Why Critical Field Decisions Depend on Good Data

27 September 2021All, Architecture and Engineering, autodesk, Construction, Datadata management, Field, Project Management



Construction data can range from financial and operations numbers to estimate calculations, project characteristics, and building information and details from the project’s BIM model. Data can come from sensors, machines (like drones), people, cameras, computers, supply chains, invoices, and other sources. Data can be used to discover patterns, probabilities, risks, potential problems, and help with project scheduling and phasing.

Construction decisions have always been made using some amount of data, even if it’s simply the price per square foot of successful construction projects.

As your sources and types of data increase, it may take longer to analyze and use it. In addition, the possibility increases that you’ll be basing a decision on bad data. According to a recent Autodesk study, based on a survey of construction companies worldwide, bad data can be described as inaccurate, incomplete, inaccessible, inconsistent, untimely, or some combination of those that render it unusable for meaningful insights or decisions.

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That same study found that, worldwide, using bad data results in billions of tons of wasted materials and schedules being exceeded by an average of 40%. The survey reported that 14% of all construction rework is caused by bad data and provided these descriptions of bad data:

  • Inaccurate/Incorrect — Data collected with the right intention, but errors occurred. For example, a measurement sensor was not calibrated, or a “5” was entered into a data field instead of a “6.”
  • Missing — Pieces of data completely absent. For example, a contractor forgot to upload progress pictures from the field, or a vendor’s phone number was not recorded.
  • Wrong — Data collected that can’t be used for its intended purpose. For example, a contractor thought they captured data on how much time was required for rework, but later discovered only the cost, not the time, was recorded. The data can’t be used because it would result in incorrect estimating on future rework.

Yet, in these times of tighter budgets and shorter schedules, being able to use trends, statistics and other data for informed business decisions is critical. In fact, it can become a company’s competitive advantage.

Fact-based informed decisions can help you avoid direct and indirect costs, as well as equip your company for a higher level of performance. If your company is going to have a data-driven future, it depends on developing data management skills within the company, either through training or hiring. An increasing need for rapid decision-making in the field, whether it’s because of schedule compression, emergency response or stakeholder request, requires a data strategy. Data management and analysis skills are increasingly important.

Getting the data into a usable form might require hiring a data scientist in companies with the budget; others may choose to train existing staff and new hires to better capture, manage, and analyze project data. When project managers and field supervisors are required to make fast decisions without guidance from the architect or owner, valid project data is key to avoiding a bad decision.

Having staff with data management and analysis skills can give your company a competitive advantage. Providing them with a common data environment ensures better data to work from. Industry leaders indicate that when access to project data was centrally located, it improved their ability to accurately capture data and in turn, analyze it.



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