Creating a data-driven culture in your water utility with low-code and no-code analytics

Water infrastructure, like treatment plants or networks, can generate lots of data. But is it useful information? How can captured data become actionable knowledge for planning, crisis management, and problem solving across organizations? Data is only useful when experts can interpret and share it so an organization can take action. We dig into new ideas around no-code and low-code analytics to show you how they can improve the way you work.

Turning data into action with domain analytics

In water and wastewater treatment plants and networks, data is collected from flow meters, water quality chemical sensors, and pressure and tank level gauges. In many cases, it is imported into spreadsheets for analysis. And there it usually stays, static and difficult to share without meetings to explain the data. The amount of data collected in this way can become overwhelming and unmanageable.

Even worse, it can be difficult to know which version of a data set is the most relevant and up to date, casting doubt on what the single source of truth is for problem solving. Enabling proactive management of water treatment plants and networks, which are vital for public health and environmental protection, requires better solutions. It requires better data management.

To turn data into knowledge, domain experts, those senior engineers and water specialists with years of accumulated knowledge, need to create analytics from accurate data, enabling their organizations to act on the results of real-world events and predict possible future scenarios. Ideally, their system can automate data collection, cleaning, and consolidation to provide a foundation of data that they can manipulate to gain deeper insights. Such systems become more powerful when they contain visual representations of data such as maps and images of assets including pumps and tanks, waterways, energy consumption measurements, and chemical test results.

With these kinds of tools, organizations can build knowledge from data and get on the path to creating data-driven cultures, fostering greater integration and cooperation among operations, engineering, and management teams.

Becoming a data-driven water culture led by domain experts

In his excellent book Principles of Strategic Data Science: Creating Value from Data, Big and Small, water data science expert, civil engineer, social scientist and reality disruptor Dr. Peter Prevos points to the power of harnessing the expertise that is often locked inside individuals who have spent decades working in the water utility industry. He recommends locating these subject matter experts within a utility and teaching them the value and skills of data science and analytics.

Dr. Prevos is a Dutch civil engineer with a Doctor of Philosophy in Marketing (!) who also manages the data science team at Coliban Water in Victoria, Australia. When he’s not performing data science himself, he’s lecturing around the world, writing articles about logic and magic and the limits of reality, and offering anti-guru business and marketing advice for engineers.

As Prevos sees it, combining domain knowledge with computer science and mathematics principles has the opportunity to create data scientist “unicorns” who can help lead a data-driven culture throughout an organization. In addition to more heady topics, his books and lectures demonstrate the value of teaching subject matter experts the ability to code to combine their domain knowledge with analytic capabilities.

Dr. Prevos’s approach is a “high code” approach, teaching engineers to embrace computer science and learn to code so they can create bespoke applications that are tailored specifically to the unique needs of a water utility.

Domain knowledge for water engineers

What is “domain knowledge” in the context of water work, and how can we use it to improve water plant and network operations?

• Water quality analysis: Domain knowledge helps identify parameters to measure, such as pH, turbidity, dissolved oxygen, and acceptable thresholds, to meet regulatory standards.
• Water supply and demand forecasting: Domain knowledge touches on factors such as population growth, climate patterns, and water usage trends to develop predictive models for water resource planning.
• Leak detection and asset management: Domain expertise is needed to analyze sensor data to identify anomalies, patterns, and potential areas of concern. This information is used to develop algorithms and predictive models that optimize maintenance schedules, prioritize repairs, and minimize water loss.
• Water distribution optimization: Organizations must analyze data on water pressure, flow rates, network topology, and customer demand in order to identify inefficiencies, bottlenecks, and areas of improvement in a distribution system.

If you work in the water industry, you probably know a lot about some of these details (some more than others, naturally), but here is the big theoretical question: Are you and your colleagues currently able to create a sophisticated analysis in one of these domains, either from scratch or by using your existing tools that clearly shows others in your organization and beyond:

• How a given process works right now?
• How a specific improvement would make it work better?

If not, low-code or no-code tools could help you achieve data excellence.

Building your data culture with low-code and no-code tools

It’s no secret that many water utilities face challenges in upskilling their workforce. Waves of domain experts are retiring, and organizations must acquire and train new talent to replace them – a real challenge when stakeholders are already exceptionally busy.

This makes finding the right technology solutions especially important. Many water utilities rely heavily on mathematical domain expertise, so a possible solution for them may be a system that offers a so-called low-code or no-code environment that engineers and business users can use to build efficient process flows in a click-and-build way.

Traditionally, many water engineers have been encouraged to rely on Microsoft Excel in the early stages of their career, and some continue that way for decades because they’ve never been given the opportunity to use more powerful tools, or they’ve simply never been encouraged to try different ways of working.

Some of them have become real wizards at getting a lot out of Excel, even with its many downsides and limitations (eg, cybersecurity concerns). But we believe that spreadsheet wizards can excel even further by embracing data analytics platforms that offer simplified, customizable interfaces that have more robust computation-building power under the hood than a spreadsheet ever can.

