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Data Management
Practices
For Solar Companies

Exercise:
Examples of
Data Usage
• Break into 4 Groups
• Group 1 & 2: Give 2 examples of how Solar-
ESPs used customer data and research to
improve solar products and service delivery,
targeting clients, customer satisfaction, sales
etc.
• Group 3 & 4: Give 2 examples of how Solar-
ESPs failed to use customer data and
research to improve solar products and service
delivery, customer satisfaction, sales etc.
- 10 minutes

Desired Activity
Areas for USEA
(Solar stakeholders
Survey n=41)
• Services opted for:
• “News and knowledge
sharing/information” –
(44%)
• “Regulation and policy
advocacy related” – 30%
• “Technical support and
capacity building/training”
– 22%

• Technology-driven data collection methods cited:
 Smart meters
 Cloud platforms/blockchain technology
 Real time data gathering
 PAYG data
 Access detectors
 Environmental monitoring
 Apps facilitating field data collection
• Traditional data collection methods cited:
 Phone/sms/email
 Traditional field research (forms, interviews)
12
41%
17
59%
Data collection methods
Manual data collection Technology-driven collection
Data Tools used by
ESPs in Uganda
(n=63)

Data support needs
cited by solar
companies (n=63)
Data sources mentioned by ESPs:
 Customer MIS data (gender,
geography, product uptake, financial
service uptake, repayment).
 Customer Satisfaction Surveys
 Product quality and energy
production measurements
 Market data
 Environmental Monitoring
 Company data (balance sheets)
 Open data sources
0
5
10
15
20
25
30
Data management
tools
Technical assistance
on data analytics
Access to datasets
Data support needs

Two Data Tools Available
For Solar Companies in
Uganda

Village
Power Loan
Portal Tool

Village
Power
Market
Database
Tool

About: OpenStreetMap
http://www.openstreetmap.org

OSM Data and Tools
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http://overpass-turbo.eu

Energy Company Use Case - OSM as a basemap with
other data
Allows companies to map their distribution data on a map
displaying publicly available data on national energy
services, energy types in districts, and financial services.
Companies can customize a map by uploading simple data
on their districts of operations, and zoom into national
data customized for the same district.
This can help with mapping new areas to operate, and
understanding the local dynamics and presence of other
services in that area.

Open Street Map National Energy Financial Data Map
Key
Green lines :
Power Lines
Number
circles:
Financial
Institutions
and Mobile
Money
Operators
Dark green:
Current
districts of
operations
Dark Blue:
Target
districts of
operations
Answers the
questions:
Where are
current energy
service
providers
concentrating,
and not
reaching?
Are ESPs
contributing to
last-mile
energy access?

Open Street Map: Overview of companies operating in selected district
Answers the
question:
Which other
energy service
providers can
customers
choose from?
Sales volumes
of other
companies not
displayed.

OSM Energy Company Personal Map
Demonstrates
company current
operations and
target
operations,
against national
grid and mobile
money/financial
institution
availability.
Answers the
questions:
How far will
customers have
to travel to reach
a MM agent?
Am I targeting the
right locations?
Where should I go
next?

OSM Energy Company Detail against energy source data per district
Demonstrates
energy source
and lighting
distribution per
district.
Answers the
questions:
What are
people in the
region
currently using
for energy and
lighting?
Where are
financial
institutions
located?

Audience
Poll
For what purpose do you use
customer and solar product
data?
• Business growth
• Targeting customers
• Customer retention
• Product development
• Reporting data to investors, association etc.
• Generating market insights
• Policy advocacy
• I do not use customer and solar product data

Dashboards for large datasets
Dashboards for small datasets
Conducting Data
Analytics Training in
Uganda
Photo: Training conducted with large
FSPs in Cambodia

Youth Savings Mobilisation vs Adults Saving
Mobilisation

Using Big Data to generate Solar Market and Business
Intelligence in Uganda
Source: Dalberg Data insights and MM4P, UNCDF. – prototype

Audience Discussion and
Feedback
What type of training will benefit your solar business?
What training will help your solar business contribute to closing the energy access
gap?

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Data Management Practices for Solar Companies

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Data Management Practices for Solar Companies