Digital Transformation Chapter 3 – FAQ

Introduction

The scope of digital transformation is vast — from retail and finance to manufacturing, every industry faces unique applications and challenges.
In this chapter, we focus specifically on manufacturing, exploring how digital transformation enhances process efficiency, operational performance, and intelligent decision-making.

However, the abundance of information, diverse viewpoints, and limited time of managers and on-site personnel often make it difficult to quickly grasp the key points.
That’s why we’ve prepared a clear and concise Frequently Asked Questions (FAQ) guide.

Through answers to the most common questions, we help you clarify the core concepts and practical benefits of digital transformation.
By the end, you’ll not only understand its true value for manufacturers, but also gain sharper insight into your own company’s needs and direction.

And when you’re ready to take the next step, we’ll be here to discuss, align, and help you find the most suitable solution for your transformation journey.

Digital Transformation (DX) is the process by which enterprises leverage data and technology to redesign workflows and decision-making, enabling greater agility and competitiveness.
It is built upon five core elements:

• Data-Driven Decisions

Transforming data into actionable insights, rather than relying solely on experience or intuition.

• Process Redesign

Going beyond simply digitizing workflows — redefining processes to achieve efficiency, transparency, and scalability.

• Cross-Department Integration

Connecting systems across R&D, production, finance, and supply chain to eliminate information silos.

• Intelligent Applications

Applying technologies such as AI, IoT, and cloud platforms to enhance prediction, optimization, and real-time responsiveness.

• Continuous Improvement Culture

Cultivating a data-driven decision-making mindset that enables organizations to adapt quickly and continuously evolve.

At its core, digital transformation is about using data and technology to drive cultural and process change, aligning with organizational strengths.
Only when these foundations are in place can new tools truly take root — enabling transformation that delivers lasting competitive advantage.

Although digitization, digitalization, and digital transformation are closely related, they represent different levels of maturity.
Digitization and digitalization form the foundation of digital transformation — they optimize traditional manual processes through technology, paving the way for the next stage of strategic evolution.

True transformation, however, involves a fundamental shift in organizational models, typically progressing through three key stages:

• Digitization

The conversion of traditional, physical information into digital formats using technology — for example, scanning paper forms into searchable electronic files or collecting machine data through sensors.

• Digital Optimization (Digitalization / IT Modernization)

The introduction of information systems to improve efficiency, such as ERP, MES, or CRM, enabling process automation and stronger internal coordination.

• Digital Transformation (DX)

A broader and more strategic transformation — redesigning processes, restructuring organizations, and innovating business models through data-driven decision-making, fundamentally changing how companies operate and deliver value.

In simple terms:

• Digitization turns information into 0s and 1s.

   

• Digitalization integrates systems into daily operations.

   

• Digital Transformation uses data and technology to drive enterprise-wide evolution.
  

The three stages complement one another, but only transformation creates a lasting competitive advantage.

With challenges such as labor shortages, supply chain disruptions, and the global drive toward net-zero carbon emissions, manufacturers worldwide are under increasing pressure to adapt.
These challenges accelerate the need for digital transformation to remain competitive in a fast-changing, cost-sensitive market.

Common Pain Points in Manufacturing

• Data Silos

Production data is scattered across machines, spreadsheets, and paper records — lacking integration and real-time visibility.

• Manual Errors

Scheduling, reporting, and tracking rely heavily on manual input, which is error-prone and inefficient.

• Poor Cost Visibility

Hidden wastes are difficult to identify, making it hard for managers to assess cost structures in real time.

• Market Volatility

Shorter lead times and growing demand for customization expose the inflexibility of traditional processes.

• Training Challenges

Experienced workers’ knowledge is difficult to capture, while new hires struggle to learn quickly and adapt.

• Collaboration Bottlenecks

Lack of transparency between R&D, production, finance, and sales leads to inconsistent and delayed decision-making.

