The client was looking for innovative solutions to help reduce interruptions to supply and to provide a better customer experience. The key challenge was how to identify customers most at risk of experiencing long interruptions to water supply when an incident took place. Once these “at-risk” customers had been identified, the results needed to be communicated to non-technical staff in a visual, informative manner.
Jumping Rivers utilised modern machine learning techniques to predict when an interruption event would last beyond the threshold for a customer area. Understanding that the impact was important for both NWL and the customer, Jumping Rivers built a custom simulation model for the potential impact that a specific interruption will cause. This allowed the client to not only gain insight into the probability that customers would suffer a long period without water supply but to also understand the numbers of customers that may be affected. The combination of models aids decision making in prioritisation of response to events. Thus significantly reducing the risk of customers suffering lengthy interruptions.
The model can be used standalone or as an API available to other software. In this instance Jumping Rivers also built a user-friendly visualisation web application allowing non-technical users access to the underlying predictive and simulation models. When an event occurs, engineers now have an easy way to inspect the affected geographic areas, and simulate the potential impact to the neighbouring regions.
The client also consulted Jumping Rivers about how the tool might best be deployed within their existing systems architecture, on which a range of options were presented and discussed.
The bespoke simulation model helped reduce the severity of impact to homes throughout the region with more accurate risk modelling. Additional insight found during the exploration stage of the modelling also provided some unexpected added value.
The development of a user-friendly interface allowed non-technical staff to engage and interact with the simulations to be able to make rapid decisions, leading to quicker response times and better customer service.
Northumbrian Water and other utility providers face fines for breaks in the water supply that are over 24 hours. By better understanding the customers most at risk of long interruptions, this creates financial savings for the client as well as providing better customer service.
Jumping Rivers created a data pipeline and visualisation dashboard for public and policy maker consumption. The aim was to increase transparency and encourage positive change to the workplace environment. The application allows exploration of key performance indicators stratified by a host of protected characteristics.
The client came to Jumping Rivers having already written the code for their problem in VBA. They were trying to evaluate four measurements for agreements with their clients. However, VBA is limited in speed. Jumping Rivers were required to build a bespoke R package to replace and quicken the code.
At the end of 2017, contacted Jumping Rivers. AGR TRACS International estimates the volumes of oil and gas in subsurface reservoirs. Their work involves combining a set of inputs for each reservoir layer (such as area, thickness, and up to five other inputs) – and then multiplying these inputs together.
Over the last two years, we have been working with a cutting edge electronics company to build advanced algorithms using R and Python. Since they are at the research & design stage of the development process, their data structure is unique and challenging.
After winning a Water Hub Hackathon, Jumping Rivers were contracted to create a platform for the client using R Shiny, published on RStudio Connect. The platform aggregates raw data from many third party sources both internal and external to the EA, through bespoke APIs, commercial databases, and asset management systems.
The client wanted to assess the viability of R and R Markdown as a reporting tool for creating complex, bespoke documents. We recreated sample reports for them in R Markdown, showcasing that all of their specifications could be met, and provided them with example code and training.
Jumping Rivers built a tool for creation of experimental risk assessments via a centralised web application. The dashboard allows for collaborative working during the data entry and assessment formulation, report generation and tracks versions along iteration of the process.
The IFoA required a bespoke R and RStudio platform to run their new R-based Actuarial CS1 and CS2 exams. We developed a system that delivered the exam and provided a convenient submission portal. Examiners could monitor results and feedback via a Shiny dashboard.
The client had developed an advanced, in-house Shiny application. We transformed the application into a commerical project, that is now being used by their clients.
In the spring of 2018, NHS Scotland expressed a need to move from their existing software, SPSS and SAS, to using R. The difficulty they faced was that there are over two hundred data scientists in NHS Scotland, which made training everyone in the new software a logistical challenge.
In 2018, Northumbrian held their annual Innovation Hackathon. Our winning entry, allowed enginneers to reduce leakage throughout the North East.
In spring of 2020 Northumbrian water engaged with Jumping Rivers to build a modelling solution to better understand risks to the consumer within their network in order to provide a better service.
