Innovation
Merging of human and machine components Can repair, replace or augment organic components Many cultural implications Rapidly-accelerating science Examples:
RoboCop Prosthetics Camera + visual cortex in human brain Extensive use of smartphones Pacemakers/heart monitor implants
Push-based brands are focused on telling customers about themselves and trying to cause a sale before value is created Pull-based brands are about creating inherent value for customers first, generating gravitational pull—and then allowing purchases to be a natural result of that value Examples:
Nike+/Nike Fuel iOS and Android ecosystems
In-car infotainment system Allows third-party app development (closed system, not an open API) Examples:
In-car infotainment system Allows third-party app development (closed system, not an open API)
Collection and aggregation of large pools of data for analysis Many companies pool large quantities of data without knowing use cases yet Storage, privacy, security, speed and reliability are major concerns Big data + analytics needed for business insights; multi-sided platforms needed for advanced data-driven products Examples:
Collection and aggregation of large pools of data for analysis Many companies pool large quantities of data without knowing use cases yet Storage, privacy, security, speed and reliability are major concerns Big data + analytics needed for business insights; multi-sided platforms needed for advanced data-driven products
Varying degrees of machine augmentation or automation of human driving capacity Five levels of autonomous driving by US NHTSA (National Highway Traffic Safety Administration) (Level 0): No assistance or automation Function-specific Automation (Level 1): i.e. ABS, ESC Combined Function Automation (Level 2): i.e. Adaptive Cruise Control with Lane Centering Limited Self-Driving Automation (Level 3): i.e. Tesla Autopilot or early Google Car test vehicles Full Self-Driving Automation (Level 4): i.e. Google Car Examples:
Google Car Tesla Autopilot Traditional Automaker Prototypes (Mercedes, Audi, Etc)
In-car connector bridging internet and built-in systems (CAN-BUS) Provides basic trip and mechanical information to phone; some models provide 3G connectivity to function even when smartphone not present Provides ability for in-car measurements to feed into its own app or third-party applications in its marketplace Examples:
unMooch (share costs for rides with friends) Expensify (automatically log reimbursable miles driven for work)
Pricing model of charging a fee (usually subscription-based) for the value provided to a customer, rather than delivery of a tangible good Common in software world with web-based tools hosted in the cloud Increasing application to the physical world (mobility as a service via Uber and Didi, for example) Requires constant innovation by company, but stabilizes cashflow and upkeep costs Lowers cost of entry to expensive or complex systems Examples:
Salesforce Spotify Netflix Google Apps for Work FreshBooks Office 365
Augmentation or emulation of human intelligence in machine systems Creation of new, non-human forms of intelligence Includes expert systems (modeling human knowledge) as well as systems with decision-making skills Examples:
IBM Watson Assistant.ai Autonomous driving systems
Apple in-dash infotainment functionality Vehicle or 3rd-party manufacturer creates head unit in dash of vehicle Connects to iPhone and mirrors functionality through high-speed USB (and potentially future wireless connection) running specifically-designed apps in a manner safer and easier than using handset Relies on voice for primary input device Relies on mobile data connection for most functions
Application Program Interfaces to create conduits between various systems and datasets Enables internal or third-party developers Requires robust and secure architecture, including authentication, data integrity efforts and use logging Necessary for platform-based value Examples:
HomeKit Facebook Connect and other Single-Sign-On (SSO) options Ripple Fidor Apple CarPlay Software Development and Hardware Development Kits (SDK and HDKs)
Discovery, interpretation and communication of meaningful information in data Multidisciplinary—covers entire methodology and data value chain Many subfields, such as text analytics Temporal (time) element: batch (past) analytics, real-time analytics, predictive/prescriptive analytics
Examples:
Google Analytics (web properties) Sales analytics Inventory analytics Mixpanel
