 Here we are again for another let's discuss. I am excited to be joined by my two colleagues here Lisa McHenry and Stefan Burd Kruger for today's discuss. We decided we would take on the topic of data strategy You know, is it something that everybody knows about is it a common use of word and what do we actually mean by it? Is it really important or not? Like always so our let's discuss conversations. These are informal but informed conversations You know this came about because we'd be in the run a remote company of Parsons TKO We're always in these zoom meetings together and we would have these fantastic Conversations and then think to ourselves. Why did we not record that? And so we wanted to start sharing a lot of our insights with the rest of the world in a format that everyone in the company is very familiar with Which is the zoom chat meetings. So Without further ado, I'd like to introduce well myself just in case that's your first time tuning in welcome And thank you for for showing up and you know at the end or even during you could share this online with whoever else You think this could matter to you can click below and like it. Give us some comments and feedbacks. We'd love it we're still working on how to How to sand these down and turn them into a product that can help a lot of mission-driven organizations all over the US It's not the world So I'm Tony Cappuccini. I am co-founder at Parsons TKO and your Weekly host of let's discuss and I am joined today by Lisa McHenry and Stefan. So Lisa, let's introduce yourself Why I'm Lisa McHenry. I'm one of the project managers here at Parsons TKO I get to make sure that we keep the trains running on time around here and get all our projects completed on time But the best part of the organizations for me that we get to work with so I love that We're a part of making the world a better place helping mission-driven organizations Very good, and I'm Stefan bird Kruger. So I lead the data strategy practice at Parsons TKO our work is especially interesting In in the way that we treat analytics a little bit differently from a lot of the traditional uses Especially if you think of traditional uses as being in the private sector Having spent a career in the nonprofit sector. We've seen how the needs of NGOs and foundations really are pretty unique and it's led us to come up with a unique take on analytics Which we call data strategy. So I think today's a for obvious reasons a very exciting topic for for me Well, let's dive right in then I mean so we call it data strategy here No, wait, I got to stop a second. So Lisa you have coined the ultimate phrase We use a Parsons TKO every time we talk about data strategy or it's any strategy You know what so you someone say it you got it gotta go for at least it's yours. I don't want to The the answers get all the credit but the questions do all the work and that all came out of a Project we were working on we spent a lot of time doing research getting ready to do a presentation with the client and help Them to understand Kind of the analytics and the things that they had going on with their website and at the end of the presentation we kind of gathered for our debrief and We were talking about things that other people on our team did right and one of the things I complimented a fellow employee on Was all the great questions she asked She said, ah, yeah, that's nothing and it's been As the blue no answers get all the credit but questions do all the work It is about asking the right questions and I feel like that's one of the things that Stefan and his team are really good at Helping our clients ask the right questions Yeah, and I mean I love the framing of that too, which is I find in conversations I'm at that people just don't know what questions to ask that they're they're already Assuming an answer rather than oh, I just want to know this thing can this help me with that And I know we're gonna dive into that more and but really at the start of the 50,000 foot level there I'll start with the question stuff We call it data strategy is this a common term, you know when we talk about it to different groups I feel like so many people just instantly go to google analytics or my email data But that's not really what we're talking about here with data strategy So, you know, we've evolved our practice over the course of four years now So I'm wondering if you want to give us a little insights into that Absolutely, and and I think that's precisely right data strategy Has evolved at Parsons TKO. It's something that's grown out of our work You know a lot of our early projects in the data space we we call them analytics projects And we still use the term It's certainly a common term in the industry, but data strategy reflects the fact that analytics by itself Often struggles to make an impact and I think increasingly And especially Nonprofit organizations mission impact for nonprofit organizations mean something different for almost every organization And so a big part of what you have to do with your data is figure out how that data can be made relevant to your mission and so Some of our early projects in analytics we figured out how to get the data lined up We figured out how to you know get it reported put it into a format But there's still that last mile of getting the data from your dashboard to Your staff to your constituents To mission impact and so data strategy as a discipline for us It really has evolved into it's not just the data, but it's what you do with that data and so We have to figure out the business processes. We have to figure out the mechanisms by which analytics can actually change the way staff at non-profit work and and and serve their communities Thanks But so I'd say You know as we think about the terminologies and the use it seems like it's evolving everywhere, but at a slow pace You know, I don't Lisa you've you've mentioned a few times just in your intro there right with clients talk to us They talk specifically about the website And the