Page 23 - Methodology for measurement of Quality of Service (QoS) Key Performance Performance Indicators (KPIs) for Digital Financial Services

6 ACQUISITION OF DATA ON DFS tion of the Ghana Pilot Campaign) where respective
TRANSACTIONS considerations have been used.
6.1 Overview 6.2 Primary DFS data collection modes
In order to compute DFS KPI, respective input data
need to be collected. 6.2.1 General remarks
The method used should be robust and provide a The procedures in the following are defined to provide
high level of data quality. Robustness means that the operational robustness. They include steps which are in-
system should ensure security against loss of data. Data tended to provide some redundancy and elements of
quality refers to aspects such as reproducibility and data backup.
plausibility tests to detect wrong data. The term “uploading” is used in a functional way.
Figure 6-1 is a graphical representation of measure- Where smartphones are the platform (e.g. when taking
ment data flow and handling. Please note that this is a photo of a completed data log), it is assumed, unless
a rather schematic and simplified view. Details given in otherwise mentioned, that this means sending respec-
the following sub clauses have precedence. tive data by e-mail.
In the present methodology a manual method will be As far as PCs are the platform, it is assumed that FTP
used to collect the primary information, i.e. timestamp or http upload will be used. It is further assumed that for
data for events needed to compute KPI will be entered this upload, the ITU IFA server will be used.
manually by a member of the measurement team.
There is in addition, secondary information in the 6.2.2 Collection on paper, later transfer
form of summary SMS sent by the system at the end Paper printouts of respective tables are created. These
of the transaction. These SMS will be read from the de- printouts are called ‘data capture sheets’ (DCS) from
vices in a bulk fashion, and also transmitted to the data here on.
processing system. Each DCS shall carry some information to allow data
For primary data collection on DFS transactions, consistency and completeness checking:
there are two possible approaches: - Identification of the team.

a) Collection on paper and subsequent transfer into - Date.
electronic forms (e.g. Excel®). - Location of test.
- Running number of test in this specific location.
b) Direct entry to electronic forms (e.g. Excel® tables).
When a new location is used, a new DCS is used.
Both methods have their respective merits and will During testing, the team member enters data manu-
therefore be described subsequently. See also (Descrip- ally into the DCS.

FIGURE 6-1: Schematic overview of measurement data flow and handling

MoMo Service Test Data MoMo Notifcation SMS Background Measurements

MoMo • Record local condition in Location Systems • Run active tests for
Tests and Log Forms sends • Automatically send Active primary carrier
primary • Record Transaction results to Status SMS SMS records to data Tests services (packet data,
data Data Log Forms on A and destination SMS, USSD)
acquisition • Record events in Event Log Forms B side

• Transfer content of data forms
Primary to Excel tables Convert • Convert record • Automatic data
data • Mail Excel tables to data SMS backup content to SQL Data upload to DFS Data
capture destination records import code Upload Server
• Back-up procedures (photo/mail)

Import to • Import Excel tables to main Import to • Import notification Import to • Convert data and import
database database SMS to SMS database into Background
• Data Validation database • Validate data database Measurement data base
• Data Validation

Process data to reports

Methodology for measurement of Quality of Service (QoS) Key Performance Indicators (KPIs) for Digital Financial Services • 21Methodology for measurement of Quality of Service (QoS) Key Performance Indicators (KPIs) for Digital Financial Services • 21