The pressing need to enhance contingent hiring efficiency
Employers are under pressure to fill contingent positions effectively in an environment of low unemployment and talent shortages. Having the right talent at the right time has never been more critical for business success.
To compete for top talent, organisations are turning to technologies like artificial intelligence (AI) and data analytics to improve their contingent hiring processes. But this shift is not happening fast enough.
A survey by Deloitte revealed that 83% of companies worldwide possess a low analytics maturity. Only a handful of organisations take the initiative to tap into the full potential of data. It's estimated that only 35% of companies are using AI and forecasting analytics to predict future talent demand.
Let's explore how AI tools in contingent hiring can reduce time to fill and predict future talent needs.
Enabling talent demand planning for contingent roles
Demand planning in contractor talent acquisition traditionally relies on historical data and manual analysis. Unfortunately, manual solutions struggle to meet dynamic hiring needs. This results in challenges accommodating sudden hiring surges due to inefficient processes.
However, AI technology and demand planning software now enable organisations to swiftly adapt to market changes, anticipate talent demand, and automate aspects of contingent hiring. For instance, employers streamline screening for high-volume or lower-skill roles with automated online assessments or pre-recorded video interviews, saving time and improving efficiency.
At Pontoon, we take a data-driven approach to bulk and seasonal hiring, particularly for roles requiring lower-level skill sets. By leveraging our proprietary forecasting tool, we predict future hiring needs based on previous demand and the likelihood of prospective hires. Our visualisations help spot candidate trends, such as seasonal demand before they happen, so our clients can be sure their business needs are met quickly and accurately.
Decreasing time to fill with AI and data analytics
Achieving efficient time-to-hire is critical in bulk talent acquisition. Analytic forecasting models now play a crucial role in tackling this challenge. Advanced algorithms swiftly analyse large datasets to identify patterns and generate shortlists of suitable candidates. Visualisation tools streamline processes and enable HR professionals to significantly reduce the time required to fill multiple repetitive roles, all while maintaining candidate quality.
When Pontoon's MSP client needed to quickly source and onboard 200 contractors during the busy holiday season, we partnered with suppliers to deploy an AI assessment tool. Candidates meeting score thresholds and passing compliance checks could bypass interviews, enabling us to complete all hires in under four weeks. This approach not only accelerated the process but also enhanced candidate quality, as suppliers rigorously vetted and submitted only the top candidates, minimising attrition.
The future of contingent hiring: Evolving alongside data and AI
AI and predictive talent models are gaining traction, enhancing their impact on talent acquisition. The demand for flexible talent is rapidly rising. Organisations must adapt to avoid losing their competitive edge. Staying on top of AI-enhanced hiring tools and adopting forward-thinking contingent workforce planning is crucial for businesses to thrive in today's rapidly advancing technological landscape.
Demand planning for bulk talent hiring is witnessing a paradigm shift thanks to AI and forecasting analytics. By leveraging AI to streamline contingent hiring and analyse seasonal trends, companies benefit from decreased hiring time and predictive insights into future talent needs. Organisations must be bold and strategically embrace the game-changing solutions to stay competitive. With proper demand planning, talent acquisition leaders can push the boundaries and elevate hiring strategies to previously unattainable levels.