data and you know to your point. What questions could I ask? I often find myself in conversations where It has really little to do with google analytics and it's how are you tracking data back to a crm system? How are you actually considering getting to know the people that are interacting with your organization in a way where you could try to increase engagement with them and More times than not that's not happening on a website you know, it's just are these the types of things we like to steer into and What does that kind of work look like when we take it on? Yeah, I think that I've noticed that with our clients we tend to see like you say they're just seeing that one touch point and they don't tend to make those connections that bring everyone together and You know, I've got this person in this department over here that we've got in our listed maybe in a crm Maybe not. Maybe it's just an excel spreadsheet that they're a donor Um, and then over here I've got that they're a member and then over here They're subscribed as a newsletter and so in some units we see that Those systems aren't even talking to each other They don't realize that somebody is a donor and a member in an email subscriber all at once There's potential there to even deepen that relationship further But because the information is so siloed they don't realize there's any connection without that strong crm Yeah, I mean I think that is that problem is endemic Um And it comes a lot from this the structure of the tools that we use Uh, we rely on the platforms that we Purchase that we rent that we bring in and make a part of our engagement stack The tools that we use and we let them define the boundaries of what they do Our audiences as nonprofit organizations Don't see our email system separate from our website separate from our social They see their experience with an organization And so being able to have your platforms Understand that that audience journey moves back and forth between those different platforms And just as importantly the data that we Use to to inform those experiences needs to also start weaving back and forth And following that user journey wherever it goes so we can make sure that we're delivering a consistent experience A relevant experience So that's uh, I think breaking down those silos between platforms is a huge part of of our work Overall at Parsons JKO, but especially for the the data strategy team It's so it's interesting to me when I when I think about that and I think about Maybe even called the horizontal nature of work these days, which is that Every department's touching on all these different pieces and they can all benefit from looking at it, you know is Is data an integrator for the organization at that point? Is there something It can do if you've set up the right frameworks to kind of you know, you always talk about stuff and democratize the data around the organization um, but you had also said something you know, we'll circle back to that for sure, but That each system has its own outputs for what it's collecting out of the box And you know more times than not You're reporting what the system wants you to report on to show its performance Not tied to your organizational strategy. So I'm wondering if you could talk a little bit about that, you know, I've heard you I forget what it was, but it was something you were saying, you know, like we want to instrument your strategy not strategy of that product That's exactly right That is uh, a huge point a huge problem and a big challenge Again, this gets at my point before especially for nonprofits The systems that we use Have analytics built in those analytics are designed to Demonstrate the success of that platform Not the success of your strategy I think the you know the sort of term of art or a phrase of art that I used to address that is in order to have a Content strategy that's informed by data. You have to inform your data about your content strategy And I think that's the that's the division there is out of the box a lot of these tools They know how wonderfully your website performs as a website. It loads quickly. It's getting the pages rendered on time In you know, it can even tell you, you know, how many times people are looking at it But the google analytics doesn't know what one page is as opposed to another It leaves it up to you to figure that out in the data and often at non-profit organizations You have a lot of content. So it's leaving you to sift through tens of thousands hundreds of thousands millions of rows To figure out what happened in your data. So one of the first things we do when we're working with organizations and and Google analytics in particular is to help them teach google analytics What they do so that it can start giving back more relevant reports So let's keep going with that and then let's say Okay If I can tune those systems those still feel very Communications marketing team-based, you know, Lisa you probably see this with the groups you work with too It feels like it's always the doorway in but not always What it that can't be the only point for the whole organization to have that collected viewpoint of data You know, so what are our thoughts on that and I wonder You know, even just an ownership of how you steward that but you know talking You talk we've talked about democratizing data and getting this out. Who else can use it like what do we do beyond Looking at your web traffic, right? How does that tie into getting into a real return on investment into your finance? Right, how much money you spent to get back to see what your goal was? I don't know if either of you have some thoughts on that question I mean, I think we I can think of several organizations are at the top of my head that we've worked with in fact when we're working with now where um, a lot of the data is That there's a dispute over who owns the data. I think and what gets done with it because different departments have different goals Um, what they want the data to do, but they don't want