Collection No 6

Future of Work

The Resume of the Future

Personal data will redefine the resume.

Legend has it that Leonardo da Vinci authored the first professional resume. Written for the Duke of Milan, it consisted of 10 points that emphasized da Vinci’s military engineering expertise, while only briefly mentioning his adeptness in painting and sculpture. In concluding his resume, da Vinci described its intent as an endeavor “to make myself understood to Your Excellency for the purpose of unfolding to you my secrets, and thereafter offering them at your complete disposal.” The spirit of this initial intent remains, but the resume itself has evolved greatly since da Vinci first penned his 10 points.

Advancements in technology drive changes to the format and content of modern resumes. Resume composition tools are as diverse as ever, and so are the methods of personal storytelling. In the last 60 years, resumes have been composed on everything from typewriters to word processors to video cameras. Recently, they have expanded to include social network profiles and infographics, and soon we will be constructing resumes with the medium of this moment: our personal data.

The data resume presents great opportunities for both sides of the employment equation. For those on the hiring end, a quantified resume offers a deeper look into the experience and work patterns of a potential employee, and it creates a standard baseline from which businesses can quickly compare dozens of candidates. For those seeking employment, the data resume offers a chance to truly stand out and accurately represent oneself. It also has the potential to change the way we advertise and apply for open positions. Instead of highly qualitative—and sometimes esoteric—job descriptions, the data resume introduces a quantitative approach that cuts out adverbs and adjectives in favor of the data-focused essence of the job requirements.

One of the most common requirements listed on a job posting is the ability to work well with others. Most people work in teams, whether virtual or otherwise, and it is important that a candidate can fit into an established group. An applicant can describe his or her ability to work in a team, but a written description of an applicant’s skill says more about that applicant’s writing technique than his or her capacity for teamwork. Data presents an opportunity to get at this and other difficult questions in a new way.

A handful of easily accessible data sets can illustrate how a candidate works with others. Frequency of emails and instant messages demonstrates an aspect of communication style. Meeting frequency and attendance show another. Cross-referencing those two sets of data shows how much face time an employee engages in, as compared with that employee’s virtual communication. Impromptu discussions and team dynamics are harder to capture, but not out of reach. Some data collection apps like Reporter, which uses randomly timed surveys, can be customized to capture specific data sets with a little extra effort. Armed with this data, the story of teamwork and collaboration becomes fuller and richer and, quite possibly, more reliable.

Our data is as personal as our fingerprints. Idiosyncrasies make this data extremely valuable in the process of matching candidates to roles. However, a complete revolution of the resume is not yet at our door. The value of these personal data sets cannot be fully realized until they can be pulled together from the disparate silos they currently call home. The tools and know-how to do so is currently beyond that of most HR departments and hiring managers, and typically reside only in the technical departments, where fluency in the tools of database management are more prevalent. Eventually, data analysis tools will improve and these silos will break down. The skills required to analyze complex data sets will become available to HR professionals, who will then find themselves empowered to accept and analyze hundreds of applicant data sets at a time. These are not perfunctory hurdles, but what lies on the other side of them is a whole new way to evaluate candidates.

Data changes the way we look at our own lives and drastically alters how we evaluate others. It can provide employers with valuable insights as they attempt to hire the best possible candidate, and it can allow candidates to frame their experience in a way that is deeper, richer, and more honest. In the coming age of the data-driven workplace, the data resume will benefit the most important resource for any organization: the people.

Personal Data in Action

Throughout 2014, I used a mobile application called Reporter to collect information about my daily activity and interactions. Reporter sends surveys at random times throughout the day, and the survey questions are fully customizable. The questions I asked myself were: where are you, what are you doing, and who are you with? This data now provides insights into how I collaborated and worked in teams over a 10-month period.

The first chart shows how I spent my time at work—whether I was working with others or working on my own. That activity is then shown distributed over time. Including the beginning and end dates of each project across that timeline reveals how much my activity changed from project to project.


The second chart shows the role of the team members I interacted with while at work. Those interactions are then plotted over time, showing the sum and frequency of my interactions with each coworker. Including the project team composition in the pie charts reveals how the team makeup affected my individual interactions.


Visualizing this data allowed me to uncover several interesting insights. First, there are clearly different rhythms of activity and interaction among the projects. Second, smaller teams and shorter projects were heavier in collaboration, whereas the big teams and longer projects relied more on scheduled meetings. These two insights indicate that working in teams required flexibility and continual adaptation. Third, the level of team-led involvement varied slightly from project to project, but the core team involvement was consistent. Regardless of who was in charge, the team had to collaborate to move the project along.

Eric Boam

Eric is an avid quantifier of my life, data-viz enthusiast, and a music zealot, pursuing how they intersect. He frequently thinks about data of all sizes and the future.

Write a Comment

Recommended Stories