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DIGITAL & IoT: A TALE OF THE HAVES AND HAVE-MORES- McKinsey & Company

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DIGITAL & IoT: A TALE OF THE HAVES AND HAVE-MORES
- McKinsey & Company

Published in: Technology
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DIGITAL & IoT: A TALE OF THE HAVES AND HAVE-MORES- McKinsey & Company

  1. 1. CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited DIGITAL & IoT: A TALE OF THE HAVES AND HAVE-MORES
  2. 2. McKinsey & Company | 1 Today’s discussion SOURCE: Source ▪ONE: Digital matters and is changing the way we do business profoundly ▪TWO: Digitization in playing out differently across sectors ▪THREE: IoT is integral to Digital ▪FOUR: Institutions have to learn to tap value from Digital
  3. 3. McKinsey & Company | 2 ONE: DIGITAL MATTERS
  4. 4. McKinsey & Company | 3 13% 95% 90% 84% 76% 73% 64% 56% 51% 40% 98% 28% 17% Digitization now touches every aspect of the economy Retail via e-commerce Investment in ICT as a share of total investment Payments made digitally Adults with smartphones Households with broadband Adults who use social media Taxes that are e-filed Adults who use the Internet Millennials who regularly use e-mail Households subscribing to online video streaming services Freelancers who have done work online Americans who get news from online aggregators Americans with access to high-speed wireless Internet PERCENT OF US ECONOMY IMPACTED BY DIGITIZATION
  5. 5. McKinsey & Company | 4 Digital technologies are growing at an exponential rate SOURCE: Kliner-Perkins; McKinsey Some facts to ponder…. ~5+ zetabytes of data in the digital universe $0.02/GB data storage 9.1 billion networked devices by 2019 1.8 billion photos shared daily 50 billion WhatsApp messages exchanged daily
  6. 6. McKinsey & Company | 5 Industries on the digital frontier among fastest profit gainers GROWTH IN PROFIT MARGIN VS. SOFTWARE INTENSITY, SELECT US NON-FINANCIAL INDUSTRIES -1.0 0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 -1.0 0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 Media and Information Extraction IT hardware Retail Consumer goods Machinery production Automobile Utilities Logistics and transportation IT and business services Healthcare Change in software intensity1 1993 vs. 2013 (3-year averages) Change in post-tax profit margin 1993 vs. 2013 (3-year averages) 0.7 3.4
  7. 7. McKinsey & Company | 6 Across industries, in the digital universe we have observed 6 major forces of disruption SOURCE: McKinsey Digital; McKinsey Strategy and Corporate Finance practice Consumer power is paramount (Zynga) New capabilities are needed (Netflix) 1 4 Conventional tradeoffs may become obsolete (AND not OR) Change happens faster (FaceBook) 2 5 Money moves unevenly (Apple stores) Ecosystems are redrawn (ApplePay) 3 6
  8. 8. McKinsey & Company | 7 Digitization allows firms to operate, innovate and organize more effectively IMPROVE OPERATIONAL EFFICIENCY ▪ Better visibility into inventory and supply chain ▪ Benefits from process automation and “hyper”- scaling ▪ Higher utilization of current assets and resources EXPAND MARKET REACH AND ENGAGEMENT ▪ Ability to serve “long tail” of niche customers ▪ Platforms and multiple channels to reach customers worldwide ▪ Insight into customer needs allows for more tailoring DEPLOY WORKFORCES MORE EFFECTIVELY ▪ Tools to enable remote, flexible, and virtual work ▪ Better resource allocation and specialization ▪ Online platforms to find, recruit, and develop talent SPUR INNOVATION AND DISRUPTION ▪ Improved tools for design, testing, and development ▪ New and improved products, services, and business models ▪ Co-innovation platforms with suppliers, customers
  9. 9. McKinsey & Company | 8 Digitization starts with pioneering firms, then spreads to entire industries Time NEW NORMAL Advanced incumbents, established start-ups LAGGARD INCUMBENTS DROP OFF NEW TRENDS emerge INNOVATIVE START-UPS create disruptive business models EARLY ADOPTERS embrace the new models ADVANCED INCUMBENTS begin to adapt MAINSTREAM CUSTOMERS adopt TIPPING POINT
