07
Recruitment is one area of HR that is particularly rich in data, and it is also an area that has undergone a lot of change. Particularly with platforms like LinkedIn and Glassdoor, every employer – no matter how big or small – now has access to valuable big data. I believe that those HR teams which understand and work with big data are the ones which will recruit most successfully in the coming years and see the greatest ROI for their recruitment activities. Plus, as we will see throughout this chapter, automation is becoming a bigger consideration in intelligent recruitment, from automating aspects of candidate assessment and selection, to the need to recruit people with the right kinds of skills to manage data and automation in the workplace. For me, there are three key strands of intelligent, data-driven recruiting (see Figure 7.1):
· boosting your employer brand;
· identifying the best recruitment channels;
· identifying and assessing the most suitable people for your organization.
FIGURE 7.1 Intelligent, data-driven recruiting
Each of these topics could fill a whole book in its own right, and things are developing fast. But in this chapter I look at each of these three strands in turn to identify some of the main ways in which data can help to boost your recruitment activities. Innovative real-life examples are included throughout the chapter (and, indeed, this whole part of the book) to demonstrate how data are already transforming the work of HR teams.
Boosting your employer brand
Effectively, your employer brand is how people (both current, ex- and potential future employees) view your company as an employer. As any marketing colleague will tell you, branding is absolutely vital when it comes to attracting and retaining customers (in this case, employees) and, indeed, your employer brand should ideally align with your overall company, service or product brand. If the two are sending different messages – ethical manufacturer with questionable employee ethics, for example – you could struggle to attract the best talent. One recent paper by Risesmart stated that nearly 70 per cent of unemployed job seekers would not take a job with an employer which had a dubious reputation.1 On the flip side, the same paper stated that 84 per cent of employees would consider quitting their current job to move to an employer with an excellent reputation, even if the salary increase was less than 10 per cent. Your employer brand tells employees what you are as a company, what you stand for, what it is like to be part of the company and what makes you different from other employers. When creating your employer brand, you will want to consider what kind of talent you want to attract. Or, to put it another way: what kind of people best fit with your company’s culture and goals?
Measuring your employer brand
Having identified your employer brand, you need to be sure this brand image chimes with reality, and this is where data come in. You should look to test your employment brand at regular intervals. Sentiment analysis of interview and survey responses, as well as social-media posts, can really help to establish how successful your employer brand is. And if your company goes through major changes, such as a restructuring, you should absolutely look to assess the impact of such changes on your brand. Measuring sentiment before, during and after the changes will give vital insights that will help you to manage the transition and maintain a positive employer brand.
Finding out what your employees (current and otherwise) think
You may already have heard of the net promoter score. This is a key performance indicator (KPI) commonly used by sales and marketing departments to assess how willing customers are to recommend the company’s service or products to others. Using data, you can apply the same thinking to your employer brand. Indeed, ‘how likely are you to recommend the company?’ is a common question on employee surveys. Rather than taking the temperature of this once a year, many companies are using ‘pulse’ surveys: asking just this one simple question on a weekly, monthly or quarterly basis. For this type of survey to be truly useful, responses must be anonymous. Employees may not answer truthfully if they think a negative response could have negative repercussions for them.
Creating and maintaining a positive employer brand is not just about keeping your current employees happy; it is also about how attractive your company appears to outsiders. In this way, social media and employer review sites like Glassdoor are particularly helpful when it comes to assessing your employer brand, especially among ex-employees. One severance and workforce transition study showed that more companies are mining social media and review sites after laying off an employee than three years ago.2 But this need not apply only to employees who have been let go (although it is a good way to monitor progress in a large-scale restructuring where many employees are being made redundant in stages); feedback from anyone who has left the company voluntarily will also give vital insight into people’s perception of your brand.
What makes your employer brand attractive?
