Data and the Digital Utility

Arinze Okonkwo Senior Industry Value Advisor Energy & Natural Resources November 2015

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3 months of unpaid electricity bills

~ 12 hours of electricity a day

How is that possible?

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No receipt issued

N2,500 reconnection fee

5th month…unpaid electricity bills

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Untraceable transaction

N50k for a prepaid meter…twice

9 months later…still awaiting meter

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Connection Request

Device Installation

Move In

Meter Reading Billing

Payment Receipt

Customer Queries

On site AMI Pre-Paid On site Tradition

al

Various Channels

Move Out

Debtor Management

Data Data Data

Data

Data Data Data

Data

Data

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2.5 quintillion bytes of data (2,500,000,000,000,000,000)

2000, 25% of all data stored as digital (94%, 2007)

90% of all data ever generated, in the past 2 years

33% of all data stored in 1986, on paper storage

2010, 1.8 zettabytes of data created (40zb, 2020)

2014, mobile devices exceeded world population

57.5bn iPads…enough to build a 20ft wall around South America

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Customers

Billings & Collections

Maintenance & Assets

Employees

Supply chain

Risk

Health & Safety

Financial performance

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Customers

Billings & Collections

Maintenance & Assets

Employees

Supply chain

Risk

Health & Safety

Financial performance

Collected Analyzed

Utilized Managed

Disseminated

Re-imagine business models

Re-imagine business processes

Re-imagine work

Digital Transformation

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Digital Core

Workforce Engagement

Assets and the internet of things Customer-experience

Omni channel

Supplier collaboration business networks

SAP HANA Cloud Platform

SAP HANA Platform

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Use Case 1: Customer Service

U.S. company with a base of 5 million customers specializes in the transportation and distribution of energy. It offers its services to retail electric providers and provides natural gas transportation services for retail and commercial uses.

Long call time for customer service

Disparate data

Low first call resolution

Advanced analytic engine (SAS)

Further building out BW environment

Status quo business process

Ability to predict nature of calls

Reduce handling time

Increase marketing effectiveness

Business Challenges Alternatives Considered Business Benefits

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Use Case 2: Predictive Assets

Dutch gas and electricity distribution company operating with more than 85,000 kms of power lines and 37,000 km of gas pipes. It has a base of 3.3 million customers.

Calculating the peak load at each substation took 5 analysts 3 months

High rate of errors

Need fast access to volumes of data

Could only analyse small data set

Hiring additional staff

More back office analysis

60% reduction in IT costs

Improve load forecast accuracy and frequency

Extend transformer life by 3 years

Business Challenges Alternatives Considered Business Benefits

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Use Case 3: Fraud Detection

Multi-service utility company, provides electric, natural gas, water, wastewater, and telecoms services in the U.S. $2.6Bn in generation, transportation and distribution assets.

Uncollectable and delayed collections

Fraud

Meter malfunctions not detected in time

Status quo reactive business process

Hiring additional staff

Excel spreadsheet analysis

Lower outstanding accounts receivable

Improved working capital

Lower revenue leakage

Business Challenges Alternatives Considered Business Benefits

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