Data analytics predict future talent demand

Transforming your workforce strategy with talent data analytics

In today’s rapidly evolving global economy, harnessing talent data analytics is essential for building a resilient and future-focused workforce strategy. Leading organisations are reimagining workforce planning—not just to attract top talent, but to design agile frameworks that maximise workforce potential and adaptability. Despite the importance of remaining competitive in tomorrow’s business environment, our survey insights reveal that only 10% of companies are truly future-ready.

How can your organisation become more future-focused?

A lack of data-driven decision-making can result in missed opportunities and limited growth. Ultimately, it can hinder your company's success. By integrating advanced analytics, forward-thinking companies can uncover patterns, forecast workforce needs, and build predictive models that guide talent acquisition and retention strategies. Advanced analytics leverage AI and machine learning to help organisations anticipate hiring demands, identify skills gaps, and personalise engagement—turning data into a strategic asset for workforce planning.

Bridging the gap between people and talent data analytics

Future-focused organisations need insights to advance their workforce management strategies. Leveraging analytics to target potential candidates before they hit the market, building comprehensive candidate profiles, and predicting performance outcomes through sophisticated algorithms can provide a deeper understanding of the skills needed to fill open positions. A robust analytics suite eases the decision-making burden on hiring managers and empowers recruitment teams to identify the right strategy for every need.

Predicting hiring trends: Staying ahead of the curve

Predictive analytics can look at past performance and identify associations among variables to determine when the need for staff will likely increase. Forecasting talent demand accurately is essential to any organisation's talent acquisition strategy.

Predictive analytics help companies pre-emptively identify hiring trends and design strategies to stay ahead of these. By analysing industry shifts, market trends, and seasonal fluctuations, talent acquisition teams can create data-driven hiring strategies to meet upcoming talent demands.

Prescriptive analytics: Informed decision-making

Meanwhile, prescriptive analytics provide insights into what actions employers should take to speed up the recruitment process and increase efficiency.

This practice has emerged as the "next-gen" solution in AI-driven demand planning. By conducting a "what-if" scenario analysis, prescriptive analytics allows executives to explore multiple potential outcomes and make proactive, informed decisions on talent requirements. Whether adjusting job postings or internal training programmes, prescriptive insights are crucial for optimising talent acquisition efforts.

Pontoon Intelligence to power your success story

Pontoon Intelligence is our all-inclusive suite of data reporting and analytics. It comprises predictive and prescriptive tools that critically enhance hiring processes and performance management through strategic, future-focused decision-making. An analytics platform is more than a collection of tools. It is a complex, ever-evolving combination of people, processes, data, and technology. Our tools work in harmony to aid in story framing, and our Business Intelligence (BI) team brings those stories to life. These BI specialists are one of our strongest differentiators.

Time-to-fill estimator

Our Time-to-fill estimator uses algorithms to analyse key request variables and their influence on hiring duration. By integrating market index data and Pontoon programme insights, the tool predicts the estimated time-to-fill.

This enables us to set realistic expectations with hiring managers when a request is initiated. With these estimates, Pontoon can advise hiring managers on nearby locations with faster fill times.

For example, with one of our global technology clients, we used the estimator to analyse current time to fill ratios based on location and skill set and where automation could help to decrease hiring time. We deployed an automated tool that optimised the sourcing process which reduced the time to submit qualified candidates by two days.

Supplier recommendation engine

Our Supplier recommendation engine acts as a personalised decision support system, allowing our customers to choose suppliers objectively. This tool uses machine learning algorithms to analyse suppliers' past performance and forecast which suppliers will meet customer expectations.

This predictive data tool helps clients accelerate time-to-fill and enhance candidate quality—while also improving rate compliance. For instance, when we used it to analyse supplier fill rates for a banking client, it recommended a more flexible supplier and sourcing option and saved them over $200,000 in agency markups.

Redeployment dashboard

The Redeployment dashboard helps organisations retain valuable talent and reduce recruitment costs by turning contract endings into seamless transitions. Using smart algorithms, it matches workers with expiring contracts to open roles based on title, location and availability—minimising downtime and accelerating time-to-fill. Redeploying individuals who already understand your business and culture also shortens onboarding and maintains momentum.

Clients gain real-time insights that drive immediate action, with tailored recommendations for a wide range of scenarios—from retaining senior specialists to filling mid-level roles. The dashboard’s intuitive interface enables managers to make confident decisions quickly, while its proven impact on efficiency and workforce continuity makes it especially vital in MSP environments where timing is critical.