Learnings

Outcomes

As the project is in its initial phases, specific outcomes are not yet available. However, the project is on track to develop a model targeting PSR, FP, and LNB customer identification and engagement. Furthermore, the project outputs will facilitate improved support for vulnerable customers, offering actionable insights into successful FP initiatives and effective assistance during the energy transition. 
 

Lessons Learnt

The project is still in its early phases, and while a comprehensive list of lessons learned is not yet available, several key insights have emerged: 
Early Identification of Data Access Challenges: 
It is crucial to identify any potential challenges or delays in accessing required data sources early in the project. This allows for prompt action to resolve issues and prevents setbacks that could impede progress. 
Importance of Data Quality: 
Data quality management should be prioritised from the beginning of the project. By ensuring data accuracy and integrity from the outset, delays caused by erroneous or incomplete data can be minimised. High-quality data also leads to more reliable and trustworthy project outcomes. 
Comprehensive Data Collection: 
Thoroughly identify and collect all relevant data sources needed for the project at the outset. This comprehensive approach ensures that the models developed are based on a wide range of data inputs, resulting in more robust and accurate analyses and insights. 
Data Quality Assurance: 
Implementing rigorous data cleaning, pre-processing, and integration procedures is essential for maintaining data quality and consistency throughout the project lifecycle. By adhering to these practices, potential errors or inconsistencies in the data can be identified and addressed early, ensuring the reliability of project outputs.