5 Common Challenges In People Analytics

There’s good news and bad news.

The bad news is there is no fool-proof, step-by-step guide to people analytics that can guarantee results. Its application isn’t one-size-fits-all because business models, problems, and solutions are unique to each organization. Many businesses gather the same metrics, but the reasons behind the numbers will vary.

Despite new insights, case studies, and expert advice, the field is still growing.

The good news is that there are tried and true solutions to the most common challenges businesses face. With the right strategy and approach, they can be avoided or remedied. Here are five of them and the ways that they can be overcome.

1.   Choosing data over intuition.

For millennia, business leaders have relied on their gut feelings to guide decision-making. Coupled with their experience and business acumen, it may have been enough to steer them in the right direction and lead to some successes. However, that approach isn’t evidence-based and won’t stand up to scrutiny, nor can it be consistently replicated.

In a constantly evolving business environment, any approach that isn’t based on data evidence is too much of a gamble and is unsustainable. What happens if the leadership changes? Gut feeling is usually tied to personal beliefs and values based on an individual’s experience.

The purpose of using data-informed evidence-based decisions is to ensure sound decisions. Hard data is irrefutable, and you can trust it to drive business performance. Managers must believe in data as a valuable tool in decision-making so that they habitually ask for it and use it in decision-making.

2.   Data challenges

Where is it? Can I access it? What condition is it in? Is it good quality?

Your people analytics is only as good as the data it’s built on, so a strong data foundation is crucial. How you manage your data will affect your ability to analyze and derive accurate, actionable insights successfully. Some of your top concerns in data management are availability, accessibility, and quality.

An organization’s people data is often not found in one central place or one format. The challenge is to find, consolidate and standardize the data. This is accomplished through data integration that allows for easier availability and access.

Next up is data quality. One way to improve data quality is through data preparation which includes cleansing. Data cleaning is ongoing and involves identifying and correcting or removing inaccurate, incomplete, irrelevant, duplicated, or improperly formatted data. While your data doesn’t have to be perfect to be analyzed, you should determine your organization’s standard for what is “good enough” to move forward.

3.   Asking the right questions.

Do you struggle with knowing where to start and what to measure?

Don’t collect data for the sake of collecting data. Metrics are only useful if they deliver actionable insights and drive your business outcomes. People Analytics is all about getting those big questions answered. Those questions begin with why and how and are specific to your business.

What are the issues plaguing the organization? Examples of the kind of questions you may want to be answered include:

How can we make our hiring process more efficient?

Why is turnover so high?

Are we maximizing our ROI on L&D?

These are questions that impact business performance and require decisive action. People analytics is a route to those answers, but only if you ask the right questions. The main goal is not to analyze data but to get answers to these questions to improve business performance.

4.   Data governance.

With great data comes great responsibility and great risk.

Having a practical framework is critical for any organization using people analytics as part of the decision-making process. Your governance framework contains guidelines to ensure proper use of your data, including policies on data integrity, security and privacy, access, and service. Add enforcement to that list.

You don’t want to be lax with governance. A weak framework leaves the organization vulnerable to data breaches that could hurt its reputation and bottom line and cost you employees’ trust. It also risks non-compliance with government or regulatory agencies.

Good data governance requires C-suite support and the appointment of data stewards and a data governance team.

It also calls for discernment in prioritization and application so that over-governance doesn’t make low-risk data harder to access.

A well-governed environment isn’t merely restrictive or defensive but empowers people by giving them the freedom and security to work with the data.

5.   Technology Tools

Decisions, decisions.

The broadening people analytics landscapes means there are many different options on the market. With any business decision, choosing the right technology tool is essential to ensure that it runs smoothly and drives vital outcomes for your business. In making a choice, you must keep your top priorities in mind. What are the key things that these tools should accomplish? 

There are many tools on the market to choose from, so it can get overwhelming. A technology consultancy like Pixentia can tailor people analytics solutions and support specifically to your needs.

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