The Five Levels of Digital Maturity in Global Manufacturing

A recent industry survey conducted by Supplyframe has revealed that global manufacturing remains largely behind on its path to digital maturity. The results have been mapped to a new 5-level maturity model. The average score across industries is level 2-of-5, illustrating a significant opportunity for digital transformation. 

Join us as we explore the various sections and levels of the new Supplyframe Digital Maturity Model, outlining the steps that today’s enterprises can take to accelerate their transformation and reach the highest levels of digital maturity. Click below to take our new self-assessment and discover how your organization compares to the rest of the industry!  

How Maturity Models Help Organizations Transform 

In recent years, the global manufacturing and supply chain landscape has faced near-constant disruption and elevated risk. From the Covid pandemic to chip shortages, rising geopolitical tensions, increasing product complexity, and climate change, no industry has been spared the pressures the modern world is experiencing today.

Maturity models are helpful because they enable companies to benchmark and assess strategic planning and roadmaps that provide a holistic view of the company’s digital transformation. The models also identify risks and vulnerabilities and help staff optimize resources by focusing on the most impactful investments of time and energy. The model bridges the gap between functional changes and a cultural shift that will herald a true digital transformation. 

Even though some of these factors have stabilized, many organizations are still stuck in firefighting mode, where they remain at risk from the next major disruption. Recognizing the need for change, investments in digital transformation are rising, with worldwide spending projected to reach $3.6 trillion by 2026. 

This article reviews the current state of the electronics industry and the path to digital maturity. To capture the scope of digital maturity and create a path forward for global manufacturing, Supplyframe created five categories for the Design-to-Source Maturity Model that maps survey results to a five-level scale:

The Design-to-Source Maturity Model

The results of a new industry survey have been mapped to a Design-to-Source Maturity Model that shows how global manufacturing organizations can accelerate their transformation. This model is organized into several sections of assessment: 

1. Organizational Structure – examines the level of collaboration across teams and the scope of alignment between them.

2. People and Talent – identifies capabilities, talent, and skills combined with teams’ influence in design, sourcing, and supply chain departments.

3. Design for Supply Chain: Assesses overall sourcing strategies, team goals, frequency of sourcing events, and the presence of a “shift left” approach.

4. Technology and Systems – focuses on solutions, data management, system integration, automation, and sources of insight for engineering and supply chain.

5. Analytics and Performance: This category measures key performance indicators, responsiveness, and the capability to identify critical events or disruptions proactively.

The Five Levels of Digital Maturity 

Within each of the aforementioned categories are five potential maturity levels. According to our survey results, the overall global manufacturing industry scored level 2-of-5. These are the descriptions of each level: 

Stage 1: Reactive 

This is where the journey begins for organizations beginning their digital transformation. Two essential focus areas are collaboration and trust in data. 

Organizations in the early stages tend to operate data silos, which limit collaboration with other organizations. Data sharing tends to be low, the impact small, and sometimes unreliable for the organization to rely on for decision-making.

Each department in the organization operates with its own set of digital tools. For example, marketing produces content, sales sells the prospects, and accounting calculates the cost. Data is transferred from one department to another, making coordinating inter-departmental processes difficult.

Stage 2: Opportunistic 

At this stage, decision-makers understand the need for collaboration between departments. They support data sharing, cross-organizational communication, and the automation of repeatable processes. Staff are willing to embrace innovative technologies within business operations and learn how to use data to influence strategic planning.

For example, a company integrates automation and advanced tools, which enables the business intelligence team to send data to the marketing team, which uses it to create content and campaigns. Lead information is automatically sent to the sales team, and accounts receivable use data from the same platform.

However, some things will fall through the cracks because touchpoint processes cause resistance. The company may have connected data points but still cannot identify the root causes of errors. More work is done, but it is not accurate.

Stage 3: Integrated

Here, all departments are digitally connected. The company can link business objectives to results with data-driven business processes and interconnected datasets. Data becomes the foundation of the business and is easily accessed by departments. It influences business decisions across the organization’s processes and functions. 

The increasing dependence on data enables project teams that comprise members from various departments. The company can measure results based on KPIs and metrics. Teams achieve data-driven goals through collaboration. At this point, the company can create a digital model based on opportunities instead of challenges.

Stage 4: Optimized  

The organization has advanced to a collaborative design. Procurement is included in the product development, regular sourcing, and commodity reviews. The team produces real-time intelligence and insights and has a strategic sourcing platform. 

Stage 5: Predictive 

This is the highest and final stage of the digital transformation maturity model. It is a theoretical state that envisions an enterprise where cross-functional insights, predictive intelligence, and streamlined processes are the norm. The organization continuously monitors and analyzes data to identify opportunities to enhance the effectiveness of its digital transformation. Digital technologies and capabilities keep evolving. 

At this point, cross-functional workflows and teams have replaced the traditional departmental structure. Each touchpoint is measured, and processes are analyzed to track results. The company uses a digital maturity model to identify opportunities based on data.

Measuring the Organization’s Level of Digital Maturity

Measuring the company’s digital maturity establishes the foundation of digital transformation. Knowing where you are makes it easier to plan where you want to go, how you will get there, and how long it will take to reach your destination. Here is a list of steps to take:

• Have a digital transformation strategy in place
• Make sure the strategy has buy-in from management
• Your decisions should be based on insights from facts
• Your organization has made decisions based on data
• You have the right technology and capabilities
• Create seamless, personalized experiences for the customer
• The digital experience across different channels should be consistent
• Have a plan for your digital transformation 
• Measure the success of your digital transformation

What is the right digital transformation platform

The first step to succeed in the digital-first economy is to begin the journey toward digital maturity. A digital maturity model is an effective tool that provides guidelines for a smooth digital transformation journey. 

With the right tools, you can digitize your organization’s internal processes, boost collaboration, and increase efficiency. Download Supplyframe’s Digital Maturity Model report today to learn more!