Data Over Dogma: Using Employee Data to Make Better Decisions

Date: Wednesday, November 16, 2022

Time: 1:00pm Eastern / 10:00 am Pacific

Presenters: Matthew Wride, President; Christian Nielson, Chief Revenue Officer

Cost: Free

Transcript

Matt Wride | 00:01 

Hey, Christian.  

Christian Nielsen | 00:01 

Yes.  

Matt Wride | 00:03 

Did you prepare any good jokes? ’cause I teased my invite on LinkedIn. I said that your true calling was standup com comedy. Did you, uh, prepare anything for our good, uh, our good, uh, audience today or not? I 

Christian Nielsen | 00:16 

Have only prepared disappointment in that regard. <laugh>, I, I, uh, I heard a rumor that you, you said that, and I, I should have probably taken, taken the cue, but 

Matt Wride | 00:25 

You should have at least got some material ready to go for a, a, an opening monologue to give these good folks something to, to listen to. 

Christian Nielsen | 00:34 

Well, that now our team, our, our participants now can realize that if, if there’s anything entertaining, it was not premeditated, it was all, 

Matt Wride | 00:44 

We’re also gonna start sit hearing that ding, ding, ding as everybody exits. You know, when they realize that, yeah. That the show is not what we promised. 

Christian Nielsen | 00:53 

I do have a, a dad joke alert that’s supposed to coach me back into safe territory 

Matt Wride | 01:00 

<laugh>. 

Christian Nielsen | 01:02 

Alright, I think we’ve got, we’ve got a a, a group here. We’ll have, I’m sure, a few folks joining. But we, we wanna be respectful of everyone’s time and, and, uh, get started. Um, my name is Christian Nielsen. I’m part of the decision wise leadership team and also an organizational development consultant. I’m joined by decision wise, president Matt Ride. 

Matt Wride | 01:24 

Uh, welcome or welcome to our audience, and it’s great to be with you, Christian. Yeah, 

Christian Nielsen | 01:28 

We, this is something Matt and I are, are very passionate about. We’re excited to dive in here. And spoiler alert, I probably have too many slides for what we’re, we’re going to talk about. So there might be a few that we fast forward to, but we’ll keep an eye on that chat, um, function. So please, if you’ve got questions, comments, um, feel free to to, to put those in the chat and we’ll, we’ll make sure we’re, um, uh, responding there. All right. So, uh, our topic today, using data to improve the employee experience, we’ve played with a few different topics, <laugh> for today, data over dogma. Um, but using data to make better decisions is really what we’re, we’re talking about today. And especially as those decisions impact the employee experience, which is what we, at decision wise are very, very passionate about. So, we’ve got some interesting content, some models and frameworks. 

Christian Nielsen | 02:18 

I think that it’ll be useful for our, our audience. Things that have really helped us as we’ve worked with our clients to understand and improve their employee experience, but also how to bring data, uh, to the forefront and to, to, uh, for them to use in the management of their business, management of their employee experience. So, I’ve got some quotes just to prime, prime the conversation to kind of warm us up. Uh, where there’s data smoke, there is business fire. I like that quote a lot. Uh, I tried to grab some obscure ones, mostly just to surprise Matt with quotes that maybe he hasn’t heard, but he’s probably heard some of these. Uh, but I do like that, uh, anything that gives us an advanced warning of potential problems is of immense value to our org. And so we want to, to make sure we’re utilizing that. Uh, most of the world will make decisions by either guessing or using their gut. They will either be lucky or wrong. Um, many of us, myself included, many times have been just lucky. And it looks like I’m smart after the fact, uh, if I’ve, if I’ve inadvertently made the right decision. But data can help us take luck outta the equation. 

Matt Wride | 03:23 

And that’s what we mean by dogma. Sometimes we have dogma, which can be great, you know, principles that are proven to be reliable in the past. We’re not throwing those out, but sometimes we just do things because that’s the way we’ve always done them. And that is a form of using your gut in a way. It’s not evidence-based, um, in ev in medicine, and particularly we try to make evidence-based decisions, and that principle should apply in management that we make, that we use to the extent possible evidence to try or data to try to minimize risk. So, uh, I, that’s, that’s what we’re, we’re driving at today, is even in, in managing people. It’s not about the tricks or tips that you’ve heard. It’s about you. You can approach it from a, from a data-driven mindset. 

Christian Nielsen | 04:11 

I love that. I love that. Uh, let’s get a few more. I am, uh, I may have put too many quotes in here. Uh, in a world of more data, the companies with more data literate people are the ones that are going to win. And that’s partly what we’re here to talk about. How can we build more literacy within data, for data for ourselves and also within our organization, so that we’re, we’re using this. In fact, in a moment, we’ll talk about not only routing, uh, the right data to the right people, uh, but I might even add, after you’ve routed the data to the right people, you’ve got to remind them that they have it. Because I think a lot of times we forget, we have this data in our, in our, at our disposal to help us make better decisions. And then I think the last quote for a moment, uh, from Brene Brown, maybe data, maybe stories are just data with a soul. I, I like that the power of, um, using data in, in our decision making, a lot of times it, it requires we weaving it into a story or understanding the story behind the data or deriving the story from the data. But I do like this quote. So there’s a, there’s 

Matt Wride | 05:12 

A way of thinking about it called data journalism that if we think of us as data journalists, we use the data to then compose the story. So I like sometimes reminding everyone to think about, sometimes it’s not data exploration, it’s not data and ana analysts analytics per se. At the end of the day, it’s data journalism telling the compelling story. Because as humans, we change and connect with stories. We change because of and connect with stories. So 

Christian Nielsen | 05:40 

Interesting and, and not planned. And also hashtag not sponsored it, just as you said that the, the book on my mm-Hmm, <affirmative>, uh, my table is data story. So something we care a lot about. And also, you know, data just that just sits there that isn’t compelling, that doesn’t add up to a compelling story, uh, doesn’t really serve us. So let’s, uh, let’s go further. Um, those of you who’ve been on these webinars before, uh, these next slides might be familiar, but it’s helpful just to set the ground, uh, the, the groundwork so that we’re all kind of speaking, uh, about the same, uh, thing. Here. We’d like to just kinda introduce some definitions. Let’s talk culture, employee experience, and employee engagement, because it helps if we’re all speaking the same language on this. So culture, um, a a robust definition of this, or a longer definition would be a set of values, norms, guiding beliefs and understandings that is shared by members of an organization and is taught to new members as a way to feel, think, and behave. 

