In this article, Lee Biggenden, Co-Founder & COO of Nephos Technologies explores how the AEC industry can harness and analyse insight on data resources using a data governance programme
The architectural, engineering and construction (AEC) industry is experiencing a staggering growth in data generation. Each business within the AEC industry stores an average of 3.5 TB of data – 2.5 times more than the cross-industry average. AEC business leaders need to make intelligent business decisions based on their data to get projects done faster, grow successfully and outperform competitors. Yet, data sprawl is a growing challenge with increasing reliance on storage-hungry media sources, such as drone footage and 3D imagery.
Harnessing, analysing, and acting on the insight and intelligence in today’s data resources relies entirely on an effective data governance programme. This is a vital set of processes, rules and technology tools that clarifies data ownership, storage, usage and access. It ensures data is compliant with essential regulations, such as GDPR, and those valuable data assets are protected. Shifting gear in data processes is a must to avoid hefty compliance penalties and unlock potential data value.
While facing the high demand and unpredictable supply chains of the post-COVID and Brexit world, AEC businesses could gain a competitive advantage by embracing data governance opportunities.
Challenges of data security and integrity
Amidst their other data battles, data security issues rank high on the boardroom agenda as AEC businesses face increasing internal and external risks, such as ransomware attacks. Recent research revealed that high-severity issues across AEC domains jumped 325% between Q4 2020 and Q4 2021. Data integrity is key to reacting to such threats and understanding the impacted assets, as organisations need to understand their data well.
Increased investment in AEC-dedicated apps, such as Procore, Bluebeam, and Raken, have provided global file systems and collaboration technologies to allow colleagues to share files and data and access a single source of truth – essential to maintaining data integrity. Those without such investments risk having multiple versions of files and data shared between colleagues and stored on different devices. These businesses face the challenge of tracking the lineage of the data during collaboration, raising questions of its reliability in data governance.
Getting over the barriers to adopting good data governance
Building good data governance isn’t instant, and many organisations face obstacles to implementing a successful strategy. Some don’t know where to start or underestimate the time and resources required. Others may have invested in data governance tools but don’t know how to drive business value and outputs or are constrained by unoptimised gaps in their approach.
Many who bring this function in-house become overwhelmed with how to get started. Simply finding the skills to deliver usable outputs or setting the metrics to measure value can cause many businesses to fall at the first hurdle. The right people and processes are essential to avoid the threats of costly security breaches and hefty non-compliance penalties.
These are just the tip of the iceberg when it comes to the different elements of a data governance strategy. From data quality, master data management and the challenges presented by encryption to choosing the right technology tools and enforcing policies, it is unsurprising that so many get overwhelmed when starting out on their data governance journey.
Yet, it is more than worthwhile pushing through the initial challenges to overcome these obstacles. A good data governance programme offers more than just compliance and data protection. It’s a comprehensive methodology that can minimise risk, establish coherent policies, metrics and processes, ensure compliance and create enhanced data value.
Precious time – and costs – can be saved by having trusted, good-quality data and a single source of truth, with less duplication of data and less time spent correcting data errors. With a robust data governance model, AEC organisations can use their data to predict trends and build next-level customer experiences.
The rising importance of the ‘as-a-Service’ model of data governance
Data Governance-as-a-Service (DGaaS) can help manage and guide businesses through this difficult process to achieve business improvement and robust regulatory compliance. This approach can close the gaps in data governance capabilities, take the risk away from investments and deliver the strategy and proven technologies required to ensure data governance projects succeed.
DGaaS ensures that organisations approach planning, designing and delivering a data governance strategy aligned with their core objectives. Data governance becomes part of the standard business toolkit, with technology acting as an enabler.
Key elements for a robust data governance programme in AEC
There are four key elements of a solid data governance programme that can transform the AEC landscape:
Data discovery and classification
At this stage, the data team determines exactly what data an organisation holds and where it is stored before identifying each asset and the associated level of protection required. Without this detailed insight, the data assets held by an organisation are often inadequately protected. It uses software tools to scan all data to identify all data assets and detect any mishandling and the level of risk generated.
Operationalise the process
DGaaS removes the requirement for internal operations or expertise in data governance, allowing organisations to channel resources into adding value to the business. By being involved in the initial setup, organisations can create and design the policies they wish to enforce and allow the managed service provider to deploy and manage the rest of the process.
Process creation and documentation
Next, organisations can focus purely on creating value from their data. Working directly with the managed service provider, the organisation is guided through what the project entails, what people and processes are required, and which tools will ensure success. In so doing, organisations will convert raw outputs from the toolsets into meaningful business outputs.
Data management
Organisations can now apply the raw outputs from the toolsets to drive significant value. Tangible business outputs, such as data quality, lineage, encryption and master data management, can be utilised.
Data governance as a strategic value generator
A robust data governance programme can help an AEC business to understand its data ecosystem, minimise cybersecurity risks and reduce data sprawl. It can provide key insights into the business and market landscape, all whilst ensuring compliance. Most importantly, trustworthy data-driven intelligence is a catalyst for outstanding customer experiences that provides a competitive advantage.
Adopting DGaaS releases AEC organisations from the limitations that cause many projects to fail. With flexibility and scalability to grow with the business, AEC organisations can take a long-term holistic data approach rather than investing in short-term fragmented data projects. The sooner leaders establish an effective data governance model to formalise processes and responsibilities, the sooner their data can unlock serious business potential.
