Poor Data Quality

One of the biggest hurdles you’ll encounter is a lack of high-quality data. A favorite saying among analysts is, “Garbage in, garbage out.” Simply put, if you use junk data to create your analytics reports, the results are going to be unreliable and, at times, misleading.

Before you start your program, it’s vital to assess the quality, accuracy, and sprawl of your data. Sprawl refers to where your data is stored and how spread out it is.

If you’ve already consolidated most employee information into a centralized human resources information system (HRIS), then you are in good shape. On the flip side, if workforce data is scattered across multiple applications and spreadsheets, you’ve got a lot of work to do.

Skills Gap

Unless your organization has already adopted other data analytics strategies, there’s a good chance that you will encounter skill gaps when launching your people analytics program. Even if the company has analysts on the payroll, these individuals may not have the bandwidth to adequately support your program.

Therefore, you’ll need to train your human resources personnel to assist with analytics. With that in mind, it’s important to get them involved in the software selection process early and often. Let the people who will be using the technology every day have a say in which platform you adopt. 

Also, remember that you don’t have to turn your entire team into analysts. Focus on upskilling a few key members of the staff who already have a mind for sorting through data.

Resistance to Change

As an HR leader, you know better than most that people just don’t like change, even if it is going to be good for them. With that in mind, you need to be proactive with your change management strategy.

Before you lay the framework for your people analytics program, bring your team up to speed. Let them know what you are planning, why, and how it will improve their day-to-day workflows.

Letting Perfect Become the Enemy of Good

Jess Milligan of Milwaukee Tool put it best: “Don’t be afraid to start. Don’t let perfect be the enemy of good and just get out there. You’ll learn by doing, and it’s never too late to start, and it’s never too early to start.”

Instead of waiting until your data is flawless and your analytics software is perfect, just get started. You are going to make some mistakes along the way, and that’s okay. What matters is that you learn and improve with each step.

Start With Clear Objectives

During our webinar, Milligan encouraged those new to data analytics to “start small.” Shane Noe, the VP of People Operations at ClickUp, built on her statements, stating, “I would advise against sharing analytics before you’re confident that it’s right because once you let the toothpaste out of the tub, it’s hard to put it back in.”

Instead, you should begin your journey by figuring out your “why” before you start presenting analytics data or throwing numbers around. What is your motivation for adopting people analytics technology and strategies? Once you’ve answered this question, set clear, realistic, and attainable objectives and fiercely pursue them. 

You’ll also need to identify key performance indicators (KPIs) and track them to monitor your progress toward your stated goals. Remember, each KPI only provides a small piece of the puzzle. Therefore, you must monitor multiple metrics for each objective to figure out if you are making progress and identify any roadblocks along the way. 

Invest in Data Quality and Integration

Next, ensure you’ve got lots of high-quality data from reliable sources across your organization. Invest in integration tools and systems to consolidate information from disparate sources, such as HRIS, performance management systems, and employee surveys. 

Clean and standardized data is essential for accurate analysis and meaningful insights. If necessary, enlist the services of a migration partner to help you make the jump from your disparate solutions to a consolidated platform. 

While it may be tempting to build your own custom solutions, Noe believes in a “buy first and build later” approach to people analytics. This methodology allows you to acquire a good set of analytics tools rather quickly while also enjoying the support of a development team.

Build Data Literacy

After you’ve got the right tools in place, you’ll need to empower the human resources department. This means investing in data literacy training. Data literacy refers to one’s ability to understand, interpret, and communicate with data effectively. It goes beyond simply reading information and also involves drawing meaningful insights from it.

Provide training and development opportunities to enhance staff members’ understanding of data analysis techniques, statistics concepts, and visualization tools. Encourage them to be curious, ask questions, and use the new technologies to uncover underlying causes of business challenges. 

An empowered workforce is your greatest asset for maintaining data literacy and integrity. As Noe put it, “Data integrity stems from behavior, and it’s really about training and giving recruiters and HR folks the tools to monitor their own data integrity through reporting.”

Start Small and Scale

There’s no need to launch an organization-wide people analytics program on day one, especially if the company is very large. Instead, embrace the concept of starting small and creating subsequent iterations as you progress. 

Identify a few areas of significant need and consolidate your resources toward solving that problem. For instance, you could launch your people analytics pilot program in the department that has faced the greatest attrition over the last 12 months. 

After you’ve proven your concept, explore ways to scale. If you drove down recruiting costs, improved retention, and reduced the time-to-hire, present your results to the executive team. Showing that your program can be successful can get them on board and help you acquire the resources necessary to expand into additional departments.

Be Willing to Learn and Improve

Recognize that implementing people analytics is a journey — sometimes a long one. It’s okay to embrace imperfection along the way. Learn from failures and setbacks and use them as opportunities for growth and improvement.

Encourage a culture of experimentation and innovation where your team feels encouraged to take calculated risks and explore new approaches. By embracing imperfection and learning through the process, you can adapt and evolve your analytics initiatives to drive greater value and impact over time.