For Early Careers (EC) leaders operating in a fast-moving and increasingly complex space, data can provide critical direction. It can help focus and give clarity. Data can tell us where to go. Who to target. And what might be missing.
This is especially important at a time when competition for early talent is rising, graduate vacancies are expected to increase, and early talent themselves are demanding more from employers. In this context, how can you know you are operating successfully? Driving performance in your organisation? Effectively balancing long-term priorities with short-term imperatives?
Here are five ways to practically begin implementing a data-driven approach to drive high performance in your Early Careers function.
Data provides clarity, but also requires focus in order to be effective. Are you measuring the number of candidates your organisation has attracted? Are you measuring the number of universities, or regions, or countries covered? Are you measuring satisfaction scores?
Be clear and pointed on what you are measuring and why. There are potentially thousands of different and relevant data points an EC function might collect. Before you begin a data-driven approach, focus on outlining which data points will be most practical and applicable for your strategy, vision, and function.
Do you need quantitative data, qualitative data, or both? The most effective way to measure and collate information for these will vary considerably. Consider whether you’re using the right measuring tools for the data you are trying to collect.
Quantitative metrics may be the best approach to view breadth and collect the number of candidates or universities attracted, while qualitative metrics can provide more human-centred insights and feedback based on how your attraction campaigns made potential candidates feel. Ensuring you are using the right measurements and metrics will help provide better detail and direction, enabling you to forecast patterns and trends over time.
Are you ensuring regular audits of various parts of your entire EC lifecycle? Using data to measure each part of the EC lifecycle – from attraction, recruitment, development to retention – can help you assess your strengths and areas of focus and improvement.
For example, an organisation’s data on retention (from the number of candidates retained per graduate cohort to exit interview feedback) can be crucial information if analysed properly and can help organisations improve their retention rate by directly informing their future retention strategy.
Once your data-driven approach has established your areas of strength, you can create defined goals using the data extracted. Data helps to numerate defined goals and measure progress towards the goal.
How can a data-driven approach define strategy? When approached by bp to re-think their attraction strategy, we anchored our work in data and innovative trend forecasting. In our diagnose phase, the resulting data from our research demonstrated that skills were a driving factor in attracting EC with 76% of Gen Z attributing career success to skills-learning. The result? An innovative, global, and accessible skills-based attraction initiative that would go on to win multiple awards for its innovative and impactful human-centered approach.
Data helps you turn heads, communicate the business case of your Early Careers function, and tell better stories. Being able to demonstrate a long-term approach to data is the best way to track progress and measure growth. Creatively report impact to stakeholders and continue to drive decisions using scientifically designed infographics and data dashboards.
How can a consistent approach to data have influence? Frame your data-based evaluations as an annual health check or MOT: something you do every year to see how well your system is running. This consistent, steady approach will allow you to fine-tune your EC system year-on-year, and focus on the right places to invest your time and effort, at the right time, for optimal returns. The compounding effect of a little change, done frequently, far outstrips periodic large-scale overhauls in terms of benefits and value.