What factors do you think attract potential employees to a company or make an employee more likely to recommend your company? Salary? Flexible working? The answers are: ‘no’ and ‘no’, according to data. Human Resources Today analysed Glassdoor data from more than 6,000 companies and 2.2 million employees to get some interesting findings on employer brand.3 The biggest factor affecting whether employees would recommend their company as a place to work was ‘culture and values’. In fact, an employee’s rating on ‘culture and values’ is almost five times more predictive of a company being recommended than ‘salary and benefits’. Among those under the age of 35, ‘career opportunities’ was the top driver of employer brand. This demonstrates the need for any employer to consider culture and employee development as much as, or even more than, the usual salary and benefits. I am not saying decent salaries and benefits do not impact on employer brand, but it is clear that people want to feel truly at home in a company. They want to enjoy the culture, they want to be proud of the company they work for and they want their input to be valued through good development opportunities. These are all elements to focus on when it comes to boosting your employer brand and promoting that brand to those outside the organization.
Promoting your employer brand
Another key element of branding of course is raising the profile of your employer brand among potential employees. This is especially worthwhile if you are in a highly competitive industry, like the technology world, where you are struggling to attract talent. A strong employer brand gives candidates a definite feel for what it is like to work for your company. As we have already seen, this is often more important to potential employees than salary and benefits, which is great for any company unable to compete on salary. Some innovative organizations are using data-related technology like virtual reality (VR) to capitalize on this idea, delivering 360-degree videos that show people what it is really like to work at the company. This helps employers to show off their culture, give an authentic feel for everyday life within the business and attract the best candidates.
One of my favourite recent examples comes from the unlikely world of US college football. The University of Minnesota’s (UM’s) Golden Gophers team has been using a slick VR experience to sign up in-demand players.4 The team’s VR pitch is watched using Google cardboard glasses or other VR goggles, and includes footage of practices, games, workouts, those all-important UM campus experiences, city life and even the Minnesota weather. Described as a ‘day in the life of a Golden Gopher’, it serves to immerse candidates in UM life and tell a compelling story about what it is really like to be part of the team. In the competitive world of college football, it can be hard to stand out and convey the benefits of signing with a smaller team. VR is a great way to do this authentically, which is why VR is fast becoming an increasingly popular tool among college recruiters, and I think the trend is likely to filter through to businesses.
Identifying the most effective recruitment channels for you
Most companies use a mix of recruitment channels, including newspapers, headhunters, social-media campaigns and LinkedIn searches. Different channels will work better for different industries, or even different positions within the same company. Given the diversity of recruitment channels, it is important to know which deliver the greatest return on investment (ROI). In my work with clients, I would estimate that maybe 50 per cent of recruitment spend is wasted. If a channel is not driving actual recruitment, you should stop recruiting through that channel immediately and focus on those channels that deliver the most value for your money.
Getting maximum bang for your recruiting buck
The beauty of data is that they allow you to test your recruitment channels and measure their success rate. These days, it is possible to measure everything minutely. So, rather than focusing on obvious indicators like how many CVs you get in response from different channels (which only tells you volume, not quality), you could look instead at more valuable indicators like how many offers were made to candidates from particular channels. You could even take this further and assess your most successful employees in particular roles and pinpoint which channels they came from. The point is to target your recruitment appropriately and only spend precious resources to reach exactly the kinds of people you want to attract. A good example of this comes from Marriott Hotels, a chain which employs hundreds of thousands of people all around the globe in positions as diverse as cleaning and management. Marriott has an impressive social recruiting strategy, and ranks as more effective at recruiting through a social platform than even Facebook itself.5 Marriott Hotels has the largest recruitment page on Facebook, with, at the time of writing, more than 1.1 million likes and around 50,000 people interacting with the page every week. The page obviously lists available jobs, but it also beautifully demonstrates what it is like to work for the chain through photographs and videos of life behind the scenes in the hotels. It also celebrates success by congratulating teams and employees for achievements. Perhaps more importantly, the page actively encourages constant engagement through likes and comments, and this is a two-way street, with Marriott responding to comments. Everything is designed to attract users to Marriott’s employer brand and show the company off as a desirable place to work. It then builds on that desirability through interaction, which encourages users to progress to searching and applying for positions.
