Revolution in business proceeds unnoticed: we understand the scale, is already actively using the fruits change. So it was with online recruitment in the early 2000s, when the first sites with vacancies, although the most popular channel of searching for employees remained in the press. Today, this market, according to our estimates, reaches 5-8 billion rubles., and in the next four years, according to forecasts by Goldman Sachs to rise to 13 billion rubles (about $182 million at the rate of 71 rubles per dollar).
Next, the digital, revolution is brewing today in the field of personnel management.
On the threshold of change
To understand how and why it will be HR Digital revolution, take a look at the ongoing changes in medium and large companies. Many have already made the first step — automated recruitment process. The introduction of ATS (Applicant Tracking system manage applicants) allows companies to track applicants at all stages of selection: viewing jobs and response to it, to interviews and hiring. So the recruiter understands, through what channels (websites, social networks, recommendations of employees, job fairs, etc.) comes more successful candidates and where to invest resources.
As a result of using information systems, companies have accumulated a lot of data. Their analysis and develop solutions on this basis may be the next step for the business.
Initial levels of intelligence could organize virtually any company. They represent the most basic reports, which are made by using external systems such as recruiting website. This can be reports on the dynamics of responses to jobs that would better know the portrait of “their” candidates and enrich this knowledge in the selection process. For example, if your potential candidates — “larks”, it is possible, and a recruitment advertising/job fairs should in future be adjusted on the earlier watch.
Another example of a relatively simple HR Analytics — statistics the speed of the vacancy. It can help to measure the efficiency of the recruiters and to compare their effectiveness. More complex to implement Analytics tool — data from different sources. But the most interesting and useful for business results can be obtained for more complex models and systems of HR Analytics. For example, many companies that recruit young professionals, often use as a criterion the average score in the diploma. Roughly speaking, the company makes a choice whether her “all knowing honors” or “lively Threeness”. The link between success in education and the results can be numerically analyze and make recruitment more effective for a particular position.
HR c an inhuman face
Even more interesting results are provided by the modern machine learning methods. Computers are able to support staff decisions (and in the future and make decisions) in different HR areas: supporting one of the candidates to hire, who to promote, who can resign in the next month and how much it will cost the company. All recommendations will be made entirely on the basis of data collected by the company.
In the framework of the task of recruiting the first step is the ranking of candidates (HR Scoring) on the basis of data available on the candidate, job and company. The ranking is actually the ordering of the candidates, starting with the most promising. Criteria for ranking may be different elements of the summary and vacancies: the vacancies and resumes, salaries, skills. Much more effective such projects can be implemented in analysing the data not from one, but from many companies.
As the target metric may be a time in the company (to minimize staff turnover) or efficiency (e.g., amount of sales, sales managers). How will affect the business of the company, if without the increase in staffing recruiters, it will begin to hire more effective salespeople? Revenue will certainly go up.
Machine learning is applicable in any area of HR: from the definition of career paths of employees in order to make optimal improvement to predictions of layoffs of employees, to keep them. For example, it is possible not only to predict the probability of dismissal of a specific employee in a certain period of time, but also to obtain a valuation of the losses of the company. What would it take? To have the maximum amount of data about employees and their work, as well as the history of increases and layoffs. Advanced algorithms can analyze the data about employees and their actions at work to reveal hidden patterns and learn to make predictions based on them.
Future changes will seriously change the market of HR solutions. On the one hand, will significantly increase the entry threshold to the market for providers of such services, on the other hand, employers-pioneers will gain a competitive advantage. Moreover, these decisions will be made according to the “simple interface” plus the “complex logic and algorithms”, when the whole data analysis will occur transparently to the user, and the results be issued in an understandable form. This approach significantly streamlines HR processes for cost, speed and the number of erroneous decisions.