The Big Data Approach to the Big 5 Assessment

The Big Data Approach to the Big 5 Assessment

Naveen Joshi 02/08/2021
The Big Data Approach to the Big 5 Assessment

The big 5 assessment is a handy way for recruiters to determine the personality of job-seeking candidates by assessing five key traits —agreeableness, neuroticism, conscientiousness, extraversion and openness to new experiences.

If you practice regularly and hard enough, you can learn to lie with a straight face to anyone. Beyond a certain point, it is hard for even the most perceptive of minds to tell whether someone is being completely honest with them over an interview or not. As a result, hiring the most appropriate individuals based on conventional interviewing methods proves to be difficult for organizations. Now, let’s dial up the difficulty level by a few notches. Imagine a real-life recruitment drive conducted remotely with hundreds of candidates vying for a few open vacancies in your organization. It becomes incredibly hard for recruiters to ascertain whether the personality traits projected by a candidate on the other side of the screen are owned or borrowed. To overcome such issues, several types of assessments were created to determine a candidate’s personality much more efficiently. Today, organizations mainly use tools to assess the big 5 personality traits in candidates. The big 5 assessment simplifies the process of recruitment by evaluating the personalities of candidates with respect to the following attributes:

  • Openness to new experiences.
  • Conscientiousness (defines how careful or diligent an individual is about his or her work).
  • Extraversion (defines whether a candidate is an introvert or an extrovert).
  • Agreeableness (defines whether candidates are friendly/diplomatic or rational and critical)
  • Neuroticism (defines whether candidates are mentally steady and confident in high-pressure situations or not)

Big data in psychometrics is an innovative mix to enhance recruitment-related personality assessments for organizations globally. Big data, by definition, is massive volumes of information used to train and operate AI algorithms. It is rightly credited with revolutionizing the digital world with its host of benefits. Using big data for candidate personality assessment promises to have interesting consequences for everyone involved in the process.

How Big Data Fits Into Personality Assessments


The five personality traits, abbreviated into OCEAN, are regarded as quintessential parameters for employees in any industry to be worth keeping to their employers. During the recruitment phase, candidates are asked certain questions linked to each personality attribute. Based on their answers to those questions, recruiters will know which candidate possesses which attribute in greater proportions out of the big 5 traits. These traits will reflect his or her personality type and, ultimately, enable organizations to make decisions about hiring or rejecting them.

Quite simply, big data provides the fuel for AI-powered web assessment systems to conduct personality evaluations. The historical data of thousands and thousands of job-seeking candidates helps AI-powered systems to classify an individual into a specific personality type based on his answers, facial reactions, and body language during an interview or a test. Big data is a burgeoning body of information that is constantly growing by the accumulation of more and more data on a daily basis. After the data is collected, an AI system classifies individuals into various clusters based on their responses. Big data is beneficial for organizations as it allows their online assessments to have greater depth and clarity owing to the billions of data bytes involved in the process.

Personality assessment (and big data in psychometrics) is not just limited to job recruitment. Marketing companies on social networking platforms use the data of millions of users to show them ads related to any product or service they may have googled about in the previous week or more recently. Session cookies and reactions (likes, shares, comments) on social networking websites allow corporations to know what individuals wish to purchase. The ads shown on the social media page of an individual are a result of big data and machine learning working in tandem.

Methodology of Big Data Processes in Personality Assessments

Now that we have roughly seen how big data is used for personality assessment, let us understand how organizations use large information swathes to correlate generic personality traits to the characteristics of a candidate. The questions asked by interviewers during the recruitment are initially treated in the following way:

  1. Firstly, similar types of questions are grouped together in order to reduce the number of variables in the process.
  2. The classification and grouping of questions into similar types allow organizations to build reliable psychometric models for recruitment-related personality assessments.

Organizations use statistical models such as the correlation heatmap matrix to understand how specific personality traits correlate to an individual’s character. Additional tools, such as the Classification And Regression Trees (CART) and correspondence analysis are used to clarify the groups of classified data. Data scientists and experts who are involved in the application of big data in psychometrics need to simplify the classifications down to the broadest categories to make it easier for recruiters to assign specific personality types to specific candidates based on their response to the interview questions.

Benefits of Big Data in Personality Assessments

  1. Candidates from all parts of the country or the world can give interviews or take personality assessment tests remotely. As a result, a greater number of candidates can be covered by organizations so that location-related issues are not a barrier between recruiters and the best talent available for hire. On the other hand, a large pool of candidates allows the big data to assimilate more information for future use.
  2. The involvement of AI and big data in personality assessments can be cost-effective for recruiters. Hiring personnel for the task of conducting interviews and personality assessment tests on their own can end up being a needlessly complicated and expensive affair for organizations.
  3. Remote recruitment interview questions can be pre-recorded. The questions, grouped as per big data requirements, are fed into an AI-powered system. A candidate’s answer is recorded by the system that also analyses the candidate's body language before combining all the factors together and running them through big data's gargantuan library of personality types.
  4. Perhaps the main benefit for organizations is the prospect of converting passive job-seekers (those already in a job, but probably looking for new ones) into potential job applicants for them. This is achieved through big data's reach across the entire digital spectrum to track candidates' digital footprints.
  5. As mentioned earlier, personality assessments are not just invaluable for organizational recruitment but for other purposes too. For example, big data can be useful for predicting crimes by former felons out on parole or ones who are released (based on the behavioral big data record of previous ex-convicts).

Guidelines to Use Big Data in Psychometric Personality Assessments

Ultimately, big data’s main application is for machine training of AI models and neural networks. Therefore, here’s a list of guidelines that organizations can follow while using AI-powered systems for the big 5 personality assessments:

a)   Ensure Uniformity of data For All Candidates

Consistency is key during a remote recruitment drive. Organizations must ensure consistency in the questions asked for each candidate. The collected big data must be consistent so that AI-powered assessment tools do not perform inadequately during personality assessments. AI's sorting and matching capabilities must be put to good use by providing matching job profiles to candidates. In this way, the candidates will be able to make smoother decisions and his or her personality evaluation will become easier for organizations.

b)  Use Local Validity for New Assessment Methods

Firstly, the data used for personality assessments must be selected from past records of your own organization. While it is generally seen that small sample sizes, range restriction, and unreliable measures may derail the entire exercise and impair an organization’s ability to properly determine the personality types of candidates, organizations can make corrections for these problems in the long run. As a result, initially, at least, the assessment procedures must be applied to local data to see how effective they are. In case the assessment techniques are successful, organizations can dabble into larger data sets to use personality assessment for heavy-duty recruitment.

AI and big data are increasingly being used in nearly every industrial operation today. It is inevitable that one day, organizations will start using these modern technologies for the purpose of remote recruitment too. In today’s pandemic-ridden age, remote recruitment is the only sensible option for organizations all over the world. The obvious benefits of big data in personality assessments are already enlisted. The limitations? Purists may argue that traditional personality tests are way more effective compared to AI and big data assessments. However, the concept of human error and fallibility is also apparent in traditional personality assessments.

With AI and big data’s massive bag of tricks, a master liar simply would not be able to make it through the assessment, no matter how long and hard he has practiced the art of lying with a poker face.

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Naveen Joshi

Tech Expert

Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.

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