It makes sense that a hospitality business like Marriott wants to attract the classic ‘people person’. This explains why Facebook is the most appropriate social recruitment channel for Marriott, as opposed to LinkedIn, which would perhaps be more appropriate for attracting professionals like marketers or lawyers. It is an excellent lesson for any company looking to maximize its employment channels: go with the channel most used by the type of people you want to attract. Building on its Facebook success, Marriott also created an online Facebook game (like Farmville) where potential employees can learn how to manage hotels. The game, called MyMarriottHotel, involves players doing all the things involved in running a hotel, such as: keeping guests happy, managing the kitchen, delivering room service etc. The happier they keep the guests, the more points the players score. The specific idea behind the game is to help to recruit more young people in the 17–24 age group in the Chinese and Indian markets5 – a group that research shows is spending a lot of time playing games on social media. The game reportedly has been very successful, and it certainly demonstrates new approaches to engaging prospective employees and giving them a taste of the job on offer.
Identifying new recruitment channels
Sometimes you may need to think a little further outside the recruitment box and look for entirely new channels to recruit talent, particularly in areas where there is a lot of competition to hire the best talent. Data scientists are one such group in great demand for all kinds of businesses, yet there just are not enough people with the required skills to work with big data. One survey recently carried out by researchers at Gartner found that more than half of the business leaders queried felt their ability to carry out analytics was restricted by difficulty in finding the right talent.6 To overcome this problem, Walmart decided to get creative. Rather than advertising through traditional channels, it turned to crowdsourced analytics competition platform Kaggle to find the talent it needed.7 At Kaggle,8 an army of ‘armchair data scientists’ apply their skills to analytical problems submitted by companies, with the designer of the best solution being rewarded, sometimes financially – in this case, with a job at Walmart. Candidates were provided with a set of historical sales data from a sample of stores, along with associated sales events, such as clearance sales and price rollbacks. They were asked to come up with models showing how these events would affect sales across a number of departments. As a result, several people were hired for the analytics team, and the competition was held again the following year, with candidates then being asked to predict how weather would impact on sales of different products. Mandar Thakur, senior recruiter for Walmart’s Technology division, told me: ‘The Kaggle competition created a buzz about Walmart and our analytics organization. People always knew that Walmart generates and has a lot of data, but the best part was that this let people see how we are using it strategically’.7 The crowdsourced approach led to some interesting appointments of people who, as Thakur said, would not have been considered for an interview based on their CVs alone. For example, one had a very strong background in physics but no formal analytics background: ‘He has a different skillset – and if we hadn’t gone down the Kaggle route, we wouldn’t have acquired him’.7
Walmart also ran a recruitment campaign across social media using the Twitter hashtag #lovedata, to raise its profile among the online data science community and avert their eyes away from Silicon Valley and towards Bentonville, Arkansas – the retail giant’s headquarters – when scoping for job opportunities. Another valuable source of job applicants for Walmart is referrals. Data fans – academic, industrial or armchair – are as active in online communities and social networks as any other breed of techies. Provide one with a great job and they are likely to spread the word to their associates.
The world of motorsport gives us another example of recruiting through unusual channels. Nissan and Sony have joined forces to create the GT Academy, a global annual contest designed to find the best racers from the world of videogames.9 The idea is to find the best racing gamers who play the popular Gran Turismo game and turn them into real-life racing drivers. In the contest, players drive around a track and the competitors with the best times get an in-person try-out. The winner of that try-out gets to race, in real life, for Nissan. Hundreds of thousands now enter the contest each year. All of the winners selected in the past few years are still racing – three of the winners have even raced for Nissan at Le Mans – which goes to show how successful this recruitment channel is for Nissan.
While you may not be looking to recruit an army of data scientists like Walmart or the next Michael Schumacher, these examples show why it is important to consider some of the more unusual recruitment channels, find out where your talent socializes and use that knowledge to focus on recruitment channels that deliver the biggest return for your money.
Identifying and assessing the best people for your business
It used to be said that employers made up their minds whether or not to hire a prospective candidate within five minutes of sitting down to interview them. It is hard to say if this is true or not, but many HR professionals or hiring managers would probably admit that they had made appointments based on a gut feeling: simply whether or not they felt the person was the right fit for the vacancy. As it is in many other areas of business, data and analytics are helping to take the guesswork out of recruitment. Rather than relying on the famous gut feeling, those teams taking a more scientific approach to appointing staff are finding it leads to more suitable people who stay happy and on the job for longer.