  10. 10. McKinsey & Company | 9 19 93 16 92 15 91 13 90 13 89 12 88 12 87 11 86 10 85 9 84 10 83 9 82 9 81 10 08 9 07 12 06 14 05 15 04 15 03 15 02 16 01 18 2000 19 99 20 98 20 97 18 96 19 95 19 7 -66% 13 12 7 11 7 10 7 09 9 94 80 10 79 12 78 15 77 13 76 11 75 10 74 10 1973 11 Digital disruptions can shift value dramatically, often destroying significant value pools SOURCE: RIAA The music industry Total year-end RIAA (US) revenue statistics, USD B (adjusted 2013) Ringtones & Ringbacks Paid Subscriptions On-Demand Streaming (Ad-Supported) Synchronization SoundExchange Distributions SACD CD Music Video DVD Audio Other Tapes 8 - Track Download Single Download Album Kiosk Download Music Video Cassette LP/EP April 2003, iTunes store launch 1999 – illegal upstarts (e.g., Napster) proves download potential
  11. 11. McKinsey & Company | 10 DIGITIZED SECTORS SEE CHANGES IN COMPETITIVE DYNAMICS Digital and intangible assets become more valuable Lower information asymmetry disrupts intermediaries Value chains split and end up with specialized niches Hyperscale and winner-take-all effects take hold Industry boundaries blur
  12. 12. McKinsey & Company | 11 U.S. HOTEL BOOKING REVENUE AND NUMBER OF LIVE TRAVEL AGENTS, 2000-2014 Traditional market intermediaries get disrupted 0 20 40 60 80 100 120 140 160 100 120 110 80 70 90 50 60 20142013 130 082005 06 102001 2003 201104 20072000 1202 2009 Number of live travel agents Thousands Revenue $ Billions Number of travel agents in US Online hotel revenues
  13. 13. McKinsey & Company | 12 New opportunities to create value in commercial ecosystems Production firmsDesign firms Devices 2013 5 Carriers 47 Apps and mobile web Components 0 2007 -5 29 5 12 81 1 16 17 54 Network infrastructure US WIRELESS VALUE CHAIN PROFITS, 2013 (%; $ billion) AVERAGE EBIT1 MARGIN, 2007–13 (%) 25 13 10 9 -3 -4 4 7 22 25 33Qualcomm Tianma Hann Star MediaTek Chungwha Skyworks 2 1 5 12 30 Flextronics Jabil ZTE Samsung Electronics Apple EBIT MARGINS OF LEADING FIRMS, 2014 OR LATEST AVAILABLE, 2007–13 (%)
  14. 14. McKinsey & Company | 13 Largest tech firms and their platforms rival the size of nations 2014 OR LATEST DATA China Population: 1.37 billion Facebook Monthly active users: 1.49 billion Indonesia Population: 255 million Google Android phones shipped in Q2 2015: >270 million Mexico Population: 123 million Microsoft Windows 10 downloads: 110 million United States Population: 320 million Bharti Airtel Customer base: 310 million France, Germany, UK, Spain Total population: 258 million Amazon.com Customer base: 244 million South Africa Population: 54 million Netflix Number of subscribers in 2014: >50 million
  15. 15. McKinsey & Company | 14 TWO: DIGITIZATION IS PLAYING OUT ACROSS SECTORS
  16. 16. McKinsey & Company | 15 A comprehensive view looks across assets, usage, and people affected ASSETS  Digital asset stock of hardware, software, telecom, IT services  Spending on third-party digital assets  Digitally connected non- ICT equipment  Data storage LABOR  Capital deepening: digital assets per worker by category  Time-weighted share of 12,000+ worker tasks that are digital  Digital jobs as share of total jobs in sector USAGE  Digital payments  Adoption of ERP and CRM software for front or back- office  Social technology adoption to engage suppliers, customers  Digital marketplaces
  17. 17. McKinsey & Company | 16 The MGI Industry Digitization Index Relatively highRelatively low Denotes leading digital firms within relatively un-digitized sectors Selected sectors Overall digitization Assets Usage Labor GDP share Employment share Productivity growth 2005-2014 CAGR DIGITIZATION INDICES Oil and gas Finance and insurance Wholesale trade Advanced manufacturing Health care ICT sector Government Retail trade Transportation and warehousing Hospitality 2% 0.1% 2.9% 8% 4% 1.6% 5% 4% 0.2% 3% 2% 2.6% 10% 13% -0.1% 5% 3% 4.6% 16% 15% 0.2% 5% 11% -1.1% 3% 3% 1.4% 4% 8% -0.9% Education 2% 2% -0.5% Basic goods manufacturing 5% 5% 1.2% Construction 3% 5% -1.4% Personal and local services 6% 11% 0.5% SELECTED SECTORS (OF 22 ANALYZED) November 2015 Digitization
