WWEM 2016 - IWA Papers

Paper Information :

There is a massive digital disruption happening in the world today. The availability of cheap data storage, a significant increase on cloud based computer power and the access to powerful data handling and analytics packages at zero or minimal cost has created a pivotal moment for the world. Digital has unfolded in three distinct waves, Digital Customer, Digital Enterprise and most importantly Digital Operations. The latter is perhaps the most important to the water industry, at least today.

With the huge challenges facing the global water industry as stewards of both water resources and the receiving environment, we are tasked with ensuring we economically deliver water and wastewater services to customers. Challenges such as climate change altering weather patterns creating more extreme weather events, rising population as well as urbinisation, aging infrastructure, a retiring knowledge pool with a more competitive and socially different market place for attracting and retaining talent our challenge is to deliver more for less. This in addition to dwindling resources, higher energy and chemical prices, increasing water scarcity and tighter environmental legislation on existing pollutants as well as the introduction of new, more complex pollutants.

However, whilst the challenge seems significant and the pressure to deliver more with the same or less capital, the dynamic and heavily interconnected and interdependent nature of the natural and consumption water cycle means we have opportunity to exploit through a better understanding of our "eco-system" through the application of data analytics.

However, whilst digital disruption is tearing up the rulebooks in many sectors, the water industry, despite being data rich and having the necessary dynamic interactions which create opportunity, has not been quick to adopt digital disruption. There are many reasons to why this is the case, from greater pull on capital from operations, maintenance and asset creation projects, married to a traditional approach founded on building our way out of issues to being innovation shy when it comes to adopting new technologies and techniques. Typically, water companies require an ironclad assurance of benefits against investment, with paybacks of less than three years. Digital disruption benefits are hard to quantify, primarily because of the system complexities therefore the ability to imagine new ways of working are difficult until small reveals occur.

There is also a number of other blocking perceptions and requirements that can be avoided and, with the right data management techniques can allow us usher in the digital age without the need to create a major OT/IT revolution. In this case, evolution is sufficient to deliver the benefits from the digital age.

As a market leader in digital strategy and implementation, and a recognized pioneer of data analytics across every business sector, Accenture has been working closely with the water sector and applying innovative thinking in releasing the benefits of digital. In this presentation, we cover the practical development, using implemented examples of using IoT, Big Data and Cloud Computing to show the clear roadmap to how digital disruption can be used to meet the challenges of today to create the digital utility of the future.

Some of the key lessons and approaches covered include:

• Legacy Systems and Data Protocols: Water companies have much data, most of is across disparate, legacy sources and used and managed in silos. Typically analysis is undertaken using spreadsheets, with outputs used only by a handful and complex analysis and models hidden but to a select few and only for a single purpose. Multiple versions of the same data exist; each manipulated and "cleaned" in different ways.
  
  Critical to the success of any data project is the ability to leverage as much of the legacy data and systems as possible. The catalyst of success is to establish a suitable analytics platform that ingests and can analyze data from existing sources and integrate inputs and outputs. There are exceptional analysis and modeling tools, that if integrated into the data platform allows outputs to be used multiple times, and by multiple parties, increasing value on each application.
  
  Most existing BI systems were not designed integrate and the effort involved in conforming to a unified method of data output is futile. Leaving data in it'S original source and managing it's transition using the data platform is much more effective and efficient.
• Use Legacy data and Innovate to plug the gaps: As with legacy systems, creating actionable insights from legacy data as a first priority is critical. Where essential data is not available, innovate through use of engineering principles can help create surrogate information that is sufficient to yield benefits. Increase the "digital footprint" of every existing data point before embarking on expensive data generation exercise.
• Perfection isn't progress: Data quality perfection isn't required in order to develop it into something meaningful. Careful data architecture overcomes common problems associated with historic, undisciplined asset tagging conventions. Taking a systematic, "big file" approach to data ingestion allows an effective means of overcoming these legacy issues and achieving fast outcomes. Cleaning data on the fly is an imperative to deliver outcomes in weeks not years.
• Create Familiarity: Use the latest software technology, but create an environment that mimics more common systems such as Java. This reduces the dependency on highly skilled Big Data technology developers, creating a faster and more effective delivery workforce.
Equally this applies to the finished user interface. Utilize familiar graphics and company legacy system interfaces. This supports the uptake by the ultimate users.
• Build confidence and benefits quickly: Identify and tackle use cases initially with engaged members of the company, based upon a definite requirement one at a time. This allows the momentum of success to build and drive traction in the business. Typically 2/3rds of benefits are derived from use cases that follow the initial set of hypothesis.
• Simplicity to unlock the complex: The simplest of uses cases will deliver huge benefits. Following the successful approach of See Performance, Manage Performance, Optimize Performance and Automate Performance will create the environment to long-term success.