Digitizing Materials Management: Your Guide to Building a Connected Lifecycle

In this video, you’ll learn how ReVisionz approaches materials management as a dynamic, end-to-end process that drives efficiency across digital projects and operations.

From material master definition through procurement, construction and ongoing maintenance, the video walks through each stage of the materials management lifecycle and how it supports seamless supply chain execution. You’ll see how technology enablement, data quality and predictive analytics enhance digital operations, and how aligning digital projects with operational goals leads to measurable results across the asset lifecycle.

Then & Now

When I began my work in the process industries thirty years ago, asset data was commonly siloed and required time-consuming and meticulous manual entry by multiple stakeholders. Project schedules were built around this reality, accommodating the delays and complexities of manual data capture.

Today, however, project schedules tend to assume streamlined processes and efficient data management, which is not always the case. While tools and systems have evolved, the underlying challenges of data consistency and information flow are persistent.

The Push Toward Digitization

In recent years, there has been a strong push towards digitization, especially within industrial sectors. But digitization is more than simply working in Excel files with VB macros or enabling collaborative work in the cloud. It involves a more in-depth process of contextualizing information and connecting it across systems. This is essential for utilizing AI effectively and obtaining accurate results, as well as enabling real-time KPIs and reporting.

As organizations have advanced their digital capabilities, the need for structure and consistency in how data is managed has become increasingly clear. Practices such as data governance are now more mainstream, driven by the creation and adoption of international standards such as CFIHOS (Capital Facilities Information Handover Specification) and ISO 15926. Additionally, governance standards like the Petroleum Industry Data Exchange (PIDX) and vendor-specific standardizations have also gained traction. These advancements have laid the groundwork for a more agile project execution model.

The Case for Trusted Data

To achieve a fast and agile project start, organizations should have access to a repository of validated and approved data. Reusing trusted information across the enterprise rather than within a single office reduces redundancy, improves quality and accelerates smart decision-making.

This vetted data should be streamlined into a standardized integration map tailored to an organization’s needs. Prioritizing integration allows systems and tools such as design platforms, Enterprise Resource Planning (ERP) systems and maintenance applications to exchange information seamlessly and report changes that require action. One of the most critical areas where trusted, integrated data has a direct impact is the materials management lifecycle, which enables continuous alignment between digital projects and digital operations for consistency and efficiency across every stage of the asset lifecycle.

The process begins with the definition of Material Masters and their alignment with enterprise asset management systems. This foundational step enables data that is accurate and actionable from the outset. Reference and design data are then captured and integrated into design tools, which transforms raw information into precise material requirements.

These early activities form the backbone of a well-orchestrated supply chain. From procurement to warehouse management and workface planning, each stage supports timely execution, prevents bottlenecks and helps maintain control throughout the project.

Materials management is a continuous process that extends into operations and supports long-term performance. Organizations that view it as a dynamic, evolving cycle are better positioned to optimize asset reliability and lifecycle value.

Legacy Barriers to Efficiency

In industrial facilities, Material Masters used in CAPEX with a focus on bulk components and tags frequently differ from those developed in the operations phase. This misalignment exacerbates inefficiencies and sometimes causes duplication or misidentification of materials.

Commodity definitions are often seen as company-specific intellectual property, leading to more time spent on definition, system setup, data management and governance. Instead of building on existing standards, organizations spend valuable time reinventing the wheel.

Historically, standardization was primarily applied in manufacturing hubs such as the automotive industry, where repeatable parts, assemblies and finished products were expected. It was perceived as more suitable for specialized industries rather than the norm. As a result, standardization was seen as more appropriate for specialized sectors rather than broadly applicable across capital projects.

This becomes especially problematic after project turnover, when materials management continues to play a critical role in supporting long-term operations, sustaining capital projects and managing planned shutdowns and turnarounds. Effective material master data handover is essential to preserve critical data and to enhance it for use in ongoing operations.

At this stage, the focus shifts toward spare parts acquisition, inventory optimization and the efficient movement of materials through warehouses and supply chains, all of which directly support maintenance planning and reliability.