Christian Nielsen | 06:36 

It’s the everything about the organization interlocks to form the culture, not only to form it, but to reinforce it, which is why culture can be difficult to change. Um, but I love this definition, Matt, and I think you helped shape this, that, that it, I like that it’s stresses that it’s taught to new members as a way to think, feel, and behave. And it’s kind of the shorthand for our, our definition of culture is the way we do things around here. Mm-Hmm. Um, when you join an organization very quickly, you start to pick up on the way we do things around here. Example, I, I use, I, I one time, uh, previously worked in healthcare settings. Very quickly I learned which meetings you start to wear ties to just by looking around, am I the only one not wearing a tie? Um, it seems like another, uh, another age when I was wearing a tie. 

Christian Nielsen | 07:22 

But, um, the way we do things right here, so that, that’s culture. Um, you notice what, we have a world in this, this little icon here. If we add people to that world we’ve created to that the way we do things around here, they’re going to experience that world. That’s what we’re talking about. The employee experience, the sum of perceptions employees have about their interactions with the organization in which they work, or how we experience the culture. Once we add people, uh, that their experience with that culture, or the way we do things around here, um, adds up to their employee experience. And that’s where, uh, we, it’s nice to make the distinction between culture and employee experience, uh, because, because it really opens up where we can have an impact, where we can take action. 

Matt Wride | 08:06 

Well, not, not everybody, um, experiences. The culture embraces it, um, thrives in it. So the same way, and when we talk about experience, we’re acknowledging those differences and telling leaders, you’ve gotta be worried about the experience. Not only what it is about what it’s like at your organization, but then how, how does that fit to each of the people that you manage and lead? That’s really where the why, the why it’s important to make the distinction between experience and culture. 

Christian Nielsen | 08:36 

I love that. I love that. And then the last of our definitions, I, I gave a, um, kind of a presentation on a similar topic last week. And I, I made the joke of, what if my whole presentation was just glossary? What if this whole webinar was just definitions? Uh, it is not, this is the last one. Uh, employee engagement, uh, an emotional state where we feel passionate, energetic, and committed to our work, uh, toward our work internally, fully invest our best selves in the work that we do. And this is, in many ways, a response to the employee experience. In fact, I’m gonna speak about kind of that relationship period a moment. But it’s based on, uh, uh, what I bring to the, the work, my own background, my own experiences, my values, what, what I’m looking for out of a workplace experience, when that meets the experience that the organization is providing, that determines the level I’m going to engage, how much I choose to bring of my best self to that role. 

Christian Nielsen | 09:33 

And our, our response there. So the, these three things, we didn’t want just to define them, but we also wanted to show the, the inner linkages here, that between the, between these three, that the cultures, definitely the culture informs the employee experience, which dictates, uh, how much people are going to engage, um, in, in the work experience. Um, and this is, uh, an important truth that I’ve learned in doing this work. And that is, you can’t build employee engagement, not directly. I, I never paused too long there, because I didn’t want you to feel like there’s no hope. And also, most of my, the last 10 years of my work experience has been spent trying to improve employee engagement. It can be done, but it’s important to recognize that you’re, you’re not improving engagement because people get to choose if they engage, you’re in, in, you’re strengthening the invitation to engage by building a stronger employee experience. 

Christian Nielsen | 10:26 

So we’re gonna be talking about data, but a lot of it’s gonna be steered around two questions. What experience are we creating for our employees? And is it the right experience? And we wanna talk about how we use data to answer both those questions, but we also wanna use how, or discuss how we use data to just to make better decisions in general, and to use those, um, the data that we have to not just go by gut so we can, we can use some, um, take some of the risk out of our, our decisions. 

Christian Nielsen | 10:58 

So a, a few more concepts that are helpful as we start to dissect what experience are we creating, and is it the right one? You know, that that definition of employee experience talked about the sum of perceptions. Well, a lot of what adds up to our employee experience are these moments of truth. And we like to use these, these concepts as Kronos and Kairos. Again, we have introduced these on other webinars, but I think it bears repeating and also setss the stage for where we’re headed. But Kronos and Cairos, there are two terms from ancient Greece that were used to, to talk about time. Now, Kronos refers to chronological time. These, um, time, these moments that can be planned, uh, predetermined points in time. So chron, chronological time, seconds, minutes, hours, the things that we can understand and predict. And we use that to talk about the employee experience, these planned moments, uh, the lifecycle moments. You know, we know what someone’s going to be hired. We know they’re eventually gonna leave our organization. And in between there, there are some things that we can expect to happen. We expect an onboarding experience. We expect different training activities, anniversaries, performance reviews, promotions. And these are important because if we can expect them, we can study them, we can plan for them, we can script the experience we want to create in those moments. Yeah. And that’s an important part of employee experience. 

Matt Wride | 12:18 

And as we think about data, we’re, we’ve gotten much better over the last four years or so in grabbing data from these kronos moments, from onboarding exits. And, and we’re using those. And we, and what we need to do is get that information back to operational leaders faster, uh, but probably more curate it better, get it more organized, and get it back to our operational leaders so they can do something with it. Um, but, uh, yeah, uh, it’s certainly, I agree. The great thing about differentiating between Kronos and Chiros, which we’ll get to, is it allows us to match our data to the, to the events that we care about. It’s, it gives us a structure as we think about gathering data 

Christian Nielsen | 13:01 

And, uh, excellent points. And another key consideration is when we’re trying to understand employee experience or gather employee feedback, it’s different than customer data. Customer data. You can look at different things in the way they’re interacting with your website or your products or transactions that cash registers and, and service points and things like that. Um, customer experience, uh, or excuse me, employee experience data. We wanna be very careful about how we’re tapping into the, their feedback at key moments that don’t seem cumbersome Mm-hmm. That don’t disrupt the flow of work too much. And these Kronos moments are logical points to, to ask, how was this? What did that feel like? And, and, and ask some really nice, uh, carefully curated, uh, survey items there. Um, Kai, uh, Kairos. But before we get into Kairos, we wanna talk about this concept of vuca. Vuca of, of course is Spanish for cow. 

Christian Nielsen | 13:52 

Just kidding, A joke didn’t play last time, and I still said it again. Yeah, it didn’t work. That is vaca. VUCA is, uh, volatility, uncertainty, complexity, and ambiguity. So the, this is why we can’t only rely on Kronos, we, because there are things we can’t plan on. I guarantee whoever was, um, in charge of trains this day wasn’t planning on this happening, uh, out, out the, you know, a second story window. Um, but it’s important to recognize and appreciate and just own that there are things that are gonna happen that we can’t plan on. For example, in 2018, I didn’t have a lot of clients talking about a mass and immediate move to remote work, but boy, that changed as, as we progressed a couple years later. And, and the pan, the pandemic happened. There are things that aren’t in our control to script, plan out and, uh, kind of legislate the experience we want to create for people. 

