Sponsored by

Building Resiliency in Manufacturing with AI and Streaming Analytics  Leading a Data-Led Recovery

A N I D C I N F O B R I E F | A U G U S T 2 0 2 0

#AP241185IB

Executive SummaryASEAN manufacturing activity contracted sharply after governments imposed near lockdowns and social distancing measures to curb the spread of coronavirus infections. Thailand, Malaysia, and the Philippines reported an 11% average drop in discrete manufacturing, and with neither a cure nor an end of the pandemic in sight, ASEAN is bracing for further impact against the backdrop of lackluster global consumer demand for goods and disruptions to global supply chains.

Amid the uncertainty, one thing is clear: ASEAN manufacturing must move forward toward a recovery phase. This requires a paradigm shift of focus on shoring up business resiliency, a top priority for manufacturers, according to IDC research.

Manufacturers will require new capabilities to bounce back quickly in response to change, to the original or an improved state. This cuts across the organization, its entire operations, and across the supply chain to preserve business continuity and consistency of product supply in the event of short and long-term disruptions.

This also calls for a “data-led” digital transformation amid the pandemic which has accentuated the importance of digital technologies in the pursuit of Industry 4.0. Think capabilities to deliver autonomous, data-rich, and insights-based manufacturing operations for operational improvements and business opportunities.

This IDC InfoBrief takes a closer look at this data-led recovery and how artificial intelligence (AI) and streaming analytics can accelerate industry recovery in the short, medium, and long term.

An IDC InfoBrief | Leading a Data-Led Recovery: Building Resiliency in Manufacturing with AI and Streaming Analytics 2

ASEAN Manufacturers’ Top 3 Priorities over the Next 3 to 4 Years1

Reducing operational risk and improving resiliency

Better operational excellence in manufacturing

Improved supply chain performance

Source: 1 IDC Asia/Pacific Industry 4.0 Survey 2020, n = 145 (ASEAN Manufacturing n = 40; ASEAN Oil & Gas and Logistics n = 60; ASEAN Mining and Utilities n = 45)

Data as of June 2020

ASEAN Manufacturing Amid COVID-19

Total stimulusUS$173 billion

MalaysiaUS$60 billion stimulus packageAid for small and medium-sized enterprises (SMEs) for rent, utility, and electricityReduced buying volume and moderate decline in employment

72% 72% 68%

ThailandUS$37 billion stimulus packageLowered interest rates loan and loan restructuring for SMEs

US$27 billion stimulus packageTax reduction, deferral debt repayment, and finance restructuringDrastic reduction in exports

Indonesia

SingaporeUS$42 billion stimulus packagePayment deferral and government subsidies up to 80% for insurance premiumPurchasing Managers’ Index (PMI) most resilient in ASEAN

PhilippinesUS$7 billion stimulus packageReduced lending rates for areas in manufacturing

Future of Industry Calls for Data and InsightsIndustry 4.0, the vision for sustainable industry value creation, is not just a technology strategy but about delivering outcomes. In the race to recovery and improving production performance, manufacturers will require innovation, agility, and connected assets, the building blocks for assimilating data and insights for strategic decision making to bring manufacturing to the next level.

3

Future of Manufacturing

Source: 1 IDC FutureScape: Worldwide Supply Chain 2020 Predictions — APEJ Implications, Doc #AP45864020, January 20202 IDC FutureScape: Worldwide Manufacturing 2020 Predictions — APEJ Implications, Doc #AP44620520, January 2020 3, 4 IDC FutureScape: Worldwide Internet of Things 2020 Predictions — APEJ Implications, Doc #AP44720219, January 20205, 6 IDC Asia/Pacific Industry 4.0 Survey 2020, n = 145 (ASEAN Manufacturing n = 40; ASEAN Oil & Gas and Logistics n = 60; ASEAN Mining and Utilities n = 45)

By the end of 2021, 35% of all large manufacturers will have automated supplier and spend data analysis, resulting in 15% procurement productivity gains.1

By 2021, 20% of manufacturing companies will have started to treat their assets as internal customers, leading to a 40% reduction in asset downtime.2

By 2021, 90% of Internet of Things (IoT) deployment will include AI solutions for autonomous or edge decision making, supporting organizations’ operational and strategic agendas.3

By 2024, 45% of manufacturers will use IoT platforms with digital innovation platforms to operate networks of asset, product, and process digital twins for a 25% reduction in cost of quality.4

Where ASEAN Organizations Need to Focus Now Invest in AIoT and cloud edge computing as foundational capability

Which strategic priorities are ASEAN organizations investing the most for Industry 4.0?5

Incorporate cloud edge computing, Industrial Internet of Things (IIoT), Artificial Intelligence of Things (AIoT), automation, and robotics for reliability, optimization, and creating new value add.