Digital transformation strengthens industrial competitiveness by integrating data, optimizing processes, and enabling intelligent collaboration.
It ensures that manufacturers can maintain efficiency, quality, and agility — even amid market uncertainty.

The first step of digital transformation is to evaluate your digital maturity.
This assessment is essential for understanding where your company currently stands — in terms of data, processes, systems, and culture — and for identifying gaps before planning the right next step.

Key Dimensions of Digital Maturity

• Data Management

Evaluate whether your data is complete, traceable, and available in real time, or if it still relies on manual entry and fragmented records.

• Level of Digitalization

Determine whether daily workflows have been digitized or automated, or if they still depend primarily on paper-based communication and manual processes.

• System Integration

Assess whether your departmental systems are interconnected or operate independently, creating information silos.

• Digital Mindset and Literacy

Gauge the organization’s openness to data-driven decision-making and adoption of new tools.
Do employees possess digital skills and a willingness to learn?

• Strategic Objectives

Check whether the company has a clear digital transformation vision and measurable KPIs, rather than simply pursuing “system implementation.”

Identifying the right starting point begins with understanding pain points and applying incremental improvements.
Instead of striving for perfection from day one, focus on ensuring that each phase delivers tangible transformation results — enabling steady progress toward higher digital maturity.

What defines success in digital transformation?
We measure it by ROI and the achievement of expected goals.
According to research by BCG, only 30% of enterprises reach their transformation objectives — because success depends not only on technology, but more importantly, on the following factors:

• Executive Commitment and Determination

As the saying goes, “What leaders care about becomes what the company cares about.”
Leaders must act as transformation ambassadors — not only delegating authority, but also demonstrating visible commitment and active support for the initiative.

• Clear Vision and Goals

A clear objective defines the path forward. Transformation cannot remain a slogan; it must include concrete KPIs and a realistic roadmap aligned with business priorities.

• Cross-Department Collaboration

Successful integration of IT and OT requires close cooperation across departments to prevent the formation of information silos.

• Strong Data Governance

Transformation depends on complete, accurate, and traceable data — the foundation for effective analysis and decision-making.

• Talent Development and Culture

Since most people prefer familiar routines, investing in training and a culture open to experimentation reduces resistance and increases system adoption.

• Incremental Implementation

Adopt a “Pilot First, Scale Later” approach — start by addressing one key pain point, validate results, and expand gradually to minimize risks.

• Performance Tracking and Continuous Improvement

Digital transformation is not a one-time project but a continuous optimization journey.
Tracking outcomes with data ensures progress stays on the right path and aligned with business goals.

Digital transformation is a long-term journey, not a one-off initiative.
Only by combining leadership commitment, data foundations, and organizational culture can companies truly align their strategy, implement transformation effectively, and build sustainable competitive advantage in a rapidly changing market.

6. How to Evaluate the Cost and ROI of Digital Transformation

Digital transformation is not merely about implementing systems — it’s about aligning investments with ROI (Return on Investment) and assessing their tangible and long-term impact.
Evaluation should cover efficiency gains, cost reduction, and sustainable competitiveness, taking into account both direct and indirect costs such as systems, hardware, training, and organizational change.

• Direct Costs

Include expenses related to system implementation (e.g., MES, APS, IoT platforms), hardware integration, and consulting services for deployment and configuration.

• Indirect Costs

Refer to the training and workflow adjustments required during transformation. These changes may temporarily affect production efficiency or cause minor operational disruptions.

• ROI Evaluation Dimensions

Assess whether digital transformation leads to improvements in efficiency, cost reduction, quality, and revenue growth.
Both short-term and long-term outcomes should be measured, focusing on how digital assets enhance resilience and competitive advantage.

• Measurement Approach

At the early stage of implementation, establish shared goals and KPIs, and define baseline metrics for ongoing tracking.
We recommend evaluating performance over a 1–3 year period, rather than chasing short-term results.

The ROI of digital transformation should not be judged solely by financial figures.
True value lies in whether these changes make the organization more adaptive, stable, and growth-oriented amid market fluctuations — that is the core return on investment.