Christian Nielsen | 14:47 

Um, and that’s okay. But we need to recognize that that creates kind of these other moments, these kairos moments, the unplanned moments. And this, this term comes from the concept of the right moment. Uh, and it’s more focused on how we get it in these, these unscripted moments, or these unplanned moments and moments of truth that are inherently unpredictable. And I love this part, tend to reveal the underlying values and culture of the organization. If you can’t script it, if it’s not a, a very deliberate, uh, you know, such as an onboarding exercise or checklist that you’re, you’re implementing, if you can’t script a moment, you better hope that you’ve got your, your values and your culture dialed in so that we get it right. And here’s what that looks like. It’s, uh, this is a very scientific line that our colleague Dave Long drew and we’ve been using for a while. 

Christian Nielsen | 15:35 

Um, but these are just examples of, um, kairos moments, mistakes, workplace conflict, lifestyle challenges or, or changes or, uh, failures, personal issues, you know, personal health crises, whether it’s you or a family member, if that takes over and suddenly one day you find out someone in your family has a terminal illness, you have to show up to work the next day. You know, what’s your supervisor going to say to you? How do your coworkers treat you? Um, how does that, you know, where do you maybe need to be flexible with some of the benefits in the organization to allow for some humanity when someone’s going through some, some crisis? And does your culture help fill in the gap so that people know how to act when, when you’re going off road here? 

Matt Wride | 16:21 

And you would think based on that, that graphic in front of you, that you can’t measure that. You can’t measure the messiness. But the reality is, we can, through, we see it as we, as we do poll surveys. We, we gather information that tells us trends. But a really important way that we measure this, this sort of, uh, messy point, is how well are our leaders, uh, serving the needs of their teams through, for example, 360 data that we bring in that can tell us leadership effectiveness. And yeah. So it’s not like we can’t measure this too. And in fact, we do have ways and, and tools that do that. And so you are, you, you need to think about both the, the plan moments and the unplanned moments, and realize that both can be effectively measured. 

Christian Nielsen | 17:06 

Love that. And, and going back to our two big questions. What experience are we creating? And is it the right one, looking at your Kronos moments and also looking for evidence that you’re getting it right in the kairos moments, uh, when you know if these things are happening or when they’re happening. And obviously, this is not a com exhaustive list. Well, 

Matt Wride | 17:25 

A a nice example is exit interviews. If you’ve got good exit interviews, you’re gonna find a few of these where you’re gonna learn that this wasn’t handled really well, that there was just a blow up. And you can gather enough of those to see trends. Yeah. That’s the power of data 

Christian Nielsen | 17:40 

E Exactly right. Exactly right. So groundwork laid. Uh, we wanna talk a little bit about diving more, uh, purely in on data and how to think about data and, and, and start to deploying that in your organization, um, for, especially on the, the, the people side. So I wanna break this part of the conversation into two components. One, I I have this concept around going deep with employee data, pulling experience data. If you’ve got the resources and the political will inside the organization to do it, there’s some amazing things that are possible if you can build your own data science team around your, your people experience. Now that, I also wanted to recognize that that’s not an option for most organizations. Very few of our clients can, can go all the way with that. Uh, but that’s not a reason not to, to go down the path of using data for shaping the employee experience. 

Christian Nielsen | 18:32 

We can get a lot of the values with some simplified metrics and some, so I wanna spend, uh, some time on employee experience data for the rest of us. So we’ll go deep and then we’ll go, uh, kind of more broad. So going deep, uh, this next slide shouldn’t be too big of a surprise. If you wanna go deep with employee experience data, you are going to need some data. Spoiler alert. So, and there’s different ways to think of this. I borrowed this framework from a, another organization that wasn’t applying it to people analytics, but I think it, it painted this part of the conversation really well. If we have, we wanna talk about, well, how much data are we going to need? Well, it depends on what you wanna accomplish. If you don’t want any analytics, then you don’t need much data. Um, and everything can be a fun surprise for you. 

Christian Nielsen | 19:18 

Uh, you don’t need much data. Now, that’s not most of us. At a minimum, we wanna understand what’s happening at our organization. You know, an example, I use October turnover. Was it higher or lower than September? What are we seeing? Are we losing people or some other metric? But we need some data. If we want some de descriptive analytics around what happened, if we wanna go a little further and understand why it happened, we need more data. If we wanna get into diagnostic, not only why, what, how turnover was in October, but why did people leave? What changed? What, what is influencing, uh, departure there? And if we wanna go further predictive analytics, well, what’s gonna happen in December? Uh, what will happen? Uh, can we predict you’re gonna need more data to get to that level? And then if we want to, uh, be more influential and have more causative or causal relationships and understanding and in insights, uh, around prescriptive analytics, how to make something happen, we need, uh, a bit more data. 

Matt Wride | 20:22 

The, the last one, prescriptive analytics is a really good example where we, we, we finally get to the point where we can measure fit. And I’m not talking about cultural fit, which is just a question of, Hey, is this a cool person that I’d like to get a beer with? Right? I’m talking about fit, where their skillset, um, maybe what they bring to the table is going to align with, um, that their, not just the org, but even to the team level. And, um, with analytics, we can get better at matching, um, people to environments. Um, yeah, not there yet. And that, that’s well in the future, but we we’re starting that work now. 

Christian Nielsen | 21:04 

I love that. Yeah. There’s some exciting things on the horizon, especially as, um, some of the tools that are more advanced become very accessible to even very small orgs. Some machine learning AI and, and some interesting things are, are becoming, uh, uh, available and, and much easier to implement, which is, um, scary and exciting, uh, <laugh> depending on how, how those tools are used. Um, but years ago when our clients shifted from just wanting survey data to wanting more advanced people analytics, I, I realized that I needed a better way to understand and categorized data so that I could a, a better framework for thinking about, okay, well, what data’s out there, how do I use it? How do I think about it? And so we created this simple model around people, analytics, uh, categories. So there’s, there’s a few here. Uh, the first one we’ll talk about is demographic data. 

Christian Nielsen | 22:01 

And this is data that describes your employee population. And you’ve got this already as to certain extents and different levels of completeness in your HRIS. You’ve got, you know, if you’ve got birthdate, you know, age, if you’ve got higher date, you know, tenure, uh, you probably have data on, on position, or maybe even time in position, which is even more useful. Um, ethnicity, gender, educational background. You might have manager, non-manager, uh, union, non-union, anything you’re tracking, um, exempt, non-exempt. Um, anything you’re tracking that describes your employee population, these characteristics. Um, and, and a lot of this data, by the way, is easiest to, to capture when you hire someone. Um, but it can also be updated, uh, through, you know, follow up exercises. A lot of our clients, it’s been really interesting is, so DEI and, and, and diversity equity inclusion efforts have always been a corp component of our assessment instruments and our consulting, uh, approach. 

