Currently, data on construction sites is scattered across various mediums, such as spreadsheets, post-it notes, meeting memos, emails, WhatsApp threads, and sometimes on separate software.

So, although we have data, it’s unstructured, making it difficult to connect, visualize, and analyze it so we could use it for decision-making during the existing construction project and in the future.

This means it is impossible to lead most construction sites with data and instead of exploring what methods work best in the construction process, we rely on existing models. As a result, building productivity has remained the same in the last four decades.

Let me explain how construction sites can improve productivity by collecting data more effectively.

What type of data should we collect on construction sites?

Construction data is always connected to the project at hand, which includes the building, its construction plan, and its progress. The main data revolves around two basic elements: location and time.

These elements form location-based schedules that narrate the type of spaces, the job site locations, and the construction timeframe.

In an ideal situation, we can incorporate additional data into a location-based schedule, such as

➡️ Task data which helps us understand the tasks required to complete the locations.

➡️ Product data that identifies required materials for completing different locations.

These four key data blocks – location, time, task, and product – help you to lead construction sites toward better efficiency. By understanding the specific locations, the timeframe, and the required materials, you can ensure that construction projects are completed on time and as quickly as possible.

This provides context for other essential data: quality, conditions, and finance.

Let’s take a closer look.

Location data

What are the different locations that make up the building project? In industrial construction, the building is considered a product that comprises various locations, such as rooms, installation areas, or cross-area intervals. Location data can be easily incorporated into the IFC model during the planning stage.

Time data

Time data refers to calendar time. It is self-explanatory: It estimates the duration of completing different locations.

Product data

Product data helps you to understand the necessary building materials. At simplest, it is the bill of quantities, or it can also be refined into a list of materials.

Task data

Task data provides information on what needs to be done to complete the project. When we combine task data with location data, we can break it down into smaller, more easily understandable pieces.

Precise task data is essential for efficient building. The more accurately you can describe the tasks, the better you understand what needs to happen. For instance:

  • In which order should the tasks be completed?
  • What types of obstacles hinder the completion of these tasks?

At present, the job site tasks are described in a very generic manner, such as “building a partition wall on the ground floor.” In this case, the task still lacks detailed information about the specific work phases and materials required. This information currently exists only in the workers’ minds.

Quality data

When combined with other data, quality becomes a part of production:

When combined with other information, quality is part of the production, meaning that the tasks on site include quality checking. The data collected from these tasks then provides insights into the methods used to prepare the product, while the quality data confirms that the final product meets the agreed-upon standards. The quality is confirmed, for example, by measuring or taking a photo.

There are three categories to evaluate quality data: product usability (e.g., straightness of a wall), buyer requirements, and authority requirements.

Condition data

The data on the site’s conditions helps you understand the factors that influence your ability to stick to the plans. Condition data can share information, for example, on:

  • Humidity and temperature levels to determine if they are ideal for quick drying of the materials
  • Particulates to determine if the working conditions are safe for the workers.

Different sensors can measure the conditions and report them using color codes. However, condition data is not very useful on its own. Connecting it with location and task data helps you ensure you can start the tasks on-site on time.

Financial data

All construction sites gather financial data, but if you want more insights beyond just euros or dollars, you need to connect it to the product data.

Good financial data helps you understand:

  • How much have you used the money so far?
  • What is the prediction of total costs?
  • Have you adhered to the plans, or have they resulted in additional expenses – or is there a potential risk for higher costs?

Requirements in reporting costs are increasing. You’ll most likely need to consider and calculate your project’s carbon footprint in the future as well.

What type of benefits does data-driven management bring to construction sites and companies

Research shows that only 20% of the time spent on a job site is used for productive work. The remaining time is spent on tasks such as confirming, waiting, and addressing obstacles that arise. Often, workers cannot begin their tasks due to missing or incorrect materials, work phases being executed in the wrong order, previously completed work needing to be demolished and rebuilt, and so on.

