1. S o c i a l P e r f o r m a n c e M a n a g e m e n t H U B
How-to guide - Standard 1B
Planning Stage 1: Indicator Mapping

2. P l a n n i n g S t a g e
Transitioning from Standard 1A to 1B
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From Standard 1A you should have:
Defined your social goals and identified indicators. These provide the basis
for data collection and reporting that will enable effective decision making.
In Standard 1B: Planning Stage 1 you will:
Map your information needs or indicators and outline the various activities
that will be involved. This is a necessary step before you start collecting data. In
this first stage you will identify your information needs and map each Indicator’s
data cycle.

3. Planning St age
Indicator Mapping
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Through the process for mapping indicators, we aim to answer the following:
1. What resource requirements and constraints do we have for data
collection?
• Data collection requires considerable resources: time, training and
sometimes upgrades to data software (data storage systems, MIS).
Where there are resourcing constraints it is important to be aware of
them, and begin with collecting data for a small number of indicators.
Additions can be made gradually.
2. Does data already exist?
• Your MFI may already be collecting lots of data from multiple sources
that can be useful to track performance against social goals.

4. Planning St age
Indicator Mapping
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3. When do we need data and what for?
• Internal processes and the demands of external stakeholders will determine
when information is required, which might influence how and when data is
collected.
4. Can I take a sample of the population?
• For some areas of data collection we might not need to collect data for all
clients, but can take a sample of the population. We need to ensure that this
sample is representative.
5. What impact does this have on clients?
• Data collection requires the time of clients. In order to minimise the cost to
clients, where possible additional data collection should be integrated into
existing processes and points of contact with clients. Examples include loan
application forms, business/loan utilisation checks, routine collection
meetings.

5. I n d i c a t o r M a p p i n g
Checklist of steps
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Continuing from Standard 1A, we provide guidance for capturing,
managing, analysing and reporting data for each indicator. The Workbook
will guide you through the following process:
1. Chose the tool/source of indicator data
2. Chose data collection approach for each tool – (e.g. census/ sampling
method)
3. Decide data collection frequency
4. Decide who is collecting data
5. Embed data verification into operations
6. Determine where data is to be stored
7. Decide who is going to manage and analyse data
8. Decide on your reporting requirements

6. P l a n n i n g S t a g e
Indicator mapping
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Please open the Excel Workbook we have developed for Dimension 1. The
Worksheet entitled “6. Indicator Mapping” will guide you the indicator mapping
process outlined below:
1. Choose
tool/source of
data
2. Choose
data
collection
approach
3. Decide data
collection
frequency
4. Decide
who is
collecting
data
5. Embed
data
collection into
operations
6. Determine
where data is
to be stored
7. Decide who
is going to
manage and
analyse data
8. Decide on
your
reporting
requirements

7. I n d i c a t o r M a p p i n g
Step 1: Choose the source (touch points) for data collection
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When choosing indicators, identify the source of the data if it exists already, or decide which
tool the indicator will be included in. This will ensure that the data will actually be able to be
collected. The following considerations should be made:
How will the data collection be integrated into current operations and business
processes?
• Social data can be collected at a number of touch points, which is the point at which
data is collected. These include during loan application process, during business/loan
utilisation checks, at loan disbursement for example.
Does the data already exist?
• You may already be collecting data for particular indicators. Duplicating data collection
is costly and should be avoided.

8. D esigning your SPM Syst em
Step 1: Choose the source (touch points) for data collection
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Data can be collected formally or informally through a variety of touch points.
Formal data collection touch points include operational forms, special surveys and
qualitative research. The table below shows examples of each:
Informal
Informal data can be generated in informal meetings between staff or between field staff
and clients. Informal data can be valuable in itself or used as background data or
clarification for other types of information collection. It is often overlooked when not
recorded in a systematic way, which can be detrimental to the value of information.
Operational forms Special surveys Qualitative research
• Client membership forms
• Loan application forms
• Suggestion boxes
• Client exit survey
• Client satisfaction surveys
• Transformational surveys
• Case studies
• Focus group discussions

