Member Spotlight
Mason Throneburg, CEO & Co-Founder – Confluency
Confluency is a leading water startup that helps teams harness the full capabilities of simulation models through the integration of advanced data analytics, and deep insights of engineers and operators, to make better decisions. They collaborate with utilities and consulting firms to develop a clearer understanding of the water system and develop tailored strategies for utility digital transformation. Confluency sees an important gap in the digital water space, integrating insights from simulation models together with machine learning to support decisions across a range of timescales – operational, planning, and strategic. Confluency is funded by the National Science Foundation (NSF) under the SBIR program to develop AI solutions for water.
In working closely with utilities to integrate traditional modelling tools with analytics, how different have your approaches been based on where they are in their digital transformation journey?
Every utility is at a slightly different place in their digital transformation journey, responding to slightly different pressures and priorities – so we start by focusing on their desired outcomes and the technical capabilities and resources available. There is no one-size-fits-all solution when it comes to digital transformation. We specifically focus on value that comes from combining simulation-based models which provide “what-if” insights, together with data-driven machine learning models – but the customer needs to drive the technical approach, not vice versa. For instance, if it’s related to water distribution, the approach we take depends on the engineering models they are currently using, the data that is available, and their planning or operational goals. The utility’s digital transformation maturity and priorities also helps us determine how to help propel transformative solutions.
SWAN is all about collaboration. How do you partner with engineering firms and solution providers in delivering more holistic value to utility customers?
Confluency really values the importance of partnerships and collaboration. Being a small solution provider with an extensive consultancy background, we see how digital transformation transcends system boundaries and involves integrating people and expertise from different backgrounds. Our solutions embed various components like simulation, automation, analytics, sensors and metering, and engineering services, which naturally involves multiple stakeholders. Integrating these multiple perspectives and priorities is one of the biggest challenges – and we believe that better tools and at-a-glance insights can facilitate that alignment. One thing we emphasise is to not go for a one-and-done approach with our partners, but rather always look forward to collaborating beyond a single project or a process.
While working on operationalising a utility’s model, what are steps you take to account for the varying SCADA generations and compatibilities?
Yes, SCADA operations and accessibility are some areas that get tricky. One advantage of our hybrid simulation and data-driven approach is that we often begin to explore solution benefits in an offline context, where managing data privacy is important but security risks are reduced. This helps to establish a business-case and generate buy-in; we then incorporate real-time data to use the model to provide operational insight. Data from monitoring providers can often be accessed directly through their APIs. Accessing the SCADA data involves managing cybersecurity risk; we build security in at the base layer of our software – and we also reduce risk because our solution is advisory guidance, and so does require write-access to the system. This is also an area where partners with a deeper expertise with SCADA systems and network security can help with data acquisition and managing network security protocols.
As a solution provider, how would you address the counterargument that digital transformation is costly and runs people out of their jobs?
That is a question we come across often. Our belief is that software should augment the capabilities of engineers and operators, not replace them. The people who have worked with a system for 5, 10, 20 years have tremendous knowledge in their brains; we want to capture that knowledge in simulation and machine learning models to make it more systematically and broadly available. The great thing is, this then frees up time for the higher-value work that people are better at than machines. Regarding cost, we strongly believe that solutions need to be affordable – and that the costs need to make sense compared to the value provided. We are focused on developing a scalable platform that can be customised, enabling a utility to bring on additional functionality incrementally as the business case is established. In the medium to long term, improved operational efficiency and increased integration with planning objectives lead to improved system management and overall cost reductions.
Any words of advice for young professionals passionate about water and analytics on how they prepare themselves (ex. software development upskilling) to enter the workforce of solution providers like yourself?
The first piece of advice is to raise your hand and put your interests out there – I think all companies in the SWAN forum are looking for motivated talent to help deliver greater value from data, models, and automation. Once you know what you want, you may also need to invest in yourself. Go that extra mile to upskill, even if it requires some evenings or weekends – these skills will open up lots of opportunities for the rest of your career. I’d suggest young engineers spend time in the water workforce and master a particular technical domain (e.g. hydraulic modeling, treatment processes, etc.), so they really deeply understand the problems the industry is trying to solve. Lastly, look for opportunities to improve software development skills by participating in open-source projects, where you can obtain great feedback and further develop your network.
