The construction sector has been slow in adopting process and technology innovations. Spending on information technology accounts for less than 1 per cent of revenues for construction whereas it is well above 3% in other industries.
The Construction industry relies mainly on paper to manage its processes and deliverables such as blueprints, design drawings, procurement equipment logs, daily progress reports, and punch lists etc. Due to the lack of digitization, information sharing is delayed and may not be universal. Owners and contractors, therefore, often work from different versions of reality. Project owners and contractors often use different platforms that do not sync with one another. As a result, there is no single source
that provides an integrated, real-time view of project design, cost, and schedule.
Owners often believe that their responsibility ends when they award contracts, forgetting that they pay the economic costs of delay. For their part, contractors often do only the minimum required to meet contractual terms, leaving substantial value on the table. This is the most significant cause of the industry’s poor track record on innovation and the adoption of new technologies, tools, and approaches.
Digitization transformation means moving away from paper and toward online, real-time sharing of information to ensure transparency and collaboration, timely progress and risk assessment, quality control, and, eventually, better and more reliable outcomes. The availability of low-cost mobile connectivity, including via tablets and handheld devices, has ushered in a new generation of “mobile-first” cloud-based crew mobility apps that can be deployed, even on remote construction sites, with real-time updates. These are commercially viable for contractors and project owners of all sizes.
The insights gained through the adoption of advanced analytics in construction projects can help to improve efficiency, timelines, and risk management. Advanced analytics helped a major London infrastructure project save time and money when project leaders worked with a data-analytics company to produce a web-based adaptive-instrumentation-and monitoring system. The system absorbed field-sensor data, construction-progress data, and workforce and vehicle movements. Statistical analysis based on this information helped project teams detect anomalies and identify potential risks—critical information for a dense and historically sensitive city like London
