The Digital Transformation. Cheam Tong Liang VP, Corporate Strategy April, 2017

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The Digital Transformation Cheam Tong Liang VP, Corporate Strategy April, 2017

Transformation Drivers Customer s expectations has changed significantly and increases pressure on viability of industrial enterprises Customer Enterprise Individualized products Immediate delivery Buying an experience or ecosystem around the product Integrate software & automation Advanced communication network Security in automation Profit from industrial services Reduce time to market Improve flexibility and increase quality Reduce energy and resource consumption Automation in manufacturing insufficient, need to be a digital enterprise 2

Status of Industry 4.0 Adoption of Industry 4.0 Source : PwC Industry 4.0 or smart factory has moved from PR hype in 2013 to real investment and results Companies in Germany, US and Japan are the furthest along ~ 650M has been spent in Germany, and expecting 10.9B to be spent over the next 10 years $900B are expected to be spent yearly across the globe in Industry 4.0 adoption for next 5 years China s companies are highly flexible and open to change are readily embracing digital technologies Make in China 2025 Companies in Asia Pacific are also making progress Government initiatives in India, Korea and Taiwan 3

Challenges in the Transformation The barrier to implementation of Industry 4.0 is people and lack of digital culture and skills, not technology Need the organization leaders to lead the transformation, and create a robust digital culture in an organization Success will be dependent upon the digital knowledge of the employees Enhancing skills and organization structure will be critical Disruption isn t comfortable to many and change management will be key to ensure success Data analytics is the foundation of Industry 4.0 Need to move beyond the phase of data discovery to understanding the data to provide insight to help drive decision making 4

Data Analytics and Digital Trust Data is in the heart of Industry 4.0 Data is coming from multiple sources, both internal and external Rapid growth in number of sensors, embedded systems and connected devices Increasing horizontal and vertical networking of value chain Effective data analytics is essential to create value and becoming tools for decision making To control and improve overall business planning and manufacturing operations To get closer to customers and providing better and new services to improve profitability To provide improved maintenance of companies own assets and product owned by customers To enhance cooperation and decision making with partners in the value chain To use data in predictive or forward looking ways to develop new products and services Companies need rigorous and proactive approach to data security to build digital trust to be successful Making security a central part of all systems and processes is essential 5

Cybersecurity Concerns Operational disruption is the top data security concerns Issues are centered around ethics and control of access and use, interaction via the internet and digital risk resilience Source : PwC It is important to work with ecosystem partners with shared responsibilities for data security Third-party assurance is needed to confirm that systems are robust and strengthen trust of ecosystem participants 6

Changes in Products & Services Semiconductor Equipment Manufacturers will need to adapt and make changes to their products and services for the adoption of Industry 4.0 to stay relevant to their customers and the market Performance Management Yield Management Line/Factory Optimizer Augmented Reality Security Features Internet Access Increased Image Capturing & Processing Advanced Pay Per Use Machine-to-Machine Interaction Equipment Health Monitors Intelligent Equipment One of the IOTs Increased Material Tracking Improved Machine-to-Human Interaction Customer Specific Customization Increased Process Monitors Ecosystem Support Additive Manufacturing Quality Management Recipe Management Predictive Maintenance 7

Security & Transparency New Business & Collaborative Model Digital transformation pave way for disruptive business models New Collaborative Product Development Model Collaboration in R&D across the entire value chain Modelling and simulation with augmented reality New Digital Business Model Product optimization & uptime guarantee (Predictive Maintenance) Total fleet management & factory optimization Advanced Pay-per-Use Big data analytics & performance management 8

Vertical & Horizontal Integration Opportunity for full vertical & horizontal integration between customer, equipment manufacturer & entire value chain Vertical Value Chain Horizontal Value Chain Company Supplier Company Customer E2E Product Lifecycle Management Connected/Digital Factory Predictive Demand Manufacturing Execution Systems Advanced Asset Management Smart Manufacturing Coordination Control Integrated E2E Planning & Execution Logistics & Supply Chain Analytics Smart Spare Parts Management Smart Sourcing Smart Warehousing & logistics visibility 9

Digital Sales & Marketing Ecosystem approach to effective customer engagement for greater customer satisfaction & experience Enhanced customer relationship management Multi-channel marketing Self-service portal Dynamic pricing Personalized services E-payments Sales & Marketing Roles Creativity Tactical Execution Problem Solving 10

Moving Forward Industry 4.0 adoption will continue to accelerate with new products and services paving way for disruptive business models Significant investment needed, $900B per annum over the next 5 years The digital transformation will results in quantum leap in financial performance Global cost reduction of $421B per annum for the next 5 years $493B increased annual revenue for the next 5 years Source : Gartner Data analytics and digital trust are the foundation of Industry 4.0 Robust organizational structures needed to support data analytics Focus on people and culture to drive transformation 11

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