Asset management in the water industry is evolving, thanks to the application of geographic information systems, mobile technologies and artificial intelligence.
The amount of data generated in recent years is mind blowing. Some sources report that 90% of the world’s data has been generated in the last two years alone. Therefore, how we analyse large data sets - so-called “big data” - to inform operational management or investment decisions is highly topical and rapidly changing.
As early as the 19th century, English clergyman William Pollard acknowledged that “unless [information] is organised, processed, and available to the right people in a format for decision making, it is a burden, not a benefit”.
Transforming big data into useful operational information will give engineers a valuable decision making tool, but the need to do this in real or near real time, across all levels of a business, makes it a challenging prospect.
Big data means different things to different people in different industries.
The simplest explanation is to consider big data as the point when existing systems and processes can no longer store, analyse and convert the data being generated into useful information.
Transforming big data into useful operational information will give engineers a valuable decision making tool
Big data has been around for years, but typically was well structured and organised. The data being generated today comes from a variety of sources, in multiple formats, of varying quality and at varying times, all of which poses challenges to the water industry as to how best to use it.
The recent explosion of data generated by remote sensors, logging equipment and inspection technologies on water company assets has substantially increased the amount data collected. It all provides additional information about the behaviour of infrastructure assets, but has very little value unless it can be used to inform operational management or investment decisions. Only at this point does it become valuable in terms of delivering efficiencies and/or improving performance.
Remote sensors and logging equipment across assets provide information about the current and historic performance of a system, but further investment in this technology is still needed to increase coverage and allow the performance of whole catchments to be viewed at the click of a button.
This will help water companies move towards real time operational management and take this to the next level of self-learning asset control
Leveraging the full potential of existing asset information, real time data feeds and the ability to visualise the impact and interaction of different capital investment and operational decisions across an entire network is only possible with high tech solutions coupled with highly skilled engineers who are capable of understanding, deploying and managing these technologies.
Significant headway is being made here, although the true challenge for the water industry is how this information is shared with other decision makers, such as local authorities, the Environment Agency and private developers, to ensure that maximum value is obtained for every pound spent by delivering co-ordinated investments.
Recent advances in hydroinformatics and business analytics have proved they can help deliver efficiencies and improve the customer experience, but these technologies are often delivered in isolation.
In AMP6, the water industry appears to be shaping up towards adopting a more integrated and collaborative technological landscape where the latest and most sophisticated technologies will talk to one another and react to each other’s feedback.
Driving this technology integration in the water industry is the need to deliver so-called “totex” - total expenditure - solutions. Advanced technologies, when delivered as an integrated enterprise solution, will help engineers visualise and manage their assets in a digital environment, while planning for the most cost effective whole life solution.
Learning from other industries
Benefits from advances in mobile technology are being realised by all industries.
It has long been possible for many professions to have immediate access to business critical information and key performance indicators from mobile devices.
The water industry already has this capability, although it is not widely used, but it can now move one step further and bring mobile technology to the hands of customers.
Gas, electricity and communications suppliers are making this investment. By empowering their customers to understand and manage their own consumption, mutual benefits are being realised because customers are sharing information and also self-managing their consumption habits.
There is no doubt that such technology will find a place in the water industry.
However, rapidly advancing technology is constantly raising the bar in terms of consumers’ desire for instant communication. This, inevitably, will have an impact on water companies, as recent research has shown that information needs to be provided in less than 10 seconds otherwise attention is lost.
Water companies can also capitalise on the public’s addiction to social media, which allows suppliers to better understand the performance of their services and assets via almost instantaneous feedback.
This has been demonstrated with flood depths, obtained from time stamped photographs taken from social media sites, which are used to calibrate hydraulic models to give a better understanding of infrastructure performance under severe weather events.
The information gathered in this way is being used to develop better models to predict the impact of flooding events, improved flood warning systems and more cost effective design and planning of flood mitigation schemes.
Integrating these technologies in a water industry environment will undoubtedly be challenging. However, the rewards for utilising them will far outweigh the difficulties.
If water companies can harness the power of enterprise geographic information systems (see box), capitalise on mobile technology and deploy the latest computing technologies needed to crunch through the big data, they will be in a strong position to deliver personalised services to cater for customers’ individual needs. Given recent legislative changes bringing retail competition to the water industry, the water companies of today need to be on top of these technologies if they want to be the water companies of tomorrow.
- Ben Ward is a research engineer and asset management specialist at Aecom
Enterprise GIS (EGIS) describes the geospatial technologies used to share spatial data across multiple departments within an organisation. EGIS leverages spatial data in a central repository, where data is maintained only once but then viewed, analysed and interpreted. This enables instant access not just to data, but also to useful information for every aspect of an organisation’s operation.
The benefits extend well beyond what you would expect in terms of enhanced asset management, and include improved planning, operational performance and customer management. For example, by allowing planning and operational teams to instantly visualise the impact of proposed future network developments, the operational impact on existing assets and customers can be managed, future infrastructure is adequately designed and sized, and an improved service is provided to the public which can then understand the impact of developments early.
The challenges of using EGIS to its full potential in the water industry lie in integrating complex datasets, including networks and treatment processes, with incident data and real time sensor feeds in a modern GIS platform. EGIS offers one solution for water utilities to gather, organise and use the complex information that defines their infrastructure assets and operations. It is also a way to escape the “big data to small information” conundrum faced by many organisations.
EGIS and recent advancements in mobile technologies can help the water industry move from reactive to proactive asset management - an industry goal for some time.
Deterioration modelling and investment optimisation, once seen as dark arts, are now clearly understood and supported by sound mathematics.
This is thanks to the coupling of improved corporate data collection systems, for example work order management systems, with advanced statistical analysis and decision support software.
The advantages of highly complex mathematical modelling such as evolutionary algorithms are being made possible by the power of cloud computing. What is reassuring is that this technology is now being delivered by easily understandable software solutions that are putting the power of decision making back into the hands of engineers rather than computer scientists.