In the dynamic construction landscape, where each project demands precision, efficiency, and timely delivery, embracing technological advancements becomes paramount. One such technological marvel increasingly proven to be a game-changer is data analytics in Project Management Information System (PMIS).
The construction industry is among the most data-intensive markets, which is why there is a growing need for better construction analytics and big data management. It is because of the big data that construction firms can significantly improve their project management and optimize costs, which will ultimately lead to the wider adoption of the technology.
What is Data Analytics in Construction?
Data Analytics in Construction is the process of examining historical and real-time data generated throughout a construction project to extract meaningful insights. Data Analytics is a way of identifying patterns, trends, and linkages in the existing data. Its objective is to solve problems by using construction data to understand situations better and predict future behavior based on what happened before.
By harnessing advanced analytical tools and techniques, project owners can gain a comprehensive understanding of their projects, enabling strategic planning and informed decision-making.
In construction, project teams navigate various challenges like subcontractors, materials, and equipment, coupled with changes in scope and contract adjustments. As projects become more complex, especially with increased remote work, effective communication, and data-gathering tools become essential for informed decision-making.
The generated data needs to be filtered and analyzed to be useful for the decision-makers. Doing this manually takes significant time and resources. Data Analytics empowers preconstruction teams to create a budget that considers all project aspects, including regional labor and material prices.
Solutions incorporating data analytics, machine learning, and artificial intelligence are poised to revolutionize how construction firms bid on and execute projects. For example, by amalgamating relevant information, current business status, and past performance, data analytics can enhance your decision-making ability.
How Data Analytics can help Capital Project Owners?
1. Predictive Analysis
Having both historical and real-time data allows you to create predictive models, foresee outcomes, and prevent failures in future projects. For instance, you can predict project delays based on factors like weather conditions and past performance data. Predictive analytics also helps predict equipment maintenance needs, optimize procurement processes, and reduce cost overruns.
2. Project Planning and Modelling
An interesting example of applying data analytics and predictive modeling in construction involves Business Information Management (BIM) simulation software. BIM enables project stakeholders to visualize the entire project before construction starts, encompassing detailed design elements, planned materials, cost data, and other project-related aspects.
3. Warranty and Risk Analysis
Data Analytics in Construction is a valuable tool for analyzing risks by evaluating historical data, industry trends, and external factors. With data analytics, you can identify the likelihood and impact of potential risks and devise effective mitigation strategies. Additionally, it can be applied to warranty analysis, examining patterns in warranty claims, assessing equipment performance, and identifying potential weaknesses in materials or the construction process. With the help of these insights, project owners can take proactive measures, such as sourcing higher-quality materials or enhancing product design.
4. Accurate Budgeting
Cost optimization is critical in construction, from planning to implementation. Data Analytics helps with this by combining data from project management software, financial systems, and vendor invoices. This real-time visibility provides a comprehensive view of project expenses, allowing for quick action on budget deviations. Construction Analytics can also create ‘what if’ scenarios for efficient budgeting. You can evaluate project plan feasibility, optimize costs, and ensure budget accuracy by stimulating various scenarios and adjusting cost parameters.
5. Equipment Management
To avoid project delays and extra costs from equipment failures, project owners utilize data analytics and asset management tools. These tools provide real-time tracking of equipment data, preventing over or underutilization. Data analytics is also useful for comparing equipment performance to industry standards, enabling timely identification of underperforming equipment and informed decisions on upgrades or replacements. Other benefits include improved equipment selection, reduced idle time, and a simplified procurement process.
6. Quality Control and Defeat Detection
Effective quality control is required to ensure high-quality construction projects. Construction analytics allows you to examine a plethora of data points, like project specifications adherence, inspection results, and defeat reports. You can determine quality issues, understand defect causes, and pinpoint areas for improvement. It empowers you to proactively reduce defects and enhance overall project quality.
7. Cost Reduction
Data analytics empowers project owners to monitor operations in real time, monitor patterns, and receive automated reports. This data assists in identifying areas for improvement. Moreover, it allows the analysis of historical cost data, resulting in more accurate estimates for upcoming projects. This improves budget management and reduces the risk of cost overruns.
8. Streamlined Workflows
Utilizing data analytics allows you to discover opportunities for automation, enabling you to streamline the entire construction process from planning to payments. The digitization of paper-based processes is enabled by automating repetitive tasks and routine activities, reducing manual errors, eliminating unnecessary steps, and speeding up the overall workflow.
