Using AI to enable demand planning and reduce time to fill in contingent hiring
The pressing need to enhance contingent hiring efficiency
Employers face growing pressure to fill contingent roles effectively amid ongoing talent shortages. Having the right talent at the right time has never been more critical to business success.
To stay competitive, organisations are turning to artificial intelligence (AI) and data analytics to optimise contingent hiring. Yet, this shift is not happening fast enough — and the cost of delay is high.
The Adecco Group's latest report reveals that 53% of CEOs acknowledge their leadership teams struggle to align on AI strategies and timely next steps.
Additionaly, 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 now a part of everyday reality. With demand for flexible talent rapidly rising, organisations must adapt or risk losing their competitive edge. To thrive in today’s fast-evolving technological landscape, businesses must stay ahead of AI-enhanced hiring tools and embrace forward-thinking contingent workforce planning.
Demand planning for bulk talent hiring is undergoing a paradigm shift, driven by AI and advanced forecasting analytics. By leveraging these technologies to streamline contingent hiring and analyse seasonal trends, companies can reduce time-to-hire and gain predictive insights into future talent needs. To stay competitive, organisations must strategically embrace these game-changing solutions. With effective demand planning, talent acquisition leaders can redefine hiring strategies and achieve outcomes previously out of reach.