7. How to Manage Cybersecurity Risks in IT/OT Integration

Integrating Information Technology (IT) and Operational Technology (OT) can greatly improve efficiency, but it also introduces new cybersecurity risks.
Through layered network management, continuous monitoring, and employee training, manufacturers can strengthen resilience and minimize vulnerabilities.

Key Risk Management Checklist

• Strategic Planning

Incorporate cybersecurity into core business objectives and follow international standards such as ISO 27001, IEC 62443, and NIST CSF.
Conduct regular audits to ensure compliance and continuous improvement.

• Network Segmentation

Whether on-premises or in the cloud, establish clear firewalls and access control boundaries between production systems (OT) and enterprise information systems (IT) to reduce the risk of lateral attacks.

• Access Management

Adopt systems with robust risk management and identity control, enforce the principle of least privilege, track account activity, and implement multi-factor authentication (MFA) for added protection.

• Real-Time Monitoring

Deploy Intrusion Detection Systems (IDS), define standard operating procedures (SOPs), and maintain log monitoring to detect and respond immediately to suspicious activities.

• Vulnerability Management

Perform regular updates across IT/OT systems, continuously monitor for weaknesses, and address them through proactive patching and improvement.

• Employee Training

Provide periodic cybersecurity training to raise awareness among both operations and IT teams — covering common threats such as phishing emails and infected USB devices.

Cybersecurity risk management requires long-term commitment.
By combining layered architecture, technical safeguards, and personnel management, manufacturers can minimize potential impacts.
To ensure safe IT/OT integration, organizations must manage security from three dimensions: strategy, technology, and organizational processes.

8. How Can Legacy Equipment Be Integrated with New Systems?

Most factories already operate with legacy machines and infrastructure, and replacing them entirely would be costly and disruptive.
Instead, manufacturers can achieve integration through data acquisition, system bridging, and phased implementation—allowing old and new systems to coexist effectively.

Integration Methods

• Data Acquisition Modules

Use sensors or IoT gateways to capture operational data (such as output and utilization rates) from legacy machines, converting it into a format compatible with modern systems.

• Protocol Conversion

Adopt middleware technologies such as OPC UA or MQTT to enable communication between heterogeneous equipment through standardized protocols.

• Phased Implementation

Start with digitalizing critical production lines or bottleneck equipment, then expand gradually across the factory to avoid excessive upfront costs from one-time integration.

• Hybrid Architecture

Retain essential functions from legacy machines while enabling data exchange with new systems, reducing complexity and risk during modernization.

• Project Management

Adopt a dual-track approach combining short-term improvements with long-term upgrades, balancing immediate impact with future scalability.

Integrating legacy equipment with new systems is not merely about hardware replacement — it’s about adding value and extending asset lifespan.
This approach preserves prior investments while ensuring that digital transformation remains practical, cost-effective, and sustainable on the path toward smart manufacturing.

9. Which Digital Technologies Are Most Suitable for Manufacturing?

For the manufacturing industry, digital technologies enhance data transparency, process optimization, and intelligent decision-making.
From automation to smart manufacturing, different stages of transformation require different technologies.
Below is a list of the most commonly applied tools and systems:

• MES (Manufacturing Execution System)

Bridges the gap between production lines and management. Tracks operations across man, machine, material, method, and environment, enabling transparent management of work orders, progress, and quality.

• APS (Advanced Planning and Scheduling)

Responds to rapid market changes by optimizing production schedules based on capacity, demand, materials, and delivery dates, reducing bottlenecks and delays.

• IoT (Internet of Things)

Connects equipment through sensors and networks to enable real-time data collection, monitoring, and analysis of machine performance.

• AI and Machine Learning

Applied to demand forecasting, predictive maintenance, and quality inspection, helping manufacturers make smarter and more accurate decisions.

• FWR (Data Analytics and Business Intelligence)

Integrates cross-departmental data into visualized dashboards, allowing management to identify issues and take timely action.

