Please. For goodness sake, please stop measuring HR data.
See, I know why you’re doing it. You heard this “big data” thing it was a good idea, and you started gathering information. Then you realized how easy it was, so you started pulling together even more from a variety of sources. You’re hitting up your applicant tracking system, payroll system, and other data feeds to get what you want. I know, it’s hard to stop.
But then you did what many others do–nothing. You took all that information and you sat on it.
Because you didn’t slow down and start with a plan. You need to know ahead of time (or at least have a general idea) about how the information can help you. If you’re gathering data for the sake of gathering data, then you are wasting time and resources, and you’re probably harming your credibility as well.
On the other hand, if you started with a plan to associate the data with business outcomes to actually prove a point, then carry on. I hope you make better decisions and deliver more value to the business based on what information you’re pulling together.
A quick test
Here’s a quick test to help you figure out what data is valuable and which is not.
- Learning: what is more valuable in business terms, measuring training completions or measuring changed behaviors based on the training?
- Payroll: what is more valuable to the organization, calculating how many zip codes employees live in or calculating how many have benefits and how that number trends over time?
- Employee relations: how about this? Should you measure the number of sexual harassment complaints or how many disagreementsÂ you mediate between supervisors and staff?
Here’s the twist. I could easily make the case that any of these could be valuable in specific circumstances. But if you are truly looking at how your training is changing the organization and making people work smarter, then completion information just isn’t enough to do that.
The thing is, many people just gather data without any idea of how to use it. Your needs are different from those of every other organization, so something others might ignore could be incredibly valuable in helping your employer meet its goals and vice versa.
Think about the information you gather and report. Is it truly impacting the business, or is it just a “we’ve always done it” kind of activity? When I think back to the data I reported on at my last job, some of it was valuable, and some of it was a complete waste of time. And it was rarely used for decision-making, which made it doubly painful.
For instance, I had to regularly report on turnover numbers, but we never took the time to review them by team or functional role, which might have given us some insight into what was driving turnover for those specific positions.
We need to be thinking about what we gather and report on more critically. Stop gathering data just for the sake of it. Start with a purpose in mind before you piece together the first bits of information, or “begin with the end in mind,” as Mr. Covey would say.
Hope that helps. Lessons learned from someone who did it the wrong way the first time around. :-)
After reading the article and thinking about it for a while, I realised that there are so many situations when we tend to gather data for the sake of gathering. And I believe that this also happens when we have many things in mind and we need facts for all of them. However, just as you said, it’s better to take some time and analyze our ideas and then focus on gathering data where it is needed, not just randomly.
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do research pretty much the same way one would do it when doing research as an/a academic/student writing a thesis (with the added advantage of being in an environment you are familiar with), with this approach everything becomes easier and one doesn’t just collect data randomly, a typical format could be as follows:- (too bookish, I know but it makes life so easy)
1. Introduction (discussing the topic of interest)
2. Research Statement (the purpose of your research)
2.1. Hypothesis (specific issues you will research)
3. Literature Review (what others say)
4. Methodology (your approach to conduct your research)
4.1. Data (secondary/primary/variables)
4.2. Data Collection (source)
4.3. Sample (size)
4.4 Sampling Technique (approach for choosing the sample)
4.5 Model (statistical model to test your hypothesis)
5. Results and discussion
7. Limitations of the study (issues forcing one not to make certain variables a part of the research)
8. Recommendations (for any action to be taken and future areas of research or any new questions raised)
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