to get together and talk about what those goals are together Um, so I think the folks, you know over in donations and development Um, you know, they want to make sure that they're getting the information from their donations page Are people clicking more on this little pop-up that we made suggesting they donate or are they clicking on? You know some called action on another page. Are they actually coming in through our donation portal? um The people who register for our events are they coming in through the main events page or did they come to us From another direction, you know Some of them are membership organizations that have chapters all over the country And so did they come from one of our chapters is our la chapter giving us more traffic in the events than another chapter might be um, and then you know in the membership phase, um In several of our members organizations are trying to track. Well, how how do we get members? What kind of members are we getting do we have levels or people drawn to a particular level of membership? And these are all things that your analytics and your data can answer for you Okay, I I have a little bit of a detour Down something that you mentioned and and I think and I'll I'll come back to that measuring impact question tony but I think the the idea of people Not wanting to share their data and use the word before tony democratizing Uh data, I think that's a really scary thing for a lot of organizations And most often what I think it stems from is people are afraid to share and people are afraid to Ask questions about data Mainly because they don't have the means to get the answers And so I think that's one of the first things that we try to focus on is how can we make sure that When there are questions that are relevant to impact that the organization has the data that they need to answer those questions knows how to access that data And has a form in which they can interpret the data You know figure out what it actually means for the way they work together I think once you do that and and this gets into really a very shoulder Concept of data strategy, which is having a data culture I'm creating a culture that is conducive to sharing and having conversations about data You can start to spark some really really valuable conversations I mean we had we worked with an organization that had exactly that problem Um, you sort of siloed each different team had its own Set of data that it used and occasionally to to reflect on their own work But through our work we were able to create a forum in which all of these departments came together And actually looked at the audience experience as it went from Communications to external relations to development And we're starting to see oh, hey, you guys have the same problem that we have with these same people Let's think through why that is and how your data can help me solve this problem And vice versa. So I think creating the space where you can have those collaborative conversations That's that's at the heart of data strategy It's not just getting the numbers having the numbers putting the numbers in a report It's having your staff read through those numbers have conversations over those numbers You know, we talk about several different roles of data strategy One of the roles of data strategy is what I call data strategy the coffee table How can you use your analytics as a Touchpoint as a touchstone for key strategic conversations That wouldn't happen if it weren't for having this opportunity to bring people around a single point of truth And and and using that as a starting point for a lot of those those types of conversations I think that project you're just uh, we're talking about seven is a good example of that too Because one of the things I appreciated most as we went through that project was The workshops that we did with each department. Those were kind of mini coffee tables for those departments And the department itself got to have a more casual less stressful Discussion about the data that was being collected. It wasn't oh my gosh We're going to collect the state and they're going to find out that our sales aren't as good as this other departments It was no what can it tell you about you? How can it help you and how does it work and with the data other people are collecting from their data help enrich your choices Um, so by doing those workshops with each department first We kind of created that mini coffee table and then everyone had that culture that you're talking about where they were more Culturally comfortable with data and could have a broader group conversation about the time the project was ending That's exactly right and and creating a habit as well um creating a habit of being able to have those conversations and ask those questions and and to your to your famous quote Lisa, you know the questions really do all the work And and if you have an environment in which people don't feel their questions are celebrated You're starting to lose a lot of value. I think it's actually almost better When somebody asks a question and no one can answer it because then it gives you a direction This is what we should work towards we should be able to answer this question because it's interesting and it's valuable And so it starts to to create destinations for for data work, but I think strategy work overall So I have lots of thoughts on that And where we just went You know, you talked to one as you talked about data culture I'd like to get into that a little bit because you say that and I don't know if I fully understand what that looks like in a What a healthy data culture looks like inside of an organization. I'd be interested to get thoughts on that The last bit you were talking about, you know, I used to use the saying that data was the fair arbiter Let's get together and see what it really has to say, but maybe it's more like it's an icebreaker You know, if you're just starting out, it's a way we can all get together But what caught my attention in the case study