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People Analytics | 5 min

The top 5 common mistakes to avoid when using workforce analytics

The top 5 common mistakes to avoid when using workforce analytics

 

Avoid these mistakes and benefit from more accurate insights

Recently we explored our take on people analytics (or workforce analytics), and looked at some common reasons why organisations aren’t taking full advantage of all the tools that are readily available to them. Now, whether you’ve been utilising workforce analytics for sometime, or are just getting started, we want you to know about these common mistakes we often see businesses making, as well as how you can avoid them and get the most accurate (and helpful) insights out of your data!

Let’s explore.

Mistake #1: Using dirty data

Why it matters:

First thing’s first, we know that if we put garbage into a system, we’ll get garbage out. Your people analytics are no exception. Of course, we all want to make data-driven decisions, but if that data is inaccurate? It’s almost certainly pushing you in the entirely wrong direction. 

How to avoid it:

Luckily this answer will not only help you to keep your data accurate but also save you a lot of time and effort! The best way to keep your data clean and consistent is to have your HR processes, data capture and analytics happening all in the one system. With an all-in-one system, you’re able to let your data capture and analytics happen automatically in the background as you go about your normal processes every day. 

For example, when entering in a new starter into your HR system, all required onboarding tasks can be automatically triggered or sent to the appropriate person for self-service. This minimises the margin for error by completely removing the need for data being entered multiple times and into different systems.

Mistake #2: Experiencing data overwhelm

Why it matters:

We know having real-time insights available to us is invaluable, but there’s an overwhelming mountain of data in front of you and you don’t know where to start to derive meaning from it, then the benefits of being able to act on this information are null.

How to avoid it:

The first step is to complete our earlier suggestion and make sure you have the right tools in place to analyse your data, without requiring a whole team of data analysts to make sense of it. One of the easiest ways to digest data is with insights presented in simple, interactive dashboards. This allows you to quickly find the information you need, and understand what needs to be done, so you can act on the situation immediately.

Our other main tip for avoiding data overwhelm is to start small and build from there, rather than trying to be across every single metric. This brings us to our next point!

Mistake #3: Focusing on the wrong areas

Why it matters:

While we’re on the topic of data overwhelm, on top of making your insights more digestible, it’s important to focus on the areas where your business can benefit most. With today’s technology it’s possible to measure just about anything you could want to know in your organisation; from what your retention rates are, to how your training investment is paying off, to how many health and safety incidents are being reported. But with all of this information available, it’s easy to get overwhelmed, and a lack of focus could result in inaction. 

intelliHR workforce analytics - training investment
intelliHR training analytics quantifies how much you’ve been spending on training.

How to avoid it:

Take the time to confer with key teams in the business and uncover the main pain points your organisation is experiencing. With this knowledge, you can then focus in on priority areas, allowing you to make more short-term impact and avoid the data overwhelm. As with anything, workforce analytics should be seen as a tool to support your organisation in achieving its goals, and used accordingly.

Mistake #4: Focusing on the past, not the future

Why it matters:

Once you know your data is accurate and you’re able to draw insights from it, it’s also important to stay proactive with these learnings. While it’s often helpful to look back on trends from previous months or years, we also need to stay focused on what this means for the future, so we can take action to improve our situation. 

How to avoid it:

Predictive analytics tools take trends from the past to predict how these will impact the future. For example, survival analysis can draw on a number of data points to predict how long each employee is expected to stay in your organisation. With the right tools in place, you’ll be able to use your insights to make decisions guiding you for years ahead. 

intelliHR Workforce analytics - survival analysis
intelliHR’s survival analysis predicts that 90.21% of employees will stay longer than 3 years.

 

Sentiment analysis offers similar capabilities, but provides visibility over staff sentiment, and whether your people are feeling positive, negative or neutral towards their role, or specific facets of it. This allows you to drill down and discover areas that could be replicated or changed across the organisation to achieve more positive outcomes. 

intelliHR workforce analytics - business sentiment overview
intelliHR’s sentiment analysis shows how employees in your business are feeling.

Mistake #5: Not putting insights into action

Why it matters:

So you have the insights you need now, but what’s next? We can’t get value from our insights unless we actually put them into action, and start taking a proactive rather than reactive approach in everything you do. 

How to avoid it:

Our earlier tips of focusing in on key areas and ensuring your insights are easy to access and understand will have you off to a great start with this. Once you’ve actioned our first tip you’ll already be creating more time for yourself to spend on tasks that matter, like planning and actioning initiatives to improve your organisation’s performance. 

Now it’s time to hold yourself accountable! Start by setting goals for areas you’d like to see improvement in (if you haven’t already), for example, reducing attrition by 15% within the next 12 months. Then be sure to refer back to your analytics at regular intervals to check on progress and see what more needs to be done to move the needle on your goals. 


Those are our main mistakes to avoid in your workforce analytics. We hope these tips help you avoid these pitfalls and get the most out of your people data! If you feel like you might be succumbing to some of these issues currently and need some extra help getting them sorted, our Customer Success team is on stand-by to coach you through the ideas discussed here. Get started here.

Survey Playbook

 

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