Employers in every industry are turning to data, and tools such as Evolv and TalentBin allow them to crunch data in more ways than ever before to find the right candidate for the right position. Tools like these allow employers to find the best person for any given job, whether that person is actively searching for a position or not, based on their skills, interests and actions. Big data and artificial intelligence (AI) tools are increasingly being offered by vendors like LinkedIn to sift through candidates’ profiles and identify the most suitable candidates for a position, which is just as well when you consider that 52 per cent of talent acquisition leaders state the most difficult part of recruitment is identifying the right people from a large pool of applications!10 In my opinion, this is where the future of recruitment lies: using data and algorithms to identify talent and take the guesswork out of recruiting.
Predicting personality
Crucially, when recruiting a new candidate, personality and fit are as important as skill set. These can sometimes be tricky to judge, but not with the help of data and predictive analytics. Companies like Facebook and Google now can predict an awful lot about our intelligence, behaviour and personality attributes based on our profiles and online activities. For example, did you know that your Facebook ‘Likes’ can expose a great deal about your personality traits and preferences? A study by researchers at Cambridge University and Microsoft Research Labs showed how the patterns of Facebook Likes can be used to automatically predict a range of highly sensitive personal attributes.11 Using the Like data of 58,000 volunteers, the study also illustrated that the Likes can have little or nothing to do with the actual attributes they help to predict and often a single Like is enough to generate an accurate prediction. So, for example, the study found that Likes for curly fries, science, Mozart, thunderstorms or The Daily Show predicted high intelligence, while Likes for Harley Davidson, Lady Antebellum and ‘I love being a mom’ predicted low intelligence. Meanwhile ‘so so happy’, ‘dot dot curve’, Girl Interrupted, The Adams Family and Kurt Donald Cobain predicted being emotionally unstable or neurotic, while business administration, skydiving, soccer, mountain biking and parkour predicted being emotionally stable or calm and relaxed. It is pretty scary stuff for anyone who clicks Like without thinking about what they are potentially giving away!
So how do you turn this predictive capability to your advantage when it comes to identifying the right employees? It sounds obvious, but the first step is to identify exactly what you are looking for. What does your ideal employee look like? Throughout the book we have seen examples of how certain attributes were found to be linked to success in certain roles, and those kinds of insights may inform your decision. So think about the skills, qualifications and experience you are looking for. You will also want to think about culture, fit and personality attributes. Armed with this ‘shopping list’ if you like, it is relatively easy to use analytics software to sift through potential candidates to identify certain data points in applications, CVs or profiles and find the candidates with the best fit in a far more efficient, effective way, which often just takes minutes. And while the final hiring decision will always come down to a human, the algorithms will save a lot of time by narrowing the field down from maybe hundreds of candidates to the most suitable 10 or 20.
Machine learning and AI in recruitment
There are many AI-driven tools that can be used to narrow down, test and assess candidates by, for example, asking them common questions about the job. But some assessments go way beyond this to create immersive gamification experiences, a bit like the Marriott game discussed earlier in the chapter. Using machine learning and AI techniques, the process of attracting, sourcing, matching, screening and assessing candidates is automated using data from all sorts of sources, including the employer’s own data, social-media data, employee history etc. Machine learning and AI algorithms like those offered by HR software company Restless Bandit help companies to filter out much of the ‘noise’ when it comes to selecting candidates. While this used to be a slow process of humans reading every CV and sorting them into piles of ‘yes’, ‘no’ and ‘maybe’, now algorithms can model patterns of hiring to find exactly the right people quickly and easily. Crucially, this process removes the biases that humans inevitably bring to the recruitment process, meaning candidates hopefully will no longer have to hope that they will not be overlooked because the interviewer does not like the tie they are wearing, or because they went to the wrong school.
