IoT Co-Creation for Digital Transformation Outcomes Nick Chang Head of Global IoT and Analytics Practice
DIGITAL REVOLUTION Every industry, every business is under pressure
DIGITAL TRANSFORMATION Accelerate cost-efficiency Increase loyalty and grow Unlock new revenue and time to market by revenue by streams by automating improving adopting operations and customer experience new business models processes DATA-CENTRIC SERVICES MOBILE COMMERCE GLOBAL EXPANSION REAL-TIME INFORMATION PROCESS AUTOMATION DIGITAL COMMERCE PERSONALIZED ENGAGEMENT WORKFORCE MOBILITY SUPPLY-CHAIN EFFICIENCY
DATA STRATEGY FOR DIGITAL TRANSFORMATION DATA DATA DATA DATA ANALYTICS MANAGEMENT GOVERNANCE MOBILITY Any cloud Any app Abstract Access Anywhere Any use Automate Accelerate 101100101010010101010 DATA 011010101001001100101 SOURCES Mobile Structured data IoT data Unstructured data
The Physical (OT) and Digital (IT) Worlds Are Merging CLOUD CITY COMMUNICATIONS IoT IT INDUSTRIAL OT INSIGHT ARTIFICIAL INTELLIGENCE BUSINESS IT SYSTEMS BIG DATA CONSUMER ANALYTICS
The Skills and Resource Gap Skills needed by new staff for IoT projects Will your IT department add dedicated staff to support Data Analytics 69.9% IoT-related initiatives in 2017? Cloud Computing 54.8% Security 54.8% Network Edge/Perimeter 45.2% Yes Software Development 41.1% Virtualization 38.4% 26.8% Standards & Protocols 35.6% No Storage Management 28.8% General Management 73.2% 24.7% Compliance/Licensing 20.5% Distributed Computing 19.2% The case for collaboration: “Most of the bright people don’t work for you, no matter who you are.” - Bill Joy Source: 451 Research, Voice of the Enterprise: Internet of Things, Budgets and Outlook 2016
Challenges With Product/Solution Approach § Inflexibility one size does not fit all § Ambiguity around the scope of the problem § Complexity many sources of innovation outside of single business “Firms today must contend with more complex projects, intertwined consumer markets, greater competition and the trend towards instant, and constant, customer feedback. Traditional approaches to business cannot adequately address these challenges.” Longitude Research, “Co-creating the Future” 2017
Challenges of Doing It Yourselves In the digital world: § Pace of change is relentless § Problems span across multiple domains § Blurring of industry domains and boundaries “Finding the right partner with domain expertise in your business area is essential, as is that partner’s ability to collaborate with key stakeholders to identify technologies, skill gaps and opportunities for organizational process improvements.” 451 Research: Voice of the Enterprise 2016
Collaborative Creation (Co-Creation) § Definition: The process of collaborating with customers and ecosystem players in order to innovate and create new value for business stakeholders, customers and society at large § Co-creation - Innovation Turned Inside Out!
