Dwell UP – Safety Dwell ProductivitySafety
  16. 16. 16 Time is now Data Time Series Multimodal Interaction based Analytics Statistics & machine learning based Physics-based Sensors Order magnitude growth per machine every 5 yrs Video most underutilized sensor Connectivity Field force automation Autonomous system Applications Asset optimization Operations optimization Data Machines Analytics © General Electric Company, 2014. All Rights Reserved.
  17. 17. 17 AT GE WE PUT OUR IDEAS TO WORK TAKING THEM OFF THE PAPER OUT OF THE LAB AND INTO THE WORLD ENGINEERS SCIENTISTS TEACHERS LEADERS AND DOERS ALL SHARING A BELIEF THAT THINGS CAN BE MADE TO WORK BETTER IT’S WHY WE GET UP IN THE MORNING IT’S WHY WE COME TO WORK EVERY DAY TO BUILD CURE POWER AND MOVE THE WORLD WE ARE AT WORK MAKING THE WORLD WORK BETTER © General Electric Company, 2014. All Rights Reserved.
  18. 18. Thank You

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