The Holy Grail of Tenders
What if you could know in advance which tenders you'll win? For decades, this has been the holy grail of public procurement. Today, thanks to predictive analysis and machine learning, this fantasy is a tangible reality.
iaLicitaciones has developed algorithms that analyze more than 50 variables per tender, processing data from over 200,000 historical awards to predict with mathematical precision your chances of success.
Predictive accuracy
Average annual savings
Variables analyzed
Awards processed
How Predictive Analysis Works
1. Massive Data Collection
Our algorithms continuously analyze:
- Complete award history by organization
- Winning company profiles
- Price and technical bid patterns
- Seasonality and economic context
2. AI Processing
Advanced machine learning that identifies:
- Hidden correlations between variables
- Buyer behavior patterns
- Emerging market trends
- Sector-specific success factors
The 5 Key Factors in Predictive Analysis
Each factor contributes to the final success probability calculation
Buyer History
25%Award patterns, preferences and historical criteria
Competition Analysis
20%Regular participating companies and their winning strategies
Evaluation Criteria
20%Specific weight of price vs. technical in each type of tender
Timing and Context
15%Time of year, available budgets and project urgency
Technical Characteristics
20%Technical specifications and required level of complexity
Real Cases: Predictions in Action
City Council - IT Services
AI predicted high probability based on similar award history
Regional Government - Consulting
Analysis advised against participation, saving significant resources
Ministry of Health - Equipment
Precise price optimization based on AI predictions
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