The big data trend is making its way to the Human Resources area. In fact, a 2014 Towers Watson Survey (attached to this article) of more than 1,000 organizations found HR data and analytics to be among the top three areas for HR technology spending. Where HR is concerned, big data aims to empower employers and human resources to make more informed business decisions. Big data analytics offers many exciting promises:
- Gain more insight on employee performance, boosting individual motivation and overall engagement.
- Help identify and acknowledge top and low performers.
- Learn why employees leave -- and why they stay.
- Evaluate training program participation and outcomes.
- Identify great potential talent by sorting information into trends and narrowing down the talent pool.
But where do you start? Well, put simply, with the data. You've heard the expression "garbage in garbage out." The thing about data is that while everyone has it, it's frequently imperfect and we typically don't know what to do with it. As someone who works with data every day while preparing Affirmative Action Plans for CAI members, I realize it can be a source of headaches for many people. Data really is a great thing and we need it for almost everything - payroll, budgets, sales & marketing, year-end reporting, etc. But the frustrating part is that oftentimes the data is bad. And when the data is bad, the resulting decisions you make will be less than ideal.
So before you can even consider using big data to improve your HR operations, you need to get small data right. The question is what can you do to try to make small data better? While you probably won't be able to fix everything, there are a few things that you might be able to do make your job a little easier.
- Fix data at the source. The ability to download data from HR systems into Excel for further analysis is a great thing. However, I see people all the time who upon finding errors in the data just make the correction in Excel because they are trying to meet a deadline and this is the quickest way to fix the problem. That is OK but I recommend also going back to the source data and correcting it there. If you don't fix the source data, including the process that resulted in the error, the next time you run this or a similar report, you're going to have the same problem. Sounds simple but I see this issue every day! And, others who try to utilize your "big data" will see the same inconsistencies, reducing the data's and perhaps your own credibility.
- Check for Inconsistencies. Often what is supposed to be the same data, will be listed in a variety of different ways in the same system or across multiple platforms. For example the job title Accounting Assistant may be listed as Accting Assistant, Accounting Asst, Accounting Asst. or Account. Asst. For simplicity and correct reporting, a standard format for this type of data is beneficial and necessary.
- Capture the right information. If data you need is not currently available, can you start capturing the information you need? It may take some extra time initially but if it'll help you in the long run, you'll be happy you did so. Make sure there are clear processes in place to capture the data correctly the first time. With data, the more judgement required on the data input side the more inconsistency you'll see on the output side.
- Get help. You might need to get someone else involved to help you. It could be a system administrator who is responsible. Or you might just not have time to audit and correct data problems yourself. Check to see if there is someone else in your organization that could assist you with this endeavor. There are probably other people who also use the data and have an interest in ensuring your company has the cleanest possible data.
If you can, take some time and try to correct any issues you're aware of. Very few people want to deal with the same problems over and over again. Every little bit helps! Call Rick Washburn or Tom Sheehan on the team if you need help talking through your data strategy.
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