Assimilate rapid iteration and cross-functional collaboration in operations with AI systems, IoT, and robotics securely.

Leverage AI, augmented and virtual reality (AR/VR), and IoT to ideate, design, simulate, develop, and optimize products and product experiences.

Integrate data-rich insights and automation into factories and plants. This encompasses upstream and downstream data integration for resiliency, optimizing operations, and efficiency.

Increase visibility into asset behavior by incorporating IIoT/AIoT to optimize the performance of its assets using insights and predictive analytics.

Digital Innovation

Agile Integrated Operations

Innovation Acceleration

Smart Manufacturing

Connected Assets

Inhibitors to Using Data for Decision Making6

Availability and convergence of information technology and operational technology (IT/OT) data and integration with enterprise resource planning (ERP) solutions

Access to quality and actionable time series and operational data

Organizational and cultural challenges relating to data-based decision making

23%

34% 26% 13%

18% 15% 15% 11%

An IDC InfoBrief | Leading a Data-Led Recovery: Building Resiliency in Manufacturing with AI and Streaming Analytics

Leveraging Insights for Accelerated RecoveryThe success to recovery lies in the ability of organizations to predict changes and create an actionable plan. Focus on gaining capabilities that demonstrate return on investment and business continuity while leveraging a layered technology approach and developing use cases.

4

Short/Mid Term

Use Cases

Long Term

Aggregate real-time IIoT data from customer supply and demand to enable manufacturers and to predict demand and scale accordingly.

Leverage scalability of cloud computing to scale accordingly based on data points captured and determine priority workloads.

Integrate internal with external data points such as demographics of customers and prospects, workforce metrics, competitor products, suppliers’ performance, and economic situation to optimize factory and supply chain networks.

Look for opportunities to utilize digital twins to simulate scenarios to identify faults, isolating and dynamically controlling processes, mitigating risks, and minimizing human intervention.

Adapt and innovate using cognitive planning and expand toward high value use cases. Shopfloor becomes a center of business transformation and reinvention, rather than just for fulfillment purposes.

Business Continuity – Anticipate the Change Using IIoT/AIoT

Cost Optimization – Scale Accordingly

Business Resiliency –Enrich Ecosystem Data

Targeted Investment – Identify Investment Opportunities

Future Enterprises – Next Business Priority

KEY: Enable crisis visibility, activation, and

response, optimizing routes and asset

placement to maximize delivery effectiveness.

KEY: Use intelligence to enable automated

decisions based on real-time insights, reducing supply chain latency.

KEY: Address demand variability through

production optimization and scenario planning

to gain the greatest impact based on current

material availability.

KEY: Enable real-time information, ability to

simulate scenarios based on as-is supply chain

status.

KEY: Build in the structural capabilities to build a resilient supply

chain through profitable factory proximity.

KEY: Reduce planning horizons to near-real

time, incorporating new demand information and supply chain disruptions.

KEY: Enable automation utilizing AI/machine learning (ML), IoT, software and/or

hardware automation that increases remote

worker capability, and manufacturing

productivity.

KEY: Ability to share design iterations, simulations, and

specifications for rapid prototyping remotely,

integrating collaborative design and material

availability.

