Analytics and Asset Management
The water companies that have been most effective in this AMP period are those that have combined asset management and analytics effectively
Analytics doesn’t need asset management … but asset management needs analytics!
It sounds like an exam question that should be followed by the word “Discuss.”
However, in reality it’s a pertinent point. Does asset management need analytics? Given where the water industry is in terms of PR19 and the increased challenges and requirements posed by Ofwat, analytics should be at the core of every organisation’s strategic plan. The problem is that not every organisation is at the same point in their asset management journey, and often the more innocent or less mature organisations are, the more difficult it is to embed analytics and decision support into the business and land the benefits of those analytics in a way that all stakeholders can value and appreciate.
Categorically yes, asset management does need analytics. If you look at the water companies who have reaped the rewards from a successful AMP 6 and PR14, you’ll find that they are systematically and consistently optimising their asset management practices, and achieve maximum value from the management of their assets. And to do this they use data and analytics. Analytics is what gives the hindsight, insight and foresight to support an organisation’s decision making power: Providing the information on what has happened historically, why it happened, what will happen next and what should we do (prescriptive analytics). Successful asset management strategies rely on understanding the data found within an organisation. Using it to generate value and communicate effectively to stakeholders.
This in turn has led to most UK water companies investing in enhancements in data collection, reporting and quality, and predictive analytics is now a rapidly maturing discipline even if capability is varied across the industry. However to deal with the implications of TOTEX for PR19 and beyond, asset managers must understand the “what ifs?” ie. prescriptive analytics. This type of analytics helps work out the likelihood of delivering outcome delivery incentives (ODI), and failure to get a handle on prescriptive analytics could potentially leave utilities with underfunded, underperforming, or stranded assets.
This leads into the hoary old question of data – we all know data is the communication link between different parts of the business and the thread that pulls them all together. However most organisations can be described as “data fetishists” and often request data that is not actually needed for decision making (it is simply interesting). The challenge is to ensure all stakeholders understand the value of the data they have, how it’s collected, how it’s going to be used and therefore to believe that the data is credible and valuable. Once you’ve got to grips with your data and data processes, the challenge then is to land the benefits of analytics to ensure a meaningful and successful asset management strategy. This not only rolls up into a strategic business plan which meets the business KPIs, but embeds analytics and decision support into business as usual.
Analytics is becoming the lingua franca of the technical world and rapidly the minimum expectation on any asset management team.
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