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Capturing Value from IoT - Tomas Nauclér

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Asioiden internet -strategisten valintojen äärellä -päättäjäseminaari 1.6.2016: Capturing Value from IoT, Tomas Nauclér, McKinsey&Company

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Capturing Value from IoT - Tomas Nauclér

  1. 1. Capturing Value from IoT P&L benefits tomorrow while innovating the future Helsinki, Finland June 1, 2016 CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited
  2. 2. McKinsey & Company 2| IOT – The value is there Capturing the value – Tomorrows P&L and Innovating the future How to get started – What you need to think about today
  3. 3. McKinsey & Company 3| Internet Simplest definition of Internet of Things (IoT) Aka: simplest architecture diagram in the world Observing the physical world Changing the physical world AnalysisAggregation Visualization & Decisions Closed-loop actuation Enablers ▪ Lower cost to drive ubiquity (incl. sensor integration) ▪ Segmentation (ultra low power vs. dist compute) ▪ Low power, optimal computing ▪ Lower cost, low power networking ▪ Data integration and management ▪ Data validation tools and services ▪ Building data management capability in the workforce ▪ Domain specific expertise in model design ▪ Rapid translation of models to prediction in workflow ▪ Domain specific visualization tools Networked data sources Sensors Discovery and ID
  4. 4. McKinsey & Company 4| IoT hype? SOURCE: Google Trends; McKinsey; Web search
  5. 5. McKinsey & Company 5| “You can see the computer age everywhere but in the productivity statistics.” Robert Solow (1987) SOURCE: MIT News Office; New York Times Book Review
  6. 6. McKinsey & Company 6| IoT can enable 3.9 – 11.1 Trillion in value in 2025 Worksites 0.6–0.9Outside Cities 0.9–1.7 Vehicles 0.2–0.7 1.2–3.7 0.2–0.9 Factories Offices 0.2–0.7 Retail 0.4–1.2 Homes 0.2–0.3 Human 0.2–1.6 Low estimate High estimate SOURCE: McKinsey Global Institute Settings Potential value in 2025 Total 3.9–11.5
  7. 7. McKinsey & Company 7| 1 Includes sized applications only; includes consumer surplus 2 Potential economic benefit as a % of global vertical value add; Represents a rough measure of potential disruptions of each industry which would include share shifts and transfer to consumer surplus; thus does not represent industry growth IoT offers large potential across most verticals 0.1-0.3 0.5-0.8 0.3-0.8 3.9-11.1 0.1-0.5 0.5-2.2 0.3-0.6 0.3-0.9 0.2-0.4 0.1-0.4 0.6-1.5 0.1-0.2 0.3-1.2 0.2-0.5 0.4-0.8 SOURCE: IHS, Mckinsey Analysis 1.2 2.5 2.6 3.3 4.4 4.7 5.1 5.8 6.2 6.5 13.4 14.3Public sector and utilities 94.7Total Oil & Gas Advanced Electronics Aerospace & Defence TTL TMT Agriculture and chemicals Healthcare and PMP Banking and insurance Consumer Goods Automotive & Assembly Mining 11.5 Retail 13.0 Infrastructure 5% 3% 7% 6% 3% 35% 8% 15% 17% 8% 46% 45% 21% 24% 12% Potential Economic Benefit for IOT1 2025 USD Trillions Global Vertical Value Add 2025 USD Trillions Percent of Total Industry2 Percent
  8. 8. McKinsey & Company 8| 30% 70% SOURCE: McKinsey Global Institute B2C vs B2B value potential
  9. 9. McKinsey & Company 9| 38% 11.5 62% SOURCE: McKinsey Global Institute Interoperability required to unlock 40% of potential IoT value Potential economic impact of IoT, USD trillion Percent of additional value 36 43 57 56 44 20 29 17 30 Interoperability value by setting Office 0,3 0,4 Outside Home Factory 0 Retail City 0,1 0,3 Agriculture Vehicle 1,3 0,7 0,5 0,7 Worksite
  10. 10. McKinsey & Company 10| Interoperability SOURCE: McKinsey Global Institute
  11. 11. McKinsey & Company 11| Use case types SOURCE: McKinsey Global Institute Operations optimization 11.1 14 7 3 39 20 5 5 2 2 2 1 % of total Total 100 Inventory management Safety & security 0.6 Autonomous vehicles Energy management 0.6 2.3 4.3 0.4 Human productivity 0.8 0.1 0.2 0.2 Sales enablement Product development Environmental management 0.2 Health management Other operations optimization Condition based maintenance 1.6
  12. 12. McKinsey & Company 12| Business model innovations: Anything as a Service SOURCE: Web search; McKinsey Global Institute
  13. 13. McKinsey & Company 13| Provide solutions across value chainDeployed at scaleStrategy in place, in exploratory stage Have not formalized a strategy yet Companies are at differing stages along their IoT path; majority do not have a strategy in place yet Increasing connectedness 40% 38% 19% 3%
  14. 14. McKinsey & Company 14| IOT – The value is there Capturing the value – Tomorrows P&L and Innovating the future How to get started – What you need to think about today