was It was peer to peer Departments it wasn't the executive asking me for that number Maybe there's There's something in starting to create the cohorts of data sharing first where you can escape the Frankly the way I've seen it is this nervousness of well my performance my performance will reflect negatively If the data is negative on what I tried rather than hey, this was the direction I gave a shot I learned from it. How do I adapt? I think there's everyone always talks about oh, we have this culture we accept failure fail fast, but When does that actually ever manifest itself? I've seen more fear of that than I've seen Acceptance and I think maybe that also hinders some of the questions people might be willing to ask So and then to get back to the data culture point stuff and I guess or at least two what Um Yeah, I mean how would we implement that I want because it came back to it So we had all those different departments in your case study Who's the integration point for it? So when somebody asks a question to your point, right? It's a good question Does anyone of who's within their departments? They're looking at their slice of data they could collect Who is the person or where does this live within an organization or within this data culture where there's a person who says Oh, yeah, of course data can figure that out for you Because I wouldn't know who that is in a lot of organizations Yeah, I think that's that's a really good point and at a tough one to solve You know, we've worked with a lot of organizations a lot of nonprofits I can think of One that had a full-time data person I can I can think of one other that actually had a whole team of data scientists But that was definitely the exception And and for the most part there is nobody who's responsible for for analytics So that's one of the first places we have to We have to focus is is figuring out Who has access how can the organization tap into the potential of its data? And I think this is where data culture becomes really important So what do I mean by data culture data culture means that there is a habit of Using data to help inform decisions and help guide conversations So it's it's creating a a collection of habits around that and Just as often I would say more often That means figuring out how data can work its way into the day-to-day of existing processes We really avoid trying to create a new and now is the data meeting Because then everyone thinks the data meeting is where we go to talk about data And the rest of my day has nothing to do with data So figuring out what is the role of data in your editorial meeting? What's the role of data in your event planning process? And in finding those touch points is is really crucial and so at a lot of organizations your data Specialist is going to be whoever the practitioner is who's responsible for running those day-to-day processes And those those are the people, you know, we we One of the things we talk about in our projects is who are your organization is going to be the analytics hero And in finding those people in plain sight, they're already in place right where they need to be They just need to be given the The mandate and the opportunity to start using the data they already have at their fingertips those people They do the work. They are there. They know the systems. They they know what they're writing They know why they know who they're doing it for so I think that's really important but the data culture Has to include everyone in the organization So I think we always like to have our data strategy projects be organization-wide if at all possible And that means going across the organization across all those departments But it also means going up and down the organizational hierarchy It is imperative that leadership are a part of creating a data culture The leadership have the responsibility of creating the mandate oftentimes asking the questions They they ask a different set of questions than peers often will ask one another But I think those are direction setting questions and and their their work and the work of of leadership down the chain Are all responsible for figuring out how data works its way into the strategy of an organization Whereas the practitioners I think have the best chance of figuring out how data works its way into the tactics And figuring out how you get just a little bit better Every time every time you do something learning from your past experience and this To your question before tony Doesn't just mean communications. I think data can play a role In every aspect of a non-profit's work So they're ample opportunities for program staff to figure out how they can use data Both about themselves their own work their own past performance But also learning from the the outreach arms of the organization be that communications external relations government relations You name it media relations What other relations are there's there's there's a wide range there Foundation relations to owner relations exactly Lisa you had you'd brought up a point earlier And I'm wondering if you want to talk to it a little bit just It's still I know this sounds awful, but it comes off a little polyana sometimes where it's I I have seen it more times than not where Each unit I think so Lisa was making you were making the point They might want to use their data the way they want to use it How do we get past that like how do we how do we help groups show that? Yeah, you can still have that piece, but here's how it plays into the whole and why it Why are that whole makes the whole boat rise right all boats rise when the water comes up? How do we do it together as a team? I don't know if you do have thoughts on that I mean, I can think of a lot of examples I think across our clients, but one of the first things that comes to mind is actually a previous job I formally worked at a public university and the university did have a dedicated analytics group because it's such a big organization Right, but that dedicated analytics group