Transportation Management &

Optimization

Digital Engineering (IT/OT) and Streaming Analytics

Distributed AI & ML

Resilient Intelligent Decisioning

Analytics Life-Cycle Management

Model Deployment Across Resilient Infrastructure

Supply Chain Planning &

Optimization

Manufacturing Operations

Optimization

Supply Chain Digital Twin

Factory Network Optimization

Demand Forecasting for Sales &

Operations Planning

Intelligent Automation

Product Life-Cycle Management and R&D Collaboration

Critical Analytics Technology Capabilities

An IDC InfoBrief | Leading a Data-Led Recovery: Building Resiliency in Manufacturing with AI and Streaming Analytics

Essential Guidance

5

As ASEAN governments emphasize digital as indispensable at a regional and international level in the post–COVID-19 world, manufacturers big and small will be pushed to make critical investments to reduce the sharp plunge and flatten the curve toward recovery. Those that employ the right technology and gain the agility necessary to adapt to the new trading environment will become more resilient and digitally fit for the future.

Aligning one’s business focus with the economic situation will require strategic technology investments. The chart below offers a snapshot of some of the key technologies that align with the five economic stages, from enduring a downturn to the ideal state of what IDC calls a “Future Enterprise”, the gold standard that reflects organizationwide digital dexterity, rapid innovation, greater risk-taking ability, effective use of technology and data, and a customer-centric mindset.

Four Steps in the Road to Recovery

Adopt a holistic view and identify the association of different initiatives. This provides a clear guidance on the overall objectives and view of the complexity and dynamics across people, processes, and technology journey.

Establish a clear data strategy and process of integration for internal and external data points to gain insights toward the overall landscape and identify opportunities and areas for optimization.

Develop a plan to allow continuous innovation across IT/OT and integrated across platforms of IIoT/AIoT, cloud, and AI. This allows a steady stream of development and road map for products and services.

Identify quick win use cases and technology that can assist in solving problems and scale the implementation accordingly. The technology must be able to integrate and build on existing technology investments.

Consider a holistic approach

Streamline and prioritize internal and external data points

Create a strategic plan for innovation

Identify and apply a technology layering investment approach

of APEJ manufacturers say their use of data/analytics/AI/ML will be central to better adjustments to drastic changes as a permanent change post–COVID-192

Source: 1IDC COVID-19 Journey to the Next Normal 2COVID-19 Impact on IT Spending Survey, Wave 6, IDC, June 2020, APEJ n = 65

Copyright 2020 IDC. Reproduction without written permission is forbidden. This IDC InfoBrief was produced by IDC Asia/Pacific Custom Solutions. The opinion, analysis, and research results presented herein are drawn from more detailed research and analysis independently conducted and published by IDC. Any information or reference to IDC that is to be used in advertising, press releases, or promotional materials requires prior written approval. For more information, visit: www.ap.idc.asia or email: ap_permissions@idc.com.

An IDC InfoBrief | Leading a Data-Led Recovery: Building Resiliency in Manufacturing with AI and Streaming Analytics

The Five Stages to Enterprise Recovery1

Cloud-Based Analytics

Digital Twin (Enabled by IoT/

BDA/AI)

Remote Connectivity and

Monitoring

Cognitive Planning

Shopfloor, Transportation Optimization

As a Global Leader in Analytics, SAS® Helps Thousands of Manufacturers Move from a Reactive to a Proactive Approach

Message from the Sponsor

AI & Machine Learning for Everyone

SAS CloudArtificial Intelligence of Things

Seamless Deployment and Governance

Industry and Domain Expertise

Enable self-service data and analytics throughout the enterprise

Democratize AI development across data scientists, engineers, and business users

AI-driven intelligent decisioning off real-time IoT data streams

Drive new levels of operational excellence and transform product and service models

Deploy across multi-vendor, public, private, hybrid cloud, or on premises

Software, infrastructure, and services designed and managed by SAS for optimal performance and value

Qualify and deploy models across edge, cloud, and datacenter

Monitor and govern model performance and deployment centrally

Over 2,000 manufacturing customers in more than 52 countries rely on SAS

Analysts consistently rank SAS analytics as a market leader

As a global leader in analytics, SAS helps thousands of manufacturers move from a reactive to a proactive approach, using AI and machine learning to confidently detect, resolve, predict, and prevent quality and reliability issues, forecast demand while dynamically optimizing production and supply chains, and driving innovative digital services and revenues. Whether your data is streaming in from the edge in your operations, in a historian or MES system, in the cloud, or in your data center, SAS helps you sense important signals, understand what they mean, and act in real time.

About SASSAS is a leader in analytics. Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS gives you THE POWER TO KNOW®. www.sas.com