Why Master Data Management Matters in Construction Projects

Everyone knows that the degree of efficiency of processes and systems in construction execution impacts a project’s bottom line. This is why frameworks like Advanced Work Packaging have come to the fore, striving toward constraint-free project execution to maximize time-on-tools and to mitigate unnecessary delays.

Information exchange is essential throughout (and beyond) projects. The case for digitalization to facilitate communication and streamline workflows has long been made. With continuous improvement in mind, Master Data Management (MDM) arises as the logical progression to take industrial projects to the next level.

Here, we answer some common questions about MDM.

Q: How is Master Data Management (MDM) defined? And how does it relate to data standardization?

Master Data Management (MDM) is a strategic framework designed to ensure that an organization’s critical data remains consistent, accurate, and uniform across multiple systems, applications, and business processes. It encompasses governance, policies, standards, and technological tools to effectively manage and integrate key data assets.

A fundamental component of MDM is data standardization, which ensures that data is structured, formatted, and labelled consistently across all systems. This standardization process enhances data integrity and interoperability, enabling seamless communication between various business functions.

MDM and data standardization are inherently interconnected. Without standardization, maintaining data consistency within an MDM framework would be challenging. Conversely, without MDM, data standardization would lack the necessary governance and enforcement mechanisms required for organization-wide implementation. Together, they establish a structured, high-quality data environment that supports operational efficiency and informed decision-making.

Q: We know that the degree of efficiency of industrial construction and brownfield projects impacts the bottom line. Why are data standardization and MDM so important to that end?

Construction projects often face challenges due to misalignment between Engineering, Procurement, and Construction (EPC) processes, as well as the unavailability of materials and drawings at the required time. These inefficiencies result in the accumulation of non-value-added work and idle time, ultimately reducing overall productivity.

To address these issues, MODS is developing a Standard Enterprise-Wide Data Management & Validation Centre integrated with a construction project management software suite. This platform enables seamless data sharing across an organization and its departments, facilitating early identification and resolution of gaps between the construction workflow and the required engineering and procurement processes. By ensuring better alignment and real-time data accessibility, this initiative enhances efficiency and streamlines project execution.

Q: What should companies be doing now and for the future in pursuit of greater degrees of standardization?

Data management has already become a key focus for most organizations, with dedicated specialist teams and departments being established over the years. These teams are actively analyzing disparate, siloed data streams and storage locations to centralize and standardize information. Their goal is to gain a comprehensive understanding of the data available, identify commonly used datasets across departments, and determine how best to leverage this information for operational and strategic decision-making.

In many cases, organizations may not even be aware of the full extent of the data they possess—data that could be invaluable for reporting, analytics, and business insights. Given the increasing complexity and volume of data, having a dedicated resource responsible for data governance and utilization is no longer optional—it is essential.

This is where the role of the Chief Data Officer (CDO) becomes critical. A CDO not only possesses deep expertise in data management but also understands the business processes, ensuring that data-driven strategies align with organizational objectives. By fostering a data-centric culture, the CDO plays a pivotal role in unlocking the full potential of an organization's information assets.

Q: When thinking about MDM in other sectors, what lessons can be learned? And, how can we expect the tech to evolve in the industrial sector?

The construction sector appears to be significantly lagging in the effective utilization of available data and the standardization of data structures and practices. In contrast, industries such as healthcare and finance have successfully adopted standardized frameworks to facilitate seamless data exchange and interoperability. For example, healthcare relies on frameworks like FHIR (Fast Healthcare Interoperability Resources) to ensure standardized and efficient data sharing across hospitals, departments, and laboratories. Similarly, the financial sector, including banks, maintains unified and shared customer databases to streamline processes related to loans and credit scores.

To modernize and enhance efficiency, the construction industry should adopt standardized frameworks such as CFIHOS (Capital Facilities Information Handover Specification) or similar initiatives. By establishing a unified approach to data structures and management, operators, EPC (Engineering, Procurement, and Construction) firms, and software vendors can align their practices, reducing the need for stakeholders to constantly adjust processes or systems to meet owner-operator requirements. Implementing such standards will not only enhance collaboration and interoperability but also drive efficiency, reduce costs, and improve overall project outcomes.

Q: What is data validation?

In any software system, regardless of its sophistication, data remains the primary driver of efficiency and accuracy. Ensuring data validation before system operation is crucial, particularly in industries where precision is paramount.

Within the construction sector, engineering data serves as the foundation for effective planning and execution. Adhering to a master data framework or methodology—such as implementing a standardized tagging or document naming convention—helps maintain consistency and reliability across systems.

MODS offers a robust service engine designed to enforce compliance with these naming standards, ensuring that all data aligns with predefined rules and expectations. By implementing this validation process, organizations can ensure clean, accurate, and properly structured data, mitigating the risk of errors that could lead to costly disruptions at critical project stages.

Q: Master Data Management opens up the floodgates to analytics that can be used to assess past performance and translate lessons-learned to future projects. How could these data – when properly managed – be put to best use to advance brownfield project execution?

Managing data for brownfield assets presents significant challenges, particularly as these assets change ownership or custodianship (Operators) over time. Many of these facilities are aging, often resulting in fragmented data types, inconsistent procedures, and outdated record-keeping practices. However, this does not signify an insurmountable obstacle.

By systematically mapping and standardizing data into a structured format, organizations can unlock the full potential of their analytics and reporting capabilities. This transformation enables more accurate insights, improved decision-making, and enhanced operational efficiency. Delivering data to operators in the expected digital format minimizes administrative overhead, reduces transportation costs, and ensures seamless integration into existing systems.

Ultimately, this approach enhances the work scopes of both EPCs (Engineering, Procurement, and Construction firms) and operators, driving efficiency, reducing redundancies, and optimizing asset performance.

Q: Cutting across sectors, one emerging trend seems to be the interface of digital twins & Master Data Management. How would MDM support the development and accuracy of digital twins in industrial construction? What challenges might arise when integrating digital twins with legacy brownfield project data?

Master Data Management (MDM) ensures data consistency across systems by standardizing data formats, types, naming conventions, and metadata structures, effectively preventing inconsistencies in digital twins.

In brownfield projects or existing assets, data is often fragmented across siloed systems, stored in formats such as PDFs, Excel files, and scanned drawings. Extracting and validating this data can be complex and time-consuming.

MODS offers solutions that alleviate this challenge through our series of hubs, which enables automated data extraction from scanned drawings and validation based on predefined procedures. This process consolidates all data into an enterprise-wide solution—essentially forming the Data Twin, the core of the system. The Data Twin can integrate with other data sources, such as IoT and ERP systems, serving as a centralized single source of truth to enhance digital twin reliability and efficiency.

Want to go deeper?
Hear the full discussion in our podcast episode on Master Data Management, digital twins, and what it really takes to standardize data in brownfield projects.