  18. 18. McKinsey & Company | 17 Spending on digital assets Digital asset stock Transactions Interactions Business processesMarket making Digital spending on workers Digital capital deepening Digitization of work Industries are digitizing in different ways Media Oil and gas Retail tradeIndexed variables: 100 = maximum (most digitized industry)
  19. 19. McKinsey & Company | 18 THREE: IoT IS INTEGRAL TO DIGITAL
  20. 20. McKinsey & Company | 19 2025 Market Expectations IoT has potential to be big, but will be different than existing mobile or PC markets Source: McKinsey Global Institute 10+ billion new connected devices $1– 4T Economic value at stake $200-550B ICT spend 2015 realities Fragmented Many device types, diverse markets Integrated Platforms not yet emerged Solution centric Value in solutions (75%)
  21. 21. McKinsey & Company | 20 Degree of value creation will vary across verticals 4.7 TMT 5.1 Agriculture and chemicals 5.8 Healthcare and PMP 6.2 Banking and insurance 6.5 Mining TTL Oil & Gas Advanced Electronics Automotive & Assembly 2.5 1.2 2.6 3.3 4.4 Consumer Goods Retail Infrastructure 13.4 Public sector and utilities 14.3 13.0 11.5 Total 94.7 Aerospace & Defence 0.1 – 0.5 0.6 – 1.5 0.3 – 0.6 0.1 – 0.4 0.5 – 0.8 0.3 – 0.8 0.1 – 0.5 0.1 – 0.4 0.1 – 0.2 4.0 - 11.2 0.3 – 1.2 0.2 – 0.5 0.5 – 2.2 0.4 – 0.8 0.3 – 0.9 SOURCE: IHS, Mckinsey Analysis PRELIMINARY Potential Economic Benefit for IOT1 2025 USD Trillions Global Vertical Value Add 2025 USD Trillions Top Use Cases ▪ Self-checkout – billing/material handling ▪ Layout optimization ▪ Air quality monitoring ▪ Centralized and adaptive traffic control ▪ Increase farm yield ▪ Operations management ▪ Defense – After sales service improvements ▪ Aerospace – After sales service improvements ▪ Insurance – personal transportation ▪ Monitoring and treating illness ▪ Improving wellness ▪ Operations management ▪ Monitoring and treating illness ▪ Logistics routing ▪ Autonomous vehicles ▪ Operations Management ▪ Improved equipment maintenance ▪ Operations Management ▪ Improved equipment maintenance ▪ Passenger vehicles – After sales service improvements ▪ Air quality monitoring ▪ Centralized and adaptive traffic control ▪ Chore automation ▪ Energy Management ▪ Operations Management ▪ Improved equipment maintenance Percent of Total Indus- try2, Percent 5% 3% 7% 6% 4% 35% 8% 15% 17% 9% 47% 44% 20% 31% 12% 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
  22. 22. McKinsey & Company | 21 IoT will solve business problems that were traditionally hard to solve 1.5 2.2 0.2 0.2 0.9 0.4 0.2 0.8 0.4 1.3 0.2 0.9 0.5 0.3 1.2 Highest value verticals Connected home Connected lifestyle Healthcare Retail/ Commerce Automotive Agriculture Telco and Utilities Advertising Defense / Security Oil & Gas and Mineral extraction Public sector & Smart cities Education Media & Entertainment Asset and Logistics SC Finance / Insurance 2025 economic value $ TrillionsVerticals ConsumerIndustrial Sample business problem How IOT solves the problem Value created by IOT ▪ Patient monitoring needed for improving treatment ▪ Heart patient adherence for recommended treatment is ~50%. Non-adherence in chronic coronary artery patients increases risk of hospitalization by 10-40% and mortality 50-80% ▪ Treatment adherence is linked to a 50% decrease in treatment costs for cardiac patients ▪ Early detection of complications such as rapid gain in weight in a patient with CHF can lead to prevention of an acute exacerbation, pulmonary edema, and even sudden cardiac death ▪ Patient monitoring will create ▪ $0.2 – 1.1T ▪ Road accidents are attributed mostly to human error ▪ Safety is a top priority for car manufacturers; 1/3 of new car buyers want their car to prevent them from accelerating above the speed limit ▪ Vehicle-to-vehicle (V2V) communication, computer vision, and local intelligence will help reduce accidents by 40% ▪ Autono- mous vehicles will create ▪ $0.4 – 0.5T