Co-Creation is Transforming Solution Creation How often has your organization worked Co-creation transforming innovation with customers on co-creation? 73.4% 48.5% Total Total 57% Not for profit Not for profit 61% Energy Energy 49% Infrastructure/City … Infra planning 57% Healthcare Healthcare 55% Financial Services Financial Services 61% Technology Technology 60% Automotive 83% Automotive Transport 48% Transport Manufacturing 61% Manufacturing 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% Agree All of the time Often Occasionally Sometimes Never Source: Longitude Research, “Co-creating the Future” 2017
Hitachi Co-Creation Approach H E R I TA G E O F A W A R D - W I N N I N G T H O M S O N R E U T E R S : I N N O VAT I O N C U LT U R E 119,000 “Top 100 Global Patents Innovators”
Hitachi Co-Creation Ecosystem – Getting Various Elements Together Customer Challenges Note: need NewCo name in final version Partners Hitachi “NewCo name” Software vendors Lumada Co-Creation System integrators Innovation through collaboration Hitachi R&D Hitachi Business Units Global Center for Social Industrial Power and energy Innovation (CSI) Water Urban Financial NEXPERIENCE Healthcare Government
Different Levels of Co-Creation We SHOW We do it We do it you how WITH you FOR you Enablement Innovation Execution CUSTOMER HITACHI RESOURCES RESOURCES
Hitachi Co-Creation Methodology Hitachi collaborates with customers to co-create unique solutions to specific customer challenges and data. Deployment @ scale Customer Create solution Validate Engage Build model HITACHI List of use cases Analytical model Proof of concept Proof of value Iterate as needed
Life Cycle of Co-Created Solutions Operationalize Co-create solution Deploy Operate and @ scale manage Customer Build Create Validate Engage model solution HITACHI Delivered Business Business Integration Value Prioritized Analytical Proof of Proof of Customer list of use concept model value HITACHI cases Iterate as needed
Engage 3. Conduct interviews, hold 1. Understand customer workshops, share vision business and challenges 2. Understand data model Prioritized use cases 5. Garner Consensus and agree 4. Define use cases on IP ownership
Build Model 2. Explore Data by sifting through various sources 1. Define Use cases in detail Analytical Model 3. Prepare data model 4. Develop analytical model
Create Solution 2. Build solution-model code and algorithms 1. Deploy IoT analytics platform Proof of outcome 4. Perform functionality testing 3. Build UX wireframes/UI with sample data design model
Validate 2. Update data and analytical 1. Integrate with customer IT and pipeline OT ecosystems Proof of value 4. Validate business outcomes 3. Test robustness and KPIs
Case #1: Predictive Quality at Daicel Corporation
Case study: Predictive Quality at Daicel Corp. Daicel is a global manufacturer of chemical and pyrotechnical products. • HQ: Osaka, Japan • FY2016 Revenues – ¥ 440 B ($4 B) • Employees:11,556 Automotive airbag inflator is one of Daicel’s core business. Issues: Globally improving product quality, increasing productivity and improving worker’s field of operation in automotive airbag inflator production processes
Engage to define specific use cases Activities • Interview stakeholders and research to identify, evaluate and prioritize IoT/Analytics opportunities • Explore the possibility of co-creation bringing IoT/Analytics expertise and image analysis technologies to the table Outcomes • Defined scope of project: Enhance Manufacturing Execution System (MES) by incorporating IoT technologies; first at Harima plant and then scale to other plants • Specific use cases: Improve quality and increase productivity by accurate traceability, detecting signs of operational failures and deviations in worker activities on the front lines
Build an analytical model with data Activities Analysis targets and sensing methods Category Analysis Targets Sensing methods • Collect the manufacturing performance data captured from Man Worker activities Depth cameras the perspective of 3M - Man, Machine & Material Position of supervisor Omni-directional camera & parts suppliers • Capture human joint position information in 3D via Machine Location of work Fixed Camera, High cameras and distance image sensors abnormalities, speed camera welding defects • Identify and list all possible deviations by questioning Material Parts supply PTZ camera* workers at great length and identify all work processes * PTZ (Pan, tilt, zoom): captures subjects in high resolution & pin-point accuracy Feature value • Use algorithms & pattern recognition to detect worker Pre-processing Judgement extraction irregular movement compared to standard movement. Head Both hand work movement judgment Judgment Smoothing result Joint Waist One hand work Model movement judgment - abnormal position selection type information Normalization Outcome - Degree of Arm Whole body work abnormality judgment movement • Analytical model Standard movement models High level system view of irregular movement detection algorithm
Create Solution to generate outcomes Activities • Introduce cameras as new sensing data sources combined with advanced analytics • Blend 3D image analysis with data from MES, IT systems & IoT feeds • Build data pipeline and analytical workflow • Continuous data monitoring and refinement of man, machine & materials assets Outcomes • Initial results of identification & removal of defective parts improves the overall non-defective product ratio • Analytics solution ready for pilot
Validate the delivered value Activities • Joint verification in Pilot tests at Daicel's Harima Plant (Tatsuno City, Hyogo Prefecture) • Detect signs of operational failures in production line facilities & deviations in worker activities Outcomes • Reduced the time to discovery of man, machine & materials defects • Reduced number of product recalls and quick elimination of defect root causes • Ready for multi-site deployment The role of supervisor shifted from ‘After the fact’ to ‘Prevention of failure’
Case #2: “City of Innovation” Campus Strategy
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