to read the article?
We’ll forward it to your inbox.
In the construction industry, general contractors and first-tier subcontractors face a common challenge: dealing with risky subcontractors or suppliers. Addressing these risks can be frustrating and time-consuming, often relying on memory alone, which is insufficient in today's business landscape.
Fortunately, modern business owners have found a solution: data analytics. By leveraging computer technology that incorporates artificial intelligence into industry-specific platforms, GCs and construction professionals can effectively manage construction projects and mitigate risks associated with subcontractors.
Here are four key ways analytics can help:
1. Streamline subcontractor performance tracking
Keeping tabs on subcontractor performance is crucial. Instead of waiting for issues to affect multiple jobs at various stages, data analytics allows you to detect abnormal variations in labor, materials, and time allocation for all subcontractors, regardless of the project's size. By monitoring their workforce, responsiveness, and overall execution and management abilities, AI-driven reports provide clear insights into subcontractor pre-qualification and management.
2. Monitor subcontractor reputation
While a subcontractor may have performed well in the past, it's essential to stay informed about any changes. By integrating analytics into your construction technology toolkit, you can automatically check for liens or any new OSHA data since your last collaboration. This eliminates the need for constant monitoring, as AI can perform due diligence using third-party data and ensure you always know who you're dealing with.
3. Optimize payment schedules
Ensuring that subcontractors bill you accurately is vital to mitigate risk exposure. Over-billing or under-billing can significantly impact your margins, especially if you realize the issue after making payments. With data analytics, you can strategize when to pay subcontractors, minimizing financial risks that might otherwise be considered an unavoidable cost of doing business.
4. Learn from past experiences
Learning from past experiences is crucial for general contractors. Instead of relying on memory or checklists, data analytics and construction management software can be used to create a "lessons learned" database. This database tracks historical subcontractor performance and helps identify similar occurrences in the future. By implementing a monitoring system that flags potential risks, you can stay up-to-date on abnormalities in subcontractor activity, such as timely payments and adherence to agreements. This proactive approach ensures that you're not caught off guard by potential problems and allows for timely intervention.
Predictive risk assessment means increasing your margins
Data analytics can enable predictive risk assessment by analyzing various factors, such as subcontractor performance data, project complexity, and external influences like weather patterns or material availability. By identifying potential risks in advance, GCs can proactively implement mitigation strategies, allocate resources effectively, and minimize the impact of unforeseen events on project timelines and budgets.
Instead of relying on institutional knowledge or a fallible memory, strategic general contractors and first-tier subcontractors use technology to keep track of construction companies worth partnering with.
By integrating data analytics in your business you will have a valuable tool for continuous improvement and benchmarking within subcontractor management. By analyzing performance metrics and comparing subcontractors' performance against industry standards, GCs can identify areas for improvement and implement best practices. This data-driven approach fosters a culture of continuous improvement, leading to enhanced subcontractor relationships and better project outcomes over time.
Talk to our team to learn how Briq can help your business make better business decisions. Book a call today.
