Efficiency Is Key to Random Digit Sampling

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The cost to make unproductive dialings will vary from company to company and location to location. Interviewer salary, supervisor time and related overhead all must be considered. Estimates by large and small research companies suggest the cost of a dialing ranges from 50 cents to 90 cents. If 69 cents, a well-documented figure presented to Survey Sampling, is used to continue our example, the cost impact is clear:

Sample Type I

Sample Type II

Total unproductive dialings

3523

2165

Estimated cost of dialing

$.69

$.69

Cost to dial unproductive numbers

$2430.87

$1493.85

By using the less efficient Sample Type I, an additional $937.02 in data collection costs will be incurred.

Greater efficiency can provide other benefits as well. With fewer unproductive numbers to dial, studies can be completed with shorter field times. In addition, encountering fewer bad numbers can boost interviewer morale.

Methodologically, efficiency has peaked

Given the significant impact of efficiency on research costs, it is no wonder that research and development to identify additional ways to improve efficiency continues.

In terms of random digit sampling methodology itself, efficiency has peaked. During the last decade, when computers allowed sampling to become a sophisticated state of the art process, various methods were employed to provide highly efficient random digit samples, including:

- frequent database updates to freshen area code, exchange, and working block data,

- cleaning out low utilization working blocks from the database,

- stratification to area code, exchange, and working block in proportion to known directory listed households,

- purging known business numbers using business database sources.

Further increases in efficiency cannot be developed methodologically without significantly risking the statistical integrity of the sample. We at Survey Sampling believe in maintaining the representativeness and projectibility of random digit samples and therefore have not moved in this direction. Rather we have broadened our scope and investigated ways to improve sample efficiency during the data collection phase of a study.

New inroads to greater efficiency

A new technology has been developed to identify a large portion of the unproductive numbers in random digit telephone samples without affecting the samples' integrity. Survey Sampling recently introduced the new "Sample Screening Service" after nearly two years of research and development.

The Sample Screening Service employs a proprietary methodology to identify disconnected and unassigned numbers in a sample before the sample is dialed during data collection. Importantly, the service involves a post-production process so the integrity of the sample is not compromised in any way. Random digit samples are selected by standard methodologies, then the standalone process is applied to identify and mark unproductive numbers.

The service identifies, on average, half of the disconnected or unassigned numbers in a sample, which results in a 10-15% increase in sample efficiency. Survey Sampling's normally high working phones rates of 65-75% is improved to an effective working phones rate of 75-85%.

The 10-15% additional increase in efficiency achieved by utilizing the Screening Service extends the many benefits of sample efficiency discussed above. Further cost savings during the data collection phase of the research study will be realized and so will shortened field times, better interviewer morale, and a generally more efficient operation.