Charles Hipps 20 November 2018

The rise of predictive analytics in local government recruitment

Recruiting is the perfect shop window for predictive analytics for local government leaders who want to ensure they are hiring the best quality candidates. After all, the market for top talent is highly competitive and hence the pressure on recruiters to hire quickly and minimise costs per hire is an issue at the top of the minds of recruiting managers.

Getting a hire wrong isn’t only costly, poor hiring can lead to lower productivity, reduced levels of employee morale and engagement and ultimately more attrition. It is a vicious circle.

Predictive analytics are a crucial component of contemporary e-Recruitment. They play a core role in helping to reduce reliance on the gut instinct of recruiters and hiring managers by enabling them to effectively utilise the plethora of recruiting data the business has already collected e.g. data on high, medium and low performing employees; candidate demographics, sources of hire and background data; assessment and psychometric data; structured interview data etc.

Knowing what worked well in the past can help to fine-tune the types of candidates that carry high favour within a firm. The benefits to recruitment include:

• Saving recruiters time
• Getting to the top candidates first
• Finding a needle in a hay stack
• Reducing bias and increasing diversity

Research shows there is a need for this. Studies by the Social Mobility Commission have shown that numerous industries are failing to hire talented youngsters from less advantaged backgrounds because they recruit from a small pool of elite universities and hire those who fit in with the culture - still favouring middle- and higher-income candidates who come from a handful the country’s top universities.

Furthermore, recent studies from Royal Holloway University of London and the University of Birmingham suggests managers often select candidates for client-facing jobs who fit the ‘traditional’ image of a role, with many placing as much importance on an individual’s speech, accent, dress and behaviour as on their skills and qualifications.

This introduces disadvantages for candidates whose upbringing and background means they are not aware of ‘opaque’ city dress codes - for example, some senior investment bankers still consider it unacceptable for men to wear brown shoes with a business suit

Data from machine learning can ease pressure on local government leaders helping to instantly and automatically review all applications globally and flag up to 33% of all candidates they will end up extending an offer to. In so doing, it is possible to free up significant amounts of recruiter resource each year – time which could be spent on adapting better engagement techniques to ensure a leading candidate with many offers at their disposal is more likely to buy into the culture, mission and vision of our clients ahead of market competitors with equally tempting offers on the table.

In the recruitment game, closing down top talent ahead of competition is a big challenge and this technology is helping to offer a solution to this and reduce decline rates to suit corporate objectives.

Inevitably, algorithmic techniques like data mining can help to eliminate human biases from the decision-making process. But, crucially any algorithm is only as good as the data it works with. To do this well, it is important to be self-critical when testing big data to ensure that you do not inherit the prejudices of prior decision-makers or reflect the widespread biases that persist in society at large.

This also has the potential to widen the spread of candidates and open up talent pools to diverse groups of talent, thereby avoiding challenges around elitism. The technology can automatically flag to a recruiter, candidates that have all the key indicators of success they're looking for, but that didn’t get a qualification from the likes of Oxbridge. All of this is done by simply using digital transformation to replicate collective decision making, which in turn reduces the influence of bias by individuals or processes.

Harnessing the potential means you’re not just dismissing elitism theories but you’re also identifying & quantifying any historic bias reducing the potential for new bias in future decision making. It means you can mitigate the influence of disparate impact and focus on just winning great hires.

Throughout a continual trial-test-refine process of using big data, you should be able to Identify ranges in which there is no significant statistical impact and go on to build better algorithms without disparate impact. By identifying & quantifying the features that determine a candidate’s success, you will be better able to quantify the disparate impact and correct the algorithm.

Reporting wise, it helps with ensuring that you are providing stronger evidence and recordkeeping to support hiring decisions and can accept more applications with lower resource implications and the automated cycle of recruitment means you should have a better talent pool of candidates coming through that reflect the future leaders you want joining your organisation.

In summary, predictive recruitment analytics and big data intelligence tools are changing the way organisations view, analyse and harness their talent data. Leveraged efficiently, predictive analytics allows staffing teams to create economic value from their talent data, helping them become more competitive and successful.

Charles Hipps is CEO of Oleeo

Protection is a two-way street image

Protection is a two-way street

Russ Langthorne outlines how the workforce can be protected from the debilitating effects of HAVS and WBV through real-time, accurate and objective monitoring and measurement.
For your free daily news bulletin
Highways jobs

Administration Officer

The Coal Authority
£19,137 to £21,264
To apply please click the Apply Now link below. Mansfield, Nottinghamshire
Recuriter: The Coal Authority

Programme Assistant

City of York Council
£11.37 per hour
We are WorkwithYork and we are working with our client to find a Programme Assistant working with the Homes for Ukraine project. York, North Yorkshire
Recuriter: City of York Council

IT Security Manager

City of Bradford MDC
£42,614 - £47,665 pa
This is an exciting opportunity for an enthusiastic IT Security Manager Bradford, West Yorkshire
Recuriter: City of Bradford MDC

Recovery Support Worker x 3

Wakefield Council
£12,963.50 - 14,113.00
We are seeking to appoint suitably skilled, motivated and caring recovery support workers Wakefield, West Yorkshire
Recuriter: Wakefield Council

Transport Craftsperson

Wakefield Council
£25,927.00 - £28,226.00
You will be joining us at a very exciting time as we move to Featherstone later this year to a state of the art fleet maintenance facility Wakefield, West Yorkshire
Recuriter: Wakefield Council

Partner Content

Circular highways is a necessity not an aspiration – and it’s within our grasp

Shell is helping power the journey towards a circular paving industry with Shell Bitumen LT R, a new product for roads that uses plastics destined for landfill as part of the additives to make the bitumen.

Support from Effective Energy Group for Local Authorities to Deliver £430m Sustainable Warmth Funded Energy Efficiency Projects

Effective Energy Group is now offering its support to the 40 Local Authorities who have received a share of the £430m to deliver their projects on the ground by surveying properties and installing measures.

Pay.UK – the next step in Bacs’ evolution

Dougie Belmore explains how one of the main interfaces between you and Bacs is about to change.