Really only had like a general knowledge of what analytics were available to them And not any kind of concept of what the departments might need from those numbers And so what ended up happening was training didn't filter down to anyone in any departments on how What can the system really do for you and what questions can you ask? And so because they didn't know what was possible. They just didn't ask questions and then all of those Numbers that were generated Scared them they didn't know what was going to be done with them they didn't know really understand how they affected them and so the concern was oh god I have to go to this meeting again where they're going to talk about data and They're going to decide that my department doesn't need as much funding next year as it did got this year because Our numbers are different, but I don't know how our numbers are different or how to explain why they're different or What I could do to prove that we still need the money All right that that that's helping me now now I'm seeing it a little better Because it's it's the way, you know, we talk about transformation, right or change Change is that thing that's going to happen to you whether you want it to or not like it's coming for transformation You can actually be a participant in it so your data your data culture is starting to Sink in a little more with me now stuff and I could start to see how I could start to see how it takes root right and where everybody starts to get a similar understanding and then it It really could become an integration force for an organization to all start seeing things similarly While still watching their aspect of the castle wall, right? Everybody on the same team looking in the same direction. I think You've won me over on the the data the data culture being a very powerful A very powerful tool and really bringing cohesion within organizations Um and in it. I like I like what you guys are saying too where let's not Create meetings just before that. Let's make it part of the actual routine You know what let's make it part of the process most of the organizations when I was in house It was like the board meeting coming everybody's scramble and like pull together some data It's like well, that's not the time we should be doing it, right? It should be It should you should already have that and be thinking about it more in depth I see that panic a little bit too and it's like, oh my gosh. We got to get the funding report together Um Whereas it should be I'm writing a tweet today. What can I learn from some of our best tweets? What can I learn from some of our worst? What can I learn from tweets that audiences? That I'm trying to target today responded well to Those are the kinds of questions that we should be able and encouraged to ask And answer on a day-to-day basis And there's you know, there's another point I wanted to go back to and this again triples down on the democratization idea When you think about the analytics heroes the people who return to and say yes They're making a difference with data and they're helping the organization make a difference with data You want that person to be an enabler of Data success at the organization not a bottleneck of data success at an organization And I think this is another thing that we've seen often is you have a person You say this person is responsible for data and then anyone with a data question Goes to that person and then just waits for an answer and that person the next day is completely overloaded And and the organization stops getting benefits from them and they ultimately leave because they're too stressed out and and so I think you know, I think to Probably the best metaphor I can come up with for this is you don't want data oracles that everyone comes to You want data missionaries Who can go out throughout the organization and help Really bring people into the fold and and help everyone else find data in their own lives So I think that's a really important distinction And an easy mistake to make even when you're making progress It can be it can be very easy to have that progress be trapped in just a few individuals or just a few systems One thing I'd play off to your stuff and that you just said that kind of triggered something for me um The fact that you know, we tend to just think data numbers, but You know tweets other visual things are things that we can pull data from and then improve those visuals It's not just about increasing ownership or increasing membership Directly necessarily but using our other tools to do that and one of my favorite Ways that you've defined data as a tool is as a myth buster because I think for a lot of our clients They think that the organization is one thing our home page gets all of our hits all of our traffic comes in through the home page Well, you can use your data to bust that myth You know all of our donors come in through events because they came to an event. Well, is that true? Let's look at the data Just a lot of ways that data can help you be a myth buster to make sure that your organization is following the right assumptions a lot of stalled progress at organizations Stems from disagreement on fundamentals You know a lack of alignment between teams that have differing opinions on On the reality of their work and so so analytics can absolutely and data strategy can absolutely be used Analytics used as a part of its successful data strategy can be used to bring those teams together and get people centered around a single point of truth and I think Something else you were saying really gets at an important part of successful Use of data is data with context Because you can always skew a number to agree with whatever point you're trying to make So what's really important is to make sure you're always Being very clear about what the number represents But also pairing that number with a reminder of the reality And so this is again where where data is just the the touchstone and around it you have your strategy Um, you know, this