Like most things, technology has led to huge changes in the way recruiting is done. Traditional methods are slow, inefficient, and tremendously time-consuming. What’s next in this technological evolution? One answer is data mining.
There is a range of ways that data mining techniques can be used to improve recruitment efficiency. If you’re wondering how then wonder no more! In this article, we dig into data mining techniques and how they will assist you in recruitment.
Before we get ahead of ourselves, let’s take a quick look at data mining as a concept. Essentially, data mining is creating useful data out of raw data by finding patterns in massive collections of data. To do this, there are a few steps to be followed.
First, an organization will collect relevant data, including every bit of data that stores and tracks their processes and outcomes. It doesn’t matter what structure or source it is, for data mining it matters that it’s relevant! This data is stored and managed either on the cloud (ideally) or on in-house servers.
Analysts and data specialists look through the data to decide how it should be organized in order for it to be useful. Specialized software can sort, curate, and classify the data, and can even extract insights from unstructured data. Once it’s curated and stored, it can be used to gain insights into the business. This is the process of data mining from start to finish.
Data mining techniques are being used by all sorts of businesses, from massive conglomerates to grocery store chains and more.
Netflix uses data mining to suggest shows and movies for you to watch, Amazon uses it to suggest products for you to buy, and grocery stores have used it to determine when to sell which products at which price. Clearly, if you’re using data mining techniques correctly, you can significantly improve your sales or revenue.
However, data mining techniques can be geared towards anything, not just improving income. Studies have been conducted in the healthcare industry to show how data mining techniques can be used to ease the decision making processes for medical experts, or for diagnoses of specific disorders.
There have even been instances where universities made use of data mining techniques to recruit students. So, as you would expect, it is a useful tool for the recruitment process too. Data mining can help you make the best decisions on recruits, in a shorter period of time, while putting in less effort.
There are several data mining techniques that can be used in recruitment. To use these techniques you should have data collection processes in place and should ensure that you are not mismanaging data.
We will take a look at some data mining techniques for recruitment here:
Essentially, this technique involves finding and examining patterns in data to come to educated conclusions about outcomes. For example, in business, a specific trend in sales data can lead to action being taken on increasing the inventory of a specific product.
Similarly, in recruiting, you can track patterns of successful candidates. You’ll be able to understand which types of candidates are making it through interviews, and who is succeeding at being hired at your company. This information will make it easier for you to select new candidates, as you will know what to look for.
Technically this falls into machine learning techniques too, but it is a predictive model that allows you to efficiently mine data. Basically, a decision tree takes the input data and enables us to understand how it affects the outputs. In recruiting, this could mean that it gives us insight into whether a candidate will be successful.
It could predict the likelihood of the candidate being hired, which means recruiters can spend less time on other candidates or on screening in general.
Using this technique, information is presented graphically. For example, data is presented using maps, graphs, tables, and the like. This allows the information to be more understandable and digestible. Consequently, there will be more understanding of trends and patterns in the data and thus better decisions can be made.
When it comes to recruiting, this is very useful. Recruiters will not be overwhelmed with information, will easily be able to highlight key ideas like which types of candidates are usually successful and what traits to look for, and will be able to develop a clear plan of action much more easily.
By now, it shouldn’t even be a debate whether you should implement data mining techniques into recruitment processes or not. However, if you need more convincing, here are some of the benefits of doing so.
Not only can you gather insights about which candidates are best suited for your company, but you can also mine your current pipeline to determine which stages of your hiring process need to be altered or improved. This can be done by figuring out when candidates are dropping out of the process, or looking at which stages are taking a large amount of time.
Using data mining, and analytics in general, you have the ability to ensure that unconscious biases do not play a role in your recruitment process. As such, you can ensure objectivity, and as a result, will have a much more diverse talent pool.
You can also gain insights into which candidates are actually engaging in your ads. If you see that it is skewed towards a certain demographic, you can then alter the ad to attract more diverse candidates.
You can use data mining techniques to keep an eye on your current, internal, talent, and on your managers. This helps to ensure that you understand work attitudes, how people react to different managerial styles, why people leave your organization, and much more.
Today, data is more important than ever before. In fact, it is one of the most valuable tools and assets you can have. Ensure that you are making good use of it, by implementing data mining techniques in your recruitment processes. This will lead to more efficient recruitment, better hires, and all-around improved Human Resources practices.
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