Modern technologies like RFID, real-time location tracking and operational software improve visibility and streamline execution. Meanwhile, data quality monitoring fosters reliable information and advanced analytics help translate raw data into predictive insights.

These tools both enhance visibility and provide the insights needed to anticipate material needs, reduce downtime and support proactive maintenance. This level of operational intelligence transforms materials management from a back-office function into a driver of reliability and performance.

Why the Industry Needs Disruption

For years, materials management has been limited by fragmented systems, manual processes and disconnected workflows. Despite advancements in technology, many organizations continue to rely on outdated practices that hinder efficiency and visibility.

For years, materials management has been limited by fragmented systems, manual processes and disconnected workflows. Despite advancements in technology, many organizations continue to rely on outdated practices that hinder efficiency and visibility.

This is typically not due to a lack of tools or poor process design, but the natural tendency of teams to revert to familiar habits and legacy ways of working. In fact, the biggest obstacle after committing to digital transformation is not technology, it’s the people’s resistance to change. Fear of disruption and reliance on old methods can quietly stall even the strongest digital strategies.

But here’s the truth. Disruption is exactly what we need. Progress depends on intentional, coordinated change.

Replacing reactive workarounds with integrated, data-driven strategies improves accuracy and streamlines execution across the asset lifecycle. With modern tools, standards and analytics, materials management can become a continuous, scalable process that supports both project delivery and long-term operations.

There hasn’t been a better time to move beyond the status quo and realize the full value of a connected materials management approach. That’s why ReVisionz works with organizations to break through the common barriers that hold materials management back.

By aligning governance, integration and data structures from project to operations, we help teams move faster with fewer disruptions. Our approach reduces the friction caused by disconnected systems and supports a more reliable, data-driven foundation for maintenance, planning and long-term performance.

A successful materials management strategy begins with how materials are defined. Whether you’re planning a capital project or operating a facility for decades to come, material master definition is the starting point. It establishes the structure for everything that follows, from requirements gathering to procurement, logistics, warehousing and maintenance.

While material master planning is critical during CAPEX, its greatest impact is realized in operations. Running a facility for the next 40 years or more requires a deeper understanding of how digital transformation impacts data quality, accessibility and decision-making.

Concepts like connected data, APIs, AI, data warehouses, cloud computing and real-time dashboards or end-to-end-visibility solutions are now fundamental to should be part of every day discussions.

Getting Started

The entry point to this workflow is material definition. This is the single most important step when an organization invests in optimizing materials management. However, it’s easy to get overwhelmed at this stage. That’s why organizations should either approach this in clearly defined phases or partner with an organization who can shepherd the organization through the pitfalls and opportunities of this kind of alignment.

When considering material definition, start by evaluating your current systems and processes. Even if you’re starting from scratch, there is a current method in place for managing your assets.

Key Questions to Ask:

1. What technologies are currently in place to manage your master data?
2. Are there clear processes in place for creating, updating and maintaining your material master?
3. What are the pain points in the current process?

Data Quality & Governance

Once material definition is underway, the focus should shift to data quality and governance. These topics don’t need to be finalized at the start, but organizations should have a clear understanding of their importance and a plan for adoption.

Establishing a strong data foundation includes defining taxonomies, data validation rules and governance structures. With this foundation in place, organizations can develop frameworks to monitor and maintain the ongoing expansion of the dataset. These concepts will continue to be enhanced as organizational maturity increases, which will ultimately drive ongoing innovation.

Key Questions to Ask:

1. How is data quality and consistency handled today?
2. What are the key components of data governance to my organization?
3. How will my organization comply with data governance policies in the future?

Taxonomy

Defining taxonomy rules, descriptions, material types, categories and physical characteristics (such as dimensions, weights and center of gravities) is one of the more resource-intensive parts of material definition. This work requires cross-functional collaboration and strong business process ownership.

Depending on the scope of the material master, you may need a dedicated team of SMEs willing to engage and collaborate to consider the end-to-end requirements. Drawing from existing standards like CIFHOS, ISO 15926 or PIDX to meet your organizational requirements can provide a strong starting point. However, these standards will have to be continually challenged as business needs and technologies evolve.

