Why building digital expertise is no longer optional

18 November 2021
Gathering digital data and building the skills to manage this information has become an essential business component, say experts from Atkins, a member of the SNC-Lavalin Group

In a market that has become exceptionally competitive, architecture, engineering, and construction (AEC) firms are being squeezed on fees, and often procured on cost over value.

Meanwhile, the need for industry-wide digital transformation has become even more critical following the outbreak of the Covid-19 pandemic.

In order to remain competitive in the marketplace, we now rapidly need to change the way we work, the way we talk to project owners – and the way we deliver.

But what does it mean to ‘do digital’ better than anyone else?

Increasingly, the answer is by designing the infrastructure yourself, from the ground up. This means being able to knowledgeably handle the data you have access to and help decision makers to extract maximum value from it too. We as an industry must start elevating our digital skills and infrastructure at every level. Successful players will therefore be those that adopt data-driven, innovative solutions to enable smart and efficient project delivery.

The project benefits of this are numerous: better data sharing and use, a reduction in energy and waste, increased productivity, and improved safety, to name just a few. And it’s not just collecting the data that’s important, rather we need to mine and use it effectively to deliver unbeatable quality.

To take advantage of them, companies must get to grips with data management, big data analytics, machine learning (ML), IoT and automation and, above all, data-driven decision making.

Here are some strategies for going about it:

Data alone is not enough

Many in our industry have not fully grasped that amassing data is a pre-requisite, but not the sole objective. In fact, unless you know what you would like to improve or to develop with it – and engage with key stakeholders to understand their needs and requirements and how the data can deliver those – it is of little value. Key to that understanding is structuring the data in the right way in the first place. But how do you do that…

Take control of your data

Organisations quite often fall into the critical dilemma of building a bespoke solution or using technology solutions off-the-shelf to speed up digital maturity.

In order to remain competitive in the marketplace, we now rapidly need to change the way we work, the way we talk to project owners – and the way we deliver.

With the democratisation of technology, it is now more technically and commercially viable to develop solutions based on specific needs and reduce an organisation’s dependency on external vendors. This is empowering organisations to make the most of digitising their domain knowledge and expertise and harnessing data as opposed to relying so heavily on third party technology providers and commercial off-the-shelf (COTS) solutions. Such a reliance could mean losing control of your data and not being able to own the process.

By developing an in depth understanding of your data, you can make informed decisions about the infrastructure and tools that will most benefit you as a business. This is a data driven approach, rather than a system centric one.

At the SNC-Lavalin Group, for example, we have spent a tremendous amount of time understanding our data. This has enabled us to build our own technology agnostic programme and project management capability that produces and consumes an extensive amount of data. We are now leveraging this data for ML algorithms and natural language processing (NLP) to identify and categorise unknown risk in construction activities.

By understanding our data and taking a data led approach to developing our internal architecture, we have managed to connect the dots between different data sources, bridging the gap between disparate functional data points.

As an example, one of our models was looking at the likelihood of activities failing and therefore deviating from original estimates. When we tested it, we found it to be 97 per cent accurate at predicting failures and we can now locate bottlenecks in a schedule and mitigate problems down the line or even build them into the upfront planning to provide more certainty of programme outcomes.

This would not have been possible without the upfront effort of creating our central data model and infrastructure that our data science capabilities can now leverage.

Hire based on curiosity

We have found that our highest performing teams are those that possess valuable industry knowledge, an appreciation of the value of data and a curiosity to learn new things.

The old adage of ‘you can’t teach an old dog new tricks’ is not often the case and teams that have been working in the same way, with the same tools and techniques for decades are now challenging the status quo and finding innovative new ways of working.

By understanding our data and taking a data led approach to developing our internal architecture, we have managed to connect the dots between different data sources, bridging the gap between disparate functional data points.

We have found that this often comes from curiosity and a self-learning approach, using online tools such as YouTube to teach themselves new ‘tricks’ that can be bought into their day to day working to deliver improvements.

The most successful transformations are those that have been conceived by the teams themselves as it is often derived from a need and the value proposition is there in plain sight, meaning it is much more likely to stick and be adopted at scale.

For this approach to be effective, it is vitally important that the culture of the organisation is aligned and there is an understanding that not everything we set out to do will succeed. It is important to recognise this fast, learn from it and move on to the next. Organisations that encourage a ‘fail fast’ approach provide the right environment for innovation to thrive and its likelihood of success to increase.

Automate, automate, automate

We have analysed some of our projects and found that more than 50 per cent of time was spent on looking, cleaning and collecting information. This also has the added risk of working on incorrect or outdated information that can seriously impact project budgets and timelines, or even more important, your own reputation.

One solution is adopting a consistent approach to the way in which data is structured and represented as information and then automating its collection. That frees people up to work on the higher value part of a project that their expertise is really for, and time is not wasted on data collection and manipulation. Instead, they can analyse and determine what to do with the information.

Upskill in a smarter way

Industry professionals facing rapid change are having to upskill by learning the fundamentals of key software packages, which should be seen as a vehicle to get to your end goal more rapidly but not as the solution for your fundamental issues with data and having a reliable single source of truth.

A wealth of training resources has sprung up to equip managers for the new era. Centres of excellence, such as universities and research institutes, are also yielding a growing source of talent and skill, both through tech-savvy workers and as centres of innovation in digital transformation. Building relationships in academia will be increasingly important as intellectual property connects to competitiveness.

Organisations that encourage a ‘fail fast’ approach provide the right environment for innovation to thrive and its likelihood of success to increase.

Digital professionals in the GCC are emerging quickly but compared to international benchmarks, there is still some way to go. Initiatives such as Atkins’ Data Academy, which targets AEC graduates and early career professionals, will help to shape our data-led approach whilst solving real-world industry challenges.

The digital transformation journey requires people to work in new ways. That means managers understanding their existing knowledge limitations and specialists such as data scientists working to understand the wider business objectives and how their work ties in.

The best thing that leaders can do right now is challenge convention, not feel threatened, be open to new ideas, and adopt a genuine willingness to learn from those around them.

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