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Data-driven recruiting: How to harness the power of data

Revolutionising hiring practices through data-driven decision-making.

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Modern recruitment agencies should collect and analyse data to generate actionable insights.
Change management is a key component of ensuring data-driven decision-making thrives.
Data-driven decision-making allows them to build stronger, deeper relationships with clients.

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The business world is in flux. Talent gaps are widening, leaders are struggling with the diversity imperative and predicting the skills your organisation will need next year is a challenge, never mind looking ten years down the line.

However, there is one solution that can help organisations prepare for the future – and that’s leveraging people analytics and data to make better recruiting decisions.

The idea is simple. In an age when technology is helping us do everything from drafting emails to building business strategy, a modern recruitment function should collect and analyse data, generate actionable insights and upgrade their recruitment model to make better hires.

We should be relying on evidence, not intuition. Or, as HR thought leader Dave Ulrich frames it: “People analytics provides evidence in the form of data that helps people make better decisions.”

It’s one thing to understand the benefits of data-driven recruitment, but actually establishing a strategy and baking into your organisation is another entirely.

So, the days of manually pouring over CVs and hiring on hunches are over. Instead, data analysis can help recruiters better identify and engage qualified candidates for roles, strategise for future needs and build talent pools that can solve skills needs.

However, It’s one thing to understand the benefits of data-driven recruitment, but actually establishing a strategy and baking into your organisation is another entirely. So how do you do it?

Data-enabled talent ‘win rooms’

One example we can look at comes from the United States, where the need for public sector hiring has grown in recent years amid a mass exodus of retirees during the pandemic.

Faced with a need to rapidly hire talent, public institutions in the US have focused on using data to improve four critical parts of the hiring process: expanding the candidate pipeline, sharpening job descriptions and employer branding, streamlining the hiring process, and – underpinning these processes – enabling data-based decision making.

Faced with a need to rapidly hire talent, public institutions in the US have focused on using data to improve four critical parts of the hiring process…

They have done this by creating centralised, cross-functional teams focused on rapid hiring – talent ‘win rooms’, according to McKinsey & Co – who use data coupled with expertise to transform hiring processes.

These teams have three key characteristics. They are made up of stakeholders from different teams, minimising delays in the recruitment process and avoiding miscommunication between departments. They use a central repository for data that is accessible to all, showing information like the number of candidates at each stage of the recruitment process, or the number of vacancies posted by different business units.

Crucially, they evolve and adapt as they go, using daily check-ins, weekly planning and regular assessments to iterate their working model. This means bottlenecks can be solved quickly and resources redeployed where they are most needed.

The results have been positive. According to McKinsey & Co’s research, one US federal agency reported increasing its hiring rate by 30% in the first three months after setting up a talent win room, while another decreased time-to-hire by 80% by tracking metrics on candidate feedback and process timelines and making appropriate interventions.

The growth of people analytics

Developing an effective data-driven recruitment strategy isn’t a one-off task, but an ongoing process. As such, organisations are increasingly building out their people analytics departments. More than 70% of company executives say people analytics is a top priority, according to Harvard Business Review, with analytics departments growing headcount by an average of 43% since 2020.

“Greater adoption of artificial intelligence and analytics is creating new roles in recruitment and attracting talent like data scientists and product managers, who can convert data into insight and explain the impact of new solutions,” agrees Alex Evans, Managing Director at TALiNT Partners.

An organisation can buy the latest data analytics tools and invest in technology, but without support, training and buy-in from those who will use it, any change is doomed to fail.

“We’re also seeing more transformation leaders on recruitment boards – attracting senior talent from other industries – and marketing leaders moving into these roles as they drive data strategy. The biggest challenge is getting buy-in from consultants on new tools and processes who prefer legacy systems and behaviours,” he adds.

Change management is a key component of ensuring data-driven decision-making thrives. An organisation can buy the latest data analytics tools and invest in technology, but without support, training and buy-in from those who will use it, any change is doomed to fail.

Take manufacturers Colgate-Palmolive. Building trust among colleagues around data and ensuring a business first approach to analytics interventions has been vital to effectively using data to grow, according to chief analytics and insight officer Diana Schildhouse.

“Everything we do within analytics starts with a business question, rather than a tech-first approach. We have to deeply understand what decisions our business partners need to make, when they need to make them, and what priorities are most important to their success,” she says.

Having regular conversations with colleagues around demystifying data and analytics, as well as articulating your vision for how data will drive growth…

“The greatest successes within analytics come from embedding that work into the rhythm of day-to-day business operations,” adds Schildhouse.

This means having regular conversations with colleagues around demystifying data and analytics, as well as articulating your vision for how data will drive growth. Colgate-Palmolive can articulate its entire data strategy on a single page, including all its strategic pillars. This allows the organisation to be clear about where it’s going and how it will get there.

Another outcome of a data-driven approach to recruitment is the ability to deliver more effectively on DEI or ESG initiatives. Not only will better data allow you to monitor interventions, but it can help you remove bias in the hiring process, find gaps in your talent base and identify potential candidates from different backgrounds.

For recruiters, data-driven decision-making allows them to build stronger, deeper relationships with clients by offering better insights.

“Whether it’s more accurately pricing train and deploy solutions or advising on strategic workforce planning, real-time metrics on candidate engagement and client feedback is helping recruiters adapt services and deliver more in-demand services,” says Evans.

Three key interventions to ensure data-driven recruitment thrives

– Focus on how data interventions will improve day-to-day recruitment processes. Investing in technology without developing talent is a sure way to fail

– Always opt for quality of data over quantity. Focus on data hygiene and ensure it is up-to-date and monitored. What specific intervention do you want to see?

– Iterate and update. Constantly monitor the impact of data interventions and look for gaps in knowledge or poor performance. Data interventions are an ongoing process, not one-offs.

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