How to analyse HR data to earn a more prominent role

by
January 25, 2017
How to analyse HR data

If you want to gain more credibility within your organisation, then you need to know how to collect and analyse HR data.

There are plenty of ways to collect HR data, and dozens of HR software solutions eager to help you do it. But if you want to serve a role beyond pushing paper, then simply collecting data is not enough. You need to know how to use that data to make a positive impact on your organisation.

Today, I’m going to show you seven stages of HR data analysis. As you read this article, try to work out which stage you’re at, and which stages you might be missing. This is not a “playbook” to teach you how to analyse HR data. But it does show you some of the bases you need to be covering. And if you take care of all seven stages, then I’m sure you’ll be influencing important company decisions very soon!

The seven stages of HR data collection and analysis

  1. Perform the HR function.

    This is how you collect the data.

  2. Desire to make a difference.

    What do you want to achieve?

  3. Organise how you collect HR data.

    You need it in a format you can read.

  4. Understand the data.

    What is it saying about performance?

  5. Take action.

    What can you do to improve?

  6. Analyse and compare.

    Did your action make a difference?

  7. Earn recognition.

    Present your results and build a business case.

Stage one: Performing the HR function

If you are performing any sort of HR function within your organisation, then guess what? You’re already collecting HR data!

Every time you register a sick day, authorise a holiday, or receive a new job application, you’re gathering relevant, useful HR data. Therefore, even if you are performing only the most basic of HR functions, you are already at stage one on this scale.

Of course, simply gathering this data is not enough. It is an essential piece to the puzzle, but you need to do more.

The good news is that you are not stuck in stage one. You’re at least a stage two person. How do I know? Read on to find out.

Stage two: Desiring to make a difference

Do you know what separates most human resources professionals from paper pushers? It’s the desire to make a difference. So, think about what your organisation is struggling with the most, and make this issue your goal. For example, you might be aware that your company is losing a lot of money because of absence.

Don’t worry if you don’t know how to do everything yet. That doesn’t matter – you can learn. The very fact that you want to make things better is a very special quality. Without it, most organisations will happily let you sit at your desk, entering numbers into boxes for the rest of your career. And they’ll barely even notice that you’re there.

Anyway, I don’t need to tell you this. The fact that you’re reading this article tells me you already have a desire to make a difference. It tells me that you’re ambitious and eager to learn. It tells me that you want to use the HR data you collect to make a positive impact on your organisation’s success. So congratulations – you’re already at stage two.

Stage three: Organising how you collect HR data

When you collect HR data, it is very important to be organised. Or, at least, to have an organised method of storing that data!

There are lots of ways to store HR data. The important thing is to find a method that makes it easy to read, interpret and analyse. Here are a few tips:

  • Avoid paper files.

    Not only does this make data more time consuming to collect, but it leaves you with a lot more hard work later, like manual calculations.

  • Keep it consistent.

    Where possible, stick to one method of collecting and storing data. For example, you shouldn’t track attendance on a spreadsheet, but record lateness on paper files.

  • Consider a purpose-built system.

    Most HR systems will help you collect HR data through a user-friendly interface, and then give you options to report on key metrics.

Stage four: Understanding what your HR data means

When you’ve collected a good quantity of data across a good chunk of time, then it’s time to analyse your data to see how you’re actually performing. The amount of data you’ll need will depend on the issue you’re inspecting – I can’t really tell you whether you should be looking at a week, a quarter, a year or more. It depends on so many things that we’re not going to get into today.

Either way, analysing your data is important for many reasons. For example:

  • It helps you to understand where the real problem is coming from
  • You’ll find out just how bad the problem is
  • You can compare these figures at a later date to track improvements

Imagine our earlier example – your company is losing a lot of money because of absence. By looking at the patterns within your data, you’ll be able to run your absence figures against industry averages to get an idea of where to aim for, and you might even be able to identify a more specific pattern.

For example, the data might show that your employees have very good attendance records on the whole. But the reason you are forking out so much for absence could be that 5% of your workforce are taking huge chunks of time off sick. On the flip side, you might find that absence is just fairly bad overall.