  15. 15. McKinsey & Company 15| Capturing value from IoT – Two extreme questions How to transform my core processes with P&L effects within 12-18 months? How to innovate and transform my overall business and business model to win in the future?
  16. 16. McKinsey & Company 16|SOURCE: McKinsey Most existing IoT data is not used…and even then only for anomaly detection and real-time control Comment <1% tags used for decision making No interface in place to enable real time analytics to «reach» off shore Deployment Schedule predominantly based on OEM recommended maintenance intervals People & processes Reporting limited to a few KPIs which are monitored in retrospect Analytics Data can not be access real time, enabling only “ad hoc” analysis Data Management Only ~1% can be streamed on shore for day to day use Infrastructure ~40% of all data is never stored – remainder is stored locally off shore Data capture >1% 0% 1% 1% 40% 100% ~30,000 tags measured
  17. 17. McKinsey & Company 17| Innovating the Future: Huge sources of waste in the heavy truck industry 5–10% of fuel is used to move goods Road reaches peak throughput only 5% of the time...and even then, it is only 10% covered with vehicles Used ~25% of the time over the life cycle Sources of waste include loading/unloading, traffic jams, parking time, repairs <30% ~15 m ~60% of total length theoretically available for more cargo ~3 m 50% fill rate of available load capacity ~7% of all accidents in Europe involve trucks 17% for fatal accidents Truck losses Driving losses Moving base load ~10% ~5% ~55% 20-25%
  18. 18. McKinsey & Company 18| MACS: Heavy transport cost reduced by >5 times CONNECTED AUTONOMOUS SHARED MODULAR Autonomous maintenance and loading/ unloading Reroute around congestion Modular super- structure Increased efficiency and fill-rate Real-time load sensors On-route rerouting for yield optimization Autonomous onhooking Platooning
  19. 19. McKinsey & Company 19| RFID-port detecting material inflow to construction site feeding information to application RFID/barcode scanner verifying materials delivered to site through application platform Data from construction site is available for all stakeholders of value chain Transport/construction: Cockpit for E2E material handling could reduce construction costs significantly 4 1 3 2 End-user receives on- demand information on the status of project Manufacturer and transportation company interchange information with data integration platform to optimize overall process Equipment automatically sending information on equipment condition and handled products to on- site IT system 6 5 1 2 3 4 5 6
  20. 20. McKinsey & Company 20| Machining – different long term visions and strategies
  21. 21. McKinsey & Company 21| Starting with small scale pilots to learn - example Manufacturing method optimizer 1 Should cost estimation 2 Manufacturing services market place 3
  22. 22. McKinsey & Company 22| ..for significant value capture opportunity Supply/ demand match Time to market Resource/ process Asset utilization Labor Inventories Quality Service/ aftersales VALUE DRIVERS 10-40% reduction of maintenance costs1 20-50% reduction in time to market1 Forecasting accuracy increased to 85+%3 Costs for quality reduced by 10-20%6 Productivity increase by 3-5%5 30-50% reduction of total machine downtime2 45-55% increase of productivity in technical professions through automation of knowledge work4 Costs of inventory holding decreased by 20-50%3
  23. 23. McKinsey & Company 23| IOT – The value is there Capturing the value – Tomorrows P&L and Innovating the future How to get started – What you need to think about today
  24. 24. McKinsey & Company 24|SOURCE: McKinsey Global Institute Enablers for IoT scale up Software architecture Capability build up and resource allocation Privacy, confidentiality and cybersecurity Business organization and culture M&A and partnerships Pilots starting small
  25. 25. McKinsey & Company 25| Example: Starting with small scale pilots to learn … to screens/ clickable prototypes ... … to rough wireframes: … to hand-drawn screens From customer journeys… Customer testing Customer testing …resulting in a functioning prototype and MVP Customer testing Customer testing Refine based on feedback ACTIVITY Prototype ValidateCreateFrameConnect Deliver 11-13 14-168-105-71-4 17-18WEEK
  26. 26. Capturing Value from IoT P&L benefits tomorrow while innovating the future Helsinki, Finland June 1, 2016 CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited

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