5 ways the water industry is ready for a big data revolution

Posted 7 August 2017

The water industry is ready for a big data revolutionAs the digital capabilities of water industry organisations grow by leaps and bounds, questions about the use and management of big data are flying.

We asked five industry leaders for their thoughts on the biggest challenges the water industry currently faces when it comes to data. Here’s what they had to say. 

Joanna Batstone
VP and Lab Director, IBM Research – Australia

The biggest challenge that the water industry faces is being able to turn data into insights – and the water industry isn’t alone in this challenge. 

With the proliferation of smart devices, the Internet of Things (IoT) and new meters, the volume of data is increasing exponentially. But just collecting data isn't helpful; the industry needs to be able to identify its core use cases and experiment with data to create new value.

For example, the streaming data from IoT and smart meters can augment traditional data sources. When you start overlaying weather data and external data, such as social media posts and traffic information, new patterns emerge that could uncover new linkages in the network. 

Creating a digital twin is one way to unlock this new value. A digital twin is a virtual replica of a physical asset used to visualise its performance in operation, with feedback used to improve its design and efficiency.

Roch Cheroux
CEO, SA Water

For the water industry, one of the biggest challenges big data poses is how we use it to drive business, and ultimately customer, value. We know the data is available, related cost barriers are coming down and storage is no longer a concern. The issue is making sense of what you want, and what problems you want it to solve. 

Ensuring it’s accurate and fit for purpose across the organisation is also important. Big data can be used for multiple purposes and so needs to be suitable for operational tasks as well as strategic analysis.

The goal would be to use it to support better, more informed decision-making that makes operations more efficient and customer-focused.

Another challenge with the use and especially sharing of big data is security. We’ll never be in a position where there’s no risk though, so it’s about balancing these risks with the benefits big data can bring.

It’s important our employees have the skills and knowledge to use and analyse data to identify new and better ways of doing things, as well as identify issues or problems before they impact the customer.

Kumar Parakala
Global Digital Leader, GHD

Using predictive analytics based on large volumes of data and advanced analytical tools for proactive decision-making is the big data challenge for the industry.

Water utilities have a lot of data but have limited understanding of its use. Although more companies are recognising the value of data as a strategic asset, they might not necessarily have sufficient internal capabilities to generate real value from it. 

Accessing these skills requires collaboration, partnerships and co-creation. 

Fang Chen
Senior Principal Researcher, Machine Learning Research Group, Data61, CSIRO

The biggest big data challenge for the water industry is how to use multiple data sources to better serve customers. Some utilities already gather customer feedback, but it’s not used in decision making. Figuring out how to do this will help the industry to shift from asset-centric to customer-centric.

Another big data challenge for the industry is that it needs to embrace the element of risk that comes with digital transformation. Risks and vulnerabilities are an inherent part of using digital systems, so utilities need to review security measures in terms of how control systems are segregated from each other to avoid a domino effect. 

The human element needs to be kept front-of-mind as well, as most cyber attacks happen due to human error and things like phishing scams. Employees need to be prepared and trained to deal with potential attacks. There needs to be an instant response process – once you find an early alert that something bad might happen, you need to have a procedure in place to minimise the risk of it spreading.

Dr Sander Klous
Partner-in-Charge Data & Analytics, KPMG – The Netherlands

The definition of big data is, in some ways, still unclear, so it’s best to approach the issue with an agile mindset. Open-source data is a good way to accomplish this. 

It’s a significant shift to make everything open source, which allows you to reduce the complexity or data systems so you don’t have to reinvent the wheel every time. Inevitably the issue of ownership comes up, but that’s not the most relevant question, because you can always make copies of data. 

The question should be ‘who controls the data?’. Control of data is a competitive advantage, and forces us to change the way we think and conduct business. It’s essential in the water industry to manage assets, communicate with customers and glean insights to anticipate the future.