An intuitive platform to predict and diagnose the urgency of an incident within utilities infrastructure
Industry experts from the VEC created an intelligent web-based platform to improve incident diagnosis and resource allocation accuracy with real-time updates of customer incidents.
A high-fidelity simulation considering the actual vehicle schedule, resource planning allocation, traffic and random job failure was carried out to estimate the key performance indicators (KPI) of the customer decision support tool. The platform provides a spatio-temporal forecast of job volumes using an Autoregressive Moving Average eXogenous (ARMAX) model, based on the historical job trends and prevailing weather pattern data.
Studies have shown that the model is 30% more effective than conventional methods of diagnosing the urgency of a customer-raised order.Download Case Study
Our support meant Amey Utilities could:
- Easily monitor and identify behavioural trends within incident diagnosis
- Analyse and predict incidents and their outcomes
- Replace time consuming conventional methods of multi-source data analysis
- Build in flexibility and resilience into their resource planning
- Be more precise in vehicle assignment
- Process optimisation in resource allocation
- Add strategic value to incident diagnosis
- Quicker intervention times
- Build complex logical queries with multiple criteria, gaining greater insight
- Vehicle allocation accuracy increased by over 35%
- Diagnosis accuracy increased by more than 13%
- Enhance customer satisfaction
- More accurately predict, by 50%, the weather’s influence on incidents and the job volume of work
- Save time and costs - up to 30%
"This project has shown that by using advanced data analytics we can develop a robust predictive incident planning tool that has the potential to improve customer experience across the water sector. The VEC has demonstrated methods to overcome our challenges with algorithms that can be used in a commercial solution to deliver productivity saving benefits. The professional approach of all the VEC team was exemplary, and we are keen to continue future projects with the team."
Innovation Business Partner