Introduction
In today’s rapidly evolving business landscape, digital transformation is not a luxury but a necessity. Organizations across industries—energy, manufacturing, consumer packaged goods, process industries, and defence—must evaluate their digital capabilities to remain competitive. A Digital Maturity Model (DMM) provides a structured framework to assess an organization’s readiness across key verticals such as engineering, manufacturing, procurement, logistics, supply chain, and after-sales services. By understanding their current state, businesses can identify gaps, prioritize investments, and develop a roadmap for sustained digital evolution.
For any firm embarking on a digital transformation journey, the first step is to establish a clear understanding of its current (as-is) state and define its future (to-be) vision. A Digital Maturity Model serves as a structured tool to navigate this process, offering a comprehensive assessment of an organization’s digital capabilities. It enables firms to systematically evaluate their strengths and weaknesses, helping them set realistic and achievable transformation goals.
A well-structured maturity assessment not only shapes an organization’s strategy, vision, and transformation roadmap but also highlights critical focus areas versus those that can be gradually improved. By leveraging these insights, companies can align investments with business priorities, ensuring optimal resource allocation. For executives and board members, this model provides clarity on where to allocate funding, ensuring that every dollar spent delivers maximum value and long-term business impact.
Understanding Digital Maturity Models
A Digital Maturity Model evaluates an organization’s capability to leverage digital technologies to drive efficiency, innovation, and resilience. The assessment typically covers five stages of maturity:
- Ad Hoc – Fragmented digital adoption with minimal integration.
- Emerging – Initial efforts to digitize core operations but lacking strategic alignment.
- Defined – Digital initiatives are structured with clear objectives but are not yet enterprise-wide.
- Integrated – Cross-functional digital strategies are implemented with measurable outcomes.
- Optimized – A fully digital organization with continuous improvement and data-driven decision-making.
Steps for evaluating the DMM for the business
A maturity assessment is essential for organizations to benchmark their digital capabilities, identify gaps, and prioritize investments for transformation. It provides a clear, data-driven roadmap that aligns business strategy with technological advancement, ensuring sustainable growth and competitive advantage. By assessing maturity levels, companies can make informed decisions, optimize resources, and drive long-term innovation.
Key Verticals for Digital Maturity Assessment
A maturity assessment can be conducted at multiple levels—either at the company or business unit level or within a specific function of the organization. At the broader level, organizations assess how different business units compare in their digital maturity, providing leadership with a high-level overview of performance across key domains. This helps in identifying which areas require strategic focus and investment to drive transformation.
When evaluating a specific function, such as engineering, the assessment must cover multiple subdomains, including design, release management, change management, and requirements tracking. This granular approach allows firms to pinpoint strengths and weaknesses within a particular function and align digital transformation efforts accordingly. A well-structured assessment provides insight into operational efficiencies, gaps, and opportunities for targeted improvement.
For leadership teams and decision-makers, a holistic maturity assessment spanning functions like engineering, manufacturing, and logistics enables informed decision-making and resource allocation. In this discussion, we will focus on five critical areas of digital maturity, using the aerospace industry as a case study to illustrate how companies can benchmark their capabilities and establish a structured roadmap for transformation.
Engineering
A mature engineering function integrates digital design tools, real-time simulations, and collaborative platforms. Organizations should assess their adoption of:
- Product Lifecycle Management (PLM) systems.
- Digital twin and simulation models.
- AI-driven generative design.
- Seamless integration between design and manufacturing.
Example
Airbus has achieved high digital maturity in engineering by implementing digital twin technology to simulate aircraft performance and optimize design before physical prototyping. This reduces errors, accelerates development, and enhances product reliability.
Manufacturing
Digital maturity in manufacturing ensures agile, efficient, and data-driven operations. Companies should evaluate:
- Smart factories with IoT-enabled equipment.
- Advanced Manufacturing Execution Systems (MES).
- Robotics and automation capabilities.
- Predictive maintenance and AI-driven optimization.
Example
BMW has successfully deployed Industry 4.0 principles by leveraging AI, robotics, and IoT in its production lines. The company’s smart factories optimize production efficiency, reduce downtime, and enable flexible manufacturing.
Procurement
A digitally mature procurement function leverages AI, automation, and supplier collaboration platforms. Key assessment areas include:
- E-sourcing and contract management tools.
- Predictive analytics for supplier risk assessment.
- Blockchain for procurement transparency.
- Real-time spending analytics.
Example
Boeing has transformed its procurement process by adopting blockchain technology for secure, transparent transactions and using AI for supplier risk assessment, ensuring a resilient and efficient supply chain.
Logistics & Supply Chain
A resilient supply chain integrates end-to-end digital tracking, real-time analytics, and AI-driven demand forecasting. Businesses should assess:
- End-to-end supply chain visibility.
- IoT for real-time shipment tracking.
- AI-driven inventory optimization.
- Cloud-based logistics platforms.