Christian Nielsen | 23:02 

But they really came to the forefront in the last couple of years is more and more organizations realized that it was an important part of the conversation, and they needed to, uh, be more informed. And so a lot of our clients, if they didn’t have ethnicity data, for example, they had to go back to their employee population and, and try to capture that. And it’s much cleaner to get as you onboard or bring people in. Sometimes it’s also interesting if, if you have m and a activity, a company comes in, they might have been tracking different demographics and some merged data sets can be, uh, uh, a little bit requires some, some thought and effort. 

Matt Wride | 23:35 

A lot of times, because this, this data is actually somewhat readily accessible. You can go to an H-R-R-I-S system, it feels like this work is kind of done, or, but the reality is, is we’re not doing as much as we could. And, and there’s a lot of room for growth just in this area. Um, I don’t think we’re doing a good enough, um, getting top, top leaders seen trends as far as ages and tenure, I think who we promote and how we promote them, and at what times we promote them. All of that can come from demographic data. Um, I’m not sure most organizations are, are, are really, and so while it fe and let me finish that thought, I don’t think they’re doing what they can with it. Yeah. And so while it feels like we kind of have this under control, well, I know what that is and I know where to find it. 

Matt Wride | 24:23 

That’s the not the same thing as actually actively using it and routing it and curating it and getting it to the right people. Um, we know that our senior leaders actually don’t have a very good feel for how the, how the organizations tenure and age stack up and how that may have changed over the last two to three years as we visit with clients. Christian, we know they’re not seeing that and may be obvious to people in HR or HR business partners, but it’s not, and it needs to get, it needs to get, um, consolidated and, and distributed more. So just something to think about is this is not just a Passover or flyover demographic. It’s it, or, or data point. It’s something you gotta work on. Yeah, 

Christian Nielsen | 25:06 

It’s a good point. And, and, and I, I have been guilty of saying, oh yeah, we got that. Let’s move on. And there’s, there’s more exciting data to be had, but there’s some really useful low hanging fruit here. And, and the more of this you have it, it magnifies the power of these other data sets I’m about to describe. So for example, turnover. Well, if you can describe and, and recognize population trends and who’s leaving, that’s much better than just knowing how many people have left. Is it certain ages? You know, are we seeing gender patterns in our, our departure or some other factor? So it, the demographic data really amplifies and magnifies the power of all these, these other data sets. And, and the first one is especially where, um, Matt and I live with employee experience data. And this is around those Kronos and Kyro moments, but also the employee experience at large. 

Christian Nielsen | 25:58 

You know, what are the perceptions, attitudes, and beliefs of employees? How are they experiencing the culture? And we’re really trying to, to find those natural points to tap in, understand their experience, catalog that ca and then marry that with demographic data so that it’s, um, under, you know, can provide some insight and, and, um, uh, value. Some examples of this are gonna be onboarding exit anniversary survey results. Um, you know, tapping into those key moments. You might be doing things around promotions and other things to try to understand a lot of, uh, trainings and, and formal l and d efforts have kind of post class feedback and other things to try to measure what their, their experience was there. Uh, engagement surveys, these broad employee lifecycle, or excuse me, employee experience, anchor surveys, we often call them. Um, we’re big believers in those, you know, we’ve seen popular taste kind of ebb and flow around these, these big surveys. 

Christian Nielsen | 26:55 

Sometimes people want more always on. We, time and time again, we see the market come back to these big engagement surveys because there’s value in having a broad metric. There’s also value in having kind of a shared snapshot and time understanding of, of the experience and a starting line for taking action. Um, but those, uh, can be a, a wealth of information, especially. ’cause if you do it once a year, you can usually ask more items in those surveys. Uh, 360 feedback data. Matt mentioned this, this is a great way to understand. Take that question I introduced earlier and apply it to an individual. What experience is this leader creating for those around them? And also, it’s a way to see if our values and our culture is being, uh, lived by a certain individual in a way that’s useful for us. And I say individual, but we also aggregate 360 data. So even though it’s often seen as an individual development exercise, the aggregate data from from 360, um, feedback can be a really useful data set. You know, what are our leaders struggling with across, um, different, different competency areas, or do is innovation a key component of our strategy, but our leaders, uh, you know, a part of our business are struggling with that. That’s useful information. 

Christian Nielsen | 28:13 

And let’s jump into this next category. This is outcome data. And this is where I would say most of the work we do with clients, uh, would be in those green triangles demographic and employee experience data. But we’re always begging them to bring more of their outcome data into the conversation because it unlocks a lot of possibilities. It’s also where the rest of the business starts to pay more attention. Because outcome data is any operational outcomes that are tracked by the organization. If we’re trying to understand, um, how does the employee experience or aspects of the employees experience impact what’s happening in our business? And that could be, you know, HR related outcomes like turnover or, um, we might even call engagement outcome. Um, it could also be things like production number, sales expenses, uh, uh, safety events, turnover, customer satisfaction. So if we understand kind of these demographic data out outcome data and employee experience data, we can start to unlock this top category, which would be around insights and predictions. 

Matt Wride | 29:12 

I wanna share with you an an example of that where, uh, sometimes it’s hard to get that outcome data so large. Um, healthcare organization, health system that we work with, we wanted to understand the association or the relationship between how often with someone meeting with their leader, and then the, then the perception is of the employee about the organization and about their overall levels of engagement. That’s an outcome, right? That’s actually an operational metric. How often am I meeting with, uh, one-on-ones with my, so we just couldn’t get it. So we just asked it <laugh> in the, uh, in the survey. So that’s not usually a typical question you would ask in a survey where you’re soliciting feedback and sentiment, right? Perceptions, attitudes, beliefs is, are, are usually the topics that we’re kind of covering, but we asked how often, and man, it was so insightful to see that as, as the frequency in which people were connecting with their direct manager, how that impacted and the extreme, and I’m gonna use the word extreme correlation between engagement and belonging and caring and just, just the amount of contact they had. Yeah. And so if, if we can get people to unlock the outcome, sometimes we have to cheat and ask it ourselves. But if we can find it, then we can get, then we can really start showing some really amazing associations that really can. And then, then if you talk about creating an incentive for people to get out there and do more, one-on-ones, this, this data certainly helped that. So agreed 

Christian Nielsen | 30:43 

Completely. And, and that’s a really good example and, and, and of what we’re talking about, we’re really looking for those causal relationships. If this, then that and, and trying to understand where do we have some leverage points? And especially where they’re very actionable things like the one you described, it’s not rocket science to say, Hey, better one-on-ones are gonna lead to, you know, a better outcome. And I mean, it’s not, it’s not like we’re saying, Hey, you have to invent cold fusion. It’s no, you just need to tell your managers how to, and, and, and motivate them to have these meaningful touch points. And it’s going to have a real impact on, on some important business metrics. Um, that’s really what we’re trying to do with all of this is if, if we have a, a nice foundation of data, and by the way, it can’t just be, Hey, we captured this once in 1955 and we’re good. 

