Perspectives

Workforce Reimagined

Elevator Pitch

  • Harnessing and unleashing the value of the employee ecosystem and supplier ecosystem to collectively form a workforce

  • Intersection of where human and artificial intelligence meet

  • Current workforce leverages technology and technology becomes part of the workforce and they both coexist

Key drivers

What it is today:

  • Static workforce aligned around specific skills & business functions with low levels of collaboration

  • Fragmented management tools

  • Training is ad-hoc

  • Innovation generally practiced by lone wolves in the organization

 

Where it is heading:

  • Machines and software intelligence (natural language processing and speech recognition) will be the newest recruits to the workforce, bringing new skills (human-like interactions) to help people do new jobs, reinventing what’s possible.

  • Intelligent automation takes over the heavy lifting and liberates humans to contribute to more high value tasks.

  • Project-based working groups emphasizing collaboration, agility & skill-sharing

  • Data-based organization management using predictive analytics

  • Continuous training as a core organizational competency

  • Failing fast and being iterative – employees are empowered to innovate in their roles

Path forward:

  • Identify opportunities, skill gaps and costs to deploy automation and machine learning capabilities in lieu of labor-intensive practices (e.g. Workforce safety).

  • Integrate analytics into HR

  • Pilot filling open positions with new methods of people and machine interaction

 


Where do we begin?

  • Build a blended workforce in stages where employees can let machines coexist in the environment

  • Prioritize solutions and industry relevant opportunities by dividing and distributing tasks that play to the workforce strengths

  • Machines for precision, scale and consistency

  • Humans for creativity, contextual decisions and complex communication

  • Creating employee training programs taking into account new skills that will be needed for a blended workforce

  • Integrate technology where specially trained workers were previously required (e.g. Worker safety)

Technology enablers

  • Intelligent drive – improves vehicle safety

  • Derelict satellites – cleaning up of satellite leveraging a unique combination of astronauts and logos

  • QuakeBot: writes the first draft of automated reports when an earthquake hits (leveraged by LA Times)

  • Amelia from IPSoft – intelligent helpdesk

  • Google Now/Now on Tap

  • MindMeld – suggesting effective responses to customer service agents

  • Wearables and sensors are helping to improve worker safety

  • Caterpillar’s telematics solutions which leverages video analytics to alert during unsafe conditions

  • Phillips leverages augmented devices to give surgeons freedom, portability and contextual information

  • Exoskeletons (Lockheed) – augment human physical strength and productivity

  • Amazon Kiva robots

  • Coursera’s Signature Track

  • Rethink Robotics (Baxter)

  • Apple Swift

  • Google Go

  • Metaio

  • Movero Smart Glass

Key takeaways

  • Seamless Collaboration

  • Predictive analytics-powered HR

  • Continuous training and performance

  • Rise of freelancing

  • Pace of innovation and automation

  • A new generation (millennials)

Intelligent Enterprise

Elevator Pitch

  • Enable the enterprise through the latest and greatest in intelligent software

  • Automation

  • Artificial Intelligence

  • Other intelligent devices combining mobility and smart devices

Key drivers

What it is today:

  • Businesses are facing a number of new challenges

  • New forms of competition is emerging in the form of expected and unexpected competitors

  • Digital ecosystems are blurring industry boundaries in foreseeable and unforeseeable ways

  • Disruption and impact is fairly widespread and pervasive in certain industries

 


Why is this trend emerging:

  • Intelligent Enterprise has the power to make things simpler, agile and integrate everything (e.g. products, services, tools, business models, partners, ecosystems and more)

  • Technology advances in the following

  • Sensor processing

  • Intelligent learning

  • Robotic process automation

  • Expert systems

  • Inference engines

  • Machine learning

  • Computer vision

  • Knowledge representation

Path forward:

  • Leverage intelligent automation to be the active defense against accelerating pace of change -

  • Cost-saving opportunities

  • Intelligent technologies as a competitive advantage

  • Readjust IT spend to ‘change the game’

  • Architect resilience

  • Blur the digital-physical line



Where do we begin?

  • Identify applications that require frequent and manual updates, data extracts and/or a high degree of personalization

  • Classify an application as a top priority for artificial intelligence if it depends extensively on data (e.g. Machine learning)

  • Take an inventory of labor-intensive processes and identify opportunities for automation and machine learning capabilities. This can help improve operational capabilities and scale real-time analytics even further

  • Map the identified opportunities against the corporate strategy to prioritize specific opportunities – to catch up or to gain new advantages

Technology enablers

  • Room delivery achieved through robots (Towels, laundry, etc.) – the Robotic Butler

  • Intelligent ‘worms’ monitor hazardous operations and ensure worker safety

  • Facebook and Google facial recognition rendering for photo tagging

  • Virtual gaming tutors could bring new up-sell and cross-sell opportunities

  • Room service bot to alert the Robotic Butler to replace used items in the room

  • Digital concierge

Key takeaways

Establish a top-down strategic commitment to a seamless coexistence of artificial and natural intelligence capabilities, blurring the digital-physical line

Personalized Customer & Ecosystem Experience

Elevator Pitch

  • Unifying customer experience across all channels

  • Unprecedented customer personalization

  • Drive customer value through significant opportunities

  • Upselling

  • Cross Selling

Key drivers

What it is today:

