3 People Analytics Cliches to Avoid

You have the buy-in and support you need from the executive leadership and you are well on your way towards creating the sought-after data-driven culture that is the bedrock of sound decision making.

But wait. Before you rush headlong into this brave new world, a word of caution. You may have done your research, read case studies, and observed how companies successfully implemented people analytics. What you may not have read about are the failures.

Nobody wants to advertise their failures, but they can be a cautionary tale for new adopters. It is just as valuable to know what not to do as it is to know what strategies are most effective.

There are some easily avoidable pitfalls you should be aware of that can derail your progress.

Here are three people analytics clichés arising from rookie mistakes to avoid in your journey towards building effective people analytics capacity.

1. The Copycat

People analytics is like the latest, shiny gadget that everyone wants— an air fryer.

It’s popular, everyone is talking about it, and in recent years it’s touted as the must-have appliance. Many people will purchase one simply because it’s trendy and all their friends have it.

Once purchased and unboxed they gaze at the new acquisition, smug with the pride of ownership. Only then will they start thinking about what they can cook in it. This is not the approach to adopt with people analytics.

You should not be motivated by what your industry peers are doing but what can solve your specific business challenges. People analytics is not a one-size-fits-all technology.

First comes the problem, then comes the solution. This might seem like a no-brainer but sometimes companies treat people analytics like a solution that is looking for a problem.

You should start by identifying the questions that you want the data to answer. The type of questions will make a big difference in whether the answers are actionable. They should be specific and begin with the words “why” and “how.”

The preferred strategy:

Question: How can I make my diet healthier?

Solution: An air fryer will allow me to enjoy my favorite fried foods guilt-free and reduce my calorie intake.

Question: How can we increase productivity?

Solution: By analyzing data related to staff engagement we can determine which drivers have the greatest positive impact on productivity.

2. The Under-Rug Sweeper

Analytics is only as effective as the quality of your data. The acronym GIGO comes to mind. To quote the gospel of computing, “Garbage In, Garbage Out.”

The data collection frameworks and methods that you already have in place can make or break your people analytics implementation and ultimately the accuracy of your insights.

For example, if you are skeptical about the existing performance management and competency systems then you will waste valuable resources to analyze data that you don’t trust. If you don’t trust the input, you won’t trust the output. People analytics will not fix your dodgy systems, you need to address them first.

The same applies to data that isn’t properly cleaned. Dirty data can happen when you merge datasets from multiple sources with varying levels of quality and/or without checking for duplication or errors.

Inputting faulty data into a new, state-of-the-art database will not make it valid. Don’t neglect the critical step of data cleaning and don’t sweep your dirty data under the brand-new analytics rug.

You do not want to end up making critical decisions based on erroneous or incomplete information. This has the potential to be costly. The integrity of your data is riding on your ability to get this right.

3. The Overdoer

Who doesn’t love a snazzy analytics dashboard?

Visualization is a critical part of people analytics implementation. It determines leadership’s ability to readily interpret insights and act on them. Keeping this in mind, dashboards must have certain characteristics that help them to be readable and user-friendly. This is where effective, thoughtful dashboard design comes in.

It is easy to get trigger-happy and lose the plot, building busy, confusing, reports that display too many numbers and not enough trends.

Consider this, if there is a metric you think might be useful, ask yourself if it answers a business question. For example, you may think it useful to report on a specific customer demographic like location. But perhaps reporting that answers the question, “Who are our most valuable customers?” would provide more valuable insight to act on.

These are the sorts of questions that should guide the selection of charts and reports and will help users make the most of dashboards.

Here are a few dashboard dos:

• They must be uber relevant.
• They must be designed for the specific needs of the user.
• They must deliver reports/trends at the most appropriate intervals.
• As far as possible they should be on one page (with supporting pages if necessary) to be easily digestible.
• They should provide KPIs at-a-glance.
• They should not sacrifice practicality for aesthetics.

Don’t become a people analytics cliché. Do the research and lay a foundation built on sound business strategy and data integrity. Remember the data is not your end goal but a means to an end. That end is an organization that makes decisions that have a positive and sustainable business impact.

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