What a CFO's Office Taught Me About HR Data: Lessons for HR Analysts

Plenty of HR analysts have walked out of an operating review with a polished dashboard and a leadership team that did nothing with it. Courtney Brown learned a different way to work in a room few HR pros ever sit in: a CFO's office, where she built business cases with finance leaders before moving into HR through a master's in organizational development and organizational effectiveness. The habit she carried out of that room, asking what decision a number will drive before she presents it, separates the data that gets acted on from the data that gets ignored.

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Why do finance teams act on their numbers when HR teams struggle to?

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In finance, the decision comes first and the number follows. In a CFO's office, Courtney learned to tie every data point to a strategy and then to an action, and to guard its accuracy, because credibility is thin at the executive level and small errors are expensive. The same question opens every analysis she runs in HR: "you always have to ask what decision will this data drive specifically."

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How do you make people data land with a finance-minded leadership team?

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People data lands when it points to a decision and the story never outruns the facts. Executives act on information that explains the impact of a choice; a chart that only reports what already happened gets set aside. For Courtney, integrity is the price of being believed, and a story that bends the numbers costs more than it earns: "you still want to have factual information that's storytelling, or else you're not going to be credible."

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How do you design a survey people actually finish?

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A survey people finish starts from the decision and cuts every question that does not serve it. While recording, Courtney was working through her own company's 75-question annual survey, thorough at the start and rushing by the end. Past 100 questions, answer quality falls and some people skip the survey altogether. Her design rule is strict: "every question should tie back to that purpose."

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What makes employees respond honestly?

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Tell them why the survey exists, and show that past answers changed something. Response rates climb when people trust the exercise is not theater. Communicating the why upfront, Courtney says, is what earns real answers: "employees are more likely to respond when they believe that their input is actually going to lead to action."

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Where does data belong in the hiring life cycle?

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At every stage, with the metric chosen to fit the decision in front of you. Time to fill flags where a requisition has stalled, and hundreds of applicants on one opening can signal a job description that is too broad. Onboarding gaps can push a new hire's real start back by days, sometimes a full week. Retention checkpoints at 30, 60, and 90 days show whether the job matched what was promised. As Courtney puts it: "with the right data, you can help a hiring manager see where like bottlenecks are happening."

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What actually turns data into action?

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Transparency. Sharing what a number shows, and what will change because of it, is what moves a finding off the slide and into a decision. Courtney has watched it compound at every size of org she has worked in: "transparency, especially in the HR space, being as transparent as possible is so important. It's often what turns data into action." Openness builds trust, and trust builds the accountability that keeps the work honest.

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The through line is discipline, not dashboards. A people metric earns its place on the leadership agenda only once someone can name the decision it will change.

Courtney Brown (00:02): You always have to ask, what decision will this data drive? How important accuracy and credibility are, because even small errors can erode trust. Simplifying complex information and then having it connect to business impacts. Transparency, especially in the HR space, is so important. It's often what turns data into action. Designing and implementing and then gathering the data that come from those surveys. So I think the first step is to be crystal clear on what decision you're trying to make.

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Logan (00:41): I'm joined by Courtney Brown, an HR analyst with a finance team's perspective on HR, setting her apart and how she uses people data to drive action. Courtney started her career in a CFO's office, working directly with finance leaders, building business cases and learning firsthand how data drives strategic decisions. That experience gave her a lens that many HR teams are still trying to develop. The ability to connect people metrics to business outcomes in a way finance understands.

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In this episode, we talk about how Courtney uses that mindset to build better surveys that get answered, partnering with hiring managers to use data they can act on, and creating onboarding processes that boost productivity from day one. Let's dive in.

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Logan (01:25): Today we want to talk about how HR can drive execution with data. What I find interesting when I talk to people, looking at their backgrounds, where they get started in their careers, is always interesting. When I was coming out of school and was learning how to interview, my uncle would be like, you should tell people where you're born in the family because that matters. Like, being first born has certain traits versus last born.

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Careers are the same way. You have various stops along your path that, even if they aren't directly what you're doing now, they've influenced how you think about problems throughout. Because we're talking about HR and data, and HR isn't always the most data heavy function. Marketing's like that as well.

