Pooling data and analytics to power greater efficiency in water utilities

By | Monday December 19th, 2016

Although water and power utilities face very similar pressures, they have tackled them with very different levels of success. Both sets of utilities face a common battle to reduce network operating costs, beat off increased competition and meet the increasingly complicated requirements of the regulators.

Yet it is the power sector organisations that so far have been cleverer about using their wealth of data to deal with these challenges. They have become truly data-driven by taking a strategic approach to data integration and analytics, whereas their counterparts in the water industry are still hampered by holding data in individual silos.

Time then, for water companies to learn from the more mature power operators and recognise that there are four main areas where data integration and analytics will bring major gains:

  1. Asset management – which includes optimising maintenance and operation, along with improved planning for new assets. It also encompasses supply chain optimisation.
  2. Customer management – through better service levels and the reduction of complaints, with further gains from increased efficiency of water management and other green initiatives.
  3. Regulatory performance – chiefly through analysing and measuring performance against current regulatory KPIs.
  4. Regulatory modelling – where there are major gains in mapping out requirements and resources in relation to the future.

Unfortunately, it will be extremely difficult for water utilities to obtain any of these gains while their data remains closely guarded by the individual departments who are using it to answer their own business questions. This is a huge missed-opportunity, given the constant flow of high-value data water utilities have from their customer relationship systems, geographic information systems, operational systems, telemetry, asset registers, regulatory data and good old-fashioned spreadsheets.

Following the example of the power companies, it is time for water utilities to abolish the silos and integrate all this data with external information from weather and environmental monitoring systems. By making the data accessible to everyone in the business they can give themselves infinitely more valuable datasets.

Boosting revenue and operations

Regulatory data, for example, can be analysed alongside sensor data from machines to help achieve better operation of assets and greater revenue, while simultaneously minimising regulatory fines. Effective integration also means that when the network is hit by severe weather disruption, customers affected can be quickly identified and informed of the problem and what is being done to fix it.

At the other end of the market, integration means water utilities can better scope and provide bespoke packages to major customers in manufacturing or retail, who now expect a variety of enhanced services.

The right mix of analytics

The analytics required to achieve these benefits are both traditional and advanced, all running on a single integrated view of data.

Advanced analytics is used to produce more accurate, useful and timely answers where the problem or question is well defined but challenges remain around integration and the capacity to analyse large volumes of data quickly.

Discovery analytics, by contrast, mines data for insights – putting data together to look for patterns without preconceptions, rather than asking specific questions. Data scientists work with business experts to determine what these patterns indicate and how the previously “unknown unknowns” can yield benefits.

The right outcome

Once the water utilities learn these lessons from the power and other asset-based industries, they can get to work on small-scale projects and focus on what will give them a quick return-on-investment. This way they will enable a wider strategic programme that quickly becomes self-funding.

Importantly, they will also be laying the foundations for a strategic programme that kicks aside departmental and cultural boundaries to truly unleash the power of data.

 

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