  23. 23. McKinsey & Company | 22 Mobile and IoT drive profitability in Retail in different ways Value driver Increase customer loyalty Increase traffic into the store Improve in-store operations Improve in-store labor productivity Increase conversion / basket size Capture Incremental sales through mobile Improvingcustomerexperience ▪ Layout and merchandising optimization ▪ Inventory management ▪ Product metadata / reviews ▪ Real-time product availability ▪ Real-time dynamic pricing ▪ Enhanced in-store experience (e.g., virtual fitting, smart shopping list) ▪ Mobile payments ▪ Mobile commerce (e.g., store pickup) ▪ In-store navigation ▪ Productivity tools (e.g., workforce management, shift scheduling, training) ▪ Personalized sales force ▪ Personalized real-time offers ▪ Real-time social sharing ▪ Mobile POS / self-checkout Employeeexp Total 75-90 70-75 35-50 65-85 50-70 30-45 5-15 20-40 20-35 30-35 20-30 30-50 5-15 95-115 Potential oper. profit contribution Bps 5-8% RETAIL ExampleUse-cases
  24. 24. McKinsey & Company | 23 A comprehensive retail mobile experience currently requires components from multiple players ▪ Platform for integrating social media into mobile apps ▪ Revenue: Free / volume ▪ Beacons track customer location and proximity to items ▪ Revenue: Licensing ▪ PayPal beacon automatically charges customer as they walk out of the store ▪ Revenue: Share of revenue ▪ Location-specific mobile marketing pushes advertisements to customers when they’re near the store ▪ Revenue: Transaction volume ▪ Anonymous customer tracking ▪ Real-time coupon engine sends promotions to mobile device ▪ Revenue: Subscription ▪ Comprehensive in-store customer tracking ▪ Revenue: Licensing RETAIL
  25. 25. McKinsey & Company | 24 American Apparel developed a mobile app that integrates multiple use cases… Real-time offers ▪ Mobile app tracks customer location and sends offers to mobile device upon entering a store Augmented reality Product metadata Social share Metadata eCommerce integration RETAIL ▪ American Apparel’s reliance on RFID for inventory tracking creates pain point for seemless self- checkout ▪ In-house IT solution still requires physical kiosks in store to scan items Self-checkout QR code ▪ Customer scans QR code at in-store kiosk to pair phone with RFID reader RFID tag ▪ Customer scans Impijn RFID tag at in-store kiosk to add to shopping cart Self-checkout ▪ Customer stores payment options in mobile account ▪ Customer selects payment option at time of checkout and completes process on mobile device or kiosk
  26. 26. McKinsey & Company | 25 …but to do so required integrating many different services and extensive customization by in-house IT American Apparel favored several platforms that its IT developers had previous experience with ▪ JBoss / WildFly used as application server ▪ Combination IIS / Apache Web servers used to deliver Web services (e.g., mobile app, kiosk) ▪ JSON used for packet transmission Real-time offers Developed use case with Qualcomm’s Gimbal for geofencing Product metadata ▪ Used Qualcomm Viewphoria for image recognition ▪ Used Adobe’s Scene 7 SaaS solution to pull product metadata ▪ Combined with in-house cloud-based Web services Augmented reality RETAIL ▪ Leveraged Foundry Logic to extend Retail Pro POS for mobile POS ▪ In-house mobile shopping cart Web service integrates with ATG eCommerce ▪ Results from POS wrapped in Web service to push receipt to customer Payment processing ▪ Integrated Impinj RFID tags for inventory tracking ▪ In-house Web services connect into lower-level functionality of RFID reader ▪ Wrote Web services in- house to connect with RFID antennas for theft- prevention RFID tag integration ▪ Partnered with Qualcomm to bundle QR codes for pairing at Kiosk and register ▪ Developed kiosk Web services in-house ▪ Employee / customer apps written as Web services in- house Mobile device pairing
