Data… used by many, understood by few.

It’s all around us and available for use, but not many professionals don't understand the value of data and how they can access it, organize it and use it to their advantage.

Also in the recruiting space there are very few sourcers and recruiters who really master the use of data in their process.

But when you use talent data the right way, it can give not only strategic advantages by providing insights, but it can also serve as a means of sourcing talent in a smarter and much more efficient way.

For example, if you as a recruiter are able to review the top three skills of a candidate in the blink of an eye, can filter on candidates who have been part of a fast growing company and know how to get their verified contact details with a click of a button, you’re likely to win in today’s world of recruiting.

This guide will help you understand talent data better, how you can access it and how you can make better use of it.

1. What types of data are there
2. Talent data attributes: what relevant talent data looks like
3. How to organize talent data
4. How to make use of talent data

What types of data are there

The first step in understanding the value of talent data is looking at what types of data are available and what those different categories of data can mean in sourcing and recruitment.

Data can be categorized in many different ways: 

• Quantitative vs qualitative data
• Fit vs intent data
• Public vs private data
• External vs internal data
• Company vs company data

Quantitative vs qualitative data

Quantitative data are basically numbers. 

Qualitative data is descriptive in nature and usually in the form text. 

Quantitative data in recruiting is usually used as a filter, like the number of experience years that someone has in a certain position.

Qualitative data is usually used for a recruiter to interpret the ‘quality’ and relevance of information on a candidate in respect to a job.

Fit vs intent data

Fit data is data about how well the candidate matches (fits) the job and the company.

Intent data is data about how interested the candidate is in applying for the job.

In other words fit data in recruiting is used to determine if a candidate qualifies and intent data to determine the level of probability of a candidate to say yes to a job.

Intent data can be further categorized into behavioral data (what people do and when they do it; actions) and contextual data (the situation in which people show their behavior; time, location, device…).

Public vs private data

Public data is data that is available and accessible to the public (arguably without any limitations).

Private data is data that is intended to be shared only with a specific set of people and sometimes with no one at all.

An example of public data is a LinkedIn profile that you can find online. An example of private data is a secured profile, website or database only accessible with a password.

External vs internal data

External data is data which comes from external sources like social media, external databases, websites and service providers that provide data.

Internal data is data coming from your organization itself, like data on performance reviews, hires, contracts, internal skills and internal mobility.

Person vs company data

Person data is data about an individual, like their name, job title and top skills.

Company data is data about a company that includes things like industry, company size and business.

Person data is used to search individuals and assess them on their background, interests and personality. Company data is typically used by recruiters in the context of an individual to help assess the relevancy of their experience at the companies they have worked. 

All these types of data can be analysed by either humans (recruiters) or machines (Artificial Intelligence).