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Logan (02:15): But you took a pit stop in a CFO's office, which is where people very much struggle to communicate their initiatives ultimately in a business. And so I kind of wanted to start our conversation in how working for a finance office function made your mindset towards data and kind of helped shape the rest of the things that you did moving on.

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Courtney Brown (02:40): So this again was several years ago, but I think it prepared me for shifting my overall perspective on data. And I learned that you always have to ask what decision will this data drive specifically. You know, it's about how you can clearly connect that data to strategy and then to action.

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I think I also learned how important accuracy and credibility are, because even small errors can erode trust at that executive level, you know, at that level of leadership. And I kind of also came to appreciate the storytelling that comes with data.

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And the ability to make even the simplest pieces of data into something more complex, and communicate it in a way that I think helps to alignment and drive decision making for that level of executive leadership. So it was pretty insightful.

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And yeah, that's something I still kind of, with me. Even through I did a master's program in organizational development and organizational effectiveness, that's still kind of a key question that, you know, I kind of start with before analyzing any data points or just really getting into problem solving. It's like, what decision will this data drive, essentially? So that's kind of stuck with me.

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Logan (04:17): Yeah, the interesting thing on that is, it's not data for the sake of data. And so, like, in that office, I guess, I don't know, can you talk from the finance person's perspective on how they thought about data driving decisions?

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Courtney Brown (04:36): I think, you know, things like obvious things like revenue, right? Revenue and expenses, profitability, those types of things. I mean, that's kind of what the main focus was as far as what data points we were collecting. But I think really they cared deeply about forecasting, again, like accuracy. Even from something like how well budgets align with actual performance. Risk and compliance data also kind of sit high on that radar as well.

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But I think what really truly matters, like at the end of the day, was that the data is connecting within a cause and effect. And information that isn't just describing what's happening, but also helping explain the impact of decisions in the long run, and, like, where the business is heading as well.

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Logan (05:24): Yeah, that's a good call out. Now, one of the things that is interesting about data is that storytelling piece and how you communicate it. One of the interesting things about data and stats, and whatever you want to call it, is that if you're a good storyteller, you can basically make it tell any story you want. So did you come up with any good storytelling tips, how to talk about data in the realm of the business?

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Courtney Brown (05:53): I mean, like, in that time, or even just carrying forward throughout, yeah.

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Logan (05:57): Could be either. I mean, just generally, because the call out, learning that storytelling is such a key piece of data. I mean, have you been able to kind of hone those skills? Or there, like, things that you look at and say, yeah, this is how you should communicate this particular metric?

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Courtney Brown (06:15): Yeah, I mean, I think with that is the integrity of data, right? When you're storytelling, you still want to have factual information that's storytelling, or else you're not going to be credible, right? To those, especially, you know, those that are as important as, like, executive leaders and things like that. You really want to ensure that your data integrity is, like, first and foremost, I think.

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And again, that's like a principle that I just still think about even today in my career, as it shifted from finance into HR. And then, you know, I guess with that scope of executive leadership and working in that type of environment, anticipating the executive lens and always thinking a step ahead of what leaders are even caring about before they ask.

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Courtney Brown (07:09): You know, I think, again, even in my current role, I work in hiring, and that includes executive hiring as well. And that's something that I constantly strive to anticipate, again, from that executive lens. You just want to be reactive in that sense.

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And I guess, along also with storytelling, the importance of storytelling with data is just simplifying complex information and then having it connect to business impacts. That's really key. So I think, to wrap that up in a nutshell, discipline and accountability and just data integrity. You know, I think those are key pieces that I've carried with me through that role and then all the way up to present day as well.

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Logan (08:02): So, kind of continuing the theme of data a little bit. A lot of times in HR, we send out surveys, pulse surveys, but really, I always think of that as kind of the anecdotal data collection piece, where you're able to collect things in order to get a pulse on the business, to get a pulse on the workforce. And in our prep for this, you had mentioned that you had helped design one for the UC system. So I kind of wanted to dive in a little bit there about, what kind of insights did you get from that, of how to build effective survey systems that generate you the data that you want in order to get an understanding of the business?

