ANNEXURE A « If you can’t measure it … you can’t manage it » The importance of data analytics in the management of water losses Presentation for the Water Services Forum: 15 May 2019 Presentation by: Shuntelle Gow Manager Water Cycle Management Rand Water

Background Business management concept – by Peter Drucker ANNEXURE A Background Business management concept – by Peter Drucker Expanded view…. true for water loss management

Background DATA and ANALYSIS OF DATA IS IMPORTANT ANNEXURE A Background DATA and ANALYSIS OF DATA IS IMPORTANT Data analytics is the science of analyzing raw data - to make conclusions Techniques and processes of data analytics have been automated into processes and algorithms Data analytics help a business optimize its performance.

Water loss management Water loss reduction strategies formulated from data analytics Source: American Water Works Association presentation Source: Water supplies department – Government of Hong Kong

ANNEXURE A Water loss management Using data to manage water losses in 4 easy steps Source and configure real-time data Identify the right Key Performance Indicators (KPIs) Clarify your analysis for operational insights Turn your insights into Action (Source: Innovyze© white paper)

RW strategy for WC/WDM Three pillars: Catchment quantity monitoring ANNEXURE A RW strategy for WC/WDM Three pillars: Catchment quantity monitoring Internal water loss management Customer water demand management

Rand Water’s approach – customer demand management ANNEXURE A Rand Water’s approach – customer demand management Development of tools and analysis of water demand RAND WATER DIRECT METERS LOGGED: SYSTEM INPUT VOLUME 410 Ml/d ACTIVE USE 123 Ml/d 30% of SIV Active use 123 Ml/d MINIMUM NIGHT FLOWS 287 Ml/d 70% of SIV Normal legitimate night use - 4.7Ml/d or 2% of MNF Normal Residential night use 3.2 Ml/d or 1% of MNF Night consumption 10.7 Ml/d or 4 % Legitimate non residential night use 1.5 Ml/d or 0.5% Background leakage (unavoidable) 6Ml/d or 2% domestic background leakage 1.3 Ml/d or 0.45% Background leakage on mains 0.8 Ml/d or 0.3% Background leakage on connections 3.9 Ml/d or 1.4% Night leakage (bursts and losses) 27 6 .3 Ml/d or 96% Customer night leakage estimated at 196.4 Ml/d or 68.43 Night leakage or losses 276.3 or 96% Distributi on system night leakage 79.90 Ml/d or 27.83

Rand Water’s approach – customer demand management ANNEXURE A Rand Water’s approach – customer demand management Formulated approach based on outputs of data analysis: Set optimal demand targets for customers = license targets Monitor and track performance against targets – Project 1600

Rand Water’s approach –customer demand management ANNEXURE A Rand Water’s approach –customer demand management Formulated approach based on outputs of data analysis: Advise customers on water use efficiency and where improvement measures are required Monitor and evaluate the effectiveness of customer demand management programmes Able to consolidate and prioritize for the Region – Aim is consolidation of programmes by all stakeholders Share knowledge and best practices in the Region 2018 WUE per Depot: WUEI= 1.46 Depots – exceeds license target the most Depot – best performance against license target

Rand Water’s approach –customer demand management ANNEXURE A Rand Water’s approach –customer demand management Formulated approach based on outputs of data analysis: Development or design of regional measures: WUE as additional criterion for new connection applications Automated flow management (advance pressure management project with municipalities to target areas with high wastage) – Aim is to enter into agreement with municipalities identified for this project Municipality Number of priority bulk meter supply points Potential Reduction (Mℓ/d) City of Ekurhuleni 7 37 City of Johannesburg 24 288 City of Tshwane 13 76 Emfuleni 36 Govan Mbeki 1 3 Mogale City 6 Rustenburg 2 14 Thembisile Hani Victor Khanye 8 TOTAL 57 472

Next steps – customer demand management ANNEXURE A Next steps – customer demand management Future interventions to be considered Development of bulk stepped tariff to reduce inefficient consumption Development of a Regional Information Management System – drive towards integration and accessibility of information

Conclusion Utilise data analytics to manage water losses ANNEXURE A Conclusion Utilise data analytics to manage water losses Application of sound engineering principles for decisions – eliminate decisions based on perceptions, which may lead to unfair practices This will ensure that measures applied will be fair and equitable for all customers = Legislative requirement for provision of water services = live by the principle “WATER FOR ALL” Enhance service delivery Many more benefits………..

References Brochures/articles Images ANNEXURE A References Brochures/articles http://analytics-magazine.org/smart-water-analytics-helps-reduce-water-loss-cut-costs/ https://www.innovyze.com/media/2624/innovyze-whitepaper-water-loss.pdf https://www.investopedia.com/terms/d/data-analytics.asp Images https://www.stonevp.com/if-you-cant-measure-it-you-cant-manage-it/ https://za.pinterest.com/pin/98094098109296718/ https://www.zdnet.com/article/big-data-2018-cloud-storage-becomes-the-de-facto-data-lake/ https://www.wsd.gov.hk/en/core-businesses/operation-and-maintenance-of- waterworks/reliable-distribution-network/index.html https://www.google.co.za/search?q=apparent+waterloss+management&source=lnms&tbm=i sch&sa=X&ved=0ahUKEwjY57Xihv3hAhXhRxUIHUWPCeoQ_AUIDigB&biw=1366&bih=67 3#imgrc=XhVYyIVyiEkK5M:&spf=1556807183145

ANNEXURE A THANK YOU