Connectifier is one company aiming to revolutionize the recruitment process through AI technology, and build up more than 300 million online profiles to help employers find the perfect candidate.12 The company – which was founded by ex-Google workers – collates data from across the Internet to help find people who are ideal for specific jobs, whether those people are currently searching for jobs or not. Connectifier’s platform sorts and combines data to create a complete profile of potential candidates, then lets employers feed in the types of skills and expertise they are looking for to find perfect matches based on that information.
JetBlue Airlines gives us a great example of data analytics being used to boost recruitment processes.13 Previously, the company had focused on ‘niceness’ as the most important attribute for flight attendants. Then, after carrying out some customer data analysis with the Wharton Business School, JetBlue was interested to find that, in the eyes of its customers, being helpful is actually more important than being nice, and can even make up for people being not so nice. The company was then able to use this information to narrow down candidates more effectively. This just goes to show that you do not have to be a data powerhouse like Google to use talent analytics to boost your recruitment processes.
Of course, there are a lot of costs involved in hiring an employee, including advertising and the selection process itself. And when an employee turns out not to have the required skills or to be a poor fit with the company’s culture, this can be an incredibly expensive mistake (not to mention a waste of time). While there is obviously a cost involved in implementing machine learning systems, over time they are likely to save money, effort and resources, ultimately freeing up HR’s time to focus on more valuable activities than sifting through hundreds of applications.
Identifying candidates for top-level positions
While a lot of the focus of talent analytics focuses on filling low and mid-tier vacancies (like the Xerox call-centre example we saw in Chapter 4), data and analytics in fact can be used to identify the best candidates for any position, even right up to the CEO. US-based mattress company Purple, for example, used talent analytics in the search for its current CEO, Sam Bernards.14 The ‘C-suite’ of CEOs, CFOs, CMOs and other chiefs in the company are the people who are going to guide the direction of the business. They carry a large amount of responsibility and in return often take home a sizeable chunk of a business’s earnings. When mistakes are made in appointing people at this level, disaster is a distinct and clear likelihood. So of course it makes sense that filling these vacancies should be done with as little guesswork as possible.
Corporate headhunter Korn Ferry has taken steps to ensure C-level recruitment is firmly rooted in data and analytics.15 The firm has specialized in finding candidates for the highest level jobs for almost 50 years. In recent years it has started to apply big data analytics to the wealth of data it has acquired, in order to find the best people for the best jobs. This has allowed the firm to draw up detailed profiles of the competencies, traits and experiences needed to succeed at the top level. In partnership with data scientists at the University of Southern California, the company began to build its analytics-based people placement platform (which it refers to as the Korn Ferry 4 Dimensions of Leadership and Talent – or KF4D for short). Dana Landis, Korn Ferry’s vice president of global talent assessment and analytics, told me: ‘The biggest discovery was that there are some real universals playing out – more than we expected would be the case’.15 The data revealed some strong patterns about the importance of traits and qualities required for C-level positions, including being a lifelong learner and having higher levels of emotional intelligence (eg empathy), communication skills and a tolerance for risk.
Along with traits and competencies, experience is obviously a core necessity for success in many roles. This can be covered with analytics too. Comparative analytics can show what skills a person has picked up in previous positions, and which of those they will be likely to need to carry with them as they move up the career ladder.
Another key element which the system is designed to assess is how well the candidate will fit within the culture of the organization. Mike Distefano, chief marketing officer and president of Korn Ferry’s research and analytics arm, the Korn Ferry Institute, told me: ‘One thing I always say is that people get hired for what they know and fired for who they are. So we have spent a lot of time making sure we can check that the person is a good cultural fit’.15 Clients looking to fill positions have the ability to choose whether they are happy with their organizational culture – in which case the system will find someone who is likely to fit in – or are looking to change it. If this is the case, then candidates will be suggested who are likely to be agents of change.