Christian Nielsen | 31:28 

It’s, it’s gotta be actively clean and curated and, and, and, uh, uh, current. Um, but if you’ve got that, some, some really interesting things are possible, but you need more than just the data. You need some ability to interact and pro and, and, and, um, get the value out of it. And so I’ve got this slide here, so you’ll need access to the data, but you’ll also need budget and buy-in to a certain extent to, if you’re going, if you’re going to go make this a mainstay of your, your, you know, practice going forward, um, that budget is gonna be to, you’ll, you’ll need some data science and stats expertise in-house if, depending on, you know, a lot of our clients leverage our data science team, and we love doing that work. Uh, and, and hope to always be adding that value, especially for our, our smaller clients that don’t have the ability to, to build these teams in-house. 

Christian Nielsen | 32:23 

Um, but if you are able to, you’ll need to build some internal data science and stats expertise. Now, I would say, and this is prob this may prove that I’m bad at stats, but I would say I’m above average at statistics. Uh, but I would stop, well short of calling myself a data scientist. Um, I, I, I, I know enough to ask the, the thoughtful questions and to interpret things, but I’m not the one that’s, you know, using Python or r to, to actually go do some of the advanced analysis. We need other folks to do, do that on our team. And we fortunately have, uh, some really wonderful, talented individuals that can do that. But you’ll need them to, to help collect, clean and curate data, analyze data, and identify relationships. Uh, they’ll need some software suites. Now, these are more accessible than I think they’ve ever been. 

Christian Nielsen | 33:10 

Uh, for example, are in Python. They’re pretty low barriers to entry. Some of the others have some expense to them, but, um, you’ll need some technology to be able to process that. And this is an interesting one, Matt, I think you and I both experience have experienced this, but you’ll want a subject matter expert paired with the stats expert. Um, yeah. Uh, the, the another way to say that business leaders can’t do it alone, and neither can the data science team, you, you kind of need to have the back and forth around what are we trying to understand and what outcome are we trying to influence in the business or in the employee experience, uh, and, and, and have some collaborative direction assigned 

Matt Wride | 33:50 

For sure. And, and, and sometimes, I mean, we do a lot of, uh, teaching and outreach to obviously HR professionals, talent management professionals, and sometimes I think we make the assumption that, that, that, that, that all stays in house. But the best practice here is you build a cross-functional team. You’re gonna have someone who handles it, someone who’s gonna handle information security, data science, some operational leaders. You need to go out and build, uh, really a cross-functional team to work on this. Um, and you have to, and you need a and you need a strategy, not just how we collect it, but how often we deliver it. But even things like ethics, like our, what do we collect? How often do we collect it? And are we going to make that transparent to the employee population? And, and so your cross-functional team is really nicely situated to grapple with those issues. So my main point is this is if you’re an HR leader and you’re trying to do this in-house with just your HR business partners or those that are serving different needs within the organization, you’re probably gonna fail. It needs to be a cross-functional team, and it needs to meet regularly, and you need to have a mission. But if you can get there, um, it, the, it’s the first step is sort of your, your digital strategy or your data strategy. Excuse me. 

Christian Nielsen | 35:11 

I like that. And another thing I’ll point out here on this slide, and that the animation’s gonna drive me crazy over time, but the, uh, the outcome data is, has been an interesting thing for me on the, on the service provider standpoint, because I found that most of our clients’ eyes are bigger than their stomach when it comes to that. I think it is one way to say it. So a lot of times we see people have an appetite, oh, we wanna correlate to this, to all sorts of data and things, but it that kind of, for whatever reason, they don’t have access even internally, they, you know, due to some silos, they don’t have access to customer experience data or someone’s not letting, you know, why would we, why does HR need this? Or something? But there’s some internal limiting factor that keeps them from, uh, kind of adding that to the, the conversation. And so still a journey worth going down, but, uh, it’s just, uh, unfortunate, I think missed opportunity in a lot of cases. 

Matt Wride | 36:08 

Yeah, and I jump into with data is a lot of times data gets hoarded and, but it’s not intentional. What happens is you get into these projects, they take longer than you want, and then by the time you’re ready to, to, to, uh, kind of publish findings, it’s either old or things have changed. So when, when adopting data adopt what’s known as a instead of a t to green, so I’m gonna use a metaphor for golf. Hopefully everybody understands how the game works. But you tee off and you end on a, on a putting green, instead of going from the, just thinking about whatever you want on the T and hope to get to the green. When you use a green to T strategy, you’re thinking about, okay, the most important thing I do is deliver actionable insight. So let me make sure that I keep the scope of my project and what I’m trying to deliver manageable enough that I can make sure that I hit that deadline, that I give actionable data in a timely manner so that it can be used. 

Matt Wride | 37:08 

Because that’s what we’re trying to build. We’re trying to build muscle memory where we’re getting data out. It’s being utilized, it’s being effective. And if you do that by just having a wishlist up front and kind of building this, you’ll just get stuck and bogged down and oftentimes delivering things too late. Whereas if you focus on the green and work backwards, like, what are the shots I need to do to hit to the green as opposed to just hitting the first shot, you’ll actually do much better. So, okay, we want six month report out to senior leaders about how our, uh, employee population has changed over the last three years. Set that as the goal, and then work back to what you need to do to accomplish that and hit that goal, even if the data isn’t as robust as you’d want. Get something out there. 

Christian Nielsen | 37:53 

I like that. I like that a lot. And it’s, uh, you know, having a goal and, and some parameters around success for, for your data efforts, I think is really key. So let’s go, let’s shift gears a bit. Um, employee experience data, uh, for the rest of us. So if we can’t go all the way, you know, build out our, and by the way, not to keep coming back to it, but another challenge, um, to do this work in-house is confidentiality. So, you know, if you’ll want, for some of our clients that wanna do some of this work internally, we, we can either partner with them to make sure they have ethical, transparent, uh, messaging to their, um, employees around where, what, who sees their confidential data. But my preferred style is we’ll scrub it before we send it back to ’em. So they still have the demographic linkages to the perceptions, attitudes, and belief that employee experience data, but it’s, we’ve taken away any identifying, uh, information so that they can, they can get the insights without, uh, risk for individuals. 

