Episode 63: Building Bridges with Rebecca Gosla

Alexandra: I am so excited to be joined by Rebecca Goslow today, and we are going to have a fantastic conversation about bridging gaps. So Rebecca, why don’t you go ahead and introduce yourself?

Rebecca: Yeah, awesome. I’m happy to be here. My name is Rebecca Gossela. I currently work as an associate at a company called Simplicity Education. the CEO, Christiana Gupta, founded Simplicity in October 2020 amidst the pandemic and virtual learning. when she saw firsthand a huge need for. Data systems and structures and schools.

now we’ve grown to five employees. Um,and now we empower educators to use data to gain actionable insights. And I came to the data world, by way of getting my master’s degree at Harvard in education. I studied cognitive neuroscience in undergrad and was initially interested in doing [00:02:00] research and how the brain develops and how children learn.

And then I got to grad school and realized that data, I mean, research is not for me. and then I really liked my statistics and data analysis classes that I was taking for my program anyway, and just kind of steered in that route. I strongly believe that if you work in education, you should get school experience.

So I bridged my data and education interests and worked as a data manager at a charter school in Boston for four years prior to now working at Simplicity Education.

Alexandra: And I know that that’s one of the things that connected us was your lived experience of being this kind of data manager. And I’d love to start a little bit with you talking about that role of a data manager, because I think that Oftentimes, the tasks, the work, the mindset, the skills involved in that kind of role can be a bit misunderstood.

and the kind of person that would do well in that position isn’t always clear to those of us who are coming new to this. So I’d love to hear a little bit more about your experience as a data manager about like what. What does that role actually do? and what were some of your experiences about the things you needed to be successful in it?

Rebecca: Yeah, the role of a data manager certainly means a lot of different things across the board with different schools or districts, obviously in different industries. My colleague and I are actually doing a mini research exercise right now, looking at data manager job descriptions, and we’re seeing a wide range of responsibilities in those.

But the main aspect that we’re finding a consistent across the board is the creation and maintenance of data analysis tools. Which I think is really exciting because it tells me that schools and districts are prioritizing not only using data, but they’re thinking about how to build their capacity by dedicating someone’s whole job [00:04:00] to managing the data.

And so therefore, like, increasing that capacity and other parts of a data manager aside from the data analysis tool creation is. Anything from managing the student database to scheduling and rostering to managing the assessments, the state tests, training staff on school’s data systems and how to interpret the data or creating board reports, state compliance reporting.

So it really runs, runs the gamut.

Alexandra: This is something that I see happening in so many areas around data, even in pretty well established like more tech companies, where what a data engineer is, what a data scientist is, like so many of these terms. are thrown around like they mean something concrete and solidified. And yet, you know, you ask people what they do with the same titles and their job is actually very different.

and I’d love to see the final results of that research project on the job descriptions, because I’ve definitely run into some confusion myself even there about what I call myself based on my skills and what I do. So tell me a little bit when you, if we think more generally, and I love that idea of the, like creating and maintaining data analysis systems and tools, but also the connection into the non data folks, right?

Whether that’s training, sharing, communicating, reporting, what kind of skills and training did you find was helpful for you in being successful in that role?

Rebecca: Yeah,I think that. being organized, being detail oriented, having a lot of patience and empathy. Schools collect so much data now, it’s wild. whether they have to do it for, you know, accountability or compliance purposes, or of course they’re monitoring their students outcomes and academic achievements.

and want to improve those. So there’s just generally a lot of data and it’s coming from a lot of different sources. And sometimes those sources oftentimes they [00:06:00] don’t connect. And so it’s very important to be organized and detail oriented to manage all of these disparate forms of data. And generally I think patience and empathy Are like key characteristics because not everyone in the organization or school is going to know the school’s data like you do.

So, as a data manager, you, you’re at a bird’s eye view. You see it every single day and. Not everyone does that and so having patients while explaining an analysis or explaining the logic of how you got to your conclusion and empathy for understanding that. They may not understand. What you understand is, is pretty important.

Alexandra: And I think It’s interesting that you didn’t start with what you have to be really good at math, right? Or you have to be like, have all these technical skills, because I would agree with you that I think the technical skills are a lot easier to learn, right? Someone can sit down and teach you how to do statistics and, you know, you talked about taking stats classes and really enjoying that.

We don’t take empathy classes. We don’t take classes that teach us how to communicate to people who have different skill sets or different experiences than we do. And so I think that it means A lot to have those softer skills and that patients that connection and I think that’s one of the things you know that drew me to your experience generally is that so much of success in this role is that ability to bridge across whether it’s to other data users, whether it’s bridging to non.

