People Analytics: 6 Best Practices for Successful Adoption

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Getting started with people analytics (PA) is one thing, but making sure the adoption goes smoothly is another. In this article, we look at recent developments in the people analytics space and discuss six best practices to ensure a successful adoption of PA in your organization. Here goes!

Content
Recent developments in people analytics
Getting started with people analytics
People analytics adoption: 6 best practices
Choosing software for people analytics

This article is a round-up of a great conversation I had with Lexy Martin during a recent episode of AIHR Live. If you rather watch the video, you can find the entire interview here:

 

Recent developments in People Analytics

LM: Let’s talk about value first and then about the enablement approaches I see organizations take. About 4 years ago, what I saw initially was that organizations were getting value in adopting a solution that was more cost-effective than perhaps building a data warehouse and enabling that for people analytics because it enabled them to scale their reporting and analytics staff and free them to go and do more strategic, advanced analytics activities over the years. 

One of the first areas where organizations were getting value was in HR itself; it became more effective and with the experience from that they turned to address business outcomes that were important to the C-level. There was this kind of journey to value from just adopting the technology to HR effectiveness to achieving business outcomes. 

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Over the last 4 years, I’ve seen an evolution, and now what I’m seeing is that there are these moments that matter that deliver value from people analytics and workforce planning across both the employee life cycle – where you are attracting, developing, and retaining employees – and also across key organizational effectiveness activities such as optimizing productivity, optimizing the structure of the organization, and optimizing planning itself.

Behind this value journey is an implicit trend of organizations moving towards enabling everyone with data to support their workforce decisions, whether that is on an organizational level with the analytics team doing brilliant data science or individual employees having analytics capability to support themselves. 

So, what I’ve seen is kind of a second surge of enablement practices. I’m calling that enablement 2.0. Initially, organizations may have started with giving capability to their analytics staff, their reporting staff, then to business leaders, to people managers, and to the HR community, to their HR leaders and HR Business Partners. What I’m seeing now though is that they’re starting to go deeper with more analytics topics. 

An example comes from the Merck group in Germany where they started out by enabling 3500 managers with a certain set of capabilities and now they’re giving them deeper capabilities providing more analytics topics. 

Organizations are working to provide value to employees with people analytics too. There is some brilliant work being done at Nestlé where they’re providing capabilities such as career pathing directly to the individual because managers can’t always be available for career coaching so why not use the rich data they have on their employees to show them what a potential career path is for each employee.  

In short, the main developments in people analytics over the past years have been:

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  • organizations’ journey to value with moments that matter
  • organizations try to enable everyone in the organization
  • organizations are now able to dig deeper into data and analytics

Getting started with people analytics

Before we get to the adoption of people analytics, there are some questions organizations need to ask themselves first.

LM: In a way, these are some pretty basic questions, such as: Why do it? What are our business challenges? Do we have key support?

Let’s start with why do it. Now, more than ever, organizations need people analytics to enable either a transformation of their business or to enable being able to do more with less. So the key question really is what are our business challenges for which we want to apply people analytis?

This is not just an HR challenge, it’s a business challenge; do we need to grow sales? Do we need to improve profitability? Are we able to sustain ourselves during the pandemic? Are we able to transform ourselves into a new future of work? Are we’re going to have to reskill our talent or acquire? Who should we retain from our top performers? How many scenario plans do we need to prepare for? 

In terms of key support, I think you should always have your CHRO at a minimum. Perhaps some key business leaders that are having to transform their business model need to be tagged as key stakeholders too, and do we have the support of some key HR functional leaders in the HR business partner community? Because they are often tasked with enabling their people managers with data to inform their decisions. 

People analytics adoption – 6 best practices

LM: Adoption is that you have people using it. There are choices to make about how or who you want to have adopting it.

We did a survey a couple of years ago where we looked at the leading practices of adoption and the more advanced organizations – advanced in terms of criteria like more people within the organization using analytics, more analytics topics, more data being integrated, more people analytics solutions – that were creating more value, had more wide-spread adoption. They had more managers using people analytics.

To enable that kind of adoption, there are some key practices:

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  • Start with a vision. There are some key practices to enable successful people analysis and it starts with a vision that we want to be evidence-based in our decision making or that we want to create a data-driven culture. For many of the organizations we are working with this is what it started with, we want to be data-driven and insight-led and that being part of their vision. 
  • Address key organizational strategies and issues. And know how the workforce contributes to those to guide your people analytics initiatives.
    Here, it’s going to be different for each organization, right now they may be focused on cost-control and productivity. But under a more positive environment this can be about how can we grow to meet customer demand and what are the skills that we need for that and what are the talent issues we’ll face. 
  • Achieve alignment across stakeholders. We most often see HR implementing people analytics and they need to get alignment between HR and finance on key data element definitions like head count or contractor management, or diversity.
    They also need to get alignment between HR and IT because the more successful people analytics initiatives that delivered most value to the organization, needed to tie workforce activities to financial business outcomes and IT typical owns those systems, hence the need for alignment.
  • Governance. We see a lot of organizations create some kind of governance committee to address the data element definitions. But there also is a reason to have governance on requirements that any people analytics initiative delivers some value to the organization, that it has some proposed return on investment.
    One of my favorite CHRO’s is Mark Berry at Indiana Packers in the US, a meat processing plant. He says that any effort, any solution must have a projected ROI in an associated matrix that shows that you’ve successfully achieved an ROI. The organizations that do that, and show that they succeeded with their people analytics initiative, continue to get investment for more advanced analytics capability. This is why I think it’s really important to have that governance around any initiative’s achieved ROI. 
  • Team structure. How are you going to structure your team?
  • Enabling adoption. How are you going about enabling adoption? Some organizations want to enable their HR community and their HR business partners who work with people leaders to enable them to deliver the insights from people analytics. By doing that, you kind of implicitly train their people leaders to use people analytics in their decision-making. 
    Other organizations, however, have got analytics capabilities throughout the organization so they actually enable for instance their financial analyst to also understand how to use people analytics or their engineering managers who already use analytics in some capacity to use analytics for the management of their people instead of just the production of their product so there are lots of different approaches to enabling adoption. 

When choosing PA software what do we need to keep in mind?

LM: There’s actually a good article by Erik van Vulpen with various HR analytics tools in it. It covers, Excel, Tableau, Power BI, etc. If you want to know about tools that article is a great resource. 

The most important question about tools, however, is what’s your ultimate goal? If you want to be evidence-based, and have a data-driven culture for everyone than you need a solution that can be deployed to everyone, that is easy to use, visually attractive, that guides the analysis from a key question to getting insights and being able to drill down the follow-on questions like do we have a turnover issue, where is it, what role is it with, is it in a particular region, etc. 

Or do you just want to empower your brilliant data scientist to address specific challenges and I think there are different tools for each of these extreme variations. The biggest question is: be clear on your ultimate goal. 

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