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Courtney Brown (08:51): Yeah, that's a good question, and something that I really enjoy, building surveys. Again, that's another way to gather data. And it's a template of designing and implementing and then gathering the data that come from those surveys. So I think the first step is to be crystal clear on what decision you're trying to make with even implementing the survey, right? Even asking the questions. So every question should tie back to that purpose. What decision am I trying to make at the conclusion of this? I aim for clarity, and I try to avoid really vague wording, make it as specific as possible.

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So you can really balance out those quantitative questions with the open-ended ones, and those give more context, right? So that combination gives myself, but also leadership, I think that gives us both more of a clearer picture of the numbers and the narrative they need to then drive those decision-making areas at the conclusion of the survey. So keeping that kind of at the forefront is, I think, just most important. To make sure you're really upfront, you're getting the data that you need, right? So you have everything in front of you, as opposed to having to put out any type of follow-up, or having kind of diluted answers where you're not really sure where to go next, right? It's like, well, maybe I should have made the questions a little bit more concise and more clear so that my survey takers really can hone in on, just, like, again, the qualitative responses.

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Logan (10:29): Yeah. So we've hit this twice now, and it's doing and designing things with, what decisions are you going to make with whatever action that you're taking? And I think that's such a good theme to keep going through here. But so you mentioned potentially having to send follow-ups, and obviously that's not what we want to do. Do you have any tips for increasing response rates when designing surveys?

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Courtney Brown (10:55): Yeah, I think a big part of it, I mean, time is everything, right? And time is, no one has enough of it, frankly. And it's something that also embodies the amount of energy that people are going to put into their responses, right? If you're presenting someone with a hundred plus question survey, you're less likely to get really quality answers out of that, because they're going to just try to get through it as fast as they can, just to say maybe that they, right, or —

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Logan (11:30): I won't even take it.

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Courtney Brown (11:33): People don't even take it, exactly. And, you know, we actually right now at my company are going through our Your Voice annual survey, right? And unfortunately, it was one of those things where, I think for me, I take the time to fill out the open-ended, the free responses and things, but there's about 75 questions on this thing. I will admittedly say I spent the first half really giving thorough open-ended responses, and then towards the end, I was just answering and getting it through as quickly as I could. Because at that point, you're a little burnt out.

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Courtney Brown (12:13): You just really, I think in survey design, you want to respect people's time first and foremost. So that's always something I try to keep in mind, especially from an HR perspective, right? We want to be respectful of our employees. You know, if you want to drive engagement, I think that's kind of the key aspect of just being a human, right? Is everyone is allotted only a certain number of hours in a day, so just be respectful of that.

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And yeah, so that means just keeping it as concise, easy to understand, and relevant to the employee experience while formulating the survey. So, you know, with that, I already mentioned this, but just being trustworthy and driving in that trust aspect of, I think, delivering a survey that is authentically designed to really touch on areas that employees care about, frankly. And I can't think of a specific example of a question, I just did this Your Voice survey, but I think employees are more likely to respond when they believe that their input is actually going to lead to action.

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Courtney Brown (13:19): So making sure to communicate the why upfront. Why am I even completing this survey, right? What is the point, and where is this even going to go? Are they really going to listen to me? Where will there be any type of follow-up? Like, all of those questions, I think, just making your why clear from the very beginning really will drive those response rates. And, you know, in turn, I think just the willingness to even want to put their voice out there is much more likely.

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Logan (13:50): Yeah, I think that respecting time, I find it interesting you mentioned that you will take the time to respond to all of the surveys. And I have a similar thing in the marketing realm. Like, I have to be on social media, and it's like this karma thing. Like, I have to accept cookies and all these things that I use. And so it's like, if you're sending out surveys, you have to take all of the surveys.

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Courtney Brown (14:18): Absolutely. Yeah, it is a thing. It's so true.

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Logan (14:22): It is very much a thing. Surveys can be super effective. I mean, do you do pulse surveys at all, or are your surveys usually the ones that you're designing bigger, like quarterly or monthly or annual surveys? Both? Okay.

