Reliable data gathering is a game-changer. Construction project managers and planners, particularly those leading large and complex projects, recognize that the quality of their decisions depends directly on the quality of their data. The construction industry is increasingly embracing data analytics to refine operations.

Data analytics leverages information from business operations or industry activities to uncover insights. Decision-makers can use these insights to guide their choices or evaluate the effectiveness of existing strategies.

In the construction industry, analytics programs can evaluate data related to performance, finances, and safety. This analysis helps identify areas for improvement and measures the impact of recent changes against previous processes. For example, a construction company might analyze work hours for a certain project and on the basis of that employ the number of workers required for the next project.

According to KPMG research, 45% of construction companies already use basic analytics, and another 45% are in the process of adopting digital analytics tools. Additionally, 68% have adopted or plan to implement advanced analytics systems.

Here’s a closer look at this increasingly important aspect of construction.

Use Case for Using Data in the Construction Industry

1. Improved Planning

During the planning stages of any building project, stakeholder groups have varying interests. While engineers focus on how to translate designs into real structures, contractors aim to maximize profits, and owners strive to keep costs low. These diverse interests can sometimes lead to a lack of cohesion that isn’t beneficial to the project. 

However, by leveraging the right systems and big data, stakeholders can observe how even the smallest changes impact their areas of interest. With big data and analytics, plans are maintained digitally, and algorithms process inputs to generate virtual outcomes. Real-time algorithm updates enhance communication among stakeholders, resulting in more effective and successful planning before construction even begins.

2. Real-time Project Updates

Construction companies now have access to vast amounts of data, which can be overwhelming without proper systems. With the right technology, project managers can monitor project status, stay connected with key personnel, and address issues as they arise, minimizing errors and ensuring smooth project progression. Features like smart forms for field data collection, and QR code task tracking significantly enhance real-time project progress.

Task tracking helps keep schedules on track, smart forms facilitate efficient field data collection, and QR code scanning provides quick access to project information. The data collected through these methods can inform future decision-making, identify loopholes, and pinpoint bottlenecks.

For example, a construction business can use smart forms to collect on-site data for safety inspections. Workers can complete safety checklists on their mobile devices, instantly capturing potential hazards and compliance information. This data allows project managers to promptly address safety concerns. 

3. Predict Project Outcomes

Predicting project outcomes has become more accessible through the use of both internal and external data to create predictive models. For projects similar to past ones, using internal data can yield the most accurate forecasts. 

However, for entirely new projects, companies can gather extensive data from previous projects to create predictive models that assess potential risks and rewards. Predictive models are also valuable for market forecasting, helping construction companies anticipate market trends and serve as a strategic guide for future operations.

4. Better Decision Making

Once equipped with the right software, data can significantly enhance decision-making by providing clear insights into the current state of a project or organization. This enables project managers to make quicker, more informed decisions, ensuring the smooth progress of initiatives. Data-driven decision-making reduces the likelihood of human error as decisions backed by data and numbers are more reliable.

Field service management apps with visualized data dashboards can further aid construction businesses in making better decisions. These dashboards present complex data in an easy-to-understand format, allowing project managers to quickly grasp key metrics and trends. This visual clarity helps in identifying issues, tracking progress, and optimizing resources effectively. Embracing data through such advanced tools fosters more rational and efficient decision-making.

5. Digital Twin

No discussion on construction data would be complete without mentioning digital twins. These virtual representations of infrastructure projects provide precise information throughout the project lifecycle, enabling construction businesses to achieve more with fewer resources. 

Digital twins update in real-time, presenting an accurate picture of a structure or object. Some key advantages include:

• Reducing the risk of rework and delays by anticipating build faults.
• Streamlining project execution and increasing productivity.
• Boosting profits through more successful project completions.?
  

Actionable Steps to Get Started with Data Analytics in Construction

Assess Current Capabilities: Start by evaluating your existing data infrastructure and the analytical skills of your workforce. Understanding your organization’s current state will help identify gaps and requirements for successful analytics implementation.

Develop a Strategy: Formulate a clear, focused data analytics strategy aligned with specific goals, such as improving project delivery times, enhancing safety, or increasing profitability. This strategy should include defined milestones and measurable objectives.

Invest in Technology and Training: Acquire the necessary analytics tools that meet your specific needs and ensure they integrate well with your existing systems. Equally important is investing in training for your team to ensure they can effectively utilize these tools.

Start Small: Pilot analytics on smaller projects to manage risk and learn from any mistakes. This controlled environment allows for adjustments and the development of scaling strategies based on successes and challenges.

Scale Gradually: Use the insights and successes from pilot projects to gradually expand the use of data analytics across more projects and departments. Continuous improvement should be a key objective, with adjustments made as more data becomes available and insights are gained.

Foster a Data-Driven Culture: Promote a shift in company culture towards data-driven decision-making. This involves regular training, sharing success stories, and visible support for data-driven initiatives from the leadership team.

Conclusion

Data analytics is more than a tool; it’s a game-changer. Imagine a future where every project pushes the boundaries of innovation and accuracy. From real-time progress monitoring to predicting potential issues with advanced models, data analytics revolutionizes the building process. It’s not just about efficient resource use or risk management; it’s about redefining construction. The future construction industry will not only erect structures but also pioneer an era of data-driven precision, where outcomes are anticipated, risks are mitigated, and every step is guided by intelligent insights.