Quote unquote non data users, right? We’re all actually data users, but those who don’t identify themselves as such, and helping bring all of that together, I think is so meaningful that this is what are the most important skills to be successful here. It’s not all of the quantitative skills. You need those, but they’re so much easier to learn on the job or with, you know, some basic education.

Rebecca: Yeah, exactly. And it’s interesting that you kind of touch on, bridging the gaps or bridging the connection between quote non data people and quote data people. and we may get to this later, but just I bring up now [00:08:00] that I think that we can, like, bring down these walls or bridge this Quote gap by maybe just getting rid of these labels of who we consider a data person and who’s not.

I’m sure, like, we’ve been talking about. There are people with titles like data manager and director of data systems, but then at the end of the day, like. Those job descriptions, as we just said, like, very a lot anyway, I’m sure there are skills that those roles must have all the technical skills, but I think that.

Anyone can be a quote data person if they want to, or they are interested, or in the case of a school leader, they need to make these informed, impactful decisions about student outcomes using data. so they really are data people.

Alexandra: I’ve had several people make the analogy of data being like water, you know, for lots of reasons. One of the people I had on my Dr Liz Crow, she talked about the data systems are like plumbing, right? We have to think about how they take care of the stuff inside the pipes. We have to think about how those pipes.

Get to where they need to go. We have to think about like right sizing those pipes based on, you know, how many users there are and things like that. But I realized that it also is a good analogy from the point of view of we all use water, but some of us might be plumbers, right? Some of us might work for the E P A and work on like pollution control and waterways, but we all use water in one way or another.

Whether or not it’s. Quote unquote in our job title, and we may some of us, you know, if we’re farmers might use a lot more water and have to have a closer relationship with, you know, details about the water like pH or something like that. But we all use water and we can connect over that.

Rebecca: Yeah, and I think another way, like, basically what you’re saying is we all use water. We all use data, especially in a school or a nonprofit. and so if we reconsider or redefine the way that we define what data is, then really [00:10:00] that expands the amount of. Touch points that people have with data. So, you know, in a school, it’s often equated that data equals test scores, but there’s so many other types of data that teachers are using in their day to day classrooms, like family communication, observation, survey responses.

So I think that. Data literacy skills and data analysis can be used learning those types of data as well. And then, those are also ways that to be a data person.

Alexandra: Yes. Oh, I agree so much. And I think bringing that awareness to those different kinds of data, the things that we don’t naturally think of as traditional data helps us, like you said, bring down those barriers and maybe kind of get rid of that. False distinction that some of us are data people and some of us aren’t, we just might interact with it in different ways with different skills.

so we talked a little bit about what it takes to be successful. Like I love that idea of patience and connection and empathy. what are some of the challenges that a formal or informal data manager may, you know, face in trying to be successful in this role, especially in the education world, like you said, where data comes fast and furious.

Rebecca: Yeah, there are definitely challenges and, um. Ithink pitfalls that data managers Can go into, and, um, 1 of those is assuming that your. User or your audience. knows the data, as I kind of mentioned earlier, and, you’re the one who sees all the data every day. so if you are explaining something, and just may not know what you’re talking about, especially if you bring the conclusion without the evidence behind it.

so I think it’s always important to communicate. Those insights while pointing back to the data, that supports it. you know, and also assuming that they understand the analytical methods and the logic that you used. building data literacy skills takes time and not everyone has those, quite yet.

And so, you know, just being [00:12:00] again, patient and explaining and answering questions. I also think. It’s important to not attach your insights or your conclusions to preconceived notion or judgment. Um, for example. If you are looking at a data set, and it’s the last math assessment or the latest math assessment, and the 1st grade students just, you know, just didn’t meet expectations that your conclusion that you’re giving your principal, for example, is not like, oh, there’s something’s going on in the 1st grade classroom or oh, They must really need extra help in math because that’s attaching a judgment to the data. And really what insight you want to provide is, you know, X percent of 1st graders are below expectations, something like that. And then lastly, like, I think it’s important to not dwell on the negative, using that same example, student data is not always going to meet the mark the way that we hope it to always meet the mark and since you’re the person who sees all of the data, it can be easy to get caught up in.

a negative growth or a decrease in attendance rate, but there’s always plenty of bright spots in the data and in a school environment. There’s plenty of bright spots like outside of the data. I know I would, like, just walk down the hall and, like, talk to students to, like, give me joy since the students are obviously the center of everything that we do.

And so I think not dwelling on the negative is important.

Alexandra: And remembering why you’re doing the work that you’re doing,

Rebecca: Exactly.

