Employment Enterprises Blog

Four Easy Steps to Evaluate Big Data for HR & Recruiting

Posted by Jessica Miller-Merrell on Nov 3, 2016 6:00:00 AM

how to use big data for hr

Contrary to the thought of many who work in HR and recruiting, big data doesn't have to be complicated. It is quite simple and most of you already have the data points in which to begin analyzing and evaluating to help you and your team 1) Establish patterns, 2) Predict the unpredictable and 3) Decrease uncertainty.

There are four steps when it comes to adding big data to your HR and recruiting arsenal. So let's get started. Shall we?

Step 1: Establish Goals & Priorities For Your Big Data

This is a good idea when kicking off any type of new project, program, or workplace initiative. You must have goals and priorities in order to understand exactly why, what, and how you are doing. Otherwise you will be lost. There will be uncertainty and push back from all points including business leaders, peers, and other parties.

When I think about big data, I like to take the lead from social networks like Facebook, Google, and Twitter who were some of the first to employ data scientists to develop algorithms, analyze and manage data, and establish patterns. These sites use the information that you provide and the billions of other users through private messages, status updates, and other activities to sell advertising while also working to (hopefully) make a better experience for you. They trust the data and use it to decrease risk and increase visibility for those who choose to pay for Facebook marketing campaigns.

Step 2: Collect the Data

Once you have your priorities and goals established you can begin to collect your data. Keep in mind that as HR and recruiters, we already have much of the data we need. There are two sources of data: 1) internal and 2) external.

Internal databases exist in plenty, including forecasting for vacation and sick day planning; candidate databases such as your applicant tracking system and talent community; or even your assessment and candidate testing data. This is all information that is contained or can be collected within your organization versus external sources that are outside of your company.

The external sources are the data points I'm personally most excited about. These are data from public sources including social media and other networks where individuals—candidates and customers—are sharing freely. Companies often use the data customers share on their experiences to establish better company practices and processes. The same can happen for your candidate experience, targeted recruiting efforts, or experience for existing employees.

Step 3: Analyze the Data

Analyzing the data is the most complex and can be extremely overwhelming. It's likely that you have millions, billions, or even trillions of data. It's not something that your staffing spreadsheet can handle. It requires a software or technology to manage, organize, and help establish patterns in the data. This means making a purchase in some type of technology and the likely investment in hiring a consultant or data scientist who specializes in this type of thing.

My favorite approach to display and also analyze the data is with the use of a dashboard. It helps transform complex data into simple visual aids and graphics that you can easily see, relate to, and pop into your powerpoint for that business meeting.

Step 4: Drive the Change

Data is only as good as the action that is taken. Why go to the effort of collecting and analyzing the data if you don't plan on using the information to drive a change? Big data is part of what I consider the performance of "now". It gives us insights and trends into the marketplace that we are analyzing. This means taking actionable steps as a result of your data now instead of waiting two weeks, four weeks, or six months after you receive the data. Otherwise all your hard work is worth nothing.

Big data provides an amazing resource in helping businesses, including HR, to make better and more informed decisions looking at the landscape at a larger scale or a different way. The data isn't one hundred percent. Take Google for example, which developed an algorithm that could predict the flu outbreak called Flu Trends. It worked fine for a number of years until the market changed. This change could be an anomaly or it could be part of the even bigger picture and patterns that we don't see. Big data is a guide, but it is not foolproof. It allows you to arm yourself with more data, knowledge, and resources; and in our line of work where the people are the assets, more information to make better decisions is a very good thing.

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Jessica Miller-Merrell, SPHR is a workplace technology and social media strategist. She's the founder of Blogging4Jobs.com. Follow her on Twitter, @jmillermerrell.

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