9. I n d i c a t o r M a p p i n g
Step 2: Choose data collection approach for each tool (census or
sampling method)
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For each of point of data collection and collection tool you will also need to decide whether data will be
collected on a census or sample basis. The table below demonstrates various implications of each
approach:
Implications of census approach Implications of sample approach
• Data collection becomes part of regular business. Staff
may need to take on extra responsibilities
• Initial costs (training and any IT changes) may be high,
but these will generally reduce over time
• All staff to be trained initially
• Staff ownership – should be seen as business as usual
• Continuity – High chance of continuity
• Robustness – more robust for trend analysis
• Data management can be overwhelming at the
beginning, but should become easier over time as
process is embedded into operations
• Project management should be smoother and become
easier over time as this process becomes business as
usual. Only small changes may be needed over time
• The effectiveness of a census approach is high as data
collection and processes are business as usual
• Separate time allocation for data collection which can be
inefficient.
• Generally each sample data collection approach will
cost the same over time.
• Only a few staff to be trained – loss of these staff may
require further training in the future
• Staff ownership – may be seen as separate activity and
therefore less ownership taken
• Continuity – easier to stop
• Robustness – Less robust for trend analysis
• Data management may be easier with smaller amounts
of data
• Project management can be difficult it requires effective
resource allocation and constant attention.
• The effectiveness of a sample approach may be low to
moderate as the data collection is a separate activity

10. I n d i c a t o r M a p p i n g
Step 3: Decide data collection frequency
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From Step 1 and Step 2 you should have identified the data collection source for
each indicator and whether you will collect data on a census or sample basis.
Next you need to decide how often you will collect data.
• Census data should generally be collected on an ongoing basis from all
clients and this process embedded into operations.
• Sample data should be collected in line with data needs. For example, if you
need to use information on a monthly or quarterly basis for detailed analysis
of progress, it is likely that clients will need to be regularly surveyed and
monitored. However, if an annual overview of a representative group of clients
is sufficient, it may be more appropriate to conduct a survey once a year with
a small sample of clients.

11. I n d i c a t o r M a p p i n g
Step 4: Decide on who is collecting data
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• In general, field staff such as loan officers should regularly collect client level
data, such that this process is embedded within operations as ‘business as
usual’. This can reduce costs and increase internal learning, but surveys
should be kept as short as possible so that it is manageable to have them
integrated with everyday tasks.
• It is important to be aware that for some data there may be negative
implications to having field staff collecting data from clients. Data may be
unreliable if there is insufficient buy-in from field staff. This type of data may
be collected by Head Office staff.
• If data is only needed occasionally, external assistance can be beneficial.
• Skills required: Good relationship building skills, communication skills,
familiarity with clients

12. I n d i c a t o r M a p p i n g
Step 4: Decide on who is collecting data
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Field Staff Head office staff (compliance,
R&D etc)
Third party
PPI and other
outreach
indicators
Census through membership
and loan application forms,
embedded into business as
usual
Largely inefficient practice.
Resource intensive, costly and
time consuming.
Can provide some
assistance but learnings
may not be passed on.
Costly. No existing
relationship with client
poses difficulties.
Transformation
indicators
A combination of census and
sample data can be collected
through various touch points.
Resource intensive, costly and
time consuming. Better for
infrequent or sample based
studies.
Can be useful for in-depth
studies. Costly.
Satisfaction
indicators
Potential for conflict of interest
problems with field staff
collecting most satisfaction
data. Results are also likely to
be biased through inaccurate
responses. If field staff better
to use branch managers or
admin staff.
Head office staff best to
conduct satisfaction surveying.
Conflict of interest minimised.
Internal officers/ compliance
well positioned to incorporate
into business as usual.
Can provide useful
expertise and data
collection for specific
studies. Business as usual
satisfaction surveys
however should be left to
MFI staff to increase
efficiency.
Specialised
data collection
May not have the skills or
expertise to be able to carry
out efficient and accurate data
collection of this nature. Can
be more costly.
Specialised departments/staff
in research may have
necessary skills to conduct
research.
Can be more efficient and
cost efficient to seek
external assistance for
infrequent and/or
specialised data collection

13. I n d i c a t o r M a p p i n g
Step 5: Embed data verification into operations
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Data verification can occur at a number of stages in the data collection process that include:
• At point of data collection by data collection staff
• Post data collection follow up verification by separate staff member
• Verification before data entry into storage system by back office staff
• Verification within system
Occurrence of data verification Activities required
At the time of data collection by
data collection staff
Verification process should be embedded into:
• Survey forms
• Data collection methodology
Staff need to be trained effectively to use survey forms and conduct data
collection methodology effectively
Post data collection follow up Staff members trained to verify data efficiently and effectively
Before data entry into system Back office staff trained to verify data efficiently and effectively
Verification within system Adjustments to system to be made

