What is Block Sampling?

Block sampling is a sampling technique used in auditing, where a sequential series of selections is made. This approach is very efficient, since a large cluster of documents can be pulled from one location. However, a more random selection method would do a better job of sampling the entire population. When using block sampling, sampling risk can be reduced by selecting a large number of blocks of samples.

Disadvantages of Block Sampling

While it is a simple and convenient method, block sampling has several disadvantages, which are as follows:

Lack of representativeness. Block sampling often results in non-representative samples because all items are chosen from a single section or block. This can lead to biased results if the characteristics of that block do not reflect the entire population.
Higher risk of selection bias. If the block chosen contains unusual or atypical transactions, the results of the audit may not accurately represent the overall population, increasing the risk of incorrect conclusions.
Limited coverage. Block sampling inherently focuses only on specific parts of the population, leaving other areas unexamined. This can result in overlooking key issues or risks present in other parts of the dataset.
Increased risk of missing errors. If errors or irregularities are not present within the selected block, they may be completely missed. This is particularly problematic in populations with dispersed or randomly occurring errors.
Potential for overlooking seasonal variations. Block sampling can fail to account for variations across different time periods or other relevant dimensions if the selected block does not include them.
Not suitable for heterogenous populations. When the population is heterogeneous (i.e., contains diverse elements), block sampling can be ineffective because it does not capture the diversity of the population.
Reduced audit efficiency. While block sampling may save time initially, the lack of representativeness can lead to additional work, such as revisiting the sample or expanding the audit scope to address deficiencies.

Block sampling is best suited for situations where the population is homogeneous and errors are likely to occur consistently across all sections. However, in most real-world audits, these conditions are rarely met, making other sampling methods like random or stratified sampling more appropriate for ensuring accurate and reliable audit results.

Example of Block Sampling

An auditor elects to use block sampling to examine customer invoices, and intends to pick 50 invoices. She picks invoice numbers 1000 through 1049. As another example, the auditor decides to pick all invoices issued on April 15.