The Quick Count and Election Observation
The Quick Count and Election Observation
The Quick Count and Election Observation
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THE QUICK COUNT AND ELECTION OBSERVATION<br />
Information Flows from the Field<br />
<strong>The</strong> experiences of groups that have conducted quick counts provide two very<br />
clear lessons about information flows, <strong>and</strong> each of these has important logistical<br />
<strong>and</strong> analytic implications that need to be clearly understood.<br />
First, on election day, there are very substantial fluctuations in the volume of<br />
information flows from observers in the field to the data collection center. <strong>The</strong><br />
typical pattern, summarized in Figure 7-1, is based on real data gathered from<br />
a recent Latin American election. In that particular case, the election law<br />
required that polling station officials open the polling stations by 7:00 a.m.<br />
Observers were asked to be present at the polling station by 6:15, some 45<br />
minutes before polling stations were due to open. <strong>The</strong>y were asked to report<br />
their Form 1 data, the qualitative data, immediately after the first voter had<br />
voted at their polling station.<br />
<strong>The</strong>re are very substantial<br />
fluctuations in the<br />
volume of information<br />
flows from observers in<br />
the field to the data<br />
collection center.<br />
103<br />
50<br />
FIGURE 7-1:<br />
TYPICAL DISTRIBUTION OF<br />
PHONE CALLS<br />
Calls / 10 minutes<br />
40<br />
30<br />
20<br />
10<br />
7:00 a.m.<br />
8:00 a.m.<br />
9:00 a.m. 10:00 a.m. 11:00 a.m.<br />
This pattern of fluctuations in the volumes of information is essentially the<br />
same for both the qualitative <strong>and</strong> the numeric data. At 7:00, the data collection<br />
center receives no information at all. Information begins to trickle in to<br />
the data collection center after the first thirty minutes, between 7:30 <strong>and</strong> 8:00.<br />
<strong>The</strong> earliest data to arrive come from the most efficient polling stations <strong>and</strong><br />
where observers have easy access to telephones. By 8:30, the number of phone<br />
calls into the data collection center has increased dramatically, <strong>and</strong> by 9:00<br />
that trickle has turned into a deluge. In this particular case, calls were arriving<br />
at the data collection center at a rate of some 55 calls per 10 minutes or 5.5<br />
calls a minute. After that peak period, the volume of calls coming into the data<br />
collection center starts to fall off, <strong>and</strong> then it slows down dramatically.<br />
<strong>The</strong>se uneven information flows present a logistical challenge. <strong>The</strong> task is to<br />
develop a strategy that anticipates—<strong>and</strong> then effectively manages—the peak<br />
volume of information intake. At issue are two questions. Does the group have<br />
the communications capacity to accept all the calls during the peak period?<br />
<strong>The</strong> task is to develop<br />
a strategy that effectively<br />
manages the<br />
peak volume of information<br />
intake.