Around two years ago, I wrote a Q&A on starting a career in people analytics. I was amazed by the response, and loved the conversations that followed with the people analytics community.
A lot has changed in these last two years, as the world continues to navigate COVID-19. Even in the last 6 months, the “Great Resignation” has left many companies gravitating more and more towards data-informed HR. As someone who’s been in this space for their entire career, I’m excited to see this explosive growth. As more companies build people analytics functions, I’ve been getting more and more questions about doing so. Not only am I getting questions from first-time people analytics founders, but from employers looking to build out that functionality.
Below is a Q&A I’ve created by leveraging conversations with peers, chats I’ve had with HR leaders, and my own experience building people analytics functions. This is intended to be a living document, so feel free to make suggestions or challenge anything I’ve said in the comments :D
This Q&A will focus on HR leaders as the intended reader. In the future, I might write another intended for first-time people analytics founders. Here’s a list of the questions, after which I'll go through each one.
- What are the benefits of investing in people analytics?
- What questions can people analytics functions help answer?
- What is the right size of a company to build a people analytics function?
- Are there ways of investing in people analytics prior to making the first hire?
- Where should a people analytics function sit?
- What should we look for in a people analytics founder?
- How should our company approach compensation for people analytics talent?
- At which point can we get into predictive people analytics?
1. Q: What are the benefits of investing in people analytics?
A: Essentially all verticals of modern companies have seen the value of data-informed business decisions, from Sales to Engineering, to Marketing. It allows us to check our assumptions, uncover patterns we would not have been able to see directly and hold ourselves accountable to our goals. Given that people of an organization are crucial to its success, applying the same discipline and technical savvy to that vertical is not a nice to have; it’s a given.
2. Q: What questions can people analytics functions help answer?
A: There are so many different flavors of business questions that a people analytics function can help answer, but here are a few common flavors of questions that come up:
- Leaders feel like attrition is on the upswing. Should we be concerned?
- If we keep on hiring and losing employees at this rate, will he hit our headcount targets by the end of the fiscal year?
- Employees are concerned that our referral process is hurting our goal to hire underrepresented talent. How can we look into this?
- We have a philosophy of paying for performance. Are we measuring up to that philosophy when we look at performance ratings and rewards?
- We’re trying out a new hybrid work model. How can we evaluate if the degree of collaboration has increased or decreased with this change?
3. Q: What is the right size of a company to build a people analytics function?
A: When I started my career, it was standard to make the first people analytics hire when a company reached around 1000 heads. Over time, combined with the Great Resignation, companies are investing in this space earlier and earlier. I think the average size these days is about 500 heads, but I’ve encountered an increasing number of companies starting to build at around 250, and even as low as 100. You should always consider your company’s priorities, but if you are starting your function above 1000 heads, you are probably already behind many of your peers (and competitors). When you start earlier, you have the distinct advantage of having a voice for people's data in terms of process, data hygiene, and systems as you grow. As anyone who’s gone through hypergrowth will know, it’s very difficult to work backward at larger companies where processes and systems are more set.
4. Q: Are there ways of investing in people analytics prior to making the first hire?
A: For sure! Sometimes companies are in a space where they aren’t quite ready to make their first hire, but they want to ensure they lay a solid foundation. There are a few key things companies in that situation can do.
- Document process, and data definitions as best as possible. Are recruiters using the same candidate source labels in the same way, or are you just assuming they are?
- Always ensure that the HR tools you are buying have good data practices. Could a people analytics hire access data tables regarding those tools? Do these tools have good APIs? Those are important criteria to evaluate
- Consider buying a people analytics in a box solution. You might continue with it after your first hire, you might not. Regardless, having a tool can help you get a preliminary handle on what your data look like, and give you insight into data integrity issues. One solution I’ve seen gaining a lot of momentum in this space is eqtble.
5. Q: Where should a people analytics function sit?
A: I’ve seen many different places people analytics functions sit, each with its own advantages and disadvantages
CHRO: Rolling directly into the CHRO is a common approach for a people analytics function. In this model analytics is a separate “pillar” of HR, that supports other functions like talent acquisition and business partners. It has the advantage of being embedded in the same function as one’s clients and gaining a strong understanding of the business processes that underlie people data. It can have disadvantages, however, in being isolated from other data functions and their best practices.
Centralized Data Science Function: I have also seen people analytics functions roll into centralized data science functions as a separate vertical. It has advantages in being able to leverage data science best practices and technical peers. It has disadvantages in being further from the generation of data (HR) and the key context that can provide insights.
I must mention that I have seen many companies, especially those at earlier stages, seek to put people analytics under the compensation (or another) function within HR. I think the mindset is that compensation leaders often tend to be more data-driven, but I am very critical of this model. When a people analytics function is buried under another function, its incentive structure is biased towards serving the needs of that function. At that point, I would argue this is not a people analytics function, but rather a function-specific analyst that will not have enough visibility into the holistic data landscape to provide outsized value.
6. Q: What should we look for in a people analytics founder?
A: There are various educational backgrounds and career paths I see people analytics founders coming from; questions 3, 5, and 6 on my last FAQ outline these well. When you are looking to make your first hire, though, I think there are a few additional considerations that can be extra helpful:
- Breadth. People analytics founders often need to move seamlessly from writing surveys to building data infrastructure, to acting as an internal consultants. Successful founders often have experience in various people analytics domains, usually by working as a manager at a larger company, or as a generalist at a smaller company.
- Autonomy. As noted above, I think people analytics functions are most effective when they are a self-managing pillar. As such, a people analytics leader should be comfortable functioning autonomously and in ambiguity, along with setting a long-term vision for the function. If a leader needs strong direction on what to work on, you will miss out on key-value they can provide your function that you might not be aware of.
- Respect for Data Privacy. It’s not the wild west of data anymore; employees care about how their data are used. And, according to GDPR and CCPA, they have a right to have a general sense of how their data will be treated. Anybody you hire should be able to articulate the situations where data privacy becomes especially relevant and impactful in people analytics, and how they approach those situations.
7. Q: How should our company approach compensation for people analytics talent?
A: Given that people analytics is a fairly new role, and isn’t appropriately represented in most compensation benchmarks, companies try their best to put people analytics into the “closest” job profile. This leads to a lot of inconsistency based on different assumptions though: company A may align to a data scientist profile, company B to a business analyst profile, and company C to an HR profile. What I will say is that, in a market that is demanding more and more folks in people analytics, professionals will go with companies that value the technical nature of their work. You can definitely find great talent at lower prices, but you definitely risk missing out on a good amount of talent when you align to lower-compensated job profiles.
8. Q: At which point can we get into predictive people analytics?
A: I understand that a lot of consultants, products, and thought leadership you see involve some amazing predictive analytics model. For example, many will have heard of the ability to predict attrition as a real use case in people analytics. While this is certainly true, it’s worth noting that accurate predictive analytics often requires a level of stability in your employee or candidate base that high-growth organizations rarely have. As I outline in this talk, I built an attrition prediction model with great performance but ended up having to take it off the shelf because my employer’s acquisition was announced, changing the reasons why people left the org. Predictive analytics certainly have value, but I think organizations should focus on the “first 80%” of data pipelines, dashboarding, and data integrity in the first few years of their people analytics journey.
The post "A Q&A on Starting a People Analytics Function for HR Leaders" was first published by Jared Valdron here https://www.linkedin.com/pulse/qa-starting-people-analytics-function-hr-leaders-jared-valdron/
About Jared Valdron
People Analytics @ GitHub | Data Communicator
View Jared Valdron's full profile