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Dealing with Data in the Construction Industry


The exponential growth of big data has had a profound effect on the heavy building materials industry. Per Techjury, every person this year will generate 1.7 megabytes of data in just a second. In 2019, internet users generate about 2.5 quintillion bytes of data each day.

In addition:

  • Large infrastructure projects are voluminous — requiring an average of 130 million emails, 55 million documents, and 12 million workflows
  • 95.5 percent of all data captured goes unused
  • 13 percent of construction teams’ working hours are spent looking for project data and information
  • 30 percent of engineering and construction (E&C) companies are using applications that don’t integrate with one another

The correct use and analysis of the vast amount of data available to a business has the potential to transform supply chains as we know them, but also the power to disrupt. Without the appropriate tools and expertise to manage large amounts of data, organizations can become overwhelmed and unable to gain valuable insights, causing issues across the supply chain and wider business functions.

While construction is one of the least digitized industries, firms are currently transitioning from paper-based processes to digital workflows. Harnessing the data from these digital processes will result in more valuable insights, better decision making, improvements in efficiencies and business growth.


This staggering amount of information is hard to manage without the right tools in place. Most companies either simply avoid the issue, or need guidance as they try to sort through their options to properly leverage their data. Getting beyond the big data glut to data-driven decisions requires a four-pronged approach:

  1. Get the right talent, tools and processes in place
    Big data presents unique challenges for the construction industry. Understanding which data could be useful – and how this data translates into business intelligence – requires a clear understanding of your organization’s overall goals and vision. With clear direction of how you want your data to work for you, your company can extract meaningful insights. But during this period of transition from data glut to data clarity, it’s important to clearly communicate the time frame and rollout process, so you can more easily manage expectations.
  • Collect and analyze data with an end goal in mind. 
    Big data can be used to improve performance or processes. But to accomplish these goals, you’ll need personnel who have both worked in the built environment and understand project work but also have critical research and analytical skills. Companies that don’t invest in the right people often experience failures and are slow to realize a return on their investment (ROI). But this important step can help your firm drive performance and generate strategic business insights.
  • Move beyond siloed data to data integration.
    Like many other industries, construction is notorious for storing data in silos or scattering it across systems, desktops, phones, tables, hard drives, and servers — not to mention cloud locations, other devices, and unstructured data like blueprints, timecards, emails and PDFs. Data integration can be a difficult, but not insurmountable, challenge.
  • Leverage internal or external skills to turn data insights into actionable insights.
    Data analysis is a highly specialized skill set, and frontline managers and field staff rarely understand how to implement analytical procedures or use analytical tools. Yet to make your data analysis projects effective, you need cultural buy-in. In an industry where 35 percent of total costs can be attributed to waste and remedial work, this approach to using big data in the best possible way just makes sense.


The E&C industry is making huge strides in harnessing big data to improve business outcomes, gain better visibility into their operations, and streamline their business processes. It’s all done with a little help from better tools and processes:

  • Data-driven predictive modeling. Some forward-thinking companies are building real-time systems that enable project owners to visualize — and adjust — project design during the early design stages, to speed up the design process, reduce waste and delay, and ensure accurate cost estimates.
  • Data capture and usage across the business. Rather than have construction teams waste hours looking for project data and information — a problem that’s plagued the industry for years — some leading firms are using prefabrication methods, connected jobsites, BIM, virtual reality, wearables, geolocation, and sensors to track employees, equipment and material movement, and further optimize tools, resources and worker productivity.
  • Better collaboration and efficiency. Given increasing E&C project complexity and growing demand for new E&C projects, industry leaders recognize that collaboration is a key part of achieving project consistency and efficiency across multiple stakeholders. Many firms use big data to create automated workflows between stakeholders on a project and keep all relevant personnel informed with relevant real-time updates.
  • Supplier collaboration platform links trading partners and automates processes. Transactions are executed and information collected to deliver insights with a speed and accuracy that fuels success on the heavy jobsite. The platform business model can gather data from IoT devices, telematics and more, running analytics to inform about a business’ performance. Critical business processes in a company and across its trading partners are automated, whether the processes are for procurement, production, dispatching, selling, tracking or tracing heavy building materials.


Good data practices and a solid data strategy will continue to help E&C companies develop and implement sophisticated analytics plans in the years ahead. Companies need to:

  1. Take advantage of business intelligence (BI) tools like dashboards, which store well-defined data in a central location where it can be displayed in a visual format for easier consumption. This enables users to aggregate separate data streams and compare the information within them in a single place and monitor performance in real time.
  • Include some level of machine learning (ML) and artificial intelligence (AI) to help users gain insight from data and make predictions, discover relationships between data points, identify customer or market segments more intelligently, and identify and learn from patterns hiding in large or unwieldy data sets.

Actionable insights from deep analysis of big data from your heavy building materials operations can lead to improved productivity, streamlined operations and lower costs if dealt with properly.

Tom Rice is a civil engineering graduate who serves as a business consultant and assists with the BuildIt team at Command Alkon, an AGC of Texas Highway, Heavy, Utilities & Industrial Branch and Associated General Contractor of New York State LLC member. He spent many years in the vertical construction world focusing on overall construction management and value engineering and design. For more information, visit www.commandalkon.com.