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How big data will boost productivity

It’s no secret that the construction industry has a productivity problem. Over the last 20 years, its global average value-added per hour has been largely flat. No other industry has fared worse, according to consulting firm McKinsey, which said last year that meeting global infrastructure needs will be a challenge if this doesn’t improve.

The productivity problem breeds a vicious cycle. As construction firms pursue cost-cutting to counter their dwindling profit margins, long-term investment in innovation is sacrificed. The result is an industry drastically lagging in digitisation and technology transformation programmes, which further limits its ability to boost productivity.

“Construction companies are still building structures like they did decades, if not centuries, ago; nothing’s changed,” says Adrian Butt, managing director at DataScope Systems, a provider of remote data systems.

“The industry has never taken the time to make those processes any smarter. They still rely on folders of paper, while other industries have heavily invested in technology; they’ve digitised and reaped the benefits, both competitively and from a margins perspective.

“If construction companies don’t innovate now, their survival is very much at stake. Also, from a UK economy perspective, we’ll get left behind. Other countries, including in emerging regions like the Middle East, are desperate to embrace technologies such as augmented reality, artificial intelligence (AI) and machine-learning. They will get there, undoubtedly, and then not only move past us, but also take our trade resources.”

A major barrier facing the large construction players is the difficultly to embrace change quickly. With numerous divisions across different sectors, their operations can easily become disparate and cumbersome. Adopting new innovation often requires an agility that can be difficult to find in these firms, so DataScope recommends starting small.

Demonstrating the value of utilising a series of systems into a datacentre, for example, provides a best practice model that can be used on the next phase of the datacentre project or even in another part of the business. DataScope also advises having an internal champion of the technology on site to advocate the systems as they’re built.

The software firm is built on four areas crucial to running a successful construction project: people, logistics, assets and planning. The main contractor on a project can easily lose track when managing dozens of sub-contractors, each providing hundreds of operatives, who must collaborate to ensure everything runs on time. Integrating all project elements through DataScope’s digital systems can drive vast efficiencies.

“Things fall down when the main contractor is not capable of managing those sub-contractor relationships,” says Mr Butt. “By managing those four cornerstones with the data derived from our systems, the main contractor can make sure there are very few clashes. When there are clashes, they are highlighted so the main contractor can flatten any spikes and create genuine earned value management on those projects.”

At the heart of these sophisticated systems are automation capabilities powered by technologies such as AI and machine-learning. However, these capabilities can only be truly utilised if they have useful data in the right format to digest. Large construction firms have thousands of unintegrated spreadsheets, word documents and manual processes.

Connecting and digitising these data sources will be vital to embracing the innovation that can finally enhance productivity for the construction industry and enable projects, which are more likely to be completed on time and on budget. Main contractors can also adopt a strong and consistent approach to collaborative planning with their sub-contractors via DataScope’s systems.

“Whether companies are using paper-based systems or standalone computer systems, we digitise everything on our format, which is all sat on top of big data,” says Mr Butt. “When customers get access to data like this, they can see things they couldn’t see when it was on hundreds of bits of paper in dozens of different files. All of a sudden, they start to use that data in a different way and soon the productivity will be unlocked.”


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