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B2B Customized Bid Winning Predictor
Objective
Provide an approach to reduce the cost of estimation by predicting the likelihood of winning the Bid before expending effort on estimating the product mix and quantities.
Industry: Commercial Steel Manufacturer
Services: Technology Innovation
Technology: ML Model for Bid Win Predictor
Provided justification for strategic sales investments on certain bids / markets to improve win likelihood
Savings of
3%
on multi-million dollar projects by better predicting bidding win rate
Used Machine Learning to create visibility to the Sales team to evidence the probability for success
Our Client
The client is a commercial steel manufacturer that operates steel furnaces as well as fabrication facilities. They engage with several General Contractors to submit bids to construction projects.
Challenge
A key pain point in the bidding process is the costs associated with estimating product mix and quantities needed for an opportunity. Both human resource costs as well as product costs (over/under-estimates) have an influence on Bid outcomes.
Approach
AI/ML model to provide visibility to
- Identify attributes that influence bid win probability
- Compute percentage probability for winning potential opportunities
Outcomes
- Data Integration to extract, transform and build a 360-degree view of Bids from Salesforce.com, Financial Forecasting, and SAP BW Database.
- Predictive Analytics Model – that predicts the probability of winning a bid driven by the minimal coalition of attributes, making for an easier for implementation within Salesforce.com
- Simulation and Modeling of prescriptive recommendations and what-if scenario analysis using parameter tuning and measuring the outcome changes
Impact
- Expected savings of $1.2 M by not bidding on opportunities with low likelihood of winning
- Provided justification for strategic sales investments on certain bids / markets to improve win likelihood
- Visibility to the Estimator and Sales team effectiveness
- Visibility to General Contractor partnership effectiveness
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