The more you drill down into your data, the better your understanding will become. Are the 5% all from one department? Location? Do they all perform the same job role? Are they friends?

Stage five: Applying this information in a way that helps your business

You’ve collected some data. You’re aware of a general issue. You’ve organised your data, and even found out where the issue might be coming from. Now it’s time to fix it.

Let’s pretend that your issue is absence – and that it’s mostly coming from 5% of your workforce. You’ve run the data through a Bradford Factor calculator already, which has suggested that these are not problem patterns – they are genuine instances of illness.

What do you do?

It’s impossible for me to know what problems you might be facing, and so I’m not going to tell you how to make things better in your organisation. I trust that you know how to solve problems. You just need to apply your critical thinking to whatever the data is telling you!

Look for expert advice and best practice in the area you’re trying to improve. Think about what you’re trying to achieve, and then set the wheels in motion.

In my example, I’m going to pretend that the 5% of my workforce calling in sick were working from a very crowded office. I thought that this could have been because germs were being shared very easily, and so I decided to introduce a basic hand-washing policy, complete with colourful posters and reminders, to try and prevent so many illnesses from spreading so quickly.

Stage six: Analysing the results of your actions

Continue collecting data. Ideally, you should collect data for the same length of time as you initially analysed. In other words, if you collected data over three months, you should compare it against the next three months.

Be warned though – things like the time of year might play a part, especially in cases such as absence, where more illness spreads during the winter.

In a perfect world, you’d probably want to compare one year against another year.

In my example, let’s say my overall sickness absence rate was 4% in the first year. After implementing my new hand-washing scheme, absence fell to just 2.5% for the following year. It’s quite likely that my initiative paid off!

Stage seven: Earning recognition for your results

Identifying problems is great. Fixing them is even better. But although you probably hate blowing your own trumpet, it’s an important part of your professional development to show other people that what you’re doing matters.

If the owner of your company looked at absence rates over two years, he or she might smile and say “nice, absence dropped”. But will he or she immediately think “that must be thanks to Susan in HR”? No. In fact, he or she might not even notice there’s been a change at all – they might just see the extra profits through savings, and give themselves a bonus!

So it’s important to present your findings and earn yourself some recognition, as this will earn you greater powers of persuasion for when you want to implement a more expensive initiative in the future!

Presenting your results doesn’t have to be a complicated affair full of spreadsheets, bar graphs and pie charts. Creating a powerful infographic to tell your story is a nice touch, but if you only have limited resources, it could be as simple as this:

  1. We had this problem
  2. I identified this as the source
  3. This is what I did to fix it
  4. Here’s how it helped
  5. Recommendations for future

In my example, I might write a short report like this:

During 2016, I noticed that our average absence rate was sitting at 4%. This was costing the company money, and compared to industry averages of 3%, I felt like we should be performing better.

By analysing absence data, I noticed that most absence rates were good, but that people in our Hull branch were generating worrying figures. As you know, our Hull office is very cramped, which probably encourages the spread of germs.

In January 2017, I implemented a hygiene campaign. I designed posters to encourage regular hand-washing, including fun illustrations on how to do it properly. I also assigned the branch manager the responsibility of making sure basic hygiene products were constantly stocked.

After one year of launching this campaign, I have reviewed absence rates again. Absence levels in Hull have dropped significantly, and our company average is now down to 2.5% – nearly half a percent better than the industry average! My calculations suggest that we have saved £4,956 in cost of absence over the last 12 months.

Over the next 12 months, I’d like to expand on this effort further. I propose we spend £600 on four a state-of-the-art hygiene contraptions, to be installed at each of our biggest locations. I believe this could help us reduce absence further across the board, resulting in further annual savings of around £1800.

How do you analyse HR data to earn a more prominent role?

Although this is my own preferred approach to collecting, analysing and acting on HR data, I realise that there are many styles different to my own. And again, this information is not a “playbook” – it is only meant to open your mind to new ideas.

How do you analyse HR data to earn a more prominent role, and how is it different to the stages outlined above? I’d love to hear your own take on this, so leave a comment below.

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