• Cloud Platforms

Reduce infrastructure costs and support real-time collaboration across sites and departments.

For manufacturers, digital technologies are tools — not the destination.
The recommended approach is to select technologies based on business pain points:
start by collecting data through IoT, then connect processes with MES/APS, and finally enhance decision-making with AI and analytics.
This step-by-step strategy builds a sustainable, data-driven smart manufacturing ecosystem.

10. How to Choose the Right Digital Transformation Consultant or Service Provider

The key to selecting a digital transformation partner lies in their ability to understand industry characteristics and domain knowledge, and to ensure that proposed solutions are both practical and implementable.
In this process, products, presales, and consultants each play a vital role in driving organizational change.

Key Evaluation Criteria

• Industry Experience

Assess whether the consultant truly understands the manufacturing ecosystem — can they identify factory workflows and pain points, rather than offering surface-level advice?

• Proven Success Stories

Review whether the service provider has successful implementations in similar industries or scales, and whether they can present measurable outcomes and benefits.

• Technical Capability

Since transformation involves systems such as MES, APS, IoT, and AI, the provider should have strong integration expertise and the ability to connect with existing equipment and systems.

• Methodology

Different industries and company sizes require different approaches. The provider must offer customized methodologies that fit actual needs — not just sell software.

• Local Support

Check if they have a local team capable of providing timely on-site assistance, rather than relying solely on remote support.

• Long-Term Partnership

Digital transformation is a continuous journey, not a one-off project. Providers should offer maintenance, training, and upgrade recommendations to support sustainable progress.

• Cultural Alignment

A good consultant listens, understands your organizational culture, and builds mutual trust and collaboration with your internal team.

A truly effective service provider is not just a system vendor —
but a strategic partner who grows alongside your business.
The right team should be able to understand your industry, solve your pain points, and support your evolution through close collaboration among R&D, presales, and consulting teams, ensuring that digital transformation takes root and continues to create lasting value.

11. Implementation Process and Timeline for Digital Transformation Projects

In manufacturing, digital transformation projects typically follow four key phases — Diagnosis, Planning, Implementation, and Optimization.
However, the actual process and timeline will depend on the company’s size, complexity, and transformation goals.

• Preliminary Diagnosis

Evaluate current processes, systems, and pain points.
Assess the organization’s digital maturity and establish a unified transformation vision and objectives among key stakeholders.
Estimated duration: 1–2 months.

• Strategy and Blueprint Planning

Based on the current state and desired goals, develop a digital transformation roadmap and define short-, medium-, and long-term KPIs.
Select the appropriate technologies, platforms, and service partners for implementation.
Estimated duration: 2–3 months.

• System Implementation and Pilot Testing

Begin with a pilot line or department, implementing systems and integrating equipment on a smaller scale.
Refine processes, train personnel, and validate outcomes before scaling further.
Estimated duration: 3–6 months.

• Expansion and Optimization

If the pilot demonstrates positive results, gradually expand to other departments or the entire plant.
Use real-time data tracking to review performance and continuously optimize processes and technologies.
Estimated duration: 6 months or longer.

Based on our project experience,

• SMEs (small and medium-sized enterprises) typically require 12–18 months from diagnosis to full implementation.
  
• Large enterprises may take 2–3 years or more.

The key to success lies not in speed, but in steady execution and iterative improvement — creating a continuous cycle of progress and value realization.

We hope these FAQs have provided you with an initial direction.
However, every manufacturing company is different — varying in production models, scale, customer demands, and market pressures — all of which influence your digital transformation objectives.

That’s why the above information serves only as general guidance.
We recommend scheduling a visit from our presales team, who can work with you onsite to map out your processes, identify pain points, and set clear transformation goals based on an informed assessment.

If you’re still exploring or gathering information,
we also invite you to join our official Facebook community,
where we regularly share first-hand industry insights, success stories, and transformation trends — helping you stay up to date with digital best practices and connect with us when the time is right.