Key Questions to Ask:

1. Is there a clearly defined and supported business process owner?
2. What are the taxonomy rules and descriptions needed for material types and categories?
3. How will physical characteristics be documented and maintained?

Integration & Interfaces

Integration is a very complex phase of material master development. It requires careful prioritization, and the development process does not always follow a linear path. This phase also has a considerable influence on the types of data required during material definition. Understanding data ownership, usually at the attribute level, adds to the complexity and demands clarity on responsibilities.

Along the value chain, different owners will take responsibility for populating their portion of the data, which will impact the overall trust of a given asset. It is essential at this stage to identify and define the key applications that will either maintain the material master or publish data throughout the evolution of the asset.

During CAPEX, integration frequently resides within the Master Data Management (MDM), engineering tools, ERP, Electronic Document Management Systems (EDMS), Project Management (PM) software and construction planning tools. In operations, on the other hand, interfaces will include MDM, ERP, CMMS, PLM, EDMS, PM and EAM technology. Plotting out a high-level integration architecture will help drive prioritization and define a strategic roadmap for the future.

Key Questions to Ask:

1. What are the key methods, standards and system requirements for integration across the value chain?
2. How is material master data structured and formatted across systems?
3. How often does data need to be synchronized between interfacing systems?

Roles & Responsibilities

Clear roles and responsibilities foster accountability and high-quality data management. Additionally, demarcation of a well-defined data structure enables cross discipline collaboration, proactive data management and streamlined processes throughout the asset lifecycle.

With this understanding, organizations can facilitate better data compliance within the organization and to industry standards. Potential results include faster and more strategic decision-making, reduction in errors due to outdated or inaccurate information, and cost savings through resource optimization.

Key Questions to Ask:

1. Who is authorized to create new material master records?
2. What responsibilities do data owners hold for each data element?
3. What mechanisms will ensure consistent data usage across departments?
4. What training programs will be provided to ensure stakeholders understand their roles and responsibilities?

Audit, Reporting & Analytics

Having a clear process for auditing, reporting and analyzing material master data creates an environment of transparency. Prioritized data, real-time access, defined matrixes and KPIs lay the groundwork for AI integration, which can create a continual feedback loop for continuous improvement.

Key Questions to Ask:

1. Where are all the sources of information and how will they be integrated?
2. How will we verify the accuracy of the material master data?
3. How will audit findings be reported and addressed, and who is responsible for resolving findings?
4. What type of reporting/dashboard is expected and who is the audience?

Thinking About the Future

When the foundational elements listed above work in concert, the result is not only improved operational consistency but also measurable cost savings and performance benefits.

Cost savings are typically realized across the following areas:

• Administrative Efficiency: Up to 5-10% reduction in administrative costs due to streamlined processes and reduced errors.
• Project Cost Control: Potentially 5-15% reduction in project costs through accurate material data and efficient resource allocation.
• Compliance & Risk Management: Approximately 5-10% reduction in compliance-related costs by ensuring data accuracy and regulatory adherence.

In addition to financial returns, the greatest intangible benefit is trust in the data. While this variable is difficult to quantify, it is essential for quick responses and confident decision-making. With these building blocks in place, organizations can begin to capture and structure material data that spans the entire lifecycle.

This process is ongoing and will continue to expand to optimize other opportunities within materials management. And as organizations continue to mature, a knowledgeable partner can help accelerate this process. With the right support, companies can avoid common pitfalls, optimize implementation and build internal capacity more efficiently.

Most organizations in the industrial engineering space start with piping or bulk commodities. On the other hand, most operational facilities will focus on assets or critical tags. Regardless of the entry point, applying these principles across the entire lifecycle brings greater value than limiting efforts to a single phase.

This is where ReVisionz adds structure and clarity to an otherwise complex and resource-intensive effort. We help organizations define, operationalize and sustain material master strategies that align with real-world use cases and system demands to close the gap between project priorities and operational needs. Our team brings practical experience to streamline governance, enable cross-functional alignment and ensure that material definition efforts drive long-term performance.

Continue to reimagine each of these key elements as you embark on the journey of material master definition. A well-integrated strategy enables organizations to transform materials management from a static task into a strategic capability that powers performance across the entire asset lifecycle.