The main advantage of data-driven construction is that it allows us to gain a deep understanding of the product, its production process, as well as the dependencies between different tasks. By having a real-time plan and progress tracking system, we can identify obstacles earlier, and the site management can take proactive measures to resolve them.

Data-driven construction enhances production flow and increases site productivity.

The production flow is one of the fundamental principles of lean construction. It aims to increase understanding of the production process across different locations and turns focus on completing them. Real-time data plays a vital role in this: without it, we can only react and track progress but not predict and proactively manage the project.

Increasing accuracy is a core tool for improving the production flow: the better we understand the product and its associated tasks, the better we can identify the interdependencies and issues between them.

Data-driven construction ensures you’ll get visibility on things like:

  • What is the actual duration of each work stage?
  • Which work phases and tasks tend to exceed the planned duration, and what are the underlying reasons for the delay?
  • Are there any similarities in the tasks performed across different projects, spaces, and work stages?
  • What factors contribute to waste of time, materials, space, repeating tasks, mistakes, or storage?

While the value for business is apparent, there are also significant benefits for the crew and on-site management. Traditionally, a construction project’s success has depended solely on the expertise and experience of the team involved. The planning process often occurs alongside work, requiring constant pre-planning and documentation of the same tasks. However, once the construction process has been documented and standardized in one place, the team no longer has to reinvent the wheel. As a result, the work flows more efficiently, saving time and reducing errors.

With the next work phases transparently visible to all, even inexperienced planners and workers can quickly learn and implement best practices. This helps to reduce reactivity and conflicts on the site.

How to build a solid foundation for data-driven construction management?

Data-driven construction requires two things:

1️⃣ Software to store the data in a standardized format that can communicate with all the other data sources.

2️⃣ Clear processes and routines are in place to ensure that data is collected accurately and efficiently.

Let’s take a closer look at these.

#1 Collect data in a standardized format on the software

Data-driven management requires software that stores all necessary data. Your software palette should include at least the following:

  • The architects’ project plan in the 3D model is described through the spaces and materials needed in them. When executed well, it works as a data structure for everything else: location, product, and task data instantly receive standard labels, and you get a list of materials.
  • Schedule planning and managing in one software. The general and weekly schedules need to be built on the same data and tracked in the same place. The schedule should also be easily editable in case it no longer reflects the actual situation on the site. This ensures better and more accurate planning.
  • Reporting models to help you collect data and analyze learnings. In the best-case scenario, reporting data is collected as a byproduct of site management.

When choosing software, consider the following factors:

💡 The data in all your software is in the same format and can be integrated. Ensure your data structure is standardized so you can easily combine your data.

💡 You can view reports and track changes in real time. This enables you to utilize the data for project development and management during construction rather than after completion.

💡 There are no duplicates, and you have only one truth. For example, if the task list involves installing a light fixture, there should not be multiple conflicting pieces of information on when this installation will take place. Additionally, all subcontractors should update the same schedule rather than maintain separate schedules that won’t communicate.

💡Your data is categorized. Any info that lives in an open text field is not very useful.

>> Read more about how to choose a the right construction scheduling software

#2 Create clear routines for data collection

To ensure that your data is accurate and up-to-date, you need clear processes for collecting it. Rather than treating data collection as a separate task, it should be integrated into your other processes.

You should plan schedules and monitor their progress and readiness levels in the same software. The readiness levels should be documented in daily job site meetings, and any obstacles should be collected in the same software rather than in WhatsApp threads, and so on.

Start data-driven management and improve your construction flow with Sitedrive

Sitedrive is schedule management software that combines time, location, and task data to help you better plan and manage construction sites. It creates a good foundation for data-driven management.

Get to know Sitedrive and start improving your productivity.

Henri Ahoste


Henri Ahoste

Henri has a background in construction site production, having worked as a project manager, project engineer, and site manager. He successfully scheduled and managed the production phase of a construction project worth 200 million euros and led a planning team for a 30 million euro project. In addition to his daily job, he founded a start-up whose technology is now integrated into Sitedrive. At Sitedrive, Henri works as a product manager, utilizing his construction expertise to guide product development and provide insight into the future.

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