Christian Nielsen | 38:57 

Um, but something to consider, if you wanna do it in-house, um, there’s a confidentiality thing. You’ve gotta take very, very serious employee experience data for the rest of us. So we might not be able to build that team. Let’s talk about some things that we can, we can leverage, hopefully, there’s already some things you can leverage. You know, you, you’ve got demographic data, you can capture perceptions, attitudes, and beliefs relatively easy. Um, but we’re going back to these two questions. What experience are we creating and is it the right experience? Now that isn’t just a big broad thing, but it, it can be applied to any decision you’re making around the employee experience. So, for example, uh, return to work has been challenging, and it’s all, it’s always big news when a, a huge firm drags people back into the office. You know, we’re seeing it with some very, for big organizations right now, but there’s, these questions could be asked about that moment. 

Christian Nielsen | 39:50 

It could be asked about the experience at large, but about individual decisions as well. And that’s what we’re, we’re hopefully painting a picture of here. So I wanna talk a little bit about one of our engagement models, because this is, this is a another way to measure if we’re creating the right experience, even if we don’t have all that operational data and, um, uh, the ability to, to do some in-depth analysis. You can still use these frameworks to get, uh, to assess whether you’re creating the right experience for your employees. This is a model that we, we leverage here on our engagement side. We make the distinction between things that drive satisfaction, these base level like expectations. If we’re going to the hertzberg two factor theory, these are those hygiene factors. And I might even say these are enablement in nature. Can they do the job? 

Christian Nielsen | 40:35 

Do they, you know, can they be successful here in terms of we’ve provided them with tools and resources, the basic expectations they need to do the job. Safety critical, obviously. Um, uh, but are these things in place? Sometimes we talk about being brilliant and the basics around here, uh, are those foundational needs in place? And then are we going beyond that and doing things that, if I go back to that language I used before, are we inviting people to engage? So that bottom rectangle is around, uh, are we enabling them? And then on the top, are we engaging them? And we use a model here, uh, called Engagement Magic that talks about meaning, autonomy, growth, impact, and connection. So we can think through each of our decisions, and to the extent you have data on this, are we meeting base level expectations to drive satisfaction? And are we inviting engagement by, uh, creating meaning, autonomy, growth and, and connection? So that’s another way, even if we don’t have, um, all the data in the world to assess, are we creating the right experience for our employees? Oh, you’re on mute, Matt. 

Matt Wride | 41:42 

Okay. So the reason this is helpful to talk about is part of being good at data is the final delivery has to be in a way that can be con consumed and understand. So models are helpful. Whatever you use, whether it’s something like this or so, or something else. Helping, helping, um, orient the data and putting it into a framework yeah. Um, is really important. I think that’s, uh, the key point we’re trying to make, have a framework so that it’s not just g just not that it’s just throwing out interesting tidbits, but they know where it fits within the framework, and then that implies action that should be taken. So if meaning’s low, then we can start talking about ways to improve meaning. So anyway, 

Christian Nielsen | 42:26 

That’s a good point, the framework. And, and a lot of times it’s, it’s, it’s great for hr, but this is great to teach other leaders to have some kind of framework to say, here’s what it looks like when we’re getting it right, or here’s some questions you’re a, you can ask yourself to assess if you’re getting it right. And speaking of getting it right, um, this is becoming a, a, a, a core tenant of our beliefs here at decision-wise, in terms of how, how to get it right with data is you’ve gotta get the right data to the right people at the right time. Um, we’ve seen a lot of examples of people running very strong, you know, very smooth projects to capture employee feedback. And then we we’re always rushing to say, Hey, let’s get this executive debrief out. Let’s get it shared with the, the population. 

Christian Nielsen | 43:12 

I’ve seen the companies wait as long as a year to get the results out, and this stuff has got, uh, expiration dates on it, <laugh>, it’s, it’s not valid, uh, a year out. Um, it, it’s of limited valid value, uh, a year out. And so there’s the, you, you need to get it out not only to the right people, uh, but you’ve gotta get it out pretty promptly while it’s, while it’s fresh and very usable and relevant. Um, another quote, I I snuck one more quote in here. I think I’ve got at least two more quotes. Uh, one person’s data is another person’s noise. This kind of goes to something Matt has, has been, um, teaching us about for a long time, which is around the value of curation. So you, you can’t just say, here’s all the data we captured and dump it off on a, a, a manager’s desk and say, good luck. 

Christian Nielsen | 43:59 

Uh, you know, they’re gonna ignore it or they’ll take it some weird path to and can be misused. Um, but what we wanna do is, is we want to just say, okay, the data’s not enough. We have to understand, well, what matters for this part of the organization, or this person needs to be curated and analyzed and then routed to the appropriate people. Um, so, you know, we’ve had a lot of wonderful success with manager reports, but it wasn’t until we learned, okay, what does a manager really need to know that those, those reports became really useful to say, okay, curating that, pulling it in, and then getting it to them very quickly, uh, not waiting a year, um, getting it to them. And then also to Matt’s point with, with some frameworks and interpretation around, here’s what you can do with this data. 

Matt Wride | 44:48 

And sometimes we get lost in, um, visualization and in, uh, trying to go really deep in our analysis. Um, there’s a, uh, when, uh, when you start in data visualization, the first thing you learn is that literally text or numbers is the first level of data, uh, data visualization. And that whenever possible start with that, 

Christian Nielsen | 45:13 

Hmm, 

Matt Wride | 45:14 

<laugh>, your employee engagement score is may is a more effective way of displaying that data than maybe you in a scatter plot compared to 12 other people. Like that’s, so there’s a, there’s a hierarchy or kind of an order of data visualization, and your job as a curator is to help un is to understand that, um, don’t, don’t get overly busy. Yeah. So, 

Christian Nielsen | 45:39 

Well, I I, I’ll come back to that term. You introduced early in the conversation d data journalism, journalism, right? So I think through headlines how quickly I’m ignoring emails if there’s not immediate value, um, our, our managers need to be hit with the information that matters that can help them do their job and help them address the things that are important to ’em and executives as well. That audience has a different, uh, uh, need and urgency and the, the, the type of things they need to see are, are different as, as well. And, 

Matt Wride | 46:09 

And here’s an example. Let’s say you’re conducting exit interviews and you’ve got 20 different insights. Don’t share all 20 share. These are the top five reasons people have excited for leaving. What can you do with this information to stop that, right? Or next time you have a one-on-one, think about folding in these five things. You know, we’ve, we’ve narrowed it down because every employee has a whirlwind around them, and the whirlwind is all their work and everything that’s flowing around them, and we try to try to pierce the whirlwind, and if we throw tons of stuff out, it just bounces off. But if we throw one or two things into it, it will, it will get inside and become part of that, uh, whirlwind that is the employee. 

