![shutterstock_112412093.jpg Main image of article The Best Recruiting Data of the 90s, 2000s and Today](/binaries/medium/content/gallery/dice/insights/2015/07/shutterstock_112412093.jpg)
I recently looked back at some pictures from my early days as a technologist at Microsoft and reflected on how recruiters cultivated connections with me without having social or profile data at their fingertips. They certainly were not able to understand me, as a person, as well as they could have if they were recruiting me in 2014. However, many aspects of their sourcing and pipelining tactics can be effectively applied to a big data era. I’m going to speak more about making better decisions with better data at Talent42 in a couple of weeks, but I want you to understand how data has shaped a change in the candidate experience over time. Moreover, I want to help you marry time tested recruiting best practices with emerging trends around data aggregation and analysis. So let’s take a trip through time and cull some best practices from yesterday, today and tomorrow for improving the candidate experience with better context. The Best from the 90’s I loved the projects I was working on at Microsoft. With that in mind, I was not actively updating my profile on Dice.com or anywhere else. Recruiters still found me and they made some valiant efforts to tear me away from a position I was dearly passionate about. A recruiter phoned me and explained how the projects I was working on at Microsoft paled in comparison to the projects at his employer. Based on knowing project specifications from my old resume, the recruiter understood what fields I wanted to spend time in. At this time, recruiters also reached out with messages about how my educational major and certifications tied in so well with their companies. Again, nice connection points. However, these conversations were more backward looking than forward looking. The lesson for today is that recruiters should talk about project and product roadmaps early on in conversations with candidates. The Best from the 2000s I eventually was persuaded to move over to Yahoo in 2005. I networked with hiring managers and recruiters and found the in-person conversations to be quite helpful. Yahoo learned a lot about me through face to face conversations. In addition to the resume data they had on me, they used the face to face conversations to gain information on my leadership capabilities. I found that many recruiters were good at this time in bringing together competency based information and behavioral based information. My peers were active on sites such as Dice.com and were going to events hosted by companies and industry associations. They appreciated the one on one time they got with recruiters. The lesson for today is that we should listen as much as we talk about our brand and career opportunities. Good listening skills can be used as effectively at events as they can in online forums, such as Quora, or Meetups. The Best from Today The main piece of data that recruiters did not have on me 20 years ago that they could publicly reference today is my love for the San Francisco 49ers. That passion of mine is a connection point for viewing me as a person, not just a technologist, and inspiring me to think about your brand as a collection of other passionate people. Where this gets very interesting is at the point you recognize how my love for football and my love for leading teams intersects. My resume provides a lot of information on the strategy roles I have held. The public bread crumbs I leave around the Web tell the story of how I view the process of strategizing. The lesson for today is that we should understand social data in the context of resume data. When we understand context, we can inspire candidates and have meaningful conversations with them. That’s why we love looking at pictures. They have depth, passion and context. What lessons from your recruiting past do you think we can apply to the recruiting world of today? If you are attending Talent42, let’s connect and talk about making better decisions with better data.