These data-centric platforms are also the kinds of systems expected by new employees who come from the tech sector or who have recently graduated from universities. These workers who are new to the water industry want modern, easy-to-access software systems, ideally with SaaS web interfaces and APIs, rather than aging desktop programs with limited automation capabilities. They may be underwhelmed on day one if they discover that their new job is about solving problems by emailing spreadsheets to teammates and attending a lot of meetings to reach a consensus.

These employees want systems that collect, compile, and clean data, and that have collaboration features so they can easily share their findings with colleagues – and thus make compelling arguments for how to improve their water systems.

Maximizing domain expertise with Autodesk Info360 applications

Autodesk has been building the cloud-based Info360 Insight and Info360 Plant applications to provide precisely this kind of solution for small to large water utilities, as well as the consultants who serve them. We’ve tried to make it easy for a core team of knowledge staff to get started with an Info360 subscription. There’s nothing for an overtaxed IT team to install or maintain, and it’s easy to expand user access to managers, field technicians, and external partners, as needed.

The core idea behind both Info360 Insight and Info360 Plant is to empower domain experts to build analytics using real-time sensor data without the extra work of maintaining databases or learning in-depth coding. These apps provide not just analytics but also workflow solutions, enabling water utilities to quickly identify incidents in their systems, check and correlate multiple resolution scenarios on demand, and apply recommended actions to rapidly resolve system issues.

By way of example, Info360 Insight provides detailed water network analysis capabilities like:

• Water loss, water balance, and non-revenue water
• Pressure and energy management
• Demand and fire flows

And Info360 Plant enables engineers to keep a watchful eye on water plant operations by analyzing:

• Waste and material consumption
• Equipment monitoring, asset health, asset drift
• Pump performance
• Energy and chemical consumption
• Sustainability calculations and targets

Info360 applications can automate data collection, cleaning, and consolidation of plant and network data. The browser-based interface provides a simple point-and-click analysis of associated data, analytics, mapping, images, and assets. Equally as important, the cloud-based software lets all stakeholders securely share and access all needed information from any browser.

How our customers build workflows using analytic expressions

Building new analytic expressions starts by choosing existing formula templates or creating new ones based on data sources such as physical and visual sensors, as described below for flow and level sensors in settling tanks.

Once data sources are defined, engineers can apply different parameters, such as average, opening, highest, lowest, and closing rates. Outputs, such as the moving average to determine tank turnover, are added next. Info360 Insight includes various functions to create KPIs, which extract critical data for analysis. While creating the expressions, the system will verify that formulas are correct, and check whether elements are missing or out of place.

In-app assistance is available within Info360 Insight and Info360 Plant software’s analytic builder as you write analytic expressions. The analytic builder provides a detailed menu of analytic functions to help you choose the right function when building an expression. You can select the function from the analytic, contextual help, drop-down list as you create the analytic expression you’re working with, and that function will be added to the expression. This means you can develop calculations without having to use special characters in the output naming of a node.

Contextual help while you build expressions makes analysis easier, and it can help you discover related functions that can apply your domain knowledge to new data sets. Refer to the online reference guide links at the end of this article for an in-depth view of the online help system.

Domain experts can add the analytics they’ve created to a shared digital workspace for Info360 Plant or Info360 Insight, so any authorized stakeholder can readily reuse them. New inputs can be easily added to expressions to monitor specific operations across the organization.

Relying on a single source of truth inside Info360 applications helps ensure that decisions about water operations are based on consistent data instead of individual biases and preferred methodologies. The system gains value as the knowledge of domain experts is spread throughout the organization in reliable analytics based on clean, up-to-date data. Ultimately, this empowers employees to spend less time on manual tasks and more time making data-informed decisions that are based on how processes actually work in the real world.

Go deeper into low-code and no-code

We believe that adopting data-driven analytics is one of the most important steps in every water utility’s digital journey. Do you have any data scientist unicorns in your water utility waiting to be discovered? You should nurture their talent. Tools like our Info360 SaaS apps can help them extract insights from complex data sets and turn them into actionable recommendations. They can use data to fix ongoing frustrations with leaky pipes and solve water quality conundrums, moving your culture away from outmoded ways of working – and towards more sunshine and rainbows.

Water professionals who are ready to embrace data are in luck. There’s a big trend going on here. Low-code and no-code analytics can help water utilities build a data-driven culture and change their ways of working:

• Download our e-book “Building a water data culture: How utilities can use operational analytics to turn data into decisions.“ You’ll find plenty of evidence for the value of a data culture, along with case studies that show how Stantec helps Wellington Water use data to optimize their pumps to save significant money on electricity costs and how Bristol Water uses data to keep their water quality as high as it can be.
• Read the Zapier data report: The rise of no-code, which has some excellent survey results that show the big interest among early adopters of no-code tools.
• Not sure about the difference between no-code vs low-code? Do the semantic differences matter if they both propel you forward? Read No Code VS Low Code. What’s the Difference? It. Doesn’t. Matter.
• Listen to Dr. Peter Prevos on the Value Driven Data Science podcast.