Christian Nielsen | 46:51 

I like that. I’m gonna be saying pierce the whirlwind, uh, pierce, 

Matt Wride | 46:55 

The, 

Christian Nielsen | 46:57 

Um, all right, so we’ve mentioned a few times the need to route this, and Matt, Matt used a really great term, like is around, don’t hoard the information. That’s, that’s kind of the another missed opportunity you see at too many organizations, which is get a lot of wonderful data. We partner with them to, to help them get some really great information from their employee population. And then HR keeps it to themselves. And even the greatest HR teams in the world cannot change culture by themselves. Um, well, 

Matt Wride | 47:31 

And, and Christian, sometimes we feel like we need to tell them what to do with the data rather than just stopping and giving them the data. There’s a great study at Project Oxygen, which was done to study managers at, at Google, and a phrase that has stuck with me was, I’m smart, just give me the data and I’ll decide. But we’re, so we try to be helpful, and that’s just kind of who we are as HR leaders. So not only do we want to give ’em the data, but then we wanna say, and you, you need to do this and this, and this. Stop. They’re smart people give ’em the data and trust that they can. If it’s, if it’s the right data, they’re gonna take action on it. So anyway, sometimes I think that’s what slows us down is we think, well, I can’t just give ’em the, the, the, the, the data I’ve gotta come in with with 12 recommendations Yeah. And a five step plan. 

Christian Nielsen | 48:21 

I love that. It it’s a good point. And, and we, you know, we’ve gotten on our own journey with prescriptive recommendations, and we, we, we have that built in as a core component of our technology, and it’s, but we don’t use it in place of, you know, and, and forget that hey, managers were chosen to lead for, for a reason, and we need to get this in their hands as quickly and as efficiently as possible, and give them the best chance to take meaningful action on it. In fact, a lot of the ways we measure organizational readiness for, uh, driving the employee experience is around who owns the employee experience. If it’s only hr, then they’re in kind of your infancy. I, if senior leaders are buying in, if managers and teams are recognizing their stewardship or their ownership of, um, their component of the employee experience, that’s a, a more advanced ready organization. A lot of it’s not our, our work isn’t just helping companies measure the employee experience, it’s also helping them expand ownership of the employee experience. Because more is possible when we, we, uh, we get more, uh, uh, of these key stakeholders included. In fact, that’s what this, this slide is on. Um, the three i 

Matt Wride | 49:36 

I, I was just gonna follow up with a little story. There’s a metaphor of the stone cutter, right? The stone cutters might, might hammer a stone for a hundred times before it splits. And the, the questions always arise, well, was it the last blow that cut the stone? Or was it the 22nd? Right? And I think sometimes, um, with data, it’s a little like being a stone cutter. Get it out there and keep giving it to them. Because if we, if we say, oh, the, the data says you need to hold more, one-on-ones, and here’s all of these great programs, how the old one, one-on-ones, and we don’t see the one-on-ones go up, don’t stop giving the data. Instead, instead of focusing on maybe all the time trying to teach them how to have one ones just continue to tell them, you’re not having enough one-on-ones, you’re not having enough one-on-ones, and eventually on the hundred times the stone will, the stone will, will be cut. Does that make sense? 

Christian Nielsen | 50:29 

Yeah, yeah. Yeah. I, I, I think that’s a, a, a great metaphor. I’ve heard, uh, um, something similar around bamboo, but the, the idea though I is, you know, don’t underestimate your managers, but also don’t overestimate the number of times they need to hear <laugh> a message. Might be the other way to say it. Uh, kinda, I wanna just, I, I’ll kind of go through these slides quickly, but as far as data’s considered, and I’ll go back to this idea of culture every day, every human being at your organization, co-create what it feels like to work there. But if we’re trying to craft information for every single employee and a, a unique message that we’re not gonna get anything done, the three key groups I’ve learned to focus on are senior leaders, HR, and managers and teams. And if you can simplify your approach to just think through those leaders, especially around employee experience data. 

Christian Nielsen | 51:23 

Uh, okay, what are the implications for senior leaders? What are the implications for hr? What are the implications for individual managers and teams that will, will, will make this work a lot easier for you? Um, there’s certain things that only the executive team can influence, mission, vision, or where the organization strategy and goals, policy decisions. There’s things that happen at the top that really matter. If I had more time, I’d tell you more about, you know, we have items around, um, optimism for the future, uh, or a belief in the strategy. And if employees don’t believe in the strategy, um, then my question to executives are, do you believe in the strategy? Do you have a strategy? Why? Where’s that breaking down? And if they don’t, then that’s, that’s something that frontline employees can’t fill that gap in. The manager can’t do it. HR can’t. 

Christian Nielsen | 52:07 

There’s jobs that have to be accomplished there, and employee experience data needs to be filtered and curated for them. HR owns what I would call people systems or organizational structures. There are a lot of things, including the keepers of the ex process and, and stewardship there. But influencing and shaping the employee experience should be diffused across these groups. But there are certain things like l and d programs, organizational design, communication systems, a lot of things sit with hr. Um, and, and so they, they own a component. Some of that employee experience data does rest with them, and the, the, the onus for action rests with them. But a lot of it goes through this last category. The managers are the closest to the frontline employee experience, uh, and the experience of all of us. They’re so influenced by the manager and not just the individual team experience, but also what we call writing for the brand. 

Christian Nielsen | 53:00 

Uh, we have a lot of research that indicates that the, one of the most important things a manager can do is positively represent the organization to their employees. And if they’re just building loyalty to them or, or the team unit, they’re doing them a a disservice. It’s a false kindness. It’s a short term thinking. And, and so we wanna give them the information, um, that helps ’em shape the experience on their team, but we also wanna help them understand their role in shaping their team’s view of the organization and employee data, uh, or, or the data we’re talking about can really help build some urgency and some speci specific action, uh, around that. 

Matt Wride | 53:40 

Yeah, Christian, I just really think that this point is so valuable that you bring up, which is make sure you’re curating your data for these three groups. And that’s don’t, it’s, it is tempting to have 12 groups. It’s tempting to have one. This is what we think is the optimal, and I, this is really your thinking and, and our, and our data suggests that it’s absolutely right. These are the, this is the best way to think about it. So now as you sit down, you’re like, okay, what is it that I need to get to managers? What is it that we need to understand as an HR team? And then make sure we’re getting senior leaders, the trends that, that we think we’re seeing so that they can think more strategically. But, uh, I think you hit the nail on the head when you focus just on, in, in these, in this, in this little ecosystem that you have. 