But is there one quality – or attribute – that stands out above all others as essential for leadership? The answer is ‘yes’, according to Distefano: ‘If I had to pick one individual indicator of success, then it would be agility. The data analysis has shown that candidates who score highly for agility also tend to deliver well on delivering increased profitability’.15 His advice is therefore to: ‘hire the agile, but check for fit’.15
Appointing a new CEO is undoubtedly one of the biggest challenges a business will ever face. Most companies would not make decisions about which products or services to offer without solid data analysis, so it makes sense to bring the same in-depth, analytical approach to hiring for top-level positions. The claim is that, by making the move to evaluating top talent on quantifiable data, backed by comparative analysis, companies can make sure their leadership positions are filled by the people most likely to take the business – and everyone inside it – onwards to bigger and better things.
Sourcing virtual workers
In this data-rich and connected world, it is now increasingly common for companies to draw in talent without actually recruiting people. As increasingly more businesses and applications head for the cloud, it is becoming much easier for companies to agree to hiring remote workers as and when they need them. In fact, a remote workforce can drastically cut down on a company’s overheads. In the United Kingdom, there are around 5 million ‘crowdworkers’ – people working as part of the ‘gig economy’ – often through digital platforms like CrowdFlower and Upwork.16 The obvious advantage for workers is they can work wherever and whenever they like. For employers, they can tap into talent without the expense of hiring people full-time. It is a brave new world.
Even when companies do want to hire full-time talent, increasingly more are letting employees work remotely. As the types of information stored in the cloud increase, the more jobs there are that can be worked remotely. Data entry, programming, writing, design, translating and customer service: these types of jobs are already heavily remote. But soon more teachers, nurses, researchers, psychologists and others will find their work headed to the cloud as well. Online education providers are using virtual professors to mark work, law firms are outsourcing document processing and some researchers are even experimenting with using untrained crowdworkers to analyse medical imagery. Remote working – working from somewhere other than a business’s office building – is one of the fastest-growing segments of the jobs market. One survey of business leaders reported that more than a third of those surveyed stated that over half of their company’s full-time workforce would be working remotely by 2020.17
What does this mean for recruitment? Well, the analytical techniques we have talked about in this chapter can be incredibly useful when identifying and assessing candidates who may never set foot in your offices. Also, when someone works remotely, they may not have access to the same level of one-to-one mentorship that an in-house employee may have. This may mean you need to focus your hiring on highly experienced people who already have all the core attributes needed to succeed in the role. Analytics can help you to pinpoint such candidates quickly and easily.
Identifying and promoting suitable candidates inside the company
As a final word on identifying candidates, it is often said that it is more cost-effective to promote from within than to recruit from outside the company. Another obvious advantage is that internal candidates are already well versed with the company’s systems, processes and culture. So it makes sense to keep in mind the benefits of applying the same sort of talent analytics to identifying suitable candidates from within the company. As we saw from the Human Resources Today finding discussed earlier in the chapter, the opportunity to progress and grow within a company is hugely attractive to millennials, so promoting from within is another great way to boost your employer brand. Talent analytics can help HR teams to identify the top performers in roles across the company, as well as those who are already in the best position for them.
Key takeaways
As we have seen in this chapter, it is essential that recruiters are able to understand data and analytics and use them to their advantage in boosting their employer brand, maximizing recruitment channels, and identifying and assessing candidates. Intelligent HR means using technology to automate processes where possible, freeing up time for more valuable activities. The following is a quick summary of what has been covered in this chapter:
· Your employer brand tells employees who you are as a company, what you stand for, what it is like to be part of the company and what makes you different from other employers.
· Data provide a way to measure and truly understand your employer brand, and help to promote your employer brand to potential employees.
· Given the diversity of recruitment channels, it is important to know which deliver the greatest ROI. Data allow you to test your recruitment channels and measure their success rate.
· Data and analytics are helping to take the guesswork out of recruitment and find more suitable people who stay happy and on the job for longer.
· Data and analytics can help to predict personality and fit, assess candidates, narrow down a lengthy list of candidates, identify the best candidates and attributes for certain positions (at every level of the company) and more.
· AI is beginning to play a key role in recruitment, and many recruitment-related tasks now can be automated.
For me, recruitment is one area in which analytics, particularly machine learning, offers lots of opportunities for streamlining, improving and even automating processes, which allows HR teams to save time (and, ultimately, money), as well as fill positions with the best possible candidates. Of course, once you have found the right people, you need to keep them engaged and satisfied with the company, which is what we will look at in the next chapter.
