Water companies have invested heavily in operational effort to manage leakage, as well as in technologies such as telematics, pressure management systems and District Metered Area (DMA) systems. They’re to be congratulated on having dramatically reduced leakage.
Now, however, it’s imperative to look beyond current processes and approaches in order to drive leakage levels down still further. This need arises from factors like pressure on operational costs, revised outcome delivery incentives (ODIs), and the drive to address environmental considerations and meet customer expectations.
Companies urgently need to find smarter ways to truncate the lifecycle of a leak, and bring outliers closer to the mean; predicting leaks the day before they occur, rather than noticing them 3-4 days afterwards.
The key: even more insights from your data
The key to the leakage challenge lies in finding better insights and using them to support decision-making. This way, water companies can find and prioritise their most effective options, and balance competing objectives optimally. They can reduce the number of leaks, and predict and locate those that do still occur faster and more efficiently.
To get the necessary insights, companies must capitalise further on the huge investments they have made in systems, and the large volumes of data that have been generated.
The need for a business-driven approach
To manage leakage really effectively, companies need to optimise five linked issues:
- Where on the network is leakage likely to occur?
- When a leak does occur, how can I narrow the search area to find it as quickly as possible?
- What is the optimal way to organise the work of fixing a leak?
- How can I optimise the pressure on the network so I don’t cause leaks?
- How can I allocate capital expenditure so that I replace vulnerable infrastructure before leaks occur?
Most current approaches can’t easily produce insights to address specific challenges like these, because they are data-driven. Capgemini and IBM have worked together to offer a business-driven, top-down, machine learned approach that fills this need.
You can start with a question like “how do I narrow down the search area to find a leak as quickly as possible?”, decide what data you need to answer the question, then quickly assemble that specific data ready for analysis.
Our solution combines large numbers of data sets using a versatile, open and reusable platform. You get:
- A business-driven approach to gaining insight from data. Start with the business issues you need to solve, then focus on the relevant data.
- A strategy and platform to meet a wide range of future needs – not just leakage. Bring together data of many types and from many sources to achieve any type of insight-driven transformation. There’s no need to integrate specific systems for each new insight.
- A service approach that delivers long-term benefits. Gain a continuous stream of benefits over a number of years without the need for multiple consulting projects. Choose from a range of commercial structures, including long-term managed service.
Why Capgemini and IBM?
IBM offers best-of-breed products to address every element of the architectural stack needed to get insights from data. By mixing and matching IBM’s compatible building blocks, you can get an ideal compromise between a modular offering and one that’s pre-integrated, incorporating machine learning to deliver maximum benefits.
Capgemini complements IBM’s products with:
- Expertise in operational consulting (specifically in creating and improving business models and processes).
- Experience in generating and applying insights from data.
- Worldwide teams of data science and technology specialists.
- A well-established partnership with IBM and in-depth knowledge of IBM products.
Both companies have invested significantly to create this platform, bringing sector expertise to tailor it to the water industry and its leakage challenges. We jointly offer a full range of related services including consulting, implementation and managed services provision.