is the data and this is the data that relates to the thing We're trying to do so it's the data that relates to the content We're talking about and the date range that is relevant with the audience that we're actually trying to reach So really making sure you you have that narrative around your data is what makes it reliable responsible and effective Yeah, I mean I might even tumbled down with you there too. It's I'm thinking, you know, you coined the term step and I think anecdote which I always loved I can't take credit for that I heard it from you. So I'll give you credit for it. Um, but it's you know, I We worked at a similar organization once upon a blue moon and it was like does it matter if I get A bajillion people on twitter who saw the tweet or the one michelle obama retweet and I'm like Yeah, the michelle obama retweet really matters, right? And if you were just looking at the pure numbers in a recording out, you would see one But then I I always think there's this other side to that which great You got one because you sent one tweet, right and that one tweak I put out It's like you got to have everyone Think about the processes that went into that though if you did not have a content production machine That was targeting and thinking about how that would happen. You never get the one tweet So it's there's like both sides to how data can work, right? We have to support and say hey if you want something like that You know what that takes that takes this amount of effort and this amount of effort generate It means these are this amount of staff we need or this type of budget to be able to push that out you know when we Parts dk every time you see our website you see engagement architecture and that that's one of the components within it is that How do we use data then to help us think about where we need to take the budget? How we would need to staff and those are real interesting Discussions that I enjoy having with some of our clients prospects, which is the world's changing fast This technology has changed quick the old paradigms for organizational structures Are just melting away The status quo is going to get you nowhere but left behind But it is scary because to do something totally different is unsettling And that could be almost as harmful as staying status quo So how do you how do you inch the two together and I feel like again data becomes this? Binding force for the organization to find itself within On both sides of the coin like what can we be doing on the production and outputs and also getting it together? So one thing, you know We've talked about internally before another trend I see is just I I think there's going to be There's going to be there probably is an increase in board members that are far more data savvy Than they were 10 years ago, right? They've at least listened to the news and heard about big data Or something and they're going to want to come in and they're going to ask questions and You know, is that a scary thing for organizations? Where do we start if we're Kind of still just pulling piecemeal. How do we how do we begin this kind of data strategy transformation? Do you have pointers from yeah, I'm gonna let you guys take it because I could just keep rambling Well, I mean I'll I'll start with that by going right back to where I was which is a successful data strategy is an inclusive one And it goes up and down and outside of the hierarchy So I'll take it that step further I think when we are thinking about the role of Data in an organization we have to include how is this data useful to telling our story to board members to potential funders and connecting Their interests in in the organization Which are usually mission and impact to mission and impact And and so I think the data has to be able to tell that story in order for it to be useful and interesting But once you have it and if you've mastered it and if you've actually understood What is possible with your data in terms of telling the story of your success? And then once you've You know figured out how you can report on that regularly and reliably It actually puts you in the in the driver's seat with leadership And and and donors as well So that you can say look we know how to measure impact And this is the question we would like you to ask us because we think it really tells the story of our success I think that can go alongside because good ideas will come from anywhere Both internally and externally and so I think that goes right alongside any question that donor or foundation or a board member might ask But I think very often and you know to that point about particular practitioners before The people who are actually there on a day to day basis They tend to know where to look and can find the the best stories and the best guidance on what to do next To help increase impact. So I think really using staff as an input for donor reporting strategy is is a really Innovative I guess And and rarely rarely adopted way of of driving success, especially in the realm of data So I'm turned over to Lisa for a little bit. I don't I forgot like just for the I'm thinking about it as I think about Kind of that that data hero too. I'm wondering like I know we work with a lot of different organizations So I see folks work with a lot of different tools and I think some of them are intimidated directly by the tools But they also question. Did I get the right tools? What tools do I really need? Do you have any advice you'd offer just off the cuff? I mean not necessarily name and names But what kind of of tools should they be looking for if they don't do they have the right tools? And they need to know You know, what tools do they need? I mean the I think the answer to that is always it depends So much of our work is not about replacing tools Because that can be very disruptive And it can sort of erode Existing skill sets that you have in the organization. So it's not as much about replacing tools as Either integrating the tools that you have so that they can learn