The water industry is using digital technologies and analytics to derive more value from its physical assets, but, like all businesses, it has faced challenges when trying to transform the roles and mindsets of their employees and their internal- and customer-facing processes. Employees, for example, weren’t quick to change old habits, and, when there were IT problems, many began to question the data. But those that have managed to integrate these elements — People, Processes, and Technology — have created more than data; they’ve also created value for their enterprises and society.
The water industry is using digital technologies and analytics to derive more value from its physical assets. The need for this sector to change and evolve could not be greater: The organizations that manage water supplies around the world are facing critical issues, and water scarcity is chief among them.
Because of changes in our lifestyles, including increased consumption of grain, meat, and cotton clothes, growth in water consumption per capita has doubled over the last century. And demand is increasing. According to a 2016 report from the UNEP-hosted International Resource Panel, water demand will outstrip supply by 40% by 2030. During the same period, according to the World Economic Forum, water infrastructure faces a huge $26 trillion funding shortfall. If not addressed, water scarcity will squeeze food and energy supply chains, and stall economic growth.
To help solve this problem, organizations are using digital technologies and data analytics to improve leak detection. According to the World Bank, the world loses about 25-35% of water due to leaks and bursts, and the annual value of this non-revenue water — water produced and lost by utilities — is $14 billion. Organizations are also using these tools to improve maintenance, infrastructure planning, water conservation, and customer service (including repair efficiencies and pricing).
Although members of the water industry have found success using digital technologies and analytics, they’ve also faced challenges when trying to transform the roles and mindsets of their employees and their internal- and customer-facing processes. But those that have managed to integrate their technological advances with two other key elements — people and processes — have created more than data; they’ve also created value for their enterprises and society.
People: Good leaders know that using and interpreting data is not only a search for insights; it’s also about enlisting the hearts and minds of the people who must act on those insights.
The challenge is that employees are used to doing things in a certain way, and aren’t always quick to change. For example, despite the social and efficiency value of using predictive analytics to preventwater leaks, many utility managers view themselves as heroes for responding afterthe leak has occurred. As one U.S. executive explains, “Most current practice is to wait for the service-failure event and judge performance by reacting to it, because the utility doesn’t get credit from regulators or the media for preventing leaks that the public doesn’t know about.”
Regulatory incentives often exacerbate this behavior. In many parts of the world, the increased operational and infrastructure costs are simply passed on to consumers. In other regions, however, (e.g. Australia, Israel, the U.K.), regulators steeply fine utilities for inefficiencies – and it’s no coincidence that a number of utilities in these countries have been leaders in adopting new digital tools.
But even with proper incentives, there are still challenges. For example, many U.S. utilities have installed smart meters — an investment that can easily surpass $60 million in cities with 150,000 water connections, or about 15% of average annual utility revenue and water rates. But after making this investment and charging consumers for it, there were false alerts about leaks, which caused expensive repairs and claims processing. The law of unintended consequences was also alive in operations: because of the initial problems, the field transmissions group distrusted the data — even after the IT problem was diagnosed and resolved – and therefore required additional training to assuage their doubts.
This is why it’s imperative to change roles, break down silos, and adopt new decision support systems when implementing new technologies. A water authority in Australia, which deployed a software solution for improving network efficiency, is a case in point. Its managerial team first formed a working group of personnel from business units across the organization — from retail and asset management to planning and maintenance crews. The group met weekly and by doing so they recognized that the software detected faulty incidents and provided a focal point to collect information (e.g., types of problems, magnitude, location, etc.) to make better decisions in other areas of the business. As a result, they created procedures that shortened the average repair cycle by 66%, saving millions annually.
Longer term, the information allowed the team to make more focused investments based on types and frequency of problems in each zone, and the ability to compare — and negotiate better terms with — vendors based on quality and performance.
Processes: As with other sectors, water utilities are going through a shift from treating users as connections who pay bills, to customers that have needs, habits, and strong opinions if things go wrong. And data analytics is enabling them to provide faster and more effective responses. “We can compare the efficiency in each of the six sectors making up our network and evaluate the response time it takes to identify potential damage, ensuring faster repair times,” an executive at one of Romania’s leading water utilities told us. “As well as smarter insights, the event management system ensures better managerial attention to continuous improvement in our operations and service to customers, and helps to prevent large-scale damage from hidden leaks.”
But in order to achieve those outcomes, the Romanian utility had to change its organizational processes and metrics. The utility had to re-define company metrics goals and create weekly and monthly processes for reviewing performance-against-goals. The software provided relevant data — e.g., the start time of a leak and when it was fixed, based on real-time information, not when reports were submitted. But it was new customer-facing processes such as setting repair-cycle targets and comparing performance-against-goal by region, which created a healthy sense of internal competition and led to more productive behaviors.
These issues aren’t unique to the water industry; they’re also relevant to companies in other industries that are using data and digital tools that are increasingly available.
For example, sales is the focus of potentially big improvements via new tools that can provide better lead generation, forecasting, and targeting. But in order to take full advantage of these tools, sales organizations will need to change their compensation incentives, internal processes, and the skill sets of their staffs, among other things.
More generally, while most current talk about big data seems to assume the replacement of physical assets by digital technologies, a larger and more impactful trend is the use of online tools to improve physical asset utilization in off-line businesses, as in the water industry. In that context, the role of data is not to make a manager sound analytical. Its role is to help make better decisions and drive value for the company. And you can’t do that only with technology or analytics, no matter how good they are.