Alexandra: seeing that frontline impact, the why every day, because it is easy in any nonprofit role to get so sunk into the fires that you’re fighting or the daily grind that you lose sight and lose direct experience, you know, whether it’s of the students in the hallway or the members that you serve of why you’re there. I liked what you said about the avoiding judgment, and [00:14:00] I think it links to the first thing as well in terms of creating that shared language and understanding that the way that we, as presenters of data and analysis, use words is really important. It’s not just about the statistical technique that you used, or you, like you said, the model that you built with the numbers.

It’s also how you speak about that. And it’s so easy to unconsciously make that jump from. What’s actually in the data right? X percentage of students scored Y number to our first grade teachers aren’t performing appropriately. And you can like seamlessly make that and not realize that you have applied a judgment to a number because it could be that actually they ran out of time because there was a fire drill in the middle of the test, right?

And so that’s actually what happened and that’s why they didn’t score well because they didn’t get to the last 10 questions on the test. And that requires a completely different intervention than it’s because they completely didn’t understand fractions or whatever it was.

Rebecca: Yeah. And as a data manager, oftentimes what I found is I don’t have the context for everything, right? I’m not in the classroom. I’m not like an instructional leader. I just have the data. So, providing those insights without, preconceived notions was really important. And also I wanted to touch on the piece of, or kind of just not being quick to judge, you know, using this example, the first grade teacher, um, because I think it’s really important at a school or any nonprofit or really any organization to have, a positive data culture.

and, I think all organizations have a data culture. If you use data, you have a data culture, but positive data culture exists when. Teachers or staff members feel psychologically safe. So using this first grade example again, if the principal, if I were to say to the principal, first grade teacher, you know, not performing well, that’s not making this teacher feel very psychologically safe.

And then you don’t have a positive data [00:16:00] culture because data should be used not as punishment, but as opportunities for growth.

Alexandra: That is so important and I think it is easy. To miss that in a drive to find, you know, the data to support decisions that we can easily slip into using it as a stick rather than using it as a way to just understand where we are and help all of us understand better where we want to go. Do you have any recommendations on how we, whether we are formal data managers or whether we are data users in other capacities, how we can promote a positive data culture?

Rebecca: Yeah, I think being a data manager at a school, you’re not. At least for me, I wasn’t part of the leadership team. I wasn’t, you know, in charge of moving the needle on culture or anything like that necessarily. But I think if you live out the why every day centering the students and that belief that all students can learn data should foster equity if you live those out.

that’s, you know, leading positive data culture and also. Just in your own role, prioritizing the, your time and your resources that you need to to develop those high quality actionable analyses. And so that way. The data can be used effectively and then, like, communicating clearly and openly to the school leadership and teachers, will definitely drive the positive data culture.

Alexandra: Are there things you mentioned that you weren’t in a leadership role, but these are all things that you could support. Were there things that either you saw your leadership do that was helpful or that you wished your leadership did to further support that positive data culture?

Rebecca: Yeah, I think open communication, is definitely. At least for me with. Make me feel very like the data manager, was valued, or at least the data [00:18:00] was being used. engagement with the tools, asking questions, being very communicative, about the analysis that I was providing would help. At least the data manager feel supported and then that’s therefore. Improving, just like, generally, the. Data culture at the school of the organization. I think my school was a very, good example of everyone really was on board with using data and I felt very valued, but just in general, I think open communication, is definitely like up there in terms of priorities for that.

Alexandra: That makes a lot of sense because you want to look to your leaders, not just in modeling how that communication happens, but you want to be hearing from your leaders of what are the priorities? How will we engage with those priorities? So you want to see them using data in a way that models opportunities for growth, rather than your leaders using, you know, communicating data in a way that somehow, you know, Passes judgment.

so that makes a lot of sense. You want that sort of open functional communication to be going up and down the organizational ladder, not just side to side.

Rebecca: Exactly. Yes.

Alexandra: Now, if we move on from not just having a positive data culture, but a positive data driven culture, are there other steps or other characteristics that you look to see in a culture that’s not just Having data be present, but it’s actually using data actionably into informed decisions. What does it take to kind of take that next step?

Rebecca: I think it’s openness. To learning the skills necessary to understand. The data analyses that are being presented by the data manager or whoever is doing that. and again, by engaging with the data, like, let’s just say there’s a dashboard that the data manager created engaging with that. And I think I keep honing in on this communication piece, but. [00:20:00] Using the data, I think, is 1 thing and using the dashboard engaging with asking questions about it. All of that is very important. And that’s indicative of that data is being used in that there are decisions that are being made based on the data.