  27. 27. McKinsey & Company | 26 Therefore, OEMs are driving completely integrated systems to reduce cost and control in- car experience Number of cars shipped Millions Overall trends Connected cars are soon becoming an integral part of the driving experience 1 9288848178757269 75 53 38 19131010 27 13 1716 191815 2014 10-20% 66% +4% p.a. 30-40% 2020 111 31% 20252014 85 138 3% 50%82% 18% 0 Completely integrated system Components Partially integrated system Demand forecast for CIS Million units Total car shipments Connected car penetration (%) But customers are not willing to pay more for services or new features 2 1314 6 5052 6 ~ 56k 4 2014 6 2020 1 ~ 56k Average customer spend over 5-year car lifecycle1 Insurance Telematics services Base price2 Maintenance ADAS AUTO ▪ Overall pricing pressure due to: – declining demand per capita for cars in developed markets as a result of customer behavior/sharing economy (e.g., millenials favoring Uber) – preference for affordable cars in developing economies ▪ Willingness to pay for advanced features (e.g., ADAS, Telematics) as buyers seek convenience and safety 3
  28. 28. McKinsey & Company | 27 Auto ICT market overview 47 21 27 15 10 8 5 5 89 48 20202015 Auto ICT market size1 $ Billions Body & convenience Powertrain Safety & chassis Segments CAGR 1% 6% 13% 17% Connectivity & entertainment Details follow 9.5% CAGR AUTO SOURCE: McKinsey analysis, IHS 1 IOE is a subset of total auto ICT market Description ▪ Systems for generating and delivering power (e.g., chargers, microcontrollers, converters) ▪ ADAS (Adv driver assistance systems): prevents accidents ▪ Passive safety: systems that protect occupants from injury during an accident ▪ Hardware, software, and services for infotainment and telematics ▪ Systems for functions such as door controls, window controls, and climate controls Growth drivers ▪ Fuel efficiency regulations increasing need for electronics ▪ Powertrain electrification (e.g., hybrids and electric vehicles) ▪ ADAS: regulations pushing reduction of vehicle-related accidents/ deaths ▪ Passive safety: mature and integrating into ADAS systems ▪ Greater smartphone integration ▪ Leveraging data feeds for insurance and maintenance optimization ▪ Mature market. Premium features cost optimized for use in lower tiers
  29. 29. McKinsey & Company | 28 2020 autonomous vehicle functions IoT will help reduce human error with existing technologies SAFETY AND CHASSIS DEEP DIVE Critical technologies Safety functionAdaptive cruise control Emergency braking Pedestrian detection Collision avoidance Traffic Sign recognition Lane departure warning Cross traffic alert Park assist Surround view Blind spot detection Park assist Park assistanc e/ surro und view Rear collision warning Surround view Alert Sensors Dev kit algorithm / engine Connectivity Lane keeping assistance Cameras, radar, infrared Geospatial analysis Ethernet Lane change assistance Radar, laser, proximity Signal processing CAN Driver monitoring Cameras Affective computing Ethernet Traffic sign recognition Cameras Machine vision, OCR Ethernet Parking assistance Cameras, Ultrasound 3D rendering (motion- stereo) Ethernet Adaptive front lighting Photo/ light sensor Signal processing CAN Emergency call Accelerometer N/A Ethernet, Cellular Stop and go cruise Radar Adaptive cruise control CAN Car to car N/A M2M protocol DSRC Cameras, laser, or infrared Signal processing EthernetLane departure warning Control
  30. 30. McKinsey & Company | 29 IoT Business models will evolve Potential examples Outcome linked monetization IoT will enable monetization of products "as a service" rather than a capital investment. Examples include Usage Based Insurance and Managed Printing Services Rise of need for utility players The proliferation of equipment manufacturers will require horizontal solutions. This role could be filled by new players or existing players redefining their role (e.g., John Deere Worksight) Platform model with developer ecosystem Companies are trying to build platforms for application development and monetize through API usage, devices or servers e.g., Apogee, Axeda, ThingWorx Funding partnerships with incumbents New players with disruptive technologies could partner with existing incumbents to help fund cost- savings (e.g., Ginger.io and Kaiser)
