5 Steps to Prepare Your Organisation for People Analytics

If you're preparing for people analytics, there’s a lot to do before you hire that first data scientist. To build the right foundation for success, there are five important steps you should follow that don’t even involve data, insights, or statistics.

Following these steps will help you establish and support an efficient and impactful people analytics practice at your organisation.

1. Find your why

Understanding why you're pursuing people analytics is vital to your journey. This not only means identifying the specific business needs that would benefit from a better understanding, deeper insights, or more precise analysis of your workforce, but also exploring the underlying reasons behind those needs. You could start by asking questions like:

• What are the biggest challenges or pain points we're facing as an organisation?
• What are the key areas where we could improve our workforce, and how would we measure success?
• What are the most critical business decisions we need to make, and what do I need to know to help us make them more effectively?
• What are the specific gaps in our knowledge that we need to fill in order to make better decisions?

Without taking the time to find the why for your organisation, you risk getting lost or going off course before you even begin. By finding your why early and holding onto it through the process, this will keep you focused throughout your people analytics journey.

2. Look upstream

When starting your people analytics journey, it’s important to remember that the data you’ve generated is only as good as your processes and technology. There’s a flow we like to think about from process to tech to data to analytics. When people analytics teams run into challenges, there’s likely an upstream challenge in one of these steps to address.

Begin by examining your processes. Technology is only as good as the process it’s automating, so if your processes are poorly designed and documented, your technology is unlikely to be implemented correctly. Technology should reflect how you want your business to run. If it doesn’t, you’ll likely end up with incomplete or incorrect data flowing out of the technology — making it difficult or impossible for people analytics teams to create value.This is not to say “don’t start on people analytics until the rest is done”. People analytics teams can absolutely provide great value, and some of the best teams out there are scrappy with what they have on hand. This is more of an acknowledgement of the flow and a callout that if you want long-term success of your people analytics team and to unlock that next level of value, you’ll have to address these upstream challenges. A strong people analytics leader will also be able to help you identify and navigate these challenges upstream.

So begin by ensuring that your processes are well-designed and documented. Next, double check on your technology implementation and ensure that it matches your processes. Finally, check in on the data. The data ultimately doesn’t lie, so it will tell you if the processes and tech are clean. Doing so will ensure that data flows smoothly and accurately from the technology preparing you for analytics.

3. Address data management

Another early focus for starting down the path of people analytics is data management. Without data, there’s not much for people analytics teams to do. It’s the oil to the people analytics engine. We’ve seen a number of teams get started, but then plateau around a lack of good data. At times the resources to fix data problems sit outside of HR, which makes it all the more important to navigate and commit that resource request up front when pursuing people analytics.

Making sure your data is accessible is critical, but raw data extraction is also only the beginning. A robust workforce-specific data model, proper data architecture blending your different systems data, and HR-led workforce data privacy and workforce data governance are also part of your people analytics foundation. This may require marshalling what are typically scarce internal resources, capabilities, and priorities from IT or data engineering teams to ensure that your data is clean, systematically organised, and readily analysable.

Or you can save those internal resources by working with people analytics platforms like One Model. We were founded to make this upstream challenge easier. We provide named data engineering resources, have experience developing business-specific workforce data models, and provide the data foundation that people analytics teams need to thrive.

If you skip this step, you may experience the following problems:

• Missing data: Without the right data management structure in place, you may find it difficult to extract the data you need for a given project. This can lead to incomplete or incorrect data and difficult analysis.
• Slow data: Improper data management can leave you with only monthly (or quarterly!) snapshots and that pace just doesn’t reflect how fast your business moves — let alone back-dated changes, which are frequently found in HR.
• Inability to build predictive models: Data management is critical to building predictive models. To develop predictive models, you need to extract data in a very specific way (e.g. time-stamped changes). It’ll be difficult or even impossible to build accurate and effective models without this proper data management.

By addressing data management early on in your people analytics journey, you can avoid these symptoms and ensure that your people analytics initiatives are successful. To learn more, here are five tips for getting HR data extraction right.

4. Set the tone

Setting the tone at the top is crucial for demonstrating that data-driven decision making is the way forward. This involves garnering support from your organisation's senior leaders, as well as regular reminders, activities, and actions from the CHRO or HR head.

If you’re in a leadership position, setting the standard that data is required for new projects and investment decisions goes a long way. Cultivating a data-minded culture will trickle down from the top, setting a precedent for the entire organisation. Without this high-level endorsement and sustained backing, making significant strides in people analytics can prove challenging.

5. Find help

Consider engaging with a seasoned people analytics leader either full-time or as a consultant to spearhead your people analytics initiatives and education within your function. Experienced people analytics leaders, with their unique combination of data analysis skills, HR orientation, ethical understanding, and team management expertise, can provide invaluable guidance. They’ll work to ensure alignment between your analytics efforts and broader business objectives.

Remember to also tap into the people analytics community. This strong and enthusiastic network can provide invaluable support. Engage with professionals on LinkedIn, ask questions, and use the expertise of vendors in the space. The team here at One Model is always willing to connect and assist at every stage of your people analytics journey.

New to people analytics or ready to enhance your existing program?

Either way, our eBook People Analytics 101 covers everything you need to know about establishing a strong people analytics foundation for smarter HR strategies and meaningful change across your organisation.