But I think if that those decisions are being, made in silo, then the culture just begins to fall apart. Um, so I keep going back to this open communication piece, but I think it is important to be transparent to other members of your organization about the decisions that you’re making and why you’re making those, like, based on this data, we’re doing this, and that can, that may or may not happen if Things are happening really fast or, it just, you may not even think about it, but I think if everyone sees why decisions are being made in a very transparent way with data that they tangibly can see, or at least know exists, that’s really powerful.

Alexandra: I couldn’t agree more. I mean, there’s a reason it keeps coming back to that open communication, right? That culture only exists and how we interact with each other. And if we aren’t able to communicate and share, like you said, that I used these data elements analyzed in this method interpreted with this context.

And that’s why that supported my decision in this area. And I can communicate all of that, even if you don’t necessarily agree with my final decision, you’ll understand how I got there and you’ll respect that process and you’ll be much more likely to mimic that same process in how you might make your decision for your agency or for your division within the organization.

So that makes so much sense.

Rebecca: And, uh, we’re kind of jumping around a lot, but back to, like, something that’s really important as a team manager, like, a skill to have and what you just said of, you know, if people can see literally the process, I think it’s very, very important. This would be like. Probably one of my biggest pieces of advice for anyone who wants to be a data manager is to document everything.

and it just will make it that much easier for someone to [00:22:00] understand the logic behind the decisions that you made and the analysis that you did and. Again, we’ll help with this communication piece. We’ll help those leaders make those decisions in,knowledgeable, smart ways. If there’s clear documentation on the process.

Alexandra: It also helps you when you get asked to update that analysis in six months and you’re going back being like, why did I filter out those students again? And if you’ve documented it, you’ll remember why you did that. Yes.

Rebecca: And it helps with sustainability. So, you know. I’m out 6, then someone else can understand what’s going on.

Alexandra: Or you grow into a new role or whatever it might be, you bring somebody else new on. It does really, really help it, like you said, with that sustainability as well. So we’ve talked about what you as a man data manager can do to be successful. We talked a little bit about what your leadership can do, the culture and that can support you.

I would like to dive a little bit more now into what, and I’ll put this in big air quotes, like people who identify as non data, right? Because I agree with you. I think that we can start changing the way that we talk about this, but we don’t for the moment, have great labels for that yet. so what could those folks do to better engage with and support their both formal and informal data managers in their organization?

Rebecca: think that. Being understanding and setting up guardrails, for this role, the data manager role, is, you know, very supportive and important. I think oftentimes, data manager can be lumped with I. T. you know, there is a lot of overlap with data and technology, especially in a school or nonprofit and. I’m certainly not qualified to troubleshoot an interoperability issue.

So setting up guardrails for what a data manager can and cannot do and understanding in Greece with that. is, you know, really important and can also. Event burnout from the data manager’s perspective. And then, in terms of the engaging with.[00:24:00] The data analysis, again, asking questions if you don’t understand something.

being open to learning the data literacy skills. I think a lot of times and, you know, I’m speaking from someone who is not the leader of an organization. So I know that there. Are there swamped, especially in schools, but I think taking the time to learn the basics of data literacy and data analysis can definitely go a long way and show that you’re very open and engaged with.

the data, can be very supportive as well.

Alexandra: Right, the idea that we need to get rid of the expectation that people, some people just wake up one day and know everything about data and those of us who didn’t wake up knowing everything about data that therefore we shouldn’t try it all to learn any of those skills, right?

Rebecca: Yeah. And I think if you start with the basics and later on, everyone can learn

Alexandra: And I think that goes back to one of the things you said earlier about as a data manager, one of your jobs is to make sure that you’re communicating things in a way that makes sense to your audience. And then as one of those audience members, one of our responsibilities should be to put in a basic amount of effort to learn that language, right?

That if we agree, okay, here’s how we’re going to talk about things, we’re going to put this in a way that’s approachable to everybody, but everyone’s expected to do a little bit of work to learn that shared vocabulary so that we can have a shared data culture, because one of the aspects of culture after all is a shared language.

and that we do let go of that expectation that somehow we’re just supposed to know it or not know it and we can move on, but that there is an obligation for each of us to put in that little bit of effort to learn that shared language.

Rebecca: absolutely. I really like the shared language piece. That’s awesome.

Alexandra: and I like that you put as one of the expectations as well, like to ask question. Right? That you again, sort of have an obligation to ask questions if you don’t understand, don’t just walk away, you know, and give your data people a chance to explain something or to realize that they [00:26:00] haven’t explained it in a way that makes sense to you and that they should provide a different way of engaging with it.