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Courtney Brown (14:37): Both. If we're going back to the specific ones that I was creating for the UC, it was mainly large scale, where our office was in charge of creating the generalized template for all of the UC campuses to utilize. So, and they could then take the general template and make it a little bit more specific to their exact campus's needs. As you can imagine, all UC campuses function a little bit differently. They're their own little governing bodies, and their employees have different needs across the state. So just coming up with that generalized template and then having them really make it their own.

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And then, yeah, it's been as large as that, to as scaled down to pulse check surveys, where you're just, even with my, because again, I just enjoyed doing surveys, I've in my current role as well have implemented some just for our immediate organization. So maybe about 80 people in that matter, right? So it depends. And I think still the main design and the main question remains, is this a good use of people's time? What is the why behind why I'm creating the survey? And really just making it up, up the forefront, to instill that level of trust to hopefully warrant more responses.

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You know, because I know a lot of times you get a survey and you're in box like, another one of these. Okay, well, we'll see. We'll see where my responses go for this one, right?

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Logan (16:25): Yeah, I mean, but surveys are a key piece to understanding the workforce, because you can have the hard data, like your turnover rates and headcount numbers and all of that, but you can't get a sentiment behind some of those numbers unless you have a survey. And so it's such an important piece, in order to be able to pair the hard data with some of the more anecdotal. So it's a good call out to spend time. And I've been at HR conferences, and I don't think you're alone. HR folks love surveys. And yeah, I've been next to survey companies and we'll get traffic because everyone wants to come see what's going on with the survey company.

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Courtney Brown (17:15): Oh yeah, absolutely. And what the new fun updates are, and upgrades and all those things. There's now, it's like all about AI companions and having AI create your surveys for you, right? But again, still wanting to instill that human element to what you're even asking your employees to respond to. So, yeah.

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Logan (17:37): And the AI questions may not be that good, you never know. It depends on how good the company who's selling its ChatGPT wrapper is for their AI surveys. But at any rate.

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Courtney Brown (17:46): That's true. Yeah, I would say it's kind of a good starting point, right? To get the juices flowing. And then you can use the information that AI is spitting out to formulate your own questions. Or, you know, specify, really, if it's like more generalized or broad questions, like, okay, well, my employees care about this, and kind of honing in and making it more specific. Using it as a tool, and not necessarily just letting AI put your survey together.

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Logan (18:16): Well, maybe we'll get there, but...

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Courtney Brown (18:18): Yes, I probably will someday.

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Logan (18:20): Now, I think when we were doing the prep for this, you had mentioned, kind of in the hiring, onboarding, recruiting space that you're doing stuff now, you had quite a few good examples of how you took data to drive decisions. And I think it was along the lines of helping hiring managers, or seeing what, like, hiring managers, I guess, their success rates. I don't know, maybe you can refresh me, and then we can tell the audience kind of how you used data in order to improve the holistic hiring process, recruiting all the way through onboarding.

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Courtney Brown (19:01): Yeah, to kind of generally see if your onboarding is going well, I guess, the whole process. Well, part of that, I think, again, we can kind of relate it back to just general feedback, whether that is from a survey or just elsewhere. In my current role, we do work directly with new hires that are being onboarded into our company. And so just their general, it sounds pretty simple, but their general feedback on their experience, I think, is very telling of whether your onboarding for your company is effective.

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Courtney Brown (19:42): You know, how quickly they can ramp up to productivity, as far as all those nuance-y onboarding tasks that need to be completed. Making sure that, first and foremost, your systems are working for them to be able to track those things. We do have an internal system that essentially captures their onboarding. It's like a checklist, essentially. And keeping them on track of that checklist, and then all the way up to day one, ensuring that they're able to get to that productivity level where they are successfully able to log into their laptop and log in for their new hire orientation and get connected with IT and all those things.

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If those aren't aligning, it could delay this new hire from really starting their new role for days. Sometimes even, I've seen, up to a week, a whole week later. And that's just not a good, optics wise. I mean, that's not a good look on the company, but it's also a terrible onboarding experience for the new hire as well. So just, how quickly they can ramp up to productivity, and then just aligning how they're feeling with their manager and their team. We could kind of get into retention, that's a whole other topic, I think, at like the 30, the 60, and the 90 day marks. I feel like that's a whole other conversation, but yeah, retention.

