Big Data & Analytics: A. Vaccani&Partner AG Bid Confusion, - - PowerPoint PPT Presentation
Big Data & Analytics: A. Vaccani&Partner AG Bid Confusion, Big Threat or Big Opportunity? Zollikerstrassse 141 P.O. Box 1682 CH-8032 Zurich Switzerland T +41 44 392 99 00 info@avp-group.net Presented by Scott Affelt
Zollikerstrassse 141 P.O. Box 1682 CH-8032 Zurich Switzerland T +41 44 392 99 00 info@avp-group.net www.avp-group.net
Presented by Scott Affelt January 2017
Source: Dataconomy
Big Data is high-volume, high-variety and high-velocity data that needs Analytical tools to reveal trends, patterns and correlations that can create actionable insights into decision-making. Internet of Things (IoT) is the inter-networking of physical devices, embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
45% Cost of Sensors Cost of Bandwidth Cost of RAM/Storage 60X 40X 20X
Source: Goldman Sachs Investment Research. Changes over last 10 years.
Connectivity Sensors Computing Analytics
Cost of Computing
Capital Spending Competition Profit Margins NA Growth Europe Growth Asia Growth
Old Model New Model Sears, Macy’s Amazon Yellow Taxi Uber, Lyft Kodak/Motorola Digital Cameras, iPhone Boiler OEM ?????? Don’t Let This Be You!
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
(limited by technology & cost)
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
(enabled by technology & cost)
Difficulty Value
Descriptive Analytics
What
happened?
Diagnostic Analytics
Why
did it happen?
Predictive Analytics
When
will it happen?
Prescriptive Analytics
What
should I do about it?
Source: Gartner
Sources: DOE Study on Predictive Maintenance. NETL & EPA studies on Efficiency Improvements.
Benefits Value Created Predictive Maintenance
Advanced Pattern Recognition + Diagnostics + Prognostics
Remaining useful life predictions.
Performance Monitoring
Real-time process monitoring + Diagnostics
Identify specific components contributing to inefficiency
Advanced Controls
Adaptive, Predictive Controls
– Avoided Cost of Unplanned Outages – Lower Maintenance Costs – Higher efficiency
– Better Risk Management – Real-time Decision Support – Strategic Capital Investment Decisions – Increased workforce effectiveness – Improved safety
Accenture Study 10GW Fleet Duke Energy $31.5M Cost Avoidance
Machine Learning Data Processing Traditional Controls
Machine Learning Data Processing Traditional Controls
Process/Reliability
Machine Learning Data Processing Traditional Controls
Products Services Products Services
Customer Value High Low 1980 2017
Transactional
Break/fix
Contractual
LTSA
Customer Outcomes
Optimized Assets & Production
Value Created for Customer
Customer Needs Reactively solve existing needs Proactively address real-time and emergent needs Offering Stand-alone product that become
Continual update of product, features & value created Role of Data Monitoring, Control and Safety Optimization, Improvement, Autonomy
Source: SmartDesign
Value Captured by Supplier
Path to Profit Sell the next product Enable recurring revenue streams Customer Control Points Technology know-how, IP and brand Synergies between products & services Customer reliance of Value Created Capability Development Maximize use of core competencies & existing resources Focus is on Product Leverage use of core competencies & existing resources Create new network/system value Focus is on the System
Key Components of Offering
Key Enablers
designs/knowledge
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
specifications
Key Enablers
Maintenance)
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
platforms
– Analytical tools – Connectivity – Data storage, management
– Unique process knowledge/algorithms – Physics-based life assessments
– GE Predix, Siemens – MicroSoft, IBM
– Asset Performance Management Suites – Enterprise Asset Management Suites
Machine Learning Data Processing Traditional Software
Initialization Digital Strategy Implementation Phase 1 Digital Business Analysis
External Internal
Phase 2 Strategy Formation Phase 3 Preparation of Implementation
key issues
teams
internal and external analysis
Current strategic vision What data and value of data in the business model Digital SWOT Customer expectations Competitive landscape Mapping of key players
Target focus areas to provide customer vale Digital Value Chain and gaps Monetizing strategy Make or buy Partnering strategy and interfaces
strategy with top management
requirements
implementation Implementation Strategy Development Digital Business Analysis Project Initiation
Activity postponed into Phase 2
AVP Group S.Affelt@AVP-Group.com +1 303-883-0399
Source: Dataconomy
Big Data is high-volume, high-variety and high-velocity data that needs Analytical tools to reveal trends, patterns and correlations that can create actionable insights into decision-making. Internet of Things (IoT) is the inter-networking of physical devices, embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
45% Cost of Sensors Cost of Bandwidth Cost of RAM/Storage 60X 40X 20X
Source: Goldman Sachs Investment Research. Changes over last 10 years.
