AI-Driven Resource Forecasting: A Middle Eastern Construction Firm’s Path to $1.5M Savings Annually

Industry:
about the company

Al-Qasr Constructions stands as a beacon in the Middle Eastern construction landscape, celebrated for seamlessly blending traditional designs with modern architectural innovations. With a rich legacy spanning two decades, Al-Qasr has been instrumental in sculpting the region’s skyline, bridging the past with the present.

$1.5M

Annual Savings

59.2%

Increased Forecasting Accuracy

20%

Reduction in Resource Waste

15%

Faster Project Completion

25%

Improved Resource Utilization Efficiency

The Chalange

The construction domain is intricate, layered with complexities that demand precision and foresight. Al-Qasr faced significant challenges in resource forecasting. The traditional methods they employed often misjudged the delicate balance between demand and supply. Overestimating resources led to costly surplus, while underestimations resulted in expensive last-minute acquisitions, impacting both budget and timelines.

Understanding market dynamics, geopolitical scenarios, and even regional festivities can greatly influence construction demands. Al-Qasr’s reliance on conventional forecasting tools made them vulnerable to these unpredictable variables. With each project differing in scale, scope, and design, a one-size-fits-all approach was becoming increasingly redundant and was affecting the company’s bottom line.

What did
Atlaxer Do

Atlaxer approached Al-Qasr’s conundrum with a meticulous data-first strategy. Recognizing the value of the vast data Al-Qasr had accumulated over the years, the first step was to digitize and organize this data. This goldmine was then subjected to advanced machine learning algorithms, specifically tailored to discern patterns relevant to the construction domain.

After establishing a robust data foundation, Atlaxer integrated real-time market insights into the model. Commodity price trends, geopolitical events, and even regional climatic predictions were factored in. The result was a dynamic AI model capable of forecasting resource needs with a 92.8% accuracy rate, a significant leap from their previous 33.6% accuracy.

Beyond just forecasting, Atlaxer equipped Al-Qasr with a real-time monitoring and adjustment tool. This ensured that in the face of sudden project alterations, resource allocations could be recalibrated on the fly, minimizing wastage and maximizing efficiency.

The Results

Al-Qasr’s transformation journey with Atlaxer spoke data. The company not only achieved an annual savings of $1.5M but also improved their resource utilization efficiency by 25%. The dual victory of reducing resource wastage by 20% while simultaneously enhancing forecasting accuracy by almost double validated the potency of Atlaxer’s solution.

Additionally, the real-time recalibration tool empowered Al-Qasr to navigate unexpected project changes with agility, resulting in a 15% faster completion rate. With their newfound capabilities, Al-Qasr reinforced its commitment to delivering quality without compromising on efficiency or budget.

  • An estimated annual savings of $1.5M through AI-driven forecasting.
  • 45% improvement in resource forecasting accuracy.
  • 20% reduction in resource wastage from misallocation.
  • Projects completed 15% faster on average.
  • 25% improvement in resource utilization efficiency.

Technologies Used

Python
TensorFlow
React
SQL
AWS

Ready to harness the power of data and AI to elevate your operational efficiency?

case studies

See More Case Studies