Christian Nielsen | 54:23 

Yeah. Yeah. I, it, it is proven to be very helpful for me. I, I get overwhelmed if I think through, okay, you know, we’ve got a company of 20,000 people here, or even a smaller company, like a hundred people. You can get overwhelmed about who needs to know what, but if you simplify these three groups and understand their, their spheres of influence, then you can cut right to it. So I want to kind of get back to kinda, we’ve covered a lot of ground around going deep with data and also some, maybe a lighter touch to how to answer these two questions. What experience are we creating and is it the right experience in closing, uh, we, and we’ll pause for a moment in a, or, we’ll, we’ll have questions here in a moment, I hope. We’ll, we’ll see if that chat function’s working. Um, ask what que what experience are we creating? 

Christian Nielsen | 55:11 

And if you’re not measuring get started, uh, do an engagement survey. Um, consider lifecycle surveys. Consider looking at Kronos and Kairos moments. Uh, you know, tapping in and understanding, okay, are we creating the right experience there? Um, or excuse me, are you creating the right experience? So measure the experience, then assess if it’s the right experience. Are you meeting basic expectations? Are you getting those satisfaction areas right? Um, are you creating magic or purpose path in place? Consider tying it to operational data. If you’ve got some of that, don’t hoard the data. Uh, this is a, a point that Matt has made and, and I’ve found it to be so true. Get it out to the people that can shape employee experience. Consider those three groups. Get it out. Don’t, don’t, uh, just keep it to yourselves and, and really work at not only, um, expanding the ownership and the employee experience, but also building a mindset of a, of data literacy and, and an appreciation for when we get employee experience data. 

Christian Nielsen | 56:10 

It’s a gift that can help us. Not only, uh, you know, sometimes people discount this as a touchy feeling exercise, but this is as strategic as it gets. The experience we create, uh, influences, directly influences the outcomes we get. And that can be engagement and turnover and things that are kind of relegated to hr, but it also is our customer experience. It’s the extent that we’re able to, uh, accomplish the strategy executives have, have put forth. So there’s a lot of value to this. I do love this quote. Um, we’ve come to it o often and especially as it, uh, goes to the employee experience, but I’ve learned that people will forget what you said. People will forget what you did, but people will never forget how you made them feel. Uh, one of the greatest quotes, I think around any kind of experience design and, and important for this, and if you don’t believe me or believe this quote, uh, go look at Glassdoor and see if people, uh, have long memories for how they felt about their, their workplace experience. Um, Matt, before we jump to questions, any, anything you’d add? 

Matt Wride | 57:10 

Um, yeah, that our goal with data is, is at the end of the day, manage, like you said, if, if manager’s job is to organize the work and accomplish the work of the organization, the only way they can do that is through others. And the only way you get others to buy in is the experience that they work within. And so, experience management for a leader is as just as important of a function as it is organizing the work itself. 

Christian Nielsen | 57:40 

I love that. It 

Matt Wride | 57:41 

Is, and that’s all. And that’s why data’s important because it’s now half their job. We’ve gotta give them the data they need. 

Christian Nielsen | 57:48 

I love that. I love that. We do have a, we have a question. It’s a, it’s a good question. In the organizations you support, do you, do you see employee experience committees that have active involvement on influencing experience and engagement? How would you recommend constructing an experience committee with leadership buy-in? So, that is a really good question, and, and I’ve seen it done various ways, but oftentimes there’ll be like, um, an employee engagement committee or, or something. Sometimes that’s formed in advance. Sometimes that’s who suggests they run a survey and, and how we get involved. More often, I see it as an after, um, effect where it’s, Hey, we run a survey, we want a team of change agents or people to kind of help make this move this forward. Here’s some, some challenges with that. Um, and, and Logan asked it the right way. 

Christian Nielsen | 58:37 

You need executive buy-in, they need some, uh, someone with some positional influence and power to, to help make things happen. And ideally, it’s outside of HR because, um, uh, you, it’s great if you can bring in the COO or something like that, or CEO to, to sit in a committee, but, uh, making sure you’ve got enough gravity assigned or aligned with that group is, is important. Another thing I see is training. In fact, we’re going down the path of, um, building an employee experience certification for this exact reason. Because we do see a lot of value in having kind of these fire tenders or people that are internal owners of the employee experience, um, and represent that as subject matter experts in the board. Yeah. But a lot of times, if they don’t have some kind of training and, and sorry to talk over Matt, just if I could finish the thought, if they don’t have a lot of training, they’ll ask for some strange things and, and can actually set the work back. But a little bit of training and expertise can go a long ways there. 

Matt Wride | 59:39 

I just wanna reemphasize the point. If you have committees whose job is to come up with solutions to the experience problems, that’s not gonna work because the solutions are found at the leader level, at the manager level. So what, what, what, so if the committees are there to support and train and guide and teach the, the leader driven experience that experience at the, at the direct level, then it works beautifully. And that’s why he’s, what Christian was talking about is if we teach, if we teach them how, then they can go do it because they’re ultimately the ones that have to find the solutions that work. Yeah. So committees that are tasked with solution building don’t work. Committees that tasked with support for, uh, operational leaders at that, at that key level, those work really well. Yeah. 

Christian Nielsen | 01:00:30 

Well said, well said. I know we’re, I know we’re at time, but, uh, I know Matt and I have a moment or two if there’s other questions we want, don’t wanna shortchange the conversation, uh, feel free to put those in the chat. Uh, otherwise I should have mentioned at the outset that this, uh, session does qualify for, uh, one credit of HRCI or, or interim credit. So, uh, a link, uh, to claim that credit will be, um, sent out after the, the, the session concludes. And we’ll make sure everyone gets, um, uh, credit for being here today. And then the other, the other thing I I’ll say is if you do have, uh, uh, additional questions or want to connect after the fact, you can reach us at info@decisionwise.com. Uh, hopefully, again, you can tell that we’re very passionate about this work. Uh, even if you’re not a client or, or even a prospect of us, we love to just be thought partners and, and, and, uh, discuss possible solutions. 

Christian Nielsen | 01:01:20 

So feel free to reach out, uh, as well. I’ll put in a plug for our newsletter, uh, that comes out monthly and has a lot of value in, in it as well. So, uh, if there are no other questions, I want to thank Matt for, uh, joining me in this conversation and, and everyone else for a attending. If you wanna send a note, uh, Lauren sent a a a quick question. If you wanna just ping us at info at decision-wise, we can get you the slide deck if you’re interested in that. Hopefully we added some value and expanded some of your, your toolkit for, uh, thinking with, uh, data-driven decisions. Thanks, everyone.