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Lisa Cohen


How to Make the Dreaded Task of Data Entry Less Despised

Not all data work is created equal

Published: Wednesday, March 4, 2020 - 13:02

A recent study showing that data entry is one the most redundant and hated workplace tasks raises questions about why, in the age of artificial intelligence, data mining, and smart technologies, this task is still being done manually.

Is there any way it could be less despised?

My ongoing fieldwork in a data-driven startup, referred to as Sage (a real company, but not its real name due to confidentiality requirements), suggests that technological solutions are not nearly as sophisticated as many assume—and are not going to replace human data entry any time soon.

For nearly two years, I’ve been studying the evolution of Sage’s hiring practices and jobs.

Sage’s initial plan was to develop and use AI to produce data it would sell to clients as part of its broader services. In the meantime, Sage asked its analysts to collect and enter those data manually. But when Sage ran a pilot project with an AI consulting firm, it discovered that AI would produce, at most, 5 percent of the data that Sage was collecting manually, and at a substantially higher price.

The company couldn’t afford the AI. As a result, Sage shifted its data-collection strategy from AI to human intelligence. Recognizing that analysts were too expensive and would be too dissatisfied doing this work exclusively, Sage hired dedicated data-entry operators in a satellite office to do much of the work.

Technology doesn’t always work

This type of scenario is not rare. Technology doesn’t always work as expected, and has varied effects across different jobs and organizations. The failings of technology, however, offer only a partial explanation of why manual data entry still exists as a task, and could for quite some time. To understand more, we need to consider tasks in a broader context.

Tasks rarely exist in isolation. They are part of jobs, and those jobs are made up of other tasks. They are associated with people who perform them, others who manage them or work with them, and with other jobs within occupations and organizations.

This broader context, and the relationships within it, makes it difficult for any task to be eliminated altogether but also means that a single despised task does not always mean an entirely despised job.

At Sage, the very rote task of entering data was almost inseparable from the act of collecting data. Although some of the data could be found easily in annual reports, for much of the rest, analysts, and then the data entry operators, had to search the internet for additional information. Once they found this information, they then had to enter it into a database.

It would make no sense and would be virtually impossible to automate the data entry part of this task.

This highlights that not all data entry work is created equal, and not all data-entry jobs are the same. As a result, attitudes about data entry are much more complex than the recent survey suggests.

False expectations

The Sage analysts did despise the data entry work, but not only because of the nature of the task itself. Expectations shaped their attitudes. When they were hired, many of them had expectations that they would be doing what they called analyst work—things like creating reports from data, writing content, and interacting with clients.

Some of them had initially applied for consulting jobs that were to be made of up of the aforementioned responsibilities. They were expecting work that was more glamorous, more fulfilling. In this context, it’s not surprising that they considered data entry drudgery and thought it was beneath them.

The data entry operators, on the other hand, were hired with expectations that they would be doing what the title of the job implied—data entry. Unlike the analysts, some of them reported being pleasantly surprised by the job and the amount of thinking and judgment it involved.

Even within the same job in the same organization, there can be variations in what employees do, and these variations can lead to different outcomes.

For instance, one study showed that female Transportation Security Administration (TSA) agents in the United States ended up doing many more pat-downs, an undesirable task, than male agents. The results of this were lower job quality and reduced opportunities.

Data entry operators promoted

The story at Sage is far from complete. I continue to watch as the tasks and roles evolve there. A recent strategy pivot at the company has meant that data collection became less central to the firm’s goals.

With this pivot, the role of the analysts has evolved to include much more interaction with the company’s developers in creating products for the clients and doing more to produce content.

The data-entry operator job, however, is largely unchanged. People do come and go from it, but some of the data entry people have been promoted to analyst positions, suggesting that the dreaded task may be a pathway to less dreaded work.The Conversation

This article is republished from The Conversation under a Creative Commons license. Read the original article.


About The Author

Lisa Cohen’s picture

Lisa Cohen

Lisa Cohen is an associate professor of business administration at McGill University.


Data Entry is a Huge Factor for Calibration Software

Great article. I rarely seeing anyone talking about this, but it has a big influence on whether your gage management software can be effective at reducing labor costs. The people responsible for calibration data have a lot on their plates. If your software doesn't make data entry easy, people don't like to use it. Just as importantly, if migrating data from one calibration software to another is too labor-intensive, companies will stay with their legacy platforms even if they are not performing well over the long haul. Or they'll pay to have software providers do the migration for them, so software providers have grown used to taking advantage of these deficiencies to create profit centers that should be unnecessary in the 21st century. Free or low-cost data migration concierge services is one way we've found to get companies into software models that are consistent with the simplicity and usability standards people are starting to expect in all their digital products.