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5 critical steps for engineers going digital

25 November 2021

An expert panel highlighted the steps for engineers and organisations in areas ranging from data definition to standardising digital practices.

5 critical steps for engineers going digital
Digital transformation will play a key role in improving the industry's productivity. Image credit: Shutterstock

Embracing digital transformation offers substantial benefits in an industry grappling with high risk and an acute need to increase efficiency and productivity. To analyse the steps and processes required for ‘going digital’, ICE convened subject-matter experts in October for a roundtable debate to examine the evolution required.

The debate included experts from both industry and technology providers and was convened by the ICE Digital Community Advisory Board and Bluebeam, a developer of technology solutions for architecture, engineering and construction professionals worldwide.

The panel looked at five key areas organisations should focus on to improve business outcomes and examined the potential impact on people, information, technology and process.

The discussion will be continued in an ICE-Bluebeam webinar on 2 December which will provide a practical guide on how to go digital and share critical takeaways and learnings to apply to your business.

1. Establish and track consistent data to enable target outcomes

The panel flagged the importance ensuring broad stakeholder buy-in from the start.

“Sometimes we forget to ask about data as part of the contract when we get so focused on the build,” said Rikesh Shah, head of commercial innovation at Transport for London, who co-chaired the debate.

The panel noted that such a discussion should include baselines for the project definition and scope as well as consistent file formats and common data standards.

To inform this, engineers should consider the information requirements for each stage of a project or asset’s lifecycle and the desired outcomes. This can be assisted by producing clear examples for asset data definition, the structure and level of detail required.

“That level of definition, with clear examples, will really help people to understand why you need the data and how to use it,” said Autodesk strategic engagement lead Ricardo Bittini Miret.

The panellists agreed that first reaching a clear understanding of what the data will be used for will better define what must be captured and avoid the data overload.

2. Aim for standardisation, rather than bespoke

At the same time, the panel recommended avoiding bespoke requirements and methodologies wherever possible, as this would hinder the founding and adoption of industry-wide standards. By the same token, certain NDA/private dataset hurdles can be overcome by standardising the ways that data can be shared, beyond standard security guidelines.

“Democratise it [the data], make it available to everyone; getting clarity and transparency is one of the hardest things to do,” said James Chambers, Bluebeam regional director.

The panel agreed that a project should have the aspiration of opening any data sources that don’t need to be closed for legal, security, privacy or competitive advantage reasons, while noting that education was required for engineers to better understand these factors.

The panel also underlined that employing data scientists and analysts in an industry where they are not traditionally found will improve the extent and quality of data mining and analytics.

It was also felt that an industry that often silos success and lessons learnt within a single site or single company will benefit as a whole by sharing data and making it accessible.

3. Ensure stakeholder buy-in

The best technology solutions will be doomed to failure without sufficient buy-in from the intended users, so businesses must recognise that people and processes are just as important as the technology.

The panel therefore recommended that organisations maximise their digital adoption gains by ensuring digitally proficient graduates work alongside experienced engineers.

Helping staff to completely understand the desired outcomes and efficiency gains that can be made will also drive success.

4. Create an efficient common data environment

Roundtable co-chair Mark Enzer is Mott MacDonald’s chief technical officer and head of the National Digital Twin Programme at the Centre for Digital Built Britain. He explained the need to avoid positioning technology as a silver bullet that will eradicate digital transformation issues.

“There's the people bit, the information bit, the process bit, and the technology bit and we should intentionally put technology at the end,” he said.

A common data environment (CDE) is a digital resource used to collect, manage and distribute documentation, the graphical model and other data for use across the whole project team and is a fundamental aspect of building information modelling.

The panel made the point that it’s the stakeholders’ information requirements and desired outcomes that must define an efficient common data environment. Hence, a project team should clearly identify what kind of environment is needed before choosing a CDE.

With so many digital solutions available, those selected must allow a level of interoperability.

Heba Bevan is founder at UtterBerry, which has developed artificially intelligent sensors that produce ‘big data’ sets. She said the data format should be specified in a contract to ensure it was interchangeable between platforms. She added that a CDE must be flexible enough to share data with anyone that might need it.

But Enzer offered an overarching consideration that digital solutions must be simplified and demystified to encourage broad industry adoption.

5. Standardise digital practices for project efficiency gains and visibility

“Seamless integration will really reduce the barriers to adoption and maintenance,” said Alan Mosca, co-founder and chief technology officer at project forecasting AI provider nPlan.

Automation is key to this, he added, rather than relying on manual processes such as uploading PDFs.

Only by breaking down and defining standard processes at each stage of a project/asset lifecycle can we establish what can be automated. But the panel noted that in the absence of standard lists of repetitive processes, organisations currently rely on producing bespoke ones.

To help with this, the panel recommended that engineers learn the lessons from big public sector projects.

“When HS2 was being established as an organisation, a lot of time went into defining the common data environments and how supply chains would be engaged,” said James Roundtree, Jacobs vice president and ICE advisory board member.

This article has been sponsored by Bluebeam.

This article has been sponsored by Bluebeam
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