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Charging Station Allocation

Identyfing location factors before expanding to new places

Challenges
  • Increasing Market Share: As a leading electric vehicle rapid charging network, expanding market presence and capturing a larger share of the market is essential

  • Maximizing Charger Utilization: Enhancing charger usage remains the most critical business key performance indicator (KPI)

  • Optimizing Charger Placement: Implementing predictive models to strategically locate chargers is a key business priority

  • Overcoming Consultancy Limitations: Traditional consultancies have proven expensive, lacking innovation, and involving exorbitant ongoing maintenance costs

Solutions
  • Established a Scalable Data Platform: A scalable data infrastructure with continuous integration capabilities was developed to seamlessly incorporate new data sources

  • Integrated Extensive Data Features: Combined company utilization data with over 500 data features from open-source and privately purchased sources, including climate, road traffic, car ownership, amenities, and socio-demographic factors

  • Developed a Comprehensive Predictive ML Model: Built a robust predictive machine learning model that effectively explained a significant percentage of the target variables

  • Visualized Results in Existing Tableau Environment: Leveraged Tableau platform to visualize results and KPIs for local entities

  • Enhanced Sales Presentations with Interactive Maps: Utilized KeplerGL to create breathtaking interactive maps, significantly elevating the impact of sales presentations

Values
  • High Stakeholder Confidence in Model Outputs: Key business stakeholders have significant trust in the accuracy and reliability of the model’s outputs

  • Direct Impact on Site Approval Decisions: The model directly informs and influences whether sites are approved for construction

  • Flexible Integration of New Data Sources: Owing to the solution’s thoughtful and adaptable design, new data sources can be easily added and automatically integrated into the model

  • Cost-Effective with Superior Outcomes: Achieved a solution that is four times more cost-efficient than alternatives while delivering better results

Roles

Cloud Engineer, Spatial Data Scientist, Machine Learning Engineer, Project Manager, Data Visualization

Technologies

Sectors

Energy & EV

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