9. Human Error Reduction
Manual documentation of critical data such as timesheets, reports, and delivery receipts frequently results in human errors. Data collection and reporting automation ensure high-quality, accurate, and easily accessible data, enabling informed decision-making. Furthermore, using data analytics to automate business processes not only reduces the risk of errors but also improves workflow efficiency, saving time and resources.
Why Should You Use Data Analytics in Construction?
Many growing construction firms have stuck to their conventional methods for years. It’s reasonable to question the benefits of disrupting the already established routine, given the challenges associated with operational changes. However, there’s a compelling case for embracing data and the valuable insights it provides. Here are a few advantages of utilizing your operational information:
1. Speed up Operations
If you have ever sensed that your operations can run smoothly but weren’t sure where the biggest issue lies, it might be due to the lack of data analysis. Effective reporting highlights inefficiencies like subcontractors consistently falling behind schedule. This information helps pinpoint areas where taking action can have the greatest impact on improving operational efficiency.
2. Finds out where you are losing money
Accounting is imperative in business for financial tracking. Having software that not only manages finances but also reveals where you can upscale earnings is even more impactful. By monitoring real-time financial data, observing operational patterns, and generating automatic reports, project owners gain insights into areas for cost savings.
Data Analytics in Construction breaks down job costs, enabling you to determine profitability. It helps subcontractors identify bids that enhance earnings and reveals where and why issues occurred in jobs.
3. Improves Accuracy
Top-notch data analytics software helps eliminate human error during data collection. When processes rely on people, errors are inevitable, and even minor errors can lead to big financial and time losses for your organization.
Manually recording vital information such as timesheets, site reports, and delivery receipts is prone to human error and can compromise data reliability. Automating data collection and reporting ensures higher quality, more comprehensive, and readily available data. With enhanced data accuracy, you can extract actionable insights and steer clear of misinformed decisions.
4. Advanced Safety Measures
Ensuring the safety of construction sites is vital for any construction company’s success. Workplace accidents not only have immeasurable human costs but can also lead to labor shortage, legal liabilities, and damage to the company’s reputation.
Real-time data analytics enables early detection of safety issues and high-risk patterns or behavior, Assisting in the prevention of accidents. For example, the risk of breakdowns or equipment malfunctions can be minimized by regularly reporting on necessary preventive maintenance for construction fleets.
5. Beat competitors
Having a faster, more profitable, accurate, and safer business puts you ahead of your competitors. When compared to traditional physical record-keeping, scheduling and invoicing data analytics prove to be a more reliable method.
Utilizing the data from previous projects can help you in predicting costs and risks for new bids. Using insights from your data to set rates minimizes risks and boosts confidence in tender submissions and negotiations.
In the construction industry, employing data analytics is like using a super calculator in an industry where others are still doing math on paper.
How do you effectively implement data analytics in construction?
1. Select the correct analytical tool for Projects
Choosing the right data analytics tool is crucial with the growing options available. In construction, tools should typically address schedule, cost, and risks. They can also assist with on-site health and safety management or focus on executive-level summary data for portfolio management.
2. Organize and standardize your processes for data collection
To reap the full benefits of data analytics, you must unify and standardize your data and processes. The better the quality of your input data, the higher the quality of your output data, resulting in more value for the end-user. In a shared environment, this could entail establishing a centralized data platform with standardized entry and organization methods. Given the large volume of data involved, efficient input organization can significantly expedite the analysis process, especially given the large volume of data involved.
3. Focus on your main project objective
It’s best to focus on a specific area when looking for data analytics solutions for your next project. Excessive data can cause confusion and inefficiency. Determine specific key areas where you want to enhance project predictability, like detecting and addressing safety or quality concerns. Decide on the insights you need, assess your current input format, define the desired output format, and then choose a tool that aligns with these requirements.
Precision and efficiency are crucial in capital projects. Embracing data analytics within your PMIS is the key to successful project management. Choose OnIndus for expert guidance on this transformative journey.
We offer tailored solutions, recognizing the uniqueness of each capital project and customizing data analytics to meet your specific needs. OnIndus ensures a smooth transition during data migration, preserving historical project data integrity with care.
Our ongoing support extends beyond data analysis and is dedicated to optimizing your PMIS for long-term success. At OnIndus, we see data analytics as an investment, focusing on tangible results such as efficiency gains, cost savings, and improved decision-making to maximize your return on investment.