Machine learning is a method used to devise complex models and algorithms that lend themselves to prediction – it sounds complicated and cumbersome, but this data really tells a story.
Recently one of our engineers questioned why some searches take longer than others and decided to dive into our collected data to see if his assumption that searches with less experienced CEOs are the culprit.
He was surprised to arrive at the opposite conclusion – that searches with first time CEOs took a month shorter, on average, based on placements made in the last two years. Furthermore, we found that the more experience the CEOs have, the longer it takes to place retained search roles. So while we may spend more time coaching and mentoring newer executives on how to find the right person for the job, leading it to feel like a longer process, the data shows it’s likely to close faster. It’s like Einstein said (and our own VP of Data Science, Tammy Wang, has reminded us!), “When you sit with a nice girl for two hours you think it’s only a minute, but when you sit on a hot stove for a minute you think it’s two hours. That’s relativity.”
This is just one example of how machine learning and data-driven technologies tell a story that can guide us in our mission to help our clients execute effective searches – this small tidbit of data gives us the knowledge to educate our clients about the average time a search might take, valuable information that wouldn’t be possible without our powerful, advanced algorithms and technologies.