Endnotes
1 RiseSmart [accessed 23 October 2017] The Connection between HR Analytics and Employer Brand [Online] http://info.risesmart.com/wp-rg-insight-whitepaper?utm_campaign=2017.5.1_WP_Insight_Whitepaper&utm_source=website
2 RiseSmart [accessed 23 October 2017] 2017 Guide to Severance and Workforce Transition [Online] http://info.risesmart.com/2017-guide-to-severance-and-workforce-study
3 Bersin, J (2016) [accessed 23 October 2017] Data Proves That Culture, Values, and Career Are Biggest Drivers of Employment Brand [Online] http://www.humanresourcestoday.com/data/employer-branding/recruitment/?open-article-id=5366961&article-title=data-proves-that-culture–values–and-career-are-biggest-drivers-of-employment-brand&blog-domain=joshbersin.com&blog-title=josh-bersin
4 Heitner, D (2016) [accessed 23 October 2017] Golden Gophers Go with Virtual Reality to Tempt Football Recruits [Online] https://www.forbes.com/sites/darrenheitner/2016/11/23/golden-gophers-go-with-virtual-reality-to-tempt-football-recruits/#6fd4880722e4
5 Slezak, P (2013) [accessed 23 October 2017] How Marriott Hotels Is Beating Facebook at Their Own Game in Social Recruiting [Online] http://www.recruitingblogs.com/profiles/blogs/how-marriott-hotels-is-beating-facebook-at-their-own-game-in
6 Gartner (2015) [accessed 23 October 2017] Gartner Survey Highlights Challenges to Hadoop Adoption, press release [Online] http://www.gartner.com/newsroom/id/3051717
7 Marr, B (2015) [accessed 23 October 2017] Walmart: the Big Data Skills Crisis and Recruiting Analytics Talent [Online] https://www.forbes.com/sites/bernardmarr/2015/07/06/walmart-the-big-data-skills-crisis-and-recruiting-analytics-talent/#7857e8f56b55
8 Kaggle [accessed 23 October 2017] The Home of Data Science and Machine Learning [Online] https://www.kaggle.com
9 Golson, J (2015) [accessed 23 October 2017] The Best Way to Spot Great Racing Drivers? Videogames [Online] https://www.wired.com/2015/08/best-way-spot-great-racing-drivers-videogames
10 Ideal [accessed 23 October 2017] AI for Recruiting: a Definitive Guide for HR Professionals [Online] https://ideal.com/ai-recruiting
11 Baldwin, R (2013) [accessed 23 October 2017] Study: Facebook Likes Can Be Used to Determine Intelligence, Sexuality [Online] https://www.wired.com/2013/03/facebook-like-research
12 Connectifier [accessed 23 October 2017] Hire In-demand Talent, Faster [Online] https://www.connectifier.com
13 Aslan, B (2016) [accessed 23 October 2017] To All Recruiters – Use Machine Learning to Hire Better Candidates [Online] https://medium.com/@deadlocked_d/to-all-recruiters-use-machine-learning-to-hire-better-candidates-c5aad22f3319
14 Olenski, S (2016) [accessed 23 October 2017] Using Talent Analytics When Hiring for Your Brand [Online] https://www.forbes.com/sites/steveolenski/2016/10/05/using-talent-analytics-when-hiring-for-your-brand/#141ff19b1f97
15 Marr, B (2015) [accessed 23 October 2017] Can Big Data Find Your Next CEO? [Online] https://www.forbes.com/sites/bernardmarr/2015/07/27/can-big-data-find-your-next-ceo/2/#4e1b1e19407b
16 Huws, U and Joyce, S (2015) [accessed 23 October 2017] Crowd Working Survey [Online] http://www.feps-europe.eu/assets/a82bcd12-fb97-43a6-9346-24242695a183/crowd-working-surveypdf.pdf
17 Global Leadership Summit (2015) [accessed 23 October 2017] What If … ? [Online] https://gls.london.edu