PoV: The Rise of Decision Support Tools in Water/wastewater
Updated: Feb 17, 2021
We are of the opinion that ‘digital water’ has unfortunately joined the ranks of nebulous corporate strategy, and therefore something that’s hard to calculate ROI on, translating into an endless string of consulting engagements to help ‘roadmap’ so-called ‘digital technologies’.
Recommendations for ‘going digital’ likely include a sensor here, a dashboard there, digital workforce training, how to get stakeholder buy-in to ‘digital’, and maybe even the suggested use of ‘big data’ to more effectively diagnose problems. All good ideas, and we are not against ‘digital’, but we’ve noticed that thought-leaders in water/wastewater are increasingly pointing the need to think in terms of tools that enable smarter decision-making with a clear vision of the ROI, rather than wallowing in C-suite strategy and nice sounding ‘digital water’ press-releases.
What is a Decision Support Tool?
Decision Support Tools (DSTs) come out of the data science realm, and are designed to help owners, operators, and end-users at all levels of the enterprise make more effective decisions by leading them through clear decision stages and presenting the likelihood of various outcomes resulting from different options. In plain English, these are tools to help you know when the best time to do something is, what the status of something is, and what options you have to get an optimal result. One executive we know refers to DST as his dedicated analyst who tells him what needs to know before he knows he needs it. In water/wastewater, whether you are facing a quality or quantity decision, CapEx or OpEx decision, the DSTs now exist to enable you to make the a more informed decision, mostly without the need of expensive outside advice.
Recent breakthroughs in data science and network connectivity, decision
support science, systems, and tools have entered water/wastewater and are getting adopted by forward-thinking executives
What is an example of a Decision Support tool?
When a car (i.e. an asset) is brought into a dealership because the engine light is on, the initial step is to connect the car to a computer and pull historical information from the vehicle (i.e. Data). The data is displayed in a dashboard with graphs and gages (i.e. Knowledge), and then combined with information about re
pairs for other cars of this make and model, data from the manufacturer and records of previous service for this vehicle, and using algorithms (could be AI based) a report is generated, outlining what may be wrong and recommendations on how to address the issue (i.e. Insight). The mechanic reviews the recommendations, orders the recommended parts and performs th
e repair (Action). The tool used to bring in Data, transform Data into Knowledge, and develop Insight that then is acted on is by definition a Decision Support tool.
What are some companies bringing Decision support tools to the water space?
While the phrase ‘decision support tool’ may not appear on their marketing collaterals, there are many companies who are in fact delivering DSTs to support their customers manage decisions relating to water/wastewater. Some include:
Conservation Labs offers building owners, operators, and occupants a DST that non-invasively collects water flow data by leveraging breakthroughs in acoustic sensing, then turns the data into knowledge via anomaly detection and analytics, and lastly provides insights and recommendations (eg: leak, maintenance, etc.) thanks to their AI.
AquaOso created a DST that enables their customers improved ability to manage water quantity risk. By leveraging data aggregation/labeling and AI-derived insights, real estate and agriculture executives can now see near and long-term flooding and scarcity risk for specific parcels of real estate.
SimpleWater offers a suite of DSTs that enable their customers to make more informed business and operational decisions relating to water quality risk. Accessing SimpleWater’s mountain of water quality data via API, customers are able to heat-map water quality risk by watershed, city, neighborhood, block and even a single address.
FrogLabs is a DST enabling their customers to make more informed business and operational decisions by leveraging their climate-powered machine intelligence. Knowledge of climate transformation, or even next week’s weather, is ultimately a tool for managing water-related risks.
The beautiful thing is..
Four things, actually.
DST’s are almost entirely subscription-based, enabling you, the owner, operator, or end-user, to test-drive the tool, understand the ROI, then commit to a long-term integration of the tool into your day to day operations.
Integrating DST’s into your work processes does not require a large data infrastructure project … it can be implemented in a measured and modular fashion, each with a well-defined and measurable ROI.
DST’s bring value at all levels of an organization, from helping the service tech trouble shoot and repair something right the first time, to supporting the building manager prioritize maintenance work, help the CFO better understand how long it will take the business to recover from the downturn, and help HR with staffing plans.
DSTs empower owners, operators, and end-users to become more self-reliant, and while consultants are still needed for more complex projects, many day to day firefights can be handled without them.
So, can we keep using the term ‘digital water’?
The term “digitization” is here to stay, as is its cousin “Smart Water”, collectively they are amongst the most compelling opportunities in water/wastewater over the coming 5 years. However, key for many in both private and pubic sectors, digital transformation needs to be in “bite-size” pieces which means utilizing subscription-based DSTs to demonstrate the value / ROI before long-term commitment. In summary, embracing the concept of Decision Support Tools represents an effective way accelerate organizational buy-in and overcome the inherent organizational inertia to so-called ‘digital water’.
*This is part of a series of contributions to SWM addressing the growing role of data science innovations in water/wastewater. Mazarine Ventures is an investment group focused on technology innovations that address societal and industrial water/wastewater challenges. Data science innovations is a primary area of investment focus.
John Robinson, Partner, Mazarine Ventures