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Logan (21:14): A lot of people focused on that. I mean, that's a big focus of how good the onboarding is. And depending on where you're at, what type of company, what industry, that rate may fluctuate. And it costs real dollars if it's not good.

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Courtney Brown (21:31): Yeah, absolutely. You know, just ensuring really they are having that connection with their manager and their team, and their alignment with what they were hired on to do is still what their job is months later.

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You know, what's the old, like, you're looking at a job description, and within there it says other duties as assigned, right? Well, has this new hire, from day one through day 30 or 60 or 90, are they feeling like the role is what they signed up for, and that they feel like a valued part of the team and a part of the company, and in turn, that their role is what they envisioned, essentially? So that's kind of a key aspect.

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And that even goes back to, even from before the onboarding experience, the creation of the job requisitions, that you're putting valid job descriptions that are really aligning to the actual job. Because that does happen quite a bit, there's feedback we can receive that this job isn't really what I thought it was going to be, and this isn't what was in my job description. So all those little things. I feel like I could go on and on about how to know if onboarding is going well. There's a lot of signals. There's, like, data, I would say more qualitative data that you can gather from that, as opposed to quantitative.

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Logan (23:08): What kind of qualitative data do you look for? I guess two questions. What kind of qualitative data do you look for, and what kinds of signals do you get to kind of, I don't know, that might raise the red flags or the yellow flags, if you will, or just a flag.

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Courtney Brown (23:24): Yeah. Well, I guess, okay, so there are pieces of, like, quantitative data you can look at, you know, for hiring managers and things. Those could be anything from, like, time to fill metrics, right? How long it took from the creation of, like, the job requisition to the actual filling of the role. You know, what that looks like from a money and, like, a numbers perspective, right? That's like a business —

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Logan (23:53): So in that, what are you looking for in that? Like, what are indications, you're looking at time to fill with certain hiring managers?

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Courtney Brown (24:01): Um, you mean, like, how is that data gathered?

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Logan (24:06): Not gathered, but if you're using it as a signal, what are you thinking about when you're trying to use it to gauge whether things are going well, or the hiring manager might need some help?

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Courtney Brown (24:18): Yeah. I mean, we, on our side of things, I think partner with the hiring managers, and recruiters have a big hand in this, especially where the time to fill metrics are concerned, and making sure that that is aligned with what they want their outcome to be.

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And, I mean, there's a lot to that, I think. You know, working for a company, a large company that at times can have hundreds of applicants on any job requisition, right? Where do you kind of draw the line of, okay, we've got a really large applicant pool here, and maybe we should start really honing in. And there's obvious ways within an applicant tracking system to be able to sort through, or filter out, certain applicants that aren't even aligned or meeting what the requirements of the job are, right? But that's a huge part of it. I mean, having that in, like, a scalable process, to where you're, from the beginning, not overwhelming yourself with losing the purpose of the role, right? With —

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Logan (25:46): Yeah, so —

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Courtney Brown (25:47): Go ahead.

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Logan (25:48): Yeah, so it's just, a lot of it comes down to how you've partnered with the recruiters and the hiring manager, and then how big the applicant pool is. I mean, obviously a larger applicant pool is going to lengthen that, and you have to figure out how to move people fast enough through so they don't lose them, and all of that good stuff.

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Courtney Brown (26:05): Yeah. And I think with that too, just, like, being with this certain data, you know, with the right data, you can help a hiring manager see where, like, bottlenecks are happening. Whether a job description maybe is too specific, or maybe it's too broad, and that's affecting the amount of applications that you're receiving, whether it's not a lot or way too many, where people feel like, I qualify for this, right? Or the opposite of that, where applicants are looking at a job description and they're like, I'm definitely not qualified for this role.

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So really making sure that those job descriptions aren't, you know, they're just right. They're not too narrow, not too broad. And then to see where candidates are also maybe dropping out at certain stages of, like, the recruiting process, or the hiring process. And then that's really allowing the hiring manager to adjust, whether it's a job description, the job requirements, partnering with their recruiters more effectively, and then just planning for capacity better. You know, and that's really going to ultimately make the candidate experience and the hiring process that much more smooth and more successful. And that's just one little piece of it, right? That's just a time to fill metric. I mean, there's a lot of other things that you can look at within the onboarding, the hiring, and then onboarding process.