But if you just walk away from it and say, Oh, I didn’t get it. And you don’t give them that feedback that you didn’t get it. You don’t ask the question about where you were confused. It’ll be very hard for them to build that bridge so that everybody can walk across it.

Rebecca: Yeah, and if you ask questions and then you’ll make smarter decisions, right? And also feedback is really important in this kind of work because, you know, a dashboard doesn’t get built overnight. it’s a constant iterative feedback loop, as well as analyzing the data doesn’t happen overnight.

It’s always. Digging in deeper to the data and what getting into kind of just what is really going on, in a classroom. it could be this could be standard. A could be standard B. It could be 1 student is an outlier. So just again, like the iterative cycle asking questions It should happen. at the leadership level, and then also just as a data manager, looking at the data as well.

Alexandra: When you brought up a great point, which is as a frontline person, right? If you’re a teacher or someone actually in the field doing the work, you also have a role to play in providing that context. Like you said, that insight into what that data actually means. In operation because you’re in the classroom and you could speak to that or you’re in the field working in that particular project.

And again, if you’re not there, giving that to the data manager or to your leadership, who’s trying to read this dashboard, It doesn’t, it’s not gonna come from anywhere else. It has to come from you and you have, you need to be engaged in the data to provide that context in an appropriate way.

Rebecca: Yeah, and then again, I’m going back to the open communication piece. It’s two ways, right? Well, I guess maybe three ways, but I’m thinking about the teacher example. You just gave they’re able to provide the context. and so they’re communicating up at the same time that leadership is communicating down of why decisions are being made based on specific data that the data manager is providing, but the teacher is providing the context for why[00:28:00] data is the way that it is. You know, perhaps so it’s a web.

Alexandra: And that’s that part of what makes it truly open communication is that all those channels are open and they’re all necessary. They all need to be in play to really be successful with data, like you said, in that positive data driven culture.

Rebecca: Exactly.

Alexandra: So let’s end with a little bit of an exploration of what else can we be doing?

To bring down some of these walls to build these bridges among sometimes are not very clearly defined data manager roles, those people who don’t identify as data people, but among our leadership, like, how can we build these bridges and create a stronger sense of unity? Besides, obviously, communication, I think, has to be step one.

You have to have that communication. It could be because through that communication, you can find And solve a lot of those problems, but are there other areas that may not be as obvious where we can use that to either bring a wall down or build a bridge

Rebecca: I think prioritizing time and resources to this work. And by work, I mean, to the process of. Collecting the data, analyzing it, building the capacity to do that. Maybe by having a data manager dedicated to doing that. Maybe not. Maybe that’s not for your organization, but. Dedicating the time and the resources, I think will.

Bring down that wall or bridge that gap, because then everyone, Will not feel so overwhelmed. I know in schools, oftentimes teachers, well, definitely teachers are a strap for time and they may not have. The time to collect a data point that the principal expects them to. And if time or resources were allocated differently or rearrange schedules were changed, what have you, whatever the solution is, then that teacher would feel more empowered to collect the data and use the data.

and [00:30:00] another way is making sure that goals are aligned. across the organization or the school. So that way everyone, whether you consider yourself a data person or not, of course, in quotes, can reach towards that same goal and feel more empowered to use the data or collect the data, or at least just have some sort of touch point to it.

to feel that they are on their way to achieving that goal.

Alexandra: that makes sense. And as part of that alignment of goals that it’s also connected to. So we have, like you said, a transparent decision making matrix and metrics that we understand what metrics will be used in the evaluation of success towards that goal, so that we’re all aware of how we’re going to be measured and how we can have those conversations if there’s an opportunity for growth, which then also links back to the time and resources, which is if you’re going to have these goals with these metrics, that the time is made and the resources are available to collect the data to calculate those metrics and to have the time to Read the metrics and understand the metrics and use them, you know, in interim, not just like six month check in, where it’s already too late to do something for half the year.

Rebecca: Yeah, I mean it’s all a web and it’s all super easy to implement, right?

Alexandra: of course, just snap your fingers and off it goes. No, I mean, the whole thing always is, it’s a great reminder. this is a journey. It’s not something that happens overnight.

Rebecca: Definitely.

Alexandra: Wonderful. Well, thank you so much for your time today. This has been just as delightful a conversation as I knew it would be.

If people would like to learn more about you or about simplicity, where can we send them? How can we connect them with you?

Rebecca: Yeah, the Simplicity Education website is just simplicityed. com, or you can follow us on LinkedIn or Instagram at simplicity. education.

Alexandra: Excellent. Well, thank you again so much for your time today. It’s been so wonderful chatting with you.

Rebecca: Awesome, thank you so much.