SAS, global leader in analytics, and Arab Academy for Management Banking and Financial Sciences (AAMBFS) have successfully concluded a two-day Forecasting Hackathon for Sustainability and DataForGood, powered by the ESG DataForGood Center of Excellence.
The event brought together over 70 students, fostering innovation and collaboration to address real-world challenges using SAS Viya. The hackathon aimed to inspire the next generation of data enthusiasts to develop data-driven solutions that contribute to sustainable development and societal impact.
“This hackathon reflects our commitment to equipping students with cutting-edge knowledge and practical tools to address pressing global challenges,” said Dr. Mostafa Hodeib, President of The Arab Academy For Management, Business and Financial Sciences. “By collaborating with SAS, we are empowering the next generation to harness data for sustainable solutions and create meaningful impact.”
Participants gained hands-on experience and practical knowledge in forecasting and data analytics throughout the event. They also analyzed the impact of real-world events, such as natural disasters, public policy changes, and sales promotions, to understand their effects on forecasts.
“The hackathon not only provided students with valuable skills in forecasting and analytics but also inspired them to think creatively about how data can drive sustainability and change in their communities” added Ahmed Kamal, Senior Global Academic Manager at SAS.
The top four teams, whose projects have the potential to significantly impact environmental and sustainability efforts in the future, were selected and awarded monetary prizes for their solutions.
1st place – team Future Forecasters: Forecasting Solar Power Production
The team addressed the issue of frequent power outages disrupting servers and critical operations, leading to significant downtime, operational delays, and financial losses. Their objective was to predict energy production, identify seasonal trends, forecast site availability, optimize resource allocation, and facilitate energy trading. To achieve this, the team employed various regression and statistical models to forecast solar energy production based on total energy output (kWh).
Future Forecasters generated a Heat Map for seasonality Pattern Analysis and applied some regression and statistical models in order to forecast solar energy production based on the total energy produced (kWh). This approach has facilitated for the team to plot model predictions and the true values.
Team Recommendations:
- Investigate Site- Specific Factors
- Optimize Site utilization
- Enhance Midday storage systems
- Scale Investments based on performance
2nd place – team Harmony: Yield Forecasting: Addressing Food Security in the Era of Climate Change
The team addressed the global issue of food scarcity, highlighting that 828 million people face hunger daily, with 10% living in extreme poverty. In Egypt, where over 30% of the population lives below the poverty line, access to staple foods is crucial. Climate change exacerbates this crisis, with up to 30% of global crop yields at risk.
The team implemented the ARIMA Forecasting Model to analyze historical trends and predict future crop yields based on climate factors, enabling early interventions. The findings are alarming—forecasts indicate a significant decline in wheat yields in Egypt by 2030 if no action is taken.
The team recommends leveraging innovation as a key for a more secure future and environmental protection.
3rd place – team Quantum Thinkers: Drugs Supply chain Optimization and Forecasting
The Quantum Thinkers team developed a pharmaceutical forecasting model designed to prevent drug shortages by accurately predicting the demand for medical supplies. They leveraged Random Forest models for their ability to capture complex, non-linear relationships within the data—an essential feature when addressing the diverse and intricate patterns of pharmaceutical sales and demand.
Team Recommendations:
- Enhanced Forecasting models
- Supply chain Optimization
- Bounce Rate reduction
3rd place – team SHAI: World Day for the Reduction of CO2 Emissions
The team created a scenario where a government agency or environmental organization seeks to forecast greenhouse gas (GHG) emissions to assess regulatory policies, identify improvement areas, and plan climate change mitigation efforts.
They used The Prophet model, known for its ability to analyze time series data with seasonal patterns and long-term trends. Analysis revealed that Egypt’s GHG emissions are expected to rise due to its economic growth, energy needs, coal dependency, population increase, and urbanization. While Egypt is advancing renewable energy and climate policies, balancing development with emissions reductions remains a challenge.
In conclusion, to combat climate change, key sectors must adopt sustainable practices. The power industry should transition to renewable energy, while the transport sector invests in electric vehicles and efficient public transit. Cleaner technologies and energy efficiency are vital for industrial processes and buildings. In agriculture, sustainable farming can reduce methane emissions, collectively driving progress toward a sustainable and resilient future.
Team Recommendations:
- Power Industry recommendation: Accelerate the transition to renewable energy sources like solar and wind.
- Agriculture: Promote energy-efficient building design and practices.
SAS and AAMBFS Forecasting Hackathon showcased the power of analytics to drive meaningful change in sustainability efforts. By fostering collaboration, equipping participants with cutting-edge tools, and emphasizing practical applications, this event demonstrated the importance of empowering the next generation to tackle global challenges with innovation.