The next step for materials management is understanding system integration. For Materials Masters, this typically begins with an organizational MDM system. With the foundational information that we provided in the previous Material Definition article, you should now have a functional understanding of your MDM environment. However, this is only the beginning.

The lifecycle of material data begins at object creation and extends throughout design, procurement, construction, operations, maintenance and ultimately decommissioning. Each phase relies on seamless data flow to eliminate rework, improve visibility and reduce lifecycle costs.

Integrating Design Tools With Material Masters

Integration capabilities were minimal in the mid 90’s. An organization was considered “advanced” if it could combine CSV files into an access database to generate a report. Truly connected data was left up to movies and science fiction shows. Today, it is the norm. Integrated data environments are essential for realizing efficiency gains and supporting strategic objectives.

In project materials management space, once Materials Masters are defined, they need to be passed to 3D design tools to general Bills of Material (BOMs). This step supports the procurement and supply chain process by organizing material needs by functional location and helping ensure on-time delivery for fabrication or construction.

Here are some of the key applications that could be connected beyond the material master data coming from an MDM:

• MDM
• 3D Design Tools (such as CAD platforms)
• Project Controls
• ERP
• EDMS
• EAM and CMMS platforms
• Product Lifecycle Management (PLM)
• Reporting Dashboards and Analytics Tools

Types of Integration

As you start to consider integration, it’s important to prioritize the needs along with complexity and business value. Integration has a cost, so efforts should focus on areas where connectivity will have the greatest value. Integration really depends on the business needs and where the greatest impacts will be felt. Organizations should assess integration opportunities not just from a technical standpoint, but from a process improvement and long-term scalability perspective.

To support this process, it helps to break integration planning into two categories. The first includes typical core systems used during capital projects, where accurate and timely data is critical. The second includes broader systems that come into play during later stages of the asset lifecycle or support ongoing performance management.

#1. Typical Project Integrations:

• 3D Design Tools
• Project C
• EDMS
• ERP

#2. Further Considerations:

• EAM
• CMMS
• PLM
• Manufacturing/Construction Tools
• Reporting Dashboards

Not all of these should be tackled at once, but starting with the end in mind and seeing the full strategy will reduce missed opportunities or concerns with connecting data.

Key Questions to Ask:

1. Where would integration bring the most value and why?
2. How would I measure success against each integration type?
3. Do I have the organization to support the type of integration I want?

Integration Requirements

Establishing integration requires clear objectives, an understanding of your current systems and processes, and a well-planned architecture. In many cases, middleware or an integration platform is needed to facilitate communication between systems.

Suggested Best Practices:

• Clearly define the integration scope and align it with business goals.
• Map inputs and outputs across systems to avoid gaps.
• Evaluate middleware or integration platforms for scalable, reusable connections.

Key Questions to Ask:

1. What data needs to be shared across systems?
2. What standards and protocols will be used for integration?
3. How will integration performance and reliability be monitored?

Data ownership is a critical aspect of integrating design tools within industrial engineering companies. It ensures that there is clear accountability for the data, which is essential for maintaining data integrity and security. When data ownership is well-defined, it helps in establishing who is responsible for data accuracy, updates and compliance with regulatory requirements.

This clarity prevents confusion and ensures that data management processes are streamlined and efficient. Moreover, data ownership fosters a sense of responsibility among stakeholders, encouraging them to take proactive measures to protect and maintain the quality of the data.

Developing a RACI (Responsible, Accountable, Consulted and Informed) matrix is equally important in the context of integration. A RACI matrix clearly outlines the roles and responsibilities of all stakeholders involved in the integration process. It helps in identifying who is responsible for specific tasks, who is accountable for overall success, who needs to be consulted for their expertise and who should be kept informed about progress and decisions.

This structured approach ensures that everyone knows their role and reduces the risk of miscommunication and overlapping duties. By establishing a RACI matrix, organizations can manage the integration process more effectively so that all aspects are covered and that the transition is smooth and efficient.

Key Questions to Ask:

1. Is there an existing data organization within your organization to provide overall governance?
2. Who will be the data owners and what are their responsibilities?
3. How will changes be managed within the data organization?

