Hire faster and smarter with data analytics

Some describe it as a 'revolution', others an 'explosion' and yet more 'a major leap forward'. They're referring to something that itself has many names in HR; data analytics, people analytics or workforce analytics but it all means only one thing; using the numbers game to make faster and smarter hiring decisions.

The numbers game

Most sectors have their buzzwords, including recruitment. Often these so-called strategies are just pie in the sky that most organisations might put on their wish list if they only had the resources. People analytics is different because it's already here.

Though still in its infancy, analytics is definitely a one-way street, and organisations, whether they like it or not, will have to find the resources to get on board or be left behind.

There are those who go as far as to say that not long into the future, it will be unthinkable to recruit without analytics.

In the same way that marketing, through the use of predictive analytics, has moved from being a product promotional department to the forefront of an organisation's bottom line, HR will need to make the same leap.

There are few if any departments in an organisation so vulnerable to the the human factor such as first impressions, subconscious biases and hunches than HR, no matter how hard talent acquisition tries to be neutral. It's human nature.

Imagine a finance or procurement department going to a CEO and telling them that based on their department's gut feeling and their trusted relationships with staff and clients, that profits/costs will be up/down the following year. They would be out on their ear.

It should not be any different for HR, perhaps even more so, because it is the hired talent that drives everything else right through to that bottom line. It is business outcomes that always matter and this goes beyond the hiring process.

A 'successful hire' is not 'job done' unless it benefits the organisations as a whole in the longer term.

It is in this respect that people analytics is the ultimate tool in predicting how that hire will work out. It is a strategy that can cover talent acquisition, performance management and retention and is also as objective as you can get.

What organisations should always know about themselves

With the people analytics revolution gaining speed, more businesses are recognising that it can help them figure out:

• what makes people join our organisation?
• what makes them perform well and stay on?
• who will likely be successful and/or make the best leaders?
• how can we attract more of the same?
• where do our skills gaps lie?
• what is needed to deliver the highest-quality customer service and innovation?
• who's a flight risk, why, and how can we predict it?
• what will it take to retain them?
• to what extent are employees engaged or disengaged?
• who might be toxic to the business?
• where is the organisation losing/gaining business and why?
• how our culture is best defined and who will be a good fit?
• are we truly diverse in our hiring practices?

How it can work in practice - the pioneers

By 2013 Google, king of the algorithm, had already fully switched to a data-driven HR function. The company has been quoted as saying the goal was to bring "the same level of rigour to our people decisions as it would to our engineering decisions".

- One of the ways it approached the switch was to set criteria such as for instance how many characteristics it would set as the benchmark for great leaders. It emerged that the number one characteristic was not technical knowledge but people skills.

- In hiring it was able to develop an algorithm that predicted which candidates would be more likely to succeed based on these characteristics.

The Google 'fun factor', is a proven strategy in attraction and retention. The company even tracks the time employees spend in line chatting at workplace cafeterias and uses it to measure collaboration across departments.

- Similarly it determined how to create a productive environment, employee engagement and retention and uses the data to predict problems and opportunities.

- Its algorithms have also helped improve diversity within the company in a measurable way.

Some of the others

- Insurance companies have analysed the profiles of top salespeople discovering that academic qualifications are not necessarily a strong indicator of future performance.

- One tech company can predict job candidates who are likely to become 'toxic' either through lying or cheating. Banks are also using this type of analytics to determine any possibility of fraudulent or unethical behaviours among potential candidates.

- Some companies can determine the characteristics of top salespeople based on the time they spend with customers and how they treat them.

Analytics can analyse why some people are more productive than others.

- The data allows organisations to compare the attributes of their most productive employees and leaders with new candidates to analyse similarities and predict how the latter would fare on the job.

- Data analytics can through its analysis of patterns predict unplanned absences.

- It can help companies in certain industries such as oil and gas to predict staffing needs up to ten years ahead based on global trends in the sector and geopolitical probabilities.

- Flight-risk candidates can be tracked through their employment histories on the web.

- Work safety issues can be predicted based on employee feedback from the field.

- Branding and culture can be tracked and analysed through external sources such as news articles and online web portal such as Glassdoor, and predictions made as to where it's headed.

- A business that cannot find local talent to meet needs will be able to analyse who might be available within an X radius that might be willing to make a move.

- Some companies save time and effort by testing skills in real-time with the use of video games - like CIA recruiters have been doing for years - that can assess skills such as problem solving, innovation, creative thinking, logic, reasoning, intelligence and other characteristics. Some companies provide psychological and sociological tests to recruiters for this purpose.

Jumping on the bandwagon

- People analytics is like any kind of data analysis such as marketing or other types of business analytics except that it measures the value of people to an organisation. The human factor comes when you decide what to do with the information. The data merely helps the decision making process.

As with any HR strategy it has to be about the overall needs of the business as a whole, which means sharing data across departments with regard to productivity, staffing needs, customer care, sales etc. Everyone needs to be on board.

Once gaps are identified and goals set, HR needs to work either with an internal or external analytics team who know how to gather and input the data plus analyse and help implement the results.

With the growing use of analytics, some HR departments are now looking outside their function to hire analysts such as statisticians.

- For HR departments that already have a lot of stored data, it might not be a bad idea to bring in some capable of looking at it and analysing it from an entirely different perspective than a human one. Data science is an up and coming career option for many graduates.

- There are plenty of companies - mainly the bigger ones - already engaged in people analytics that newbies can study and learn from before embarking on their own effort.

- It's a must to explore all of the available technologies that can either be incorporated into existing databases or run alongside them. Also there are many analytics vendors who are already on the bandwagon if cost is a factor in building a 'home team'. There are a number of different solutions on offer from 'off-the shelf' to embedded systems.

- Running a pilot programme can help get started but set objectives that can be easily evaluated.

- Experts recommend using algorithms with a large number of data points to narrow the field of applicants, say 10 measurable attributes that would identify leadership, rather than five, which could be based on characteristics of successful leaders already within the organisation.

Sounds infallible?

In a recent SHRM article, Carole Fleck, the content director for Diabetes Forecast magazine said people analytics were becoming as important as people skills in making insightful workforce decisions.

She cited the results of a study carried out by researchers from the University of Minnesota and Princeton, and the N.J.-based Educational Testing Service, which analysed 17 studies of job applicant evaluations.

The study found that algorithms outperformed human decisions by at least 25 per cent.

The researchers maintained that their findings hold true “in any situation with a large number of candidates,” regardless of the level of the position.

However at the same time, the data is only part of the recruitment process and is likely to remain that way as long as humans are running the show. Data analytics cannot implement the changes based on the information it provides or predicts. It cannot hold job interviews and make final hiring decisions, reward or reprimand. It can only point to a direction where such actions might need to be taken, all with the aim of creating a better more productive working environment all round.

Perhaps the industry should settle on the term 'People' analytics lest it forget what it's all about once the practice becomes an irreversible part of the recruitment process.

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