To the common eye, working in human resources means being the “fun-sucker” out of any office party, or that’s at least how HR representative Toby Flenderson is portrayed in The Office.
But in real life, working in HR comes with enormous responsibilities like keeping an eye on seemingly an entire market of competition, potential incoming talent, internal policy, and a million other roles that keep both day-to-day operations successful and long-term goals met. All of these tasks require copious analyzing and research of HR Data to stay at the top of the market and remain cutting edge.
With web scraping, beginning to gather, use, and implement data findings to understand your organization’s most valuable HR metrics is less time-consuming and costly for both you and your company than you think. Feel free to use the table of contents to get to the information that is most useful to you.
Table of Contents
HR & Big Data: 101
Understanding the wide variety of duties that any given HR representative may have begins with explaining the broad, main functions of HR. Wikipedia summarizes an HR department in this way: “[performing] human resource management, overseeing various aspects of employment [such as hiring and firing], compliance with labor law and employment standards, administration of employee benefits, organizing employee files, and [more].” You get the gist. HR goes both ways in managerial and operative functions to become one of the most robust backbones to grow and maintain any organization.
Depending on the organization’s size, HR responsibilities can be broken up into different positions to specialties and hierarchies based on experience. As with growing expertise, salary grows as well based on specific skill sets. This typically looks like a staff member(s) explicitly dedicated to staffing or recruiting, employee relations and management, administrators, and data analysts. I’ll dive deeper into the processes and importance of that role later.
Let’s talk data
But first, let’s talk about data and our understanding of how much data we unconsciously process every day. In the case you aren’t familiar, data, in its most simple terms, is information collected. In today’s world, there is a seemingly infinite stream of data coming at us not only through technology but in our everyday surroundings that our brain stores for us. From simple preferences such as what your favorite cheese to use on burgers is to learned routines, such as the fastest route to get to work in the morning because you spilled coffee on your white shirt and had to change (or is that just me?).
Understanding big data
Big data is simply large volumes of data that can overwhelm businesses on a day-to-day basis. These data sets can be analyzed by professionals to gather insights about their business and its employees. Big data is the backbone of most decisions, and it must also be the driving force of making HR decisions.
Examples of big data sets collected for HR departments could be: tracking absences, potential interest candidates, employee satisfaction/dissatisfaction, employee turnover/retention, revenue, employee engagement within the company, and much more. The data gathered from analyzing employees have both short-term and long-term benefits, such as an adjustment of policy to help improve efficiency or to prove that a particular hire has increased revenue because of their addition to the team.
HR Data Analysis: It’s Kind of a Big Deal
So, what kind of data can you use in HR? There are many aspects of HR jobs that require collecting and using data. For example: gathering information and looking into the background of any potential employee. Or, an HR representative could use data to understand the satisfaction of your employees, helping to not only keep your valuable employees around but to create an environment that fosters passion about your business and drives sales and revenue even higher. When people are doing work that they believe in, selling your brand becomes much more authentic. Let’s examine the processes of collecting valuable data to use in HR.
Use data to hire better talent
For example, deciding to expand a team and hire a new employee has a checklist of things before posting a job. Some things you must consider in crafting your new position are:
- Salary range
- Qualifications (both degree-wise and career-experience-wise)
- How the hiring process will evolve (how many interviews and with whom, test assignments)
- The tone of how you will present your company to the reader of the job posting
Now, while this may seem straightforward, collecting data to help with this process can really make a difference. Let’s pretend you’re creating a new department in your company and need to hire the best talent. If you fail to gather data from your competition about the salaries they offer, you could and either lose great candidates or hire bad ones that will not contribute to the goals of your company you might make the mistake of posting a salary that could be wildly underpaid for the position.
Data collection is also necessary when you’re collecting information about the qualifications necessary and reviewing other interview processes as well. If you’re gathering research on your competition and seeing their great hires, it would also be useful to look at their company reviews to understand how to get candidates like the ones you’re searching for.
Use data to ease your workload
It’s important to consider that posting a job on a popular job listing site, depending on the prestige, benefits, location, and overall reviews of the company, there could be hundreds of applicants. For one or even a team of people, this is where the lines begin to blur. Judging and comparing this abundance of applicants would be a too fraught decision, and bad hiring decisions mean your company isn’t performing as well it could be. Overall, it is a bad look for any HR professional. A way to combat this stress would be to use data collection tools to pick out keywords of skills to adjust your job listing to attract a more niche group of candidates to start on a great foot with your hiring processes.
Now, once you’ve got your dream hire, you want to show your pride in them, how are you going to prove that you made that great hire and can make more great hires that stay around and are passionate about your company? More data analysis! While this example is only telling of one major part of HR, the same thinking can be applied to any of the other many roles played out in the department every day.
By now, you must be thinking, “How do I gather this type of information in a cost/time-effective way?” The short answer is: web scraping!
Web Scraping And HR Data Analytics
The next piece of information vital for your success is understanding web scraping as a Human Resource tool. I like to think of web scraping as an automatic, cost-efficient research robot (it seems a lot less daunting this way, too).
We, as humans, actually conduct web scraping almost every day by recording or making a note of the information we see from websites. For example, if you have checked multiple weather sources to get a more accurate reading of the weather on a given day to help understand how you should dress appropriately, congratulations! You have effectively scraped the web for data (and you should definitely brag about it to your friends!)
All jokes aside, the more complicated web scraping bots gather data by reading a web page’s HTML (one of the languages that computers understand) and collect the information most relevant to your search. That data then essentially gets copied and pasted into a spreadsheet for you to analyze at your discretion. If you would like a more in-depth understanding of web scraping, this article is a great resource.
The beauty of web scraping is that this data collection isn’t limited to one site or time. You can gather as much data as you want, from as many sites as you want, as often as you want. You can even get real-time data every 60 seconds of the day if that makes the most sense for you and your goals. With the right tools, anything is possible.
Using Scraping Robot As Your Human Resource Tool
Each module provides an in-depth presentation of your keyword and all relevant information (depending on your module, of course) and presents the big intimidating data in a friendly, easy-to-read CSV file. Scraping Robot offers 5000 free scrapes a month, allowing you to get a feel for the module until you’re comfortable and ready to use even more data to make your informed HR decisions. It’s tangible for established HR professionals or even a college freshman asking themselves, “How much does HR make?” in the middle of their intro to business class.
When your 5000 scrapes are used up, the affordable price tag of $0.0018 per scrape allows your business to be experimental with the scrapes to play around what is right for you. There’s no hidden fees or subscription charges when you decide you need more scrapes! You can use our pricing page to play around with what fits in your budget. If one of our already established modules isn’t for you, there’s the opportunity to create a custom module to help you gather data to give you the competitive edge you’re looking for.
When looking to be successful in any HR position, it’s important to consider the big data. While this may seem like a daunting task, HR data is much easier to obtain than meets the eye. Innovative tools such as web scraping bots allow you to let Scraping Robot do the daunting work while you are off being the HR superhero of your organization. We want you to be able to brag about that superstar hire or your can’t-be-beat retention rate and have us be the not-so-super power behind your success. Starting big or small is up to you; all we know is that we’re more than happy to get you going!
The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.