Connectivity Sensors Computing Analytics
Cost of Computing
Capital Spending Competition Profit Margins NA Growth Europe Growth Asia Growth
Old Model New Model Sears, Macy’s Amazon Yellow Taxi Uber, Lyft Kodak/Motorola Digital Cameras, iPhone Boiler OEM ?????? Don’t Let This Be You!
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
(limited by technology & cost)
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
(enabled by technology & cost)
Difficulty Value
Descriptive Analytics
What
happened?
Diagnostic Analytics
Why
did it happen?
Predictive Analytics
When
will it happen?
Prescriptive Analytics
What
should I do about it?
Source: Gartner
Sources: DOE Study on Predictive Maintenance. NETL & EPA studies on Efficiency Improvements.
Benefits Value Created Predictive Maintenance
Advanced Pattern Recognition + Diagnostics + Prognostics
Remaining useful life predictions.
Performance Monitoring
Real-time process monitoring + Diagnostics
Identify specific components contributing to inefficiency
Advanced Controls
Adaptive, Predictive Controls
– Avoided Cost of Unplanned Outages – Lower Maintenance Costs – Higher efficiency
– Better Risk Management – Real-time Decision Support – Strategic Capital Investment Decisions – Increased workforce effectiveness – Improved safety
Accenture Study 10GW Fleet Duke Energy $31.5M Cost Avoidance
Machine Learning Data Processing Traditional Controls
Machine Learning Data Processing Traditional Controls
Process/Reliability
Machine Learning Data Processing Traditional Controls
Products Services Products Services
Customer Value High Low 1980 2017
Transactional
Break/fix
Contractual
LTSA
Customer Outcomes
Optimized Assets & Production
Value Created for Customer
Customer Needs Reactively solve existing needs Proactively address real-time and emergent needs Offering Stand-alone product that become
Continual update of product, features & value created Role of Data Monitoring, Control and Safety Optimization, Improvement, Autonomy
Source: SmartDesign
Value Captured by Supplier
Path to Profit Sell the next product Enable recurring revenue streams Customer Control Points Technology know-how, IP and brand Synergies between products & services Customer reliance of Value Created Capability Development Maximize use of core competencies & existing resources Focus is on Product Leverage use of core competencies & existing resources Create new network/system value Focus is on the System
Key Components of Offering
Key Enablers
designs/knowledge
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
specifications
Key Enablers
Maintenance)
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
platforms
– Analytical tools – Connectivity – Data storage, management
– Unique process knowledge/algorithms – Physics-based life assessments
– GE Predix, Siemens – MicroSoft, IBM
– Asset Performance Management Suites – Enterprise Asset Management Suites
Machine Learning Data Processing Traditional Software
Initialization Digital Strategy Implementation Phase 1 Digital Business Analysis
External Internal
Phase 2 Strategy Formation Phase 3 Preparation of Implementation
key issues
teams
internal and external analysis
Current strategic vision What data and value of data in the business model Digital SWOT Customer expectations Competitive landscape Mapping of key players
Target focus areas to provide customer vale Digital Value Chain and gaps Monetizing strategy Make or buy Partnering strategy and interfaces
strategy with top management
requirements
implementation Implementation Strategy Development Digital Business Analysis Project Initiation
Activity postponed into Phase 2
AVP Group S.Affelt@AVP-Group.com +1 303-883-0399
Source: Dataconomy
Big Data is high-volume, high-variety and high-velocity data that needs Analytical tools to reveal trends, patterns and correlations that can create actionable insights into decision-making. Internet of Things (IoT) is the inter-networking of physical devices, embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
45% Cost of Sensors Cost of Bandwidth Cost of RAM/Storage 60X 40X 20X
Source: Goldman Sachs Investment Research. Changes over last 10 years.
