Cost-Efficient Framework for Data Collection for CATI Surveys Social Surveys Collection Research Steering Committee (SSCRSC) François Laflamme December 2010 Statistics Canada • Statistique Canada Past and current research Paradata research has mainly directed its effort in improving the current data collection process and practices Paradata research has also suggested that the interviewer staffing levels are not always optimally allocated with respect to the workload sample and the expected productivity 2 Statistics Canada • Statistique Canada 2017-07-28 Challenges and objective One of the main challenges is to collect costeffective data while maintaining a high level of quality According to the forecasted budget reductions, the pressure has increased and will continue to grow The objective of the project is to propose a costefficient framework for data collection for CATI surveys 3 Statistics Canada • Statistique Canada 2017-07-28 Cost-efficient framework Five 5 dimensions: 1. 2. 3. 4. 5. 4 Metrics used for costing and budgeting surveys Resources allocation within surveys Resources allocation between surveys Collection process and practices Operational constraints Statistics Canada • Statistique Canada 2017-07-28 1. Metrics used for costing and budgeting surveys Should be based on objective, measurable and comprehensible assumptions Should be monitored throughout the survey collection Budget too high - low productivity Budget too low - more difficult to reach targets Budget often based on previous survey cycles or comparable surveys But it is exactly what we try to improve (e.g. low TPU) 5 Statistics Canada • Statistique Canada 2017-07-28 2 & 3. Resources allocation within and between surveys Within survey Interviewer staffing levels should consider sample workload and collection progress in taking advantage of the entire collection period ● Survey productivity decreases for all CATI surveys during collection Between surveys Many concurrent surveys compete for data collection resources 6 Statistics Canada • Statistique Canada 2017-07-28 Resources allocation within and between surveys What is the best strategy within survey? Examples of Resources Allocation by Data Collection Days Uniform Proportional Hours Front Loading Data Collection Days 7 Statistics Canada • Statistique Canada 2017-07-28 Resources allocation within and between surveys The main idea is to try to maintain the survey productivity for all surveys for a given RO (red line) between reasonable boundaries around the average productivity How? Daily Productivity, Some Social Surveys, January to March 2010 Winnipeg 100% LFS CCHS All Surveys 80% LFSTFC SLID Average All Surveys 60% 40% 20% 0% 30-Mar 27-Mar 24-Mar 21-Mar 18-Mar 15-Mar 12-Mar 09-Mar 06-Mar 03-Mar Statistics Canada • Statistique Canada 28-Feb 25-Feb 22-Feb 19-Feb 16-Feb 13-Feb 10-Feb 07-Feb 04-Feb 01-Feb 29-Jan 26-Jan 23-Jan 20-Jan 17-Jan 14-Jan 11-Jan 08-Jan 05-Jan 02-Jan 8 Data Collection Day 2017-07-28 Resources allocation within and between surveys The strategy is to distribute system time for a given period (day or week) in function of the inverse of the proportion of the budget spent (inversely correlated to productivity) to maintain productivity at RO level Data Collection Day Survey CCHS LFS HES CTUMS ….. Survery X 1 3 4 5 6 7 8 9 10 11 12 13 14 … … 30 Budget CCHS Budget LFS Budget HES Budget CTUMS ….. Budget survey_X C1 9 2 RO Budget (hrs) C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 Ro Capacity - Daily Hours Active surveys on that day Past collection day Next data collection day is the 3rd Statistics Canada • Statistique Canada C30 2017-07-28 Resources allocation within and between surveys In practice Need to get consistent budget figures for all surveys Need to get daily or weekly capacity system time Need to consider the active collection period of each survey Need to take into account operational constraints Is it feasible? Can it be operationalized and automated? The objective is to produce guidelines for RO to help them allocate collection resources only at the aggregate level. 10 Statistics Canada • Statistique Canada 2017-07-28 4. Collection process and practices Focus of the past research Some examples Best time to call Call scheduler features ● Cap on calls, customized time slices, Z-groups etc… Increased the proportion of evening shifts versus day shifts to improve contact rate and productivity Active management Responsive collection design No significant efficiency if budget and resources allocation remain the same. 11 Statistics Canada • Statistique Canada 2017-07-28 5. Operational constraints RO capacity Varies by day (interviewer availability) LFS week Holidays and special event Average productivity Varies by RO and survey Interviewer schedule in advance Interviewer training across surveys Etc… 12 Statistics Canada • Statistique Canada 2017-07-28 Comments 3 Separate projects Costing metrics Resources allocation within and between surveys Collection process and practices All need to take into account operational constraints All dimensions have to be considered simultaneously to succeed in improving the costefficiency of data collection. 13 Statistics Canada • Statistique Canada 2017-07-28 For more information, please contact Pour plus d’information, veuillez contacter François Laflamme [email protected] 14 Statistics Canada • Statistique Canada 2017-07-28
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