  31. 31. McKinsey & Company | 30 Five types of enablers will drive IoT potential impact Hardware technology A ▪ Low power consuming sensors ▪ Cheap processing ability ▪ Ubiquitous connectivity / low-cost mesh connectivity ▪ Further reduction in cost of cloud storage and computing Software technology B ▪ Evolution of predictive analytics and algorithms ▪ Confidence in Security across entire IoT ecosystem ▪ Standardization of the stack and interoperability Data ownership C ▪ Establish trust with consumers on sharing data ▪ Collaboration across companies and verticals ▪ Horizontal data aggregators Business Org and culture D ▪ Industry structure e.g., organized labor, third party servicing ▪ Committing to upfront investment based on clear business case ▪ HW focused companies expanding core competency to SW Public policyE ▪ Regulation for autonomous control ▪ Government and payor subsidy of healthcare IoT ▪ Agreement on fair data sharing practices
  32. 32. McKinsey & Company | 31 FOUR: INSTITUTIONS HAVE TO LEARN TO TAP INTO VALUE
  33. 33. McKinsey & Company | 32 INCUMBENTS ARE SITTING ON A DIGITAL GOLD MINE DATA RELATIONSHIPS TALENT BRAND BALANCE SHEET CASH FLOW INTELLECTUAL PROPERTY
  34. 34. McKinsey & Company | 33 MANY INCUMBENTS HAVE UNLOCKED THE VALUE OF DIGITAL…
  35. 35. McKinsey & Company | 34 …YET MORE ARE FAILING
  36. 36. McKinsey & Company | 35 SYMPTOMS ▪ Low share in digital channel ▪ Disintermediation ▪ Slow IT delivery ROOT CAUSES ▪ Low management commitment to digital ▪ Decaying business model ▪ Siloed organisational structure ▪ Missing capabilities DIGITAL TRANSFORMATIONS FAIL BECAUSE THEY ADDRESS SYMPTOMS NOT ROOT CAUSES
  37. 37. McKinsey & Company | 36 How to…design digital strategy so it can successfully address the challenges for incumbents ?
  38. 38. McKinsey & Company | 37 Nike put the customer first and invested in an end-to-end digital athletics ecosystem Case example x4 10M+ 30M+ SOURCE: Analyst reports, press articles, web search
  39. 39. McKinsey & Company | 38 Home Depot embraced an omni-channel digital strategy Case example $300M +53%yoy SOURCE: Analyst reports, press articles, web search
  40. 40. McKinsey & Company | 39 Progressive is breaking age-old insurance paradigms with digital using "user-based insurance" models 1.2M+ 50% 110 Tb Case example SOURCE: Analyst reports, press articles, web search
  41. 41. McKinsey & Company | 40 Successful digital transitioners... Put customers front and center of their strategies Develop new ways to measure "digital success" Proactively shape your ecosystem: new partners, new value sharing models Actively experiment and seek to raise the metabolic rate of the company Ruthlessly disrupt your own business model before others do Follow the money: put your best resources where the future growth is SOURCE: McKinsey Digital; McKinsey Strategy and Corporate Finance practice
  42. 42. McKinsey & Company | 41 In Summary…. Old definitions of digital haves and have-nots are outdated; now it’s about the haves and have-mores. There is no opting out of the digital economy Have-mores (firms, industries) do much more with digital; and they see tangible gains in profitability, efficiency, and ability to set new rules of competition We are at early stages still. Sectors representing 80% of the economy have yet to benefit from digitization Digital is not just about a “thing” (like improving IT) – it’s about a new way of doing things (implying people, assets, use cases) Incumbents are sitting on a digital goldmine, yet most have yet to leverage digital’s full potential

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