from one another and gain new capabilities in that way And otherwise customizing those tools So again, we talked about google analytics. Google analytics is Absolutely an imperfect analytics tool But it works very well for a lot of organizations because it is free And it is also the most common. I forget what google analytics market share is, but it's it's enormous. I think Yeah, it's very big and so that means that it's Fairly easy to find people who can help And who can use it and navigate it and interpret so Again, not to say that that means you should stay with it, but it also tends to have a lot of your your history So I think when you're in that place figuring out how you can make it work Is is usually the first place we want to go with an organization But that being said, there are times when there's there's just a tool that's better better suited if you are completely Re-architecting and making yourself a fully digital organization And you really have sort of a product mindset for for what you're doing People are going to be having complex interactions with you online. There are tools that are better suited for that if you are purely a publishing house And and you're everything you do is sort of in that in that sort of publishing mindset Editorial process flow and things like that There are better tools for that than google analytics And so a lot of that's going to depend on the specific circumstances But most often you can tailor your way to a solution without having to replace So we argue more for meeting you where you are and then Integrating what you have and customizing what you have That's that's a big goal And and again, you know depending on where you are in the life cycle If you're at the point where you can absorb radical change Then blank canvas, let's go for it. And that's that's certainly something we do often actually You know we we often find ourselves as organizations where they're they're ready to roll up their slaves and replace things But the other half of the time that's a really hard proposition And so so being able to figure out how you can succeed Within your current context. It just it makes it easier. It's less disruptive and you can often get to the same value I like that question Lisa because I have one very similar to it Which is you know a lot of what we do with our road mapping work is What are all the variety of tools you're using across an engagement architecture stack or even throughout the organization? And then once you've architected the connections between them or the understanding of why you have them Some of them will deprecate over time and replace one at a time not the whole system So we try to make these architectures so you can replug or put things back in as you need to but I I'm curious Stefan on you know if we're talking about I mean I would assume a data strategy does the same thing for data, which is we're pulling from a lot of different sources We're normalizing We're pulling them into various reports or getting them to different people If one of those systems changes out, it's not necessarily that the data strategy has to change It's just do we absorb something new and is my thinking actually correct on that? Yeah, I think it definitely is the the data should be Platform agnostic as much as possible Every now and then you do run into a platform that just can't do something useful So that's not always necessarily a reason to replace it because sometimes there are what we call proxy metrics that you can use to measure what's missing but Yes, the the analytic systems should be able to absorb changes to the underlying architecture And I I will say if if you're a nonprofit organization out there and you're thinking about a website redesign Now is the time to start thinking about analytics Because those changes while analytics can adapt it does require work for analytics to adapt And so there's a lot of cases where we see a site redesign comes the site launches Then everyone says okay, did it work are things doing better than they were before If you haven't planned for that type of a switch your analytics will not be able to piece together What was happening before and how it's different from what's happening now? Even at the high level total number of traffic that can be tricky to to suss out But if you're actually trying to ask questions about does this type of content do better now than it did before? all but impossible Or an incredible amount of tedious work. So Um, yeah, that's that's my little side rant having having unpacked problems like that for for organizations in the past But so yes, it is very possible to swap out and and just change the the tools and and absorb that kind of a change if you plan for it Well, one thing Well, my guess maybe you have lots of questions. I could probably keep going with but Each system produces its own metrics its own numbers its own format You know, what what does it look like in normalizing that is that? How do I go about that because is it really apples if I want to get apples to apples? I have to find some way to get the data into the same type of format How hard is that is that the type of thing? I definitely need to hire barson's tko or another group for can I do it at house? That's another reason I ask that question. Sorry tony Um About the tools because I see a lot of our clients They just uh, well we brought this one little tool land to do this one little thing. It was a very specialized tool And now I've got data spread out across all kinds of taxonomies like nothing matches I can't merge and get a holistic view of anything because I have all these little tiny systems There's a lot wrapped up in there. Um Um So I think merging those things together Yet can be really really tricky. That's why very often we suggest even if you are doing Analytics around individual parts of your digital ecosystem still having something that's overarching So sometimes we'll do multiple instances of analytics tools running side by side So that you have one view