Intelligent Water Systems

TOWARDS MORE Intelligent

WATER SYSTEMS

By Seyi Fabode, CEO at Varuna

When you look through most of the textbooks and papers that are written to train technicians in the water industry, one can very quickly identify that the lens through which most of these are written is one where water ‘usage’ is the prevailing theme. To a certain extent, this usage lens is/was understandable. It was measurable and trackable. You could also tie roles and incentives to this measurable metric in the water space. But that lens is now too cloudy. We need a new more intelligent lens from which we view, design, and run our water systems. We need a more biological lens. And by biology I mean a lens that focuses on quality. Yes, I know that the industry currently works to ensure that the water coming out of taps is clean and drinkable (for the drinking water side of the industry which we at Varuna focus on). But we have definitely not used this as the lens for the development of most of the new approaches and technologies in the industry. We live in a world where we have at least 30,000 new chemicals developed over the last 20 years and we do not know the effects of these chemicals on our drinking water. We do not know because we haven’t even developed tests to check whether our water is contaminated with these new chemicals. So we carry on focusing on the obvious problems we can address: non-revenue water losses.

We need to redesign our water systems towards more intelligence in detecting, managing, and running our systems to prevent biological issues. And by biological I mean quality. Because biology is what customers experience from their water utility. Most of us cannot agree on the right quantity of water for a consumer to drink. But I have yet to meet a person who does not want to drink clean water. If that, clean drinking water, is the metric that we all agree on, why aren’t we designing our water systems and running them with that as the most central factor? It’s time we did that.

I’ll stretch the biology analogy a step further and talk about the cell towers in the telecoms industry. Cell towers were designed to work like biological cells with the optimal ‘cell design,’ the spacing and structure between towers, selected to ensure the best quality signal for customers. Biology being used to define design and consequently provide the best user experience. Water lags telecoms, in terms of adoption of technologies and approaches, by ~10 years and it is time for us to start borrowing from that industry a lot more than we currently do. Because what is innovation if not taking ideas and approaches from one place and applying them in another? We need to look to biology to design intelligent water systems. What does this look like?

Intelligent systems are organizations that optimally use human intelligence with technology-enabled insights to make smart decisions, especially in the face of uncertainty and complexity. The water industry has typically focused decisionmaking based on the silo of information that is readily available. The distribution system information silo, different from the plant system information silo, separate from the water quality database populated with physical sample data, all further hindered by the asynchronous nature of the data feeds and no connections between them. Integrating all these streams of information and knowledge is the only way for the water industry to survive an increasingly complex world where weather/climate change/ consumer expectations are all putting a strain on water systems – especially the small to medium water systems. Integrating the water data/info silos for decision-making enables a water system from a state where we’re making good decisions 40% of the time to making good decisions 80% of the time. That’s a full 100% increase in the number of times we are right about an operational or a financial decision! Just because we move towards removing silos and becoming more advanced tech/human-centric businesses. According to some MIT research (Building A More Intelligent Enterprise, 2017) there are five steps towards an intelligent (water) system.

Find the strategic edge: This will require looking at the past organization decisions and situations to hone in on areas that can be improved. This will require a first step of actually digitizing all the historic data that the water system has to then model/simulate past scenarios based on these.

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Run prediction tournaments: Discover the best methods of decision-making across the organization. The beauty of having combined the data in the first step is that you can run these competitions across many data sets and not just yours. This can be achieved using anonymized data from other water systems. Varuna’s Delta product enables this. Model the experts in your midst (within and without): Simulating decisions and scenarios. This is also akin to developing resilience plans against contaminant shock and asset shocks. This modeling and scenario planning is done using artificial intelligence. And then you move to the final step, #5. Changing the way the organization operates towards a more exploratory and predictive approach to decisionmaking using human/machine intelligence. We need to move our water systems to these intelligent approaches of decision-making. The overarching goal is to make sure that water systems can deliver clean water consistently. We need to move the industry towards an approach of removing silos to improve decision-making. Going back to our ‘cell’ analogy, we need the cells/departments to be permeable so that information can be shared across the cells to improve decision-making in the whole organism, the corporation. We need a formation of cells, all coming together to give the whole organism system views, built or designed to optimize each cell while optimizing the whole system towards ensuring safe delivery of water consistently. We need self-healing, continuous learning intelligent organizations, and more intelligent water systems. •

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