Inside the Process for Cleaning HR Research Data

by   |   December 11, 2012 1:44 pm   |   1 Comments

Every day, HR departments rely on vendors such as Mercer, Aon Hewitt and Towers Watson to conduct in-depth surveys and analyze data to determine everything from compensation pay to employee attrition. So when an HR manager detects an error in data—such as mismatched job descriptions and incorrect salary calculations—it’s easy to point the finger at a survey vendor. Unbeknownst to many HR professionals, however, survey vendors must adhere to a strict code of conduct when collecting and analyzing data from their clients. While mistakes are made every now and then, data quality policies and procedures are designed to minimize errors.

Beth Ann Finis, a principal in Mercer’s information products solutions business, describes a few of the steps survey vendors take to ensure data cleanliness and the role HR leaders play in facilitating this important process.

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1. Get the right raw data. Without the proper data in the first place, companies are likely to end up with incomplete or inaccurate analyses.

To avoid this fate, Finis says the first step is for HR executives to make sure they’re gathering the right survey data. “HR professionals need to ensure that the data is coming from a reliable source, that their methodology for collecting data is sound and fits the philosophy of the organization and that they’re able to zero in on and isolate the data that’s most relevant to the company,” says Finis. For example, she says that if a company wishes to determine the proper compensation for a senior-level sales rep in the Northeast, it’s critical that an HR representative avoid including data on entry-level workers in the Southwest in its round-up of information.

2. Show a willingness to work together. Collecting and crunching the right data “is really a shared responsibility,” according to Finis. For this reason, Finis says many survey vendors go to great lengths to work in concert with HR leaders.

Collaborative initiatives include poring over survey questions together, providing clear instructions to HR representatives responsible for filling out the survey and making sure they understand the questions properly. That means giving HR professionals a number of ways to interact with a survey vendor throughout the research process, whether via phone or email. “We always tell our participants that we rely on them to ensure that the data is of high quality and to not only provide good information but to be available for questions,” says Finis.

3. Ensure the opportunity to circle back. Time-strapped HR managers are often eager to wash their hands of labor-intensive tasks such as collecting data. But that’s a mistake, according to Finis. Instead, she says that once a survey has been completed, top-notch survey vendors always sit down with a client to pore over details.

“It’s so critical that we clarify all the information provided,” says Finis. “It’s not until it’s all put together that we’re able to see where things might not make sense or maybe where an HR person misinterpreted the question.” To vet all this information thoroughly, Finis says HR leaders must be willing to submit their data on time and to set aside sufficient time for an in-depth review process.

4. Evaluate marketplace context. Even the most reliable data requires context for proper parsing. That’s why survey vendors such as Mercer stay abreast of the market changes impacting their clients. For example, the compensation data a Silicon Valley software company collects will differ wildly from that of an auto parts manufacturer in Michigan. Understanding the competition, marketplace challenges, technological advancements, pay differentiators and hiring practices of each of its clients is essential for a survey vendor “to be able to interpret the results of data analysis and to make sure that these findings make sense and can be validated,” warns Finis.

5. Conduct a multi-level inspection. It’s not enough to simply sift through data with a client and then toss it into a computer model for analysis. Rather, Finis says survey vendors perform multiple levels of review throughout the process. Once data has been collected and discussed with the client, Finis says the next step is ensuring that the data provided is consistent across the questionnaire. In other words, are there areas in the survey where the client responded differently to the same question?

6. Validate research data using public information sources. Next, the survey vendor conducts a more in-depth review by validating data against public information. Red flags might include salary information that’s out of whack with a competitor’s pay scale. Or, for example, sales figures that don’t jibe with industry averages for a particular region of the country. By detecting information that’s “out of the realm of typical norms,” Finis says survey vendors can intercept faulty data before it’s passed back to an HR team for decision making.

In the end, the combination of eyeballs and automated checks and balances is essential to avoiding error-riddled data. But only by working together can HR professionals and survey vendors keep their numbers clean.

Cindy Waxer is a Toronto-based freelance journalist and a contributor to publications including The Economist and MIT Technology Review. She can be reached at  or via Twitter @Cwaxer.

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One Comment

  1. Posted December 12, 2017 at 11:29 am | Permalink

    Fort Lewis College

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