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Logan (27:26): You have all these different stages. And to your point, right at the start, what decision is the data going to drive? And really, I mean, time to fill might not be something to dive into deeper. Like, the 30 day retention might be the bigger deal, because once you get them over 30 days, that's where we're seeing the drop off. So, I mean, I asked the time to fill thing just out of the blue, but that may not be the metric that you need to index on. It might be somewhere else. And I think keeping Courtney's principle of what decision is this data going to drive is important at the heart of any of these metrics that you're looking at.

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Courtney Brown (28:10): Yeah, absolutely.

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Logan (28:11): Do you have any remaining tips for people in the recruiting, hiring, onboarding? What's the order that I should reference that in, recruiting, hiring, onboarding, or hiring? The journey.

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Courtney Brown (28:24): I think, yeah, recruiting, we call it the hiring life cycle. But yeah, it starts with —

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Logan (28:28): Iron life cycle, there you go.

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Courtney Brown (28:30): Recruiting, because you first need to have your, well, it starts with a need, right? A need to even put together a requisition and a job posting. And then, you know, the requisition, from there you're gathering applications, and that's still part of the recruiting process, as well as interview process. Once you identify your hire, you would create an offer and extend an offer, and that becomes the hiring process. And then onboarding is when that person accepts their offer, and from pre-onboarding to their actual start date, all part of the onboarding. So you listed it correctly: recruiting, hiring, onboarding.

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Logan (29:13): Okay, good. I didn't want that to be my big mistake for today. So, in the hiring lifecycle, any tips for HR folks that you would want to leave them with?

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Courtney Brown (29:22): Transparency. Especially in the HR space, being as transparent as possible is so important. It's often what turns data into action. But also, with transparency, you're able to build trust, which in turn builds accountability. And I think that for any part of HR that you're in, you know, HR is the people role, right? You're constantly, whether it's directly working with people or indirectly, you know. I kind of have had the opportunity to do both, where I've worked for smaller organizations where I am directly, one-on-one, working with employees, in more of a generalist role, where you're able to have those one-on-one conversations. Or, you know, as large scale as working for a company with over 200,000 employees, so you're indirectly still working with people.

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So, no matter what, I think transparency, again, will build the trust and the accountability. And whenever I know I have an opportunity to build it in a way that is letting people know that they're valued, I can, you know, I see you, I hear you. I think that's just what makes a big difference. And your impact is in HR employee, but just, you know, not even putting the human element into HR, but keeping it there. But just, it's key. That's what — but the key is the secret sauce.

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Logan (31:01): It is. Well, I want to thank you, Courtney, for taking the time to have a conversation and talk through this. And I'd say two of my biggest takeaways is, what decisions are you going to make before you take actions? Whether that's using data to make a decision, collecting data through a survey, and then transparency along the way. And how do you build trust with transparency? And the transparency is how you turn data into action. So I want to leave the audience with that. So, with that, where should the audience connect with you?

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Courtney Brown (31:35): I have a LinkedIn. Let's say LinkedIn.

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Logan (31:36): There we go. LinkedIn. Connect with Courtney on LinkedIn.

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Courtney Brown (31:41): Connect, Courtney Brown. You can find me, based here in good old Sacramento, California. And I am an HR analyst. Find me on there.

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Logan (31:53): Great. I will link your LinkedIn profile in the show notes. And again, Courtney, thank you for taking the time to chat with us today.

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Logan (32:02): Thank you for joining us for today's episode of Pulse, the podcast that has real conversations with HR leaders linking people to performance. HRBench is the people analytics platform that turns HR data into business strategy. It connects to all your tools: HRIS, ATS, payroll, surveys, whatever you're using. In just a few clicks, you get over 45 metrics instantly visualized in boardroom ready dashboards, benchmarked by industry and company size. Book a demo at HRBench.com, and we'll build you a custom benchmark report using your data.