that can be global even if you're looking at one particular part um, so that's one way to To address that Sometimes you are going to have System so let's say you have one email marketing system and you swap it out for another And they have different ways in which they track even basic metrics like opens and clicks Different ways or different levels of reliability Your options are going to be pretty limited in terms of how you actually Change the way the platform that you're using calculates those things We run into that a lot of times something's broken And all we can do is submit a bug report when you're when you're using a system like that Are there other tools you could layer on top to get a normalized view? Sure. Again, that's something you would need to plan for in advance But what I find is most important for a lot of organizations This this also gets to another question we get a lot is what should my benchmark be And those benchmarks whether they are system to system or organization to organization they they matter most in terms of how you use them and And I think very often the best way to use a benchmark is to compare a benchmark against itself So time over time, uh, you know piece of content over piece of content. How can you you are your own? You know mark to pass and so how can you Compare your own content against its own past performance in your own campaigns against your own campaigns past performance That's often the best one the most useful one the most consistently appropriate one to reference and that a little bit sidesteps the question of a platform to platform Analytics, but I think so long as you're moving in the right direction So long as you're using the most recent and the most relevant Comparator to try to improve yourself. You're you're going to be moving in the right direction and and I think that's Just to continue laboring this point. I think even if you do have shifts in terms of methodology that change of the way metric is calculated Looking within each of those buckets. You're still going to be able to identify trends And so if a strategy improved a number in this paradigm And it improves the number in this paradigm, even though they're totally different levels, then you can still draw some conclusions so To the question you asked. Yeah, this is complicated stuff and it probably helps to have somebody Who can think through it and work through it with you? these these are these are the hard questions in in analytics, um, but But there's there's usually a way through All right, we are probably coming up on time from another great long conversation, but I'm wondering to Get some closing thoughts from each of you Lisa any kind of closing thoughts data strategy Yeah, it's useful. Whatever you want to throw it Like I said before I came to barson tk. I knew you know a lot about data in general But we're working with you guys I really feel like I've gotten a better idea of really what it can do and And so I appreciate when you work with our clients those moments where I see the clients kind of a light bulb go off Over their head where they suddenly realize Hey, this is approachable. This isn't scary. This is something that's very useful Oh, I see how it can help me solve this one problem that's been bugging me forever Or this one thing that my boss has really been driving at this will give me the angle that I need To make this work and so those moments that I really appreciate those and I can't wait to see many more extra stepin I think for me the big takeaway That I would like everyone to take away is the the difference in the parson's tko approach to data strategy From what a lot of people think of as just analytics It's not about the data data strategy is not about the data the data strategy is about how you apply data to your strategy and really making sure that everyone Thinks through How data works its way into your organization Both again across the organization How do all the different stakeholders and departments within your organization interact with data and up and down the chain How can leadership create a mandate and how can practitioners be encouraged to Take advantage of the data they have at their disposal by creating a thriving data culture I think that's really important. It's it's how data gets put to use in the organization. That's what data strategy is about Yeah, I remember you saying stuff and that you know your board's going to start asking you questions And you should be driving the conversation. And so that's what this gives you the power to do is to take control and trap the conversation Exactly right Thank you both this has always been a fantastic conversation, you know, I I would say data strategy is empowerment And a force multiplier for an organization, right? Don't be afraid of it. We live in an unprecedented time for the Ability of things you can collect and know But you have to not be afraid to gain understanding of that knowledge You know knowledge is powerful and it could be fearful at times But it's better to know and lead it to your point Lisa, right? Then to just have it happen to you because someone else is going to figure it out too So better better to be an active participant in that conversation. I'm wondering what the heck happened. I guess Um, well as always, uh, thank you both and thank you if you've made it through the whole way with us Maybe we'll start figuring out how to put little Easter eggs at the end of these But as always there's show notes below for you know, we'll try to get some links down there for you Pull out any kind of nuggets that we as a team thought about but leave us some comments We'd really like to hear from you Are these enjoyable have they been useful are there topics you want us to talk about we're more than happy to To dive in and take a look at those and again if this is something you've liked, please like it Socially share it and spread the word we'd welcome that and and thank you very much for it and as always Goodbye this week from Parsons TKO