Data-driven Contingent Hiring: Is Human Error Costing your Business?

It’s no secret that recruitment is one of the most expensive yet growth-stimulating tasks executed by businesses. As the gig economy continues to rise, best practice engagement of contingent talent must continue to be strengthened to mitigate risk in the form of cost, productivity, governance and human error.
Time and time again we see and hear about instances of human error resulting in catastrophic consequences. I was six years old in ’99 when NASA sent a $125 million satellite to Mars to observe meteorological properties and patterns, ending in calamity when it combusted soon after entering the planet’s atmosphere. This was later uncovered to be due to human error in measurement by the Engineering team, and no information was ever transmitted back to Earth. What a waste!
[bctt tweet=”What are you doing to reduce your propensity for hiring mistakes?” username=”ATCevent”]
Taking an example of this scale and comparing it to a contingent-hiring scenario isn’t overly reasonable, but work with me! Business X is engaged on a multi-million dollar project but is under resourced to facilitate it from a human capital standpoint, and therefore must engage externally for contingent support. How does Business X ensure they are sourcing suitable contingent talent?
What’s happening at the moment is a monumental shift away from traditional recruitment methods towards data-enriched hiring, enabled through technology. Demand on capability is ever increasing, which is forcing HR leaders to search for ways to quantify and validate a candidate’s ability pre-engagement.
According to a Bersin by Deloitte report, utilisation of data through the recruitment process is three times more likely to yield cost reduction, efficiencies and higher performing talent. Bersin also reported that an understanding and total visibility of candidate talent pools is one of the most crucial drivers of recruiting performance. When this is tied into a separate yet important argument about using data to remove unconscious bias from hiring processes, the argument becomes a whole lot more compelling!
We’ve seen massive changes in service industries in recent times, a notable example being the Taxi industry. In previous years we relied on Taxis as an on-demand service to take us from point A to B. The risk for us passengers was multi-dimensional; elongated journeys with no way of tracking them, unclear cost composition (along with hidden fees) and having zero visibility into who the driver was and his/her performance history. As a result, the service can sometimes be rather average.
The birth of Uber and other similar platforms has created new ways to use quantitative (star rating) and qualitative (written feedback) data to control the quality of service delivery. Having the capability to reward and reinforce strong performance, and remonstrate with underperformance results in regulation. Humans always do a better job when they know they’re being held accountable, which means that each driver is conscious of all areas of providing an excellent and consistent experience to their customer, which net results in better-delivered service.
So back to my point on how a business can ensure it is sourcing suitable contingent talent – imagine having access to a pool of contingent talent that you have live performance data on. You will be able to call upon your desired talent anytime anywhere to help you fulfil that multi-million dollar project. Isn’t that perfect?
[bctt tweet=”Can a Contingent talent pool help you gain the agility you need to scale your business up/down? ” username=”ATCevent”]
This is what we’ve been able to do at Weploy. Before qualifying individuals to join our talent community, we test their cognitive (ability to adapt to unknown situations/left and right brain processing) ability as well as soft skills proficiencies. This allows us to have a comprehensive representation of each person in our community’s ability to perform for our clients. When our “Weployees” do work for our clients, we compile the quantitative and qualitative data for each assignment which allows us to tightly control quality and reward and sanction accordingly. It’s incredibly rewarding when our people are able to complete assignments quicker than expected, especially because a lot of them fall into demographic categories that typically have a hard time finding work!
Realistically I’ve only scratched the surface of the ways that data and analytics are shaping the way we engage and hire contingent staff. There are so many exciting things happening in this space; Process Automation, Artificial Intelligence and Machine Learning being a few that I wish I had space to dive into in this short blog.
If one thing is abundantly clear, it’s that businesses that choose to stick with traditional methods of engagement and recruitment will be left in the wake of others who are harnessing and embracing the many tools and platforms that are mapping the path to the future.
How are you going to position yourself and your organisation ahead of the rest?
Cover image: Shutterstock

This article was sponsored by Weploy.

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