Data Synchronization

Data synchronization is vital to integrating design or operational systems because it ensures consistency across all systems, tools and processes. When data is synchronized, all stakeholders have access to the same, up-to-date information, which significantly reduces errors and discrepancies.

Synchronization streamlines workflows by automating data updates, saving time and reducing the need for manual intervention. This efficiency not only enhances productivity but also allows engineers and operators to focus on more critical tasks rather than data management.

Additionally, data synchronization facilitates better collaboration within teams. When everyone has real-time access to the same data, it improves communication and coordination, leading to more effective teamwork. This is particularly important between the different stages of projects including engineering, procurement and construction, into operations involving multiple stakeholders and complex processes.

Lastly, data synchronization helps in maintaining regulatory compliance by ensuring that data is consistently updated and accurate across all systems, which is crucial for meeting industry-specific regulations and standards as well as enabling quicker maintenance, planned changes or plant upgrades.

Key Questions to Ask:

1. What are your primary data sources?
2. What systems are currently in use and are there specific security protocols to consider?
3. What is the volume and how frequently does your data change and need to be synchronized?

Change Management & Scalability

Information is rarely static. It will continue to evolve as it flows throughout the process and along its data chain. Understanding how that data will change and around the specific processes of change is important when defining integration.

Scalability is another critical factor. As your organization grows or adopts new tools and processes, your integration architecture must be able to accommodate additional data volume, formats and workflows. Anticipating these needs upfront helps avoid costly redesigns later.

Key Questions to Ask:

1. How will architecture accommodate future growth and what are the scalability requirements?
2. How will data change throughout the process? Does it get overwritten, augmented or are historical records required for data comparison?
3. What flexibility is needed to adapt to changing business needs?

Putting the Pieces Together

All the above components go into a well-designed landscape. Cost saving typically in a properly designed integration deployment can be in the seen following areas:

System Design

Understanding integration requirements is important, as it helps prevent costly design issues such as overdesign, increased complexity, or data being unavailable at the right time or in the right tools to meet business demands. Ignoring these considerations can result in higher costs, lower user adoption, implementation delays and operational disruptions.

Collaboration/Alignment & Stakeholder Engagement

Integration is about intertwining data from multiple sources. This is often disruptive to existing ways of working and overall resource comfort levels. Telling people that “this will be better” is not  a recipe for success. To promote trust in the new path, this has to be built with early collaboration and feedback, alignment between stakeholders and early adoption, sufficient resource involvement and buy-in from key users.

Data Quality

Ensuring proper data quality through well-mapped business processes, validation and cleansing helps mitigate migration issues and reduce data mistrust. Providing adequate time for training and testing further improves data quality and confirms that data has been correctly structured and mapped.

Lessons from the Field

When integration is not approached with careful planning and alignment across system design, stakeholder engagement and data quality, the consequences can be significant. In some cases, project budgets have increased by as much as 25% due to rework, poor adoption or data issues.

One high-profile example is Nike’s ERP and supply chain integration project, which encountered major delays and cost overruns due to challenges in system alignment and readiness. For a deeper look at how integration missteps can impact business outcomes, see the full case study here.

Thinking About the Future

Integration continually evolves. New integrations will become available, different methods for integration are developed, and business needs change. Having a regular review cycle, a minimum of every three years, should be established. This doesn’t mean you need to change every three years, but understanding what changes are available, coming, and required will enable a company to be reactive and responsive to new business demands.

As part of that forward-looking approach, it’s also wise to seek out external expertise and leverage lessons learned. Benefiting from challenges and experiences from others can provide you with an expedited pathway to success. Although not every company’s journey is the same, there are often common threads. Not repeating known pitfalls can sometime have significant cost savings and also provide valuable insight into other opportunities or faster deployment.

ReVisionz brings a structured yet flexible approach to integration planning that’s grounded in real-world project experience and deep technical knowledge. We help organizations define scalable integration architectures, clarify system roles and align long-term priorities across digital project and operations environments. This allows clients to move with purpose, avoid missteps and build integrations that remain resilient as tools, teams and business requirements evolve.