Data Capture and Collection for Data Quality

September 06, 2012 by Andrea Spillmann

Last week's post provided an overview of the four stages of data collection, listing quality control mechanisms for each. This week's focuses on the first: data collection/data capture.

Data quality in data collection

Ideally, forms should be filled in completely and accurately. (photo credit:

To recap from last week, quality data is both accurate and complete. That means  missing pages, blank fields, invented values or misspelled words. For the purpose of this post, data collection includes anything from potential customers adding their name to an email list, to a beneficiary filling in an insurance claim form, to an organized team of enumerators interviewing respondents for a large-scale research survey. As you probably know too well, getting complete and accurate data in those (and most other) cases is complicated. Potential customers skip the email address field, beneficiaries don't see the back of a 2-sided form, and then there's "curbstoning" (where enumerators fill in a batch of surveys with invented values to save time observing or interviewing people). Even if documents are filled in completely and accurately, pages fly away, coffee spills, and stacks of forms get misplaced during spring cleaning.
Are all your filled-in pages in this stack...and in the right order? (photo credirt:

Ensuring data quality

All of these problems don't condemn you to low-quality data, though. Checking for accuracy and completeness throughout the data collection process, ideally at the point of entry, can help you catch and correct issues. If you're still on-site when you realize data is missing, the offending piles of forms can be found, pages can be re-collated, and, sometimes, skipped fields can be filled in. Catching data capture issues early, meanwhile, lets you tweak data collection processes, re-training enumerators, asking customers personally for their email address, or reprinting confusing forms. The earlier and more locally issues of accuracy and completeness are caught, the easier they are to fix.

Challenges to implementing quality assurance

Implementing checks throughout the data collection is much easier said than done, though. Counting individual survey pages is time-consuming and not always accurate. Meanwhile, inaccuracies or omissions don't usually show up by visually skimming forms. You need structured, digital data to help you spot problematic patterns. Getting that data entered, though, may take weeks or months. In many cases, data entry may not start at all until after the data collection is complete, at the end of a conference, survey campaign or financial quarter.

How Captricity Helps

Values entered using Captricity quickly show one field left blank across multiple forms.

Captricity offers a number of features that make ongoing data checks far easier:

  • Faster data entry for ongoing accuracy checks: Instead of waiting for your data collection to be completed, you can upload your forms as they come in. You'll get your fully-entered data back in hours. Check that all potential customers filled in their email address, that beneficiaries are seeing all of the questions or that enumerators are doing their job completely after day 1.
  • Completeness checks: Upload scanned forms to Captricity to be entered, and we'll tell you if a page is missing. Your papercut fingers will appreciate the break from counting pages.
  • On-location service: Captricity's web-based service can be accessed from any location with even the spottiest of Internet or mobile data access. Snap and upload photos of forms with your mobile phone right from the field, or use a light-weight scanner in local offices to capture batches of forms as you file them.


What's next?

Now that you've collected complete and accurate data, you need to get it all entered into a more useable, digital format...and you need that done quickly and accurately. The next post in this series will tell you how to do that. Stay tuned for more!

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