14. I n d i c a t o r M a p p i n g
Step 6: Determine where data is to be stored
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Where possible, social data should be stored in the core banking system alongside financial
and operational data and this should be a high priority for all MFIs. Social data and
financial/operational data can increase the value of each other by adding context and
meaning, and enable you to make informed and targeted decisions that positively impact on
your financial and social performance.
Social data storage
location
Implications
MIS/Core banking system Data can be analysed easily and effectively. Value
of social data increases alongside financial and
operational data.
Partial data in MIS, rest in
separate database
Data analysis is less efficient and more costly.
All data separate from MIS
(e.g Excel)
Data can still be analysed to some extent but
loses much of its value for effective decision
making if not analysed with financial data
Data captured but not stored
in system (e.g still on paper)
Data analysis is difficult or impossible and likely
not used. The value of data is lost.

15. I n d i c a t o r M a p p i n g
Step 7: Decide who is going to manage and analyse data
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It is important to ensure that staff have the appropriate skills necessary to manage and
analyse data. This will generally be back office staff/SPM champion, rather than field staff.
Where there is a lot of data, or the data is complex, seeking external support may be
necessary/more efficient.
Skills required:
• Data entry staff: Basic computer skills, familiarity with spreadsheet applications such as
Excel
• Analysis/reporting: Statistical knowledge/familiarity; good presentation skills; strong
writing skills; critical thinking skills; someone who understands current practices and
organisational objectives, good MS Office skills, especially Excel.

16. I n d i c a t o r M a p p i n g
Step 8: Decide on reporting requirements
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In determining your reporting requirements protocol, you will need to outline:
1. Who is the audience?
2. How will the data be reported?
3. Frequency of reporting/date
Your reporting audience will be internal or external stakeholders or a combination of both. Your audience
will determine the reporting format and frequency of reporting. External reporting requirements will
generally dictate the reporting document and frequency of reporting. For example Opportunity
International requires all partners to report using the SPI4 tool on a quarterly basis.
Internal reporting should, in general be more concise and more frequent than external reporting, to
ensure that regular informed decisions are made to improve performance. Internal reporting formats can
be reviewed and improved over time.

17. Step 8: Decide on reporting requirements
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Indicator
s
Data
collection
tool and
data touch
point (loan
application,
exit etc.)
Data
collection
type
(Census/s
ample)
Data
collection
frequency
(e.g.
continuous,
monthly,
annually)
Individual(s)
responsible
for
collecting
data
Data
verification
(How, by
whom)
Where is
data
stored?
Individual(s
)
responsible
for
managing/
analysing
data
Reporting
audience
Reporting
method/docu
ment
Reporting
frequency/
date
% rural
clients
Membersh
ip forms
Census Continuous Loan
officer
Back
office
MIS SPM
champion
Manag
ement
Monthly
update
Monthly
Board Quarterly
brief
QTR
Externa
l
Annual
report
Annual
%
clients
living
below
poverty
line
PPI, loan
application
Census Continuous Loan
officer
Head
office
MIS SPM
champion
Manag
ement
Monthly
update
Monthly
Board Quarterly
brief
QTR
Externa
l
Annual
report
Annual
NPS Client
satisfactio
n survey
Sample Quarterly Complian
ce officer
Back
office
MIS SPM
Champio
n
Manag
ement
Monthly
update
Monthly
Board Quarterly
brief
QTR
Externa
l
Annual
report
Annual
Indicator mapping - Example

18. C onc lus ion In the next stage you will design
your surveying tools, including:
• PPI and other outreach
indicators
• Transformation surveys
• Client satisfaction surveys
• Exit interviews
Congratulations! You have
completed the Planning Stage for
your Social Performance
Indicators.
After completing the Indicator
Mapping section of the Workbook
that accompanies this guide, you
will have effectively planned the
End-to-End process to collect,
process, analyse, and ultimately
use Social Performance data for
each of your Social Performance
Indicators.
Completing this workbook will
be extremely helpful later as you
embark on to the
Implementation Stage!
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