Strategic Data Science

for Water Utilities

WORKSHOP

Dr Peter Prevos

Manager Data Science |Coliban Water

• What is Data Science?• Case Studies• Strategic Data Science• Discussion

Strategic Data ScienceProgram

leanpub.com/strategic_data_science

What is Data Science?

Data ScienceDon’t believe the Hype

Davenport, T.H., and D.J. Patil. “Data Scientist: The Sexiest Job of the 21st Century.” Harvard Business Review 90, no. 10 (2012): 70–76.

Source: Google Trends

• Cheap data collection and storage

• Increased computing power• Open source machine

learning

Data ScienceWhat’s new?

• Flooded with data• Data deluge• Data lakes• Data flows• Data pipes

Data ScienceHydroinformatics

csgsolutions.com

Elements of Data Science

Source: Drew Conway

Subject-Matter Expertise

MathematicsComputer Science

DATASCIENCE

MachineLearning

• Useful• Sound• Aesthetic

Good Data ScienceVitruvius, Roman architect and engineer

Water screw, De Architectura, book II.

Useful Data ScienceThe Knowledge – Reality feedback Loop

• Validity• Reliability• Governance• Reproducibility

Sound Data ScienceThe Science of Analysis

• Code is Poetry• Spreadsheets invite chaos

Sound Data ScienceReproducibility

• Tell a story with each graph• Two dimensions only• Colour is not decoration• Multiple graphs for levels of

detail (drill down)

Aesthetic Data ScienceRules of Thumb

Composition C, 1935 by Piet Mondrian

Aesthetic Data ScienceData-to-Pixel Ratio

Aesthetic Data Science

Aesthetic Data Science

Case Study

The Board of directors of a water utility receives a monthly report about water quality performance.

None of the members of the Board are water quality professionals.

The report is full of numbers and statistics that the responsible manager needs to explain to the Board every month.

Data Science Case Study 1Water Quality Board Report

Another section of the report contains information about customer complaints with respect to water quality. The Board often asks how the customer experience relates to the technical data in the other section of the report.

The Board has requested the data science manager to develop a new report that provides them with an easy-to-understand overview of water quality performance.

The report needs to visually combine the technical data with the customer experience information. The report should focus on the salient aspect of water quality performance to provide a strategic perspective for the Board.

Data Science Case Study 1Water Quality Board Report

Data Science Case Study 1Water Quality Board Report

Aspect Source Availability

Catchment Paper records Intermittent

Barriers SCADA Continuous

Network Laboratory Weekly

Customer Experience Complaints Daily

Regulation Correspondence Intermittent

Data Science Case StudyWater Quality Board Report

Strategic Data Science

Data Science ContinuumData Science Continuum

Data Science Workflow

Data Science ToolsCode is Poetry

Data Science Literacy

• Informed Consent• No harm in collecting• Algorithmic fairness

Data Science Ethics

Source: koeppeldirect.com

• Leadership commitment• Systematic approach• Employee competencies• Focus on creating value• Data governance• Ethics

Data Science CultureWhat's needed?

Discussion

A water utility starts a digital metering project and seeks to collect hourly meter reads from every customer. The new technology is deployed to all customers to ensure the service obtains maximum data coverage. Customers are not provided with an opportunity to opt-out of the program.

The program has been well received by the community overall. A small segment of customers opposes this technology due to perceived risks to human and environmental health caused by low-level microwave radiation. There is no scientific evidence to justify their claims. The benefits that the water utility seeks are:

• Improved customer awareness of water consumption• More accurate capital investment forecasting• Reduced leakage, both non-revenue and revenue leaks

Data Science Case Study 2The Ethics of Digital Water Metering

The employees of the water utility are excited about other benefits this data can achieve and have proposed several data science projects.

• Detecting leaks at the customer’s property • Monitoring adherence to water restrictions • Monitoring zero water consumption

Discuss this digital metering project using the three principles of data science ethics. If any of the principles reveals any potential for ethical conflicts, then propose a way to mitigate the impact:

• Informed consent • Avoiding harm in collecting data • Algorithmic fairness

Data Science Case Study 2The Ethics of Digital Water Metering

Thank you