Example
Amazon has set the benchmark for digital maturity in supply chain and logistics with AI-powered demand forecasting, drone delivery pilots, and real-time shipment tracking using IoT sensors to enhance efficiency and customer satisfaction.
After-Sales & Customer Services
A digital-first approach to after-sales services enhances customer satisfaction and operational efficiency. Assessment areas include:
- Predictive maintenance powered by IoT.
- AI-driven customer service chatbots.
- Augmented Reality (AR) for remote troubleshooting.
- Self-service digital platforms for customer engagement.
Example
Rolls-Royce has pioneered digital maturity in after-sales services through its “TotalCare” program, which uses IoT-powered predictive maintenance to monitor aircraft engine performance in real-time, reducing unplanned downtime and improving customer service.
Sample Digital Maturity Assessment for Aerospace vertical
An example Digital Maturity Assessment Model tailored to the Aerospace Industry, with clear low, medium, and high maturity definitions for each domain:
| Verticals | Low Maturity (Legacy & Fragmented) | Medium Maturity (Digitally Transitioning) | High Maturity (Optimized & Data-Driven) |
| Engineering (R&D, Design & Development) | 2D drawings, manual handovers, siloed CAD tools | PLM adoption, basic digital thread integration, limited simulation | End-to-end digital thread, AI-driven generative design, real-time global collaboration |
| Manufacturing (Production & Assembly) | Paper-based work instructions, manual tracking, reactive maintenance | MES adoption, IoT-enabled monitoring, early-stage automation | Smart factory with IIoT, AI-driven predictive analytics, autonomous quality control |
| Procurement (Sourcing & Supplier Management) | Reactive sourcing, no supplier visibility, cost-driven decision-making | Supplier portals, early-stage analytics, risk assessments | AI-driven procurement, predictive supplier performance analytics, blockchain traceability |
| Logistics (Material Flow & Distribution) | Manual inventory tracking, fragmented logistics, high lead times | ERP-enabled material tracking, RFID/barcode adoption, route optimization | AI-powered logistics, real-time tracking, digital twin-enabled predictive logistics |
| Supply Chain (End-to-End Value Chain) | Limited integration, high cycle times, reactive issue resolution | ERP-driven, demand forecasting, limited digital collaboration | AI-powered supply chain orchestration, real-time adaptability, ecosystem-wide visibility |
| After Sales (MRO & Customer Support) | Reactive maintenance, minimal predictive insights, paper-based documentation | Digital customer portals, IoT-enabled maintenance tracking, some predictive analytics | AI-driven MRO, predictive maintenance with digital twins, omnichannel customer support |
This model provides a structured way to assess an organization’s digital maturity across critical business functions. This model should then be adopted refined and updated for specific needs of an organisation
Conclusion
Assessing digital maturity is not a one-time initiative but a continuous journey that enables organizations to stay ahead in an ever-evolving digital landscape. By leveraging a structured Digital Maturity Model, businesses gain a clear understanding of their strengths, weaknesses, and opportunities across critical functions such as engineering, manufacturing, procurement, logistics, and after-sales services. This holistic view allows companies to identify areas requiring investment, streamline operations, and align their transformation strategies with long-term business objectives. Organizations that proactively assess and improve their digital maturity are better positioned to drive operational efficiencies, enhance agility, and maintain a competitive edge.
To remain resilient and future-ready, companies must treat digital maturity as an ongoing strategic priority rather than a one-time assessment. Executives should take action by initiating a comprehensive maturity assessment, engaging key stakeholders, and developing a roadmap for sustainable transformation. Whether you are just starting your digital journey or looking to optimize existing processes, now is the time to evaluate your maturity and build a strong foundation for future growth. Take the first step today—assess your digital readiness and unlock new opportunities for innovation and success.
Appendix – Reference Clients
| Vertical | Company Example | Reference Link |
| Engineering | Airbus (Digital Twin Implementation) | Airbus Digital Twin |
| Manufacturing | BMW (Industry 4.0 Smart Factories) | BMW Smart Manufacturing |
| Procurement | Boeing (Blockchain & AI for Procurement) | Boeing Digital Procurement |
| Logistics & Supply Chain | Amazon (AI-powered Logistics & IoT Tracking) | Amazon Logistics Innovation |
| After-Sales & Customer Service | Rolls-Royce (IoT & Predictive Maintenance) | Rolls-Royce TotalCare |
What is a Digital Maturity Model, and why is it important?
A Digital Maturity Model (DMM) is a structured framework that helps organizations assess their current digital capabilities and identify areas for improvement. It is crucial because it provides a clear roadmap for digital transformation, aligning technology investments with business goals and ensuring long-term competitiveness in industries like aerospace, manufacturing, and logistics.
How can businesses assess their digital maturity effectively?
Businesses can assess their digital maturity by following a structured process that includes defining objectives, engaging stakeholders, collecting data, benchmarking against industry standards, and developing a roadmap for transformation. Using a Digital Maturity Model, organizations can systematically evaluate key functions such as engineering, procurement, and supply chain to prioritize investments and drive operational efficiency.
