Multi-Modal Transport

• Bridging of multiple modes of transport
• Digital layer starts first by helping human users plot itineraries and unify ticketing, parking, etc. 
• Advanced digital layer will actually coordinate multiple humans and multiple transit systems/vehicles for optimal reliability, safety and speed

Example

• Google Transit Planner

Mobile Environments

• Environments that come to the user, or that can be moved to various locations
• Flips paradigm of humans traveling to a particular environment—instead, environments travel to humans
• Mass-culture precedent in food trucks, pop-up stores; digital layer involves telling users where environments have been [re]located or even directly summoning environments
• Imagine offices, schools, stores or clinics arriving at your home or an another convenient location

Examples:

• Philips Hue portable lighting
• On-demand classrooms in school buses (Curitiba, Brazil)
• Pop-Up Stores and Food Trucks
• Ideo concept
• Robotic Architecture (import an environment)

Digital Natives/Gen Y (Millennials)

• Worried about the future, sometimes more than parents: (terrorism, global warming, global economic crises, job possibilities, health, etc)
• Asset-light: in some situations, may have fewer owned items, preferring liquidity and/or flexibility
• Different way of shopping than previous generations, willing to try new brands based on interactivity, message, friend recommendations or functions rather than age of brand or traditional marketing
• Expect to be able to find data easily
• Their tech is ‘always-on’
• Accustomed to online-enabled relationships & experiences
• Technology reports on past & present around them

Examples:

• Snapchat/WeChat
• Katy Perry
• Carsharing
• On-demand services

Metromile

• Leverages just-in-time, on-demand service trend
• Regulatory model for insurance permits flexible pricing
• Creates a robust data platform and aggregation network; can broker data and beat big companies at their own game
• Serves millennials & `unprofitable’ users—makes car ownership more feasible
• Freemium distribution based on convenience features
• Simple web product; graceful integration with mobile network
• Takes advantage of traditional insurance company relationship failures
• Hip, urban branding and viral outreach

Maven + GM

• Mirrors Zipcar’s model (central owner, per-hour rentals)
• Speculation that this, along with GM’s investment in Uber competitor Lyft, are part of a larger move to create demand for driverless cars

Localization

• Local-first focus for customers—locally-produced agriculture, locally-offered services, locally-manufactured products, locally-focused culture
• Digital services around localization trends usually require extensive cultural customization and awareness of physical places; for example, Facebook Pages allow end users to provide feedback on the relevance of particular services and Google Maps has detailed building maps for shopping centers and complex streets
• Local-first movements emphasize keeping spending with local businesses for health of micro-economies 

Examples:

• Farmers’ Markets (US)
• Apps for finding local resources (Foursquare, Apple’s Apps Near You)

Little Data

• Little data is data about a specific user, designed for customization of products and support of relationship-centric brands
• Social CRMs and social network APIs are useful in managing little data
• Unexpected usage can cause anything from user confusion to outright anger
• When used well, products and business-to-customer relationships feel more natural and intuitive

Examples:

• Facebook Social Graph (for an individual)
• Individual record in a social CRM

Leadership: Control to Empowerment

• Control-based leadership inherited from military models and the industrial age has limitations
• In order to respond in an agile way, teams and employees must have room to improvise
• Modern leadership focuses on empowering teams to be creative and fast
• Creation of ‘doctrine’—guidelines for acceptable improvisation, is necessary for success of employees—in addition to a bare minimum of processes and rules

Examples:

• Whole Foods customer service
• Google
• Agile development

Internet of Things

• Connection layer for physical devices, such as industrial or home sensors, thermostats, etc
• Interoperability, security and reliability of IoT systems may be a barrier to entry
• Will evolve into a Social Network of Things (SNT) where devices can better connect to and negotiate with other devices; see causeit.org/SNT for more information

Examples:

• “Smart” power meters
• Phillips Hue
• Nest Thermostat
• Withings

Integration & Interoperability

• Key element of connected products
• Use of Application Program Interfaces, Software and Hardware Development Kits, shared standards, libraries and frameworks
• Requires ability to selectively share and potentially revoke data access
• Requires clarity on where decisions are made in a chain of connected services/devices

Examples:

• USB
• APIs
• SDKs & HDKs
• Apple HomeKit
• Facebook API

Google Car

• Self-driving car project by major internet company
• Designed to run entirely without a driver

Getaround

• Allows peer-to-peer car sharing
• Service enables booking, insurance, payment and vehicle tracking
• Reduces risk of each party in the transaction, takes a percentage of transaction

Ford/Ford Mobility

• Ford + Getaround actively encourages Ford drivers to share their cars with others through the Getaround platform
• Multi-user leasing allows car sharing up to six ways; provides some basic scheduling support
• Creation of separate legal entity and organizational structure from Ford Motor Company

Distributed Workforce

• Multiple locations for workforce
• May be distributed between multiple companies
• Necessitates telepresence and advanced travel functions to be affordable and reliable
• Requires effective decision-making at edges of the organization
• Foundation of large multinational companies, but also very small firms with global presence
• In long term, may affect or effect population migration trends

Examples:

• Google
• Redhat Linux

Disintermediation

• Removal of layers of sales functions, such as dealerships or distribution networks
• First wave of e-commerce caused huge disintermediation of traditional business-to-customer sales

Examples:

• Amazon
• Direct insurance sales
• Tesla Stores/Centers

Digital Immigrants

• Acclimate to digital tools over time/as needed 
• Map digital tools to analog predecessor
• May not immediately see value in experiences which are only in digital realm

Example:

Baby Boomers (US) or other generations which did not grow up with tech

Data Rivers & Data Lakes

• Data Rivers: pipelines of data
• Data Lakes: aggregations of multiple data sources, either with or without data validation 

Examples:

• Real-time analytics performed on mass data sets
• Facebook Social Graphs (aggregate)

Data Natives/GenZ

• Data transforms automatically for/around them
• Tech is always smart
• Online-PRIMARY relationships & experiences are common
• Their technology predicts the near future and exists in both online and physical spaces

Examples:

• Video game worlds/augmented and virtual reality
• Generation ‘Y’ users
• Grew up with smartphone access

Data in Motion

• Data which changes often, such as a live feed of video or an algorithm-driven analysis of a stock market
• Dynamic
• Secured multiple ways, such as securing the ‘pipes’ the data flows through and through authentication of users authorized to access
• Data architectures built to be synchronized across systems (central data or self-reconciling systems)

Examples:

• Google Docs
• Video feeds
• Algorithm-based data sources
• Cloud-based systems
• Real-time analytics

Data at Rest

• Data which, like a file in a file cabinet or row in a spreadsheet, stays the same until a user modifies it
• Static
• Secured usually by securing the perimeter around it (locking the file cabinet, password-protecting a spreadsheet)
• Hard to synchronize across systems (copies and versions)

Examples:

• Spreadsheets
• Hard copies
• Attachments on email