Connectivity Sensors Computing Analytics
Cost of Computing
Capital Spending Competition Profit Margins NA Growth Europe Growth Asia Growth
Old Model New Model Sears, Macy’s Amazon Yellow Taxi Uber, Lyft Kodak/Motorola Digital Cameras, iPhone Boiler OEM ?????? Don’t Let This Be You!
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
(limited by technology & cost)
Predictive Preventive Reactive Optimization Advanced Control Control
Value Created
Maintenance Production
(enabled by technology & cost)
Difficulty Value
Descriptive Analytics
What
happened?
Diagnostic Analytics
Why
did it happen?
Predictive Analytics
When
will it happen?
Prescriptive Analytics
What
should I do about it?
Source: Gartner
Sources: DOE Study on Predictive Maintenance. NETL & EPA studies on Efficiency Improvements.
Benefits Value Created Predictive Maintenance
Advanced Pattern Recognition + Diagnostics + Prognostics
Remaining useful life predictions.
Performance Monitoring
Real-time process monitoring + Diagnostics
Identify specific components contributing to inefficiency
Advanced Controls
Adaptive, Predictive Controls
– Avoided Cost of Unplanned Outages – Lower Maintenance Costs – Higher efficiency
– Better Risk Management – Real-time Decision Support – Strategic Capital Investment Decisions – Increased workforce effectiveness – Improved safety
Accenture Study 10GW Fleet Duke Energy $31.5M Cost Avoidance
Machine Learning Data Processing Traditional Controls
Machine Learning Data Processing Traditional Controls
Process/Reliability
Machine Learning Data Processing Traditional Controls
Products Services Products Services
Customer Value High Low 1980 2017
Transactional
Break/fix
Contractual
LTSA
Customer Outcomes
Optimized Assets & Production
Value Created for Customer
Customer Needs Reactively solve existing needs Proactively address real-time and emergent needs Offering Stand-alone product that become
Continual update of product, features & value created Role of Data Monitoring, Control and Safety Optimization, Improvement, Autonomy
Source: SmartDesign
Value Captured by Supplier
Path to Profit Sell the next product Enable recurring revenue streams Customer Control Points Technology know-how, IP and brand Synergies between products & services Customer reliance of Value Created Capability Development Maximize use of core competencies & existing resources Focus is on Product Leverage use of core competencies & existing resources Create new network/system value Focus is on the System
Key Components of Offering
Key Enablers
designs/knowledge
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
specifications
Key Enablers
Maintenance)
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
Key Components of Offering
Key Enablers
Value Created for Customer
Value Captured for Supplier
platforms
– Analytical tools – Connectivity – Data storage, management
– Unique process knowledge/algorithms – Physics-based life assessments
– GE Predix, Siemens – MicroSoft, IBM
– Asset Performance Management Suites – Enterprise Asset Management Suites
Machine Learning Data Processing Traditional Software
Initialization Digital Strategy Implementation Phase 1 Digital Business Analysis
External Internal
Phase 2 Strategy Formation Phase 3 Preparation of Implementation
key issues
teams
internal and external analysis
Current strategic vision What data and value of data in the business model Digital SWOT Customer expectations Competitive landscape Mapping of key players
Target focus areas to provide customer vale Digital Value Chain and gaps Monetizing strategy Make or buy Partnering strategy and interfaces
strategy with top management
requirements
implementation Implementation Strategy Development Digital Business Analysis Project Initiation
Activity postponed into Phase 2
AVP Group S.Affelt@AVP-Group.com +1 303-883-0399