  • Cluster-based marketing (‘The We’)

  • Segmentation

  • Generalized experiences (e.g. generic ads)

  • Community-centric

  • Market-share battleground

  • Customers have fragmented, inconsistent experience across different channels

  • Customer information captured in the back-end does not reflect in the front-end

  • Abstract recommendations driven by random generation

 

Why is this trend emerging:

  • Individualized marketing (‘The Me’)

  • Personalization (The Internet of Me)

  • Contextual experiences (e.g. location-based ads, social media preferences driving ads)

  • User-centric experiences

  • Interactive & immersive

  • Mind-share battleground

  • Mind-share results in wallet-share

  • An Omni-channel experience that is seamless and consistent

  • The CI/CX layer incorporates all of the user’s preferences

  • Logical recommendations driven by customer analytics

Path forward:

  • Technology enables but trust endures

  • Zero ‘moment of truth’ both from the demand and supply side

  • Personalized predictive push approach rather than pull approach

  • Highly localized preferences

  • Migration from human trust to digital trust

 


Where do we begin?

  • Start with customer data and identify use cases where context-based services can play a role in personalization services

  • Assess technology capabilities to handle high load, speed and real-time for personalized customer services

  • Identify technologies that can complement or supplement existing products or services, preferably by looking at early adopters for inspiration

  • End-to-end strategy and envisioning for the ‘Internet of Me’, bringing the individual voice to the table

  • Architect an omni-channel customer experience

Technology enablers

  • Nest Thermostats – communicate with cars’ APIs

  • Whirlpool – schedule energy-intensive tasks when the rates are lower

  • Ralph Lauren – sensor-embedded clothing that captures activity

  • Smart meters that give information on energy consumption on a real-time basis

  • iBeacon

  • If This Then That (IFTTT)

  • Pandora

  • FuelBand

  • Nike+iPod

  • SPG app – guests can unlock their rooms with Apple Watch

  • Disney World app & Disney MagicBand

Key takeaways

  • It’s beyond just mobility!

  • Customer experience is the new competitive weapon

  • Contextual experience allows businesses to craft unique experiences

  • Measuring and valuing outcomes over transactions

Harnessing Hyper-scale

Elevator Pitch

  • Unleash the value of all corporate investments

  • Technology infrastructure

  • Operations including data center, cloud, etc.

  • Data

  • Business Process

Key Drivers

What it is today (Industrial Era):

  • Traditional value chain models are linear and one-way

  • Supply-side economies of scale

  • Asset-heavy (Physical)

  • Growth characteristics – organic and inorganic

  • Market cap - $500 Billion

  • Measurement - GDP

 

Why this is possible (Digital Era):

  • Platform ecosystems (continuous and non-linear)

  • Demand-side economies of scale

  • Asset-light (Digital)

  • Unprecedented data volumes

  • Reduced cost of storage

  • Unlimited computing power

  • Broadening IT scope

  • Growth characteristics – asymmetric and network effects

  • Market cap - $2.5+ Trillion

  • Measurement – Evolving (e.g. Digital Density, ‘free goods’)

Path forward:

  • IT & Business process enablement using platforms including Application infrastructure outsourcing

  • Platform strategies especially opening up data and APIs to partners, creating ecosystems

  • Maturing SMAC (Social, Mobility, Analytics, Cloud) are opening up new possibilities for revenue generation

  • Interoperability: opportunities to leverage an echelon of standards (Wifi, Bluetooth, Zigby, Zwave, NFC)

  • Software-defined networking

Where do we begin?

Identify platform investments in key parts of the business where there is potential to ’change the game’ (disrupt) and/or assess the threat of being disrupted

Assess knowledge gaps in demand-side economies of scale, network effects and asymmetric competition

Assess technology capabilities, gaps and enablers (e.g., in-memory computing);

  • Platform Enablers: Foundation (Cloud); Treasure Chest (Mobile); Digital Glue (API’s), Real-time (IoT, Wearables) and Accelerators/Containers (Open Source)

  • Governance Enablers: Agile (Release/Change management); DevOps (Process, people and tools); Testing (Rapid, ecosystem-based)

Leverage advances in data supply chain:

  • Complex multi-variate analysis (e.g., Optimizing Funnel Conversion, Behavioral, Customer Segmentation, Predictive, Market Analysis & Pricing Optimization, Active Security Defense and Fraud Detection)

  • Gaming Analytics - Slot Revenues, TITO (Ticket-in Ticket-out), Server-based Gaming, Cashless

Technology Enablers

  • Philips has launched a healthcare platform with 3 technology partners (platforms coexist with traditional business model)

  • Salesforce.com

  • Amazon IoT

  • Alibaba Cloud

  • Kaiser Permanante Digital Health Platform

  • GE Predix Industrial Internet Platform

  • GM Connected Car

  • Fiat Chrysler

  • Automobiles Connected Cars

  • Schneider Electric Smart Cities, Buildings and Homes

  • Telefonica Vivo

  • M2M Control Center Platforms

Key takeaways

  • Technology-based disruption has lowered entry and exit barriers resulting in asymmetric competitive opportunities and threats

  • Speed of growth achieved through asset-light technology scaling cannot be easily matched by asset-heavy business models