Staying at the forefront of asset management increases efficiency and boosts the bottom line, yet many organisations run into the tricky problem of imperfect data sets. But one industry expert argues that using templates and industry comparisons helps side-step that challenge.
“My response is always that we can use templates and calibrate Australian data against existing data sets,” said Andy Gibson, ANZ technical practice leader – wastewater networks planning at AECOM.
“The benefit of this is that it drives data collection processes and ensures that the ‘right’ data is being collected going forward."
For his session at the upcoming Ozwater’17 conference in Sydney, Gibson will be discussing a strategy that forecasts asset failures and then optimises total expenditure against risk and business objectives, with the added benefit of delivering better customer service in the process.
The concept is fairly simple: fix only things that need fixing. But the very nature of many water utility assets means this is easier said than done.
Most of the asset value of an organisation sits underground, said Gibson, which presents a huge challenge to manage risk and balance it with customer expectations and levels of service required by the regulator.
“The average sewer will have a life expectancy of 50 to 150 years, which is a large age range. So the target is to replace the sewer at the optimum time: if you do it too early, you’ve potentially wasted money; if you do it too late, you might end up with something like a collapse.”
This is especially important when considering the regulatory environment within which many utilities function.
“We always need to take care of customers and protect public health from both a potable and wastewater perspective,” he said.
“You can’t just say you want a billion dollars to complete a project; you have to show what you’re doing with that money, how you came to that decision, what is the value added and how have I managed my risk.”
Being able to assess and predict asset failures is then crucial for setting budgets and managing long-term programs of work, particularly in cities where growth requirements have to be balanced with an ageing asset base.
In response, AECOM, SEAMS and Exeter University in the UK developed a suite of tools that predicts how assets transition through condition grades and different risk profiles. They also drive and refine the data collection process.
“Imagine 5000km of pipes; to collect information on their condition costs about $6 per metre, which adds up quickly,” Gibson said.
“It’s impractical to collect information on every single pipe, which means we need to become more efficient at forecasting when and where failures will occur, and devoting resources to just those problem areas.”
Using 35 years of data from the UK, where the process was developed, a series of templates were developed to calibrate and compare utility performance. From this, Gibson said they can develop performance models that indicate potential intervention strategies based on different constraints – from target performance levels to capital programmes.
For example, “if a utility has a certain budget, we can forecast what staying within those constraints would mean for the deterioration and performance levels of a sewer network”, Gibson said.
“What a model like this does is it allows us to plan effective and efficient data collection based on the expected condition of the pipes. Over time you start to figure out where high risk pipes are, which means you can reduce the amount of time and money you spend on collecting data.”
Gibson said this forecast methodology can predict the deterioration of a network in different cohorts going forward 30 or so years.
Implementing a similar strategy helped save one UK client AU$8 million, said Gibson. But there are other roll-on benefits for the end user as well.
“Any asset management process that delivers great customer service is cutting edge,” he said.
Having a strategic plan for asset management – present and future – helps utilities better communicate the breakdown of where revenue (bills) are spent and makes the process more transparent.
“Doing this kind of predictive modelling enables our clients to engage with customers and show them where revenue is required to deliver a series of performance targets. It then becomes easy to have the conversation around performance levels versus customer bills.,” Gibson said.
“It communicates what happens to service over the next 10 years if we do nothing, as well as what will happen to their service over the next 10 years if bills are changed in that same time period.”
To learn more about how to stay at the forefront of asset management best practice, join us at Ozwater’17 in Sydney. Click here.