A few months back, we started research on viewing Recruitment as a Forecasting function. Conceptually, this made a lot of sense as Recruiters are increasingly handling large volumes of data and are sampling from a pool of profiles based on a set of constraints (skills required, location, time to hire, wage limits, and a host of criteria). Imagining a Recruiter as a Forecaster is a natural progression of the job – but with it comes a great form of responsibility. It requires a more profound sense of self-investigation and self-awareness.
The good news about Forecasting is that it is something one can keep improving on – provided there is a set of systemic steps and processes in place. In Superforecasting, Bill Flack, a retired USDA employee who lives in Kearney, Nebraska, is contrasted with famous media pundits and other experts who purport to predict everything from hot stock market picks to presidential politics. Bill Flack has proven himself super accurate across 300 geopolitical questions by going through a very disciplined data collection and analysis process.
Forecasting is a great skill that be acquired in the digital age and need not be reserved for a few pundits. The problem with pundits is, while they may tell a good story about a possible future, they are seldom held accountable for their predictions (who has really checked the accuracy of every forecast of, say a Tom Friedman)
Imagine the power of being so precise in finding and predicting will be the best fit for an organization – that is, Super Recruiting
But this journey is not easy. This email is an attempt to unpack a framework that will be useful for you. In our framework, there are many elements, but we have written about two themes.
- Handling Bias
- Making Talent Intelligence Relevant for execution
(It is an eight-